Artificial intelligence (AI) has transformed our interactions with the world, spawning complex apps and gadgets known as intelligent agents. ChatGPT, a chatbot hybrid of AI and human-computer interaction, converse with humans and have a wide range of possible uses. Chatbots have showed potential in the field of medical education and health sciences by aiding learning, offering feedback, and increasing metacognitive thinking among undergraduate and postgraduate students. OpenAI's ChatGPT, an advanced language model, has substantially enhanced chatbot capabilities. Chatbots are being used in the medical related field for teaching & learning, mental state categorisation, medication recommendation, health education and awareness. While chatbots have been well accepted by users, further study is needed to fully grasp their use in medical and healthcare settings. This study looked at 32 research on ChatGPT and chatbots in medical-related fields and medical education. Medical education, anatomy, vaccines, internal medicine, psychiatry, dentistry, nursing, and psychology were among the topics discussed in the articles. The study designs ranged from pilot studies to controlled experimental trials. The findings show the exponential growth and potential of ChatGPT and chatbots in healthcare and medical education, as well as the necessity for more research and development in this sector. [ABSTRACT FROM AUTHOR]Copyright of Malaysian Journal of Medicine & Health Sciences is the property of Universiti Putra Malaysia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Malaysian Journal of Medicine & Health Sciences

This study presents an exploration into the application of the artificial intelligence chatbot ChatGPT 3.5 in the context of two Hispanic literature survey courses at the University of Delaware during the spring 2023 semester. The introduction of ChatGPT into these learning environments aimed to address two key challenges in teaching Spanish and Latin American literature: falling enrollment rates and rising instances of plagiarism. ChatGPT’s role was twopronged: it served as a component of in-class discussions and a resource for final papers. A total of twenty-one students participated in a follow-up survey designed to gauge their perceptions of ChatGPT as an innovative learning tool. The outcome revealed mixed, yet promising, responses to the use of AI technology in a literature classroom. The data suggest that the ongoing incorporation of cutting-edge tools like ChatGPT into literature courses holds the potential to captivate a diverse group of students and increase enrollment. In addition, the data collected, along with the professor’s analysis of final papers, indicate that ChatGPT can be effective in curbing plagiarism. Responsible AI utilization is becoming increasingly vital in various job markets, and integrating such skills into curricula from STEM to Humanities is crucial for our students’ future career success. (English) [ABSTRACT FROM AUTHOR]Este estudio presenta una exploración de la aplicación del chatbot de inteligencia artificial ChatGPT 3.5 en el contexto de dos cursos panorámicos de literatura hispana en la Universidad de Delaware durante el semestre de primavera de 2023. La introducción de ChatGPT en estos entornos de aprendizaje tenía como objetivo abordar dos desafíos clave en la enseñanza de la literatura española y latinoamericana: la caída de las tasas de inscripción y el aumento de los casos de plagio. El papel de ChatGPT fue doble: sirvió como componente de las discusiones en clase y como recurso para los trabajos finales. Un total de veintiún estudiantes participaron en una encuesta posterior diseñada para medir sus percepciones de ChatGPT como una herramienta de aprendizaje innovadora. El resultado reveló reacciones mixtas, pero prometedoras, ante el uso de la tecnología de IA en clases de literatura. Los datos sugieren que la incorporación de herramientas de vanguardia como ChatGPT en los cursos de literatura tiene el potencial de cautivar a un grupo diverso de estudiantes y aumentar la inscripción. Además, los datos recopilados, junto con el análisis de los trabajos finales por parte de la profesora, indican que ChatGPT puede ser eficaz para controlar el plagio. El uso responsable de la IA se está volviendo cada vez más vital en varios mercados laborales y la integración de estas habilidades en los planes de estudio, desde STEM hasta Humanidades, es crucial para el futuro éxito profesional de nuestros estudiantes. (Spanish) [ABSTRACT FROM AUTHOR]Copyright of Middle Atlantic Review of Latin American Studies is the property of Middle Atlantic Council of Latin American Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Middle Atlantic Review of Latin American Studies

Evaluating a large language model's ability to solve programming exercises from an introductory bioinformatics course.

Computer programming is a fundamental tool for life scientists, allowing them to carry out essential research tasks. However, despite various educational efforts, learning to write code can be a challenging endeavor for students and researchers in life-sciences disciplines. Recent advances in artificial intelligence have made it possible to translate human-language prompts to functional code, raising questions about whether these technologies can aid (or replace) life scientists' efforts to write code. Using 184 programming exercises from an introductory-bioinformatics course, we evaluated the extent to which one such tool—OpenAI's ChatGPT—could successfully complete programming tasks. ChatGPT solved 139 (75.5%) of the exercises on its first attempt. For the remaining exercises, we provided natural-language feedback to the model, prompting it to try different approaches. Within 7 or fewer attempts, ChatGPT solved 179 (97.3%) of the exercises. These findings have implications for life-sciences education and research. Instructors may need to adapt their pedagogical approaches and assessment techniques to account for these new capabilities that are available to the general public. For some programming tasks, researchers may be able to work in collaboration with machine-learning models to produce functional code. Author summary: Life scientists frequently write computer code when doing research. Computer programming can aid researchers in performing tasks that are not supported by existing tools. Programming can also help researchers to implement analytical logic in a way that documents their steps and thus enables others to repeat those steps. Many educational resources are available to teach computer programming, but this skill remains challenging for many researchers and students to master. Artificial-intelligence tools like OpenAI's ChatGPT are able to interpret human-language requests to generate code. Accordingly, we evaluated the extent to which this technology might be used to perform programming tasks described by humans. To evaluate ChatGPT, we used requirements specified for 184 programming exercises taught in an introductory bioinformatics course at the undergraduate level. Within 7 or fewer attempts, ChatGPT solved 179 (97.3%) of the exercises. These findings suggest that some educators may need to reconsider how they evaluate students' programming abilities, and researchers might be able to collaborate with such tools in research settings. [ABSTRACT FROM AUTHOR]Copyright of PLoS Computational Biology is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The incorporation of artificial intelligence (AI) into education has heralded a transformative era in the way students learn and faculties teach. Among the burgeoning array of AI tools, ChatGPT stands out as a versatile and powerful resource. Developed by OpenAI, ChatGPT is an AI-driven conversational model that generates human-like responses. This research draws on the Constructivism Learning Theory to uncover the key drivers pushing higher education students to use ChatGPT for academic purposes, and the multifaceted consequences it brings to the academic environment, by integrating the perspectives of key stakeholders: students, faculty, and education experts/leaders. The key findings of in-depth, face-to-face, interviews with key stakeholders revealed 12 main drivers that motivate students and their faculty to use ChatGPT mainly for learning purposes. However, the findings identified the multifaceted (six positive and another six negative) consequences of using ChatGPT for academic purposes. Recommendations for mitigating the negative consequences of ChatGPT were discussed with key stakeholders, particularly education experts/leaders, who were more concerned about using ChatGPT for academic reasons. The research reveals that higher education institutions should establish clear guidelines as a part of higher education policy, supplemented with training sessions for students and their faculty, about the responsible use of ChatGPT for academic purposes to mitigate any ethical concerns. [ABSTRACT FROM AUTHOR]Copyright of European Journal of Investigation in Health, Psychology & Education (EJIHPE) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

European Journal of Investigation in Health, Psychology & Education (EJIHPE)

Examining the threat of ChatGPT to the validity of short answer assessments in an undergraduate medical program.

Morjaria, L., Burns, L., Bracken, K., Ngo, Q. N., Lee, M., Levinson, A. J., Smith, J., Thompson, P., & Sibbald, M.

Objectives: ChatGPT is an artificial intelligence model that can interpret free-text prompts and return detailed, human-like responses across a wide domain of subjects. This study evaluated the extent of the threat posed by ChatGPT to the validity of short-answer assessment problems used to examine pre-clerkship medical students in our undergraduate medical education program. METHODS: Forty problems used in prior student assessments were retrieved and stratified by levels of Bloom's Taxonomy. Thirty of these problems were submitted to ChatGPT-3.5. For the remaining 10 problems, we retrieved past minimally passing student responses. Six tutors graded each of the 40 responses. Comparison of performance between student-generated and ChatGPT-generated answers aggregated as a whole and grouped by Bloom's levels of cognitive reasoning, was done using t-tests, ANOVA, Cronbach's alpha, and Cohen's d. Scores for ChatGPT-generated responses were also compared to historical class average performance. RESULTS: ChatGPT-generated responses received a mean score of 3.29 out of 5 (n = 30, 95% CI 2.93-3.65) compared to 2.38 for a group of students meeting minimum passing marks (n = 10, 95% CI 1.94-2.82), representing higher performance (P =.008, η2 = 0.169), but was outperformed by historical class average scores on the same 30 problems (mean 3.67, P =.018) when including all past responses regardless of student performance level. There was no statistically significant trend in performance across domains of Bloom's Taxonomy. CONCLUSION: While ChatGPT was able to pass short answer assessment problems spanning the pre-clerkship curriculum, it outperformed only underperforming students. We remark that tutors in several cases were convinced that ChatGPT-produced responses were produced by students. Risks to assessment validity include uncertainty in identifying struggling students and inability to intervene in a timely manner. The performance of ChatGPT on problems requiring increasing demands of cognitive reasoning warrants further research. [ABSTRACT FROM AUTHOR]Copyright of Journal of Medical Education & Curricular Development is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Journal of Medical Education & Curricular Development

Generative Artificial Intelligence (GAI) has revolutionized the field of higher education, and sparked debates on the potenti al of tools such as ChatGPT, Humata.ai or Sudowrite in teaching, learning and assessment processes. While their integration in this context offers numerous opportunities (e.g., instant feedback, generation of resources and teaching materials, adaptive learning, interactivity, etc.), it also poses significant challenges that raise ethical and academic integrity concerns, such as the re liability of information, transparency regarding the sources used, or data privacy and security. The aim of this article is to examine the ethical implications of GAI in higher education from a three-fold perspective (students, faculty, and institutions). Additionally, it aims to analyze its impact on aspects related to security, accessibility, sustainability and even new forms of plagiarism and academic fraud that involve impersonation of authorship. Based on the literature review conducted, and in accordance with the ideas proposed by some authors, possibilities for integrating GAI into university classrooms will be explored. This will be achieved through pedagogical practices that guide students in the proper use of GAI and enable faculty to seek new educational approaches. This transformation process will require the establishment of clear guidelines that align with ethical codes and integrity policies of higher education institutions. Ultimately, the reflection on how to combine education, innovation, and academic integrity will provide these three groups with a new opportunity to drive improvements in university education. (English) [ABSTRACT FROM AUTHOR]La Inteligencia Artificial Generativa (IAG) ha revolucionado el ámbito de la educación superior, y ha abierto el debate en torno al potencial de herramientas como ChatGPT, Humata.ai o Sudowrite en los procesos de enseñanza, aprendizaje y evaluación. Si bien su integración en este contexto presenta numerosas oportunidades (i.e., retroalimentación instantánea, generación de recursos y materiales docentes, aprendizaje adaptativo, interactividad, etc.), también plantea importantes desafíos que ponen en entredicho la ética y la integridad académica como la fiabilidad de la información, la transparencia respecto a las fuentes utilizadas o la privacidad y seguridad de los datos. El objetivo de este artículo es examinar, desde una triple perspectiva (alumnado, profesorado y centro), las implicaciones éticas de su uso en educación superior. Se busca también analizar su impacto en aspectos vinculados con la seguridad, accesibilidad, sostenibilidad e, incluso, nuevas formas de plagio y fraude académico que suplanten la autoría. A partir de la revisión bibliográfica realizada, y según lo que plantean algunos autores, se explorarán posibilidades de integración de la IAG en las aulas universitarias, mediante prácticas pedagógicas que orienten al alumnado e n su correcta utilización, y permitan al profesorado buscar nuevos enfoques educativos. Este proceso de transformación exigirá el establecimiento de unas directrices claras que se ajusten a los códigos éticos y las políticas de integridad de las instituci ones de educación superior. En definitiva, la reflexión sobre cómo aunar educación, innovación e integridad académica brindará a la comunidad universitaria una nueva oportunidad para impulsar mejoras en la enseñanza universitaria. (Spanish) [ABSTRACT FROM AUTHOR]A Inteligência Artificial Generativa (IAG) revolucionou o domínio do ensino superior e abriu o debate sobre o potencial de ferramentas como o ChatGPT, Humata.ai ou Sudowrite nos processos de ensino, aprendizagem e avaliação. Embora a sua integração neste contexto apresente inúmeras oportunidades (ou seja, feedback instantâneo, geração de recursos e material didático, aprendizagem adaptativa, interatividade, etc.), coloca também desafios importantes que põem em causa a ética e a integridade académica, como a fiabilidade da informação, a transparência em relação às fontes utilizadas ou à privacidade e segurança dos dados. O objetivo deste artigo é analisar as implicações éticas da sua utilização no ensino superior, numa tripla perspetiva (estudantes, professores e instituição). Pretende-se também analisar o seu impacto em aspetos ligados à segurança, acessibilidade, sustentabilidade e inclusive a novas formas de plágio e fraude académica que imitem ou roubem a identidade da autoria. Com base na revisão bibliográfica realizada, explorar-se-á a forma de integrar a IAG nas salas de aula universitárias, de forma controlada e respeitadora, através de práticas pedagógicas que orientem os estudantes na sua utilização correta e permitam aos professores lançar as bases de novos modelos educativos. Este processo de transformação exigirá o estabelecimento de diretrizes claras, em conformidade com os códigos éticos e as políticas de integridade das instituições de ensino superior. Em última análise, a reflexão sobre a forma de conjugar educação, inovação e integridade académica proporcionará a estes três coletivos uma nova oportunidade de promover melhorias no ensino universitário. (Portuguese) [ABSTRACT FROM AUTHOR]生��人工智能的出现给高等教育带�了�命化的影�, 也开�了关于ChatGPT�Humata.ai�Sudowrite 等 工具在教育�学习�评估过程中应用潜力的讨论。如果说这些工具在该领域的使用确实带�了更多的机会（ 如实时�馈�教学�料�资�生��自适应学习�互动等等）, 但与此�时, 也对�德和学术诚信�出了挑 战和质疑, 如信�的��性�信���的�明度�数�的��和安全性。因此该研究主�从三个角度（学生 �教师�机构）出�, 对生��人工智能的使用在高等教育中的�德影�进行查验。�时也对它在安全性� 无障�性���续性�甚至是模仿剽窃作者的作弊欺诈新形�等方�的影�进行分�。通过对已有文献的查 验和�考, 试图探寻将生��人工智能�入大学课堂的方�, 在�控且互相尊�的情况下, 通过教学实践指 导学生正确地使用人工智能, �时也为教师的教学新模�奠定基础。这一转�过程需�建立一系列清晰的符 ��德标准和高等教育机构学术诚信�求的准则。总而言之, 关于如何将教育�创新�学术诚信相��的� 考, 为三个群体�供了推动大学教育改善的新机�. (Chinese) [ABSTRACT FROM AUTHOR]Copyright of RELIEVE - Revista Electrónica de Investigación y Evaluación Educativa is the property of RELIEVE - Revista Electonica de Investigacion y Evaluacion Educativa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ibrahim, H., Liu, F., Asim, R., Battu, B., Benabderrahmane, S., Alhafni, B., Adnan, W., Alhanai, T., AlShebli, B., Baghdadi, R., Belanger, J. J., Beretta, E., Celik, K., Chaqfeh, M., Daqaq, M. F., Bernoussi, Z. E., Fougnie, D., Garcia de Soto, B., Gandolfi, A., Gyorgy, A., ... & Zaki, Y.

The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work—a possibility that has sparked ample discussion on the integrity of student evaluation processes in the age of artificial intelligence (AI). To date, it is unclear how such tools perform compared to students on university-level courses across various disciplines. Further, students' perspectives regarding the use of such tools in school work, and educators' perspectives on treating their use as plagiarism, remain unknown. Here, we compare the performance of the state-of-the-art tool, ChatGPT, against that of students on 32 university-level courses. We also assess the degree to which its use can be detected by two classifiers designed specifically for this purpose. Additionally, we conduct a global survey across five countries, as well as a more in-depth survey at the authors' institution, to discern students' and educators' perceptions of ChatGPT's use in school work. We find that ChatGPT's performance is comparable, if not superior, to that of students in a multitude of courses. Moreover, current AI-text classifiers cannot reliably detect ChatGPT's use in school work, due to both their propensity to classify human-written answers as AI-generated, as well as the relative ease with which AI-generated text can be edited to evade detection. Finally, there seems to be an emerging consensus among students to use the tool, and among educators to treat its use as plagiarism. Our findings offer insights that could guide policy discussions addressing the integration of artificial intelligence into educational frameworks. [ABSTRACT FROM AUTHOR]Copyright of Scientific Reports is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial intelligence (AI) is increasingly integrating into our society. University education needs to maintain its relevance in an AI-mediated world, but the higher education sector is only beginning to engage deeply with the implications of AI within society. We define AI according to a relational epistemology, where, in the context of a particular interaction, a computational artefact provides a judgement about an optimal course of action and that this judgement cannot be traced. Therefore, by definition, AI must always act as a 'black box'. Rather than seeking to explain 'black boxes', we argue that a pedagogy for an AI-mediated world involves learning to work with opaque, partial and ambiguous situations, which reflect the entangled relationships between people and technologies. Such a pedagogy asks learners locate AI as socially bounded, where AI is always understood within the contexts of its use. We outline two particular approaches to achieve this: (a) orienting students to quality standards that surround AIs, what might be called the tacit and explicit 'rules of the game'; and (b) providing meaningful interactions with AI systems.

Adilov, N., Cline, J. W., Hanke, H., Kauffman, K., Meneau, L., Resendez, E., Singh, S., Slaubaugh, M., & Suntornpithug, N.

Abstract This article develops an index to measure the level of susceptibility of courses to cheating using ChatGPT (Chat Generative Pre-trained Transformer), an advanced text-based artificial intelligence (AI) language model. It demonstrates the application of the index to a sample of business courses in a mid-sized university. The study finds that the vulnerability index varies across disciplines and teaching modalities. As advanced language models become more common in academic settings and create new educational challenges, the study provides an intuitive and practical mechanism for instructors and academic units to measure and assess the vulnerability of their courses to various language-based predictive models. [ABSTRACT FROM AUTHOR]Copyright of Journal of Education for Business is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background Objective Method Results and Conclusion The increasing prevalence of Artificial Intelligence (AI) language models, exemplified by ChatGPT, has sparked inquiries into their influence on creative writing skills in educational contexts. This study aims to quantitatively investigate whether ChatGPT's use negatively affects university students' creative writing abilities, focusing on originality, content presentation, accuracy, and elaboration in essays. The research adopts an experimental approach to shed light on this concern.This study aims to quantitatively investigate whether the utilization of ChatGPT, an AI chatbot, adversely affects specific dimensions of creative writing skills among university students, with an emphasis on originality, content presentation, accuracy, and elaboration.The experimental study involves 600 students from 10 universities, divided into a control and an experimental group (EGp). The EGp incorporates ChatGPT in their creative writing process as an intervention. The study evaluates originality, content presentation, accuracy, and elaboration, utilizing the Wilcoxon Signed�Rank Test for analysis.The findings reveal a detrimental association between ChatGPT use and university students' creative writing abilities. Analysing both machine�based and human�based assessments substantiates earlier qualitative observations regarding ChatGPT's adverse impact on creative writing. This study highlights the necessity of approaching AI integration, particularly in creative writing disciplines, with caution. While AI tools have merits, their integration should be thoughtful, considering the potential drawbacks. These insights inform future research and educational practices, guiding the effective incorporation of AI while nurturing students' writing skills. [ABSTRACT FROM AUTHOR]Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Using natural language processing to support peer-feedback in the age of artificial intelligence: A cross-disciplinary framework and a research agenda.

Bauer, E., Greisel, M., Kuznetsov, I., Berndt, M., Kollar, I., Dresel, M., Fischer, M. R., & Fischer, F.

Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments.

ChatGPT versus engineering education assessment: A multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity.

Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., Lyden, S., Neal, P., & Sandison, C.

ChatGPT, a sophisticated online chatbot, sent shockwaves through many sectors once reports filtered through that it could pass exams. In higher education, it has raised many questions about the authenticity of assessment and challenges in detecting plagiarism. Amongst the resulting frenetic hubbub, hints of potential opportunities in how ChatGPT could support learning and the development of critical thinking have also emerged. In this paper, we examine how ChatGPT may affect assessment in engineering education by exploring ChatGPT responses to existing assessment prompts from ten subjects across seven Australian universities. We explore the strengths and weaknesses of current assessment practice and discuss opportunities on how ChatGPT can be used to facilitate learning. As artificial intelligence is rapidly improving, this analysis sets a benchmark for ChatGPT's performance as of early 2023 in responding to engineering education assessment prompts. ChatGPT did pass some subjects and excelled with some assessment types. Findings suggest that changes in current practice are needed, as typically with little modification to the input prompts, ChatGPT could generate passable responses to many of the assessments, and it is only going to get better as future versions are trained on larger data sets. [ABSTRACT FROM AUTHOR]Copyright of European Journal of Engineering Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Chat Generative Pretrained Transformer fails the multiple-choice American College of Gastroenterology self-assessment test.

Introduction: Chat Generative Pretrained Transformer (ChatGPT) is a natural language processing model that generates human-like text. METHODS: ChatGPT-3 and ChatGPT-4 were used to answer the 2022 and 2021 American College of Gastroenterology self-assessment tests. The exact questions were inputted in both versions of ChatGPT. A score of 70% or higher was required to pass the assessment. RESULTS: Overall, ChatGPT-3 scored 65.1% on 455 included questions and GPT-4 scored 62.4%. DISCUSSION: ChatGPT did not pass the American College of Gastroenterology self-assessment test. We do not recommend its use for medical education in gastroenterology in its current form. [ABSTRACT FROM AUTHOR]Copyright of American Journal of Gastroenterology (Lippincott Williams & Wilkins) is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Can artificial intelligence pass the American Board of Orthopaedic Surgery examination? Orthopaedic residents versus ChatGPT.

Background: Advances in neural networks, deep learning, and artificial intelligence (AI) have progressed recently. Previous deep learning AI has been structured around domain-specific areas that are trained on dataset-specific areas of interest that yield high accuracy and precision. A new AI model using large language models (LLM) and nonspecific domain areas, ChatGPT (OpenAI), has gained attention. Although AI has demonstrated proficiency in managing vast amounts of data, implementation of that knowledge remains a challenge. Questions/purposes: (1) What percentage of Orthopaedic In-Training Examination questions can a generative, pretrained transformer chatbot (ChatGPT) answer correctly? (2) How does that percentage compare with results achieved by orthopaedic residents of different levels, and if scoring lower than the 10th percentile relative to 5th-year residents is likely to correspond to a failing American Board of Orthopaedic Surgery score, is this LLM likely to pass the orthopaedic surgery written boards? (3) Does increasing question taxonomy affect the LLM's ability to select the correct answer choices? Methods: This study randomly selected 400 of 3840 publicly available questions based on the Orthopaedic In-Training Examination and compared the mean score with that of residents who took the test over a 5-year period. Questions with figures, diagrams, or charts were excluded, including five questions the LLM could not provide an answer for, resulting in 207 questions administered with raw score recorded. The LLM's answer results were compared with the Orthopaedic In-Training Examination ranking of orthopaedic surgery residents. Based on the findings of an earlier study, a pass-fail cutoff was set at the 10th percentile. Questions answered were then categorized based on the Buckwalter taxonomy of recall, which deals with increasingly complex levels of interpretation and application of knowledge; comparison was made of the LLM's performance across taxonomic levels and was analyzed using a chi-square test. Results: ChatGPT selected the correct answer 47% (97 of 207) of the time, and 53% (110 of 207) of the time it answered incorrectly. Based on prior Orthopaedic In-Training Examination testing, the LLM scored in the 40th percentile for postgraduate year (PGY) 1s, the eighth percentile for PGY2s, and the first percentile for PGY3s, PGY4s, and PGY5s; based on the latter finding (and using a predefined cutoff of the 10th percentile of PGY5s as the threshold for a passing score), it seems unlikely that the LLM would pass the written board examination. The LLM's performance decreased as question taxonomy level increased (it answered 54% [54 of 101] of Tax 1 questions correctly, 51% [18 of 35] of Tax 2 questions correctly, and 34% [24 of 71] of Tax 3 questions correctly; p = 0.034). Conclusion: Although this general-domain LLM has a low likelihood of passing the orthopaedic surgery board examination, testing performance and knowledge are comparable to that of a first-year orthopaedic surgery resident. The LLM's ability to provide accurate answers declines with increasing question taxonomy and complexity, indicating a deficiency in implementing knowledge. Clinical Relevance: Current AI appears to perform better at knowledge and interpretation-based inquires, and based on this study and other areas of opportunity, it may become an additional tool for orthopaedic learning and education. [ABSTRACT FROM AUTHOR]Copyright of Clinical Orthopaedics & Related Research® is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

If, as current proponents of AI posit, these tools exist to help us do our jobs more quickly (Lopez, [12]), then we need our students to be prepared to improve on the AI-generated text. In closing, AI-based tools are certainly a potential opportunity as a tool for writing, as long as the ideas fed to the AI systems are not sensitive, and as long as human writers still have the abilities to refine and powerfully edit any text that is smoothed by an AI system. This guest editorial is framed around two propositions regarding why we still need to teach engineering writing: First, to teach students to write is to teach them to think; and second, AI is a tool and not a replacement for teaching writing. Faculty wonder how artificial intelligence (AI) such as ChatGPT will revolutionize higher education, where writing is a key competency and where our careers are built on our ability to productively publish. [Extracted from the article]Copyright of Journal of Engineering Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In 2022, OpenAI released ChatGPT, a generative artificial intelligence (AI) chatbot that can instantly respond to user-provided queries in a conversational manner. While it can be a powerful tool for completing a great number of written tasks, instructors are worried about students misusing ChatGPT and other AI programs in their coursework. Though this concern is valid, we propose that the emphasis on trying to circumvent cheating with AI is misplaced. In the following commentary, we argue that the way students are assessed should fundamentally change. Instead of asking students to simply reproduce knowledge in essays or exams - tasks that are easily accomplishable for an AI like ChatGPT - students should engage in class-specific, guided self-reflection and take part in assessing their own work. Self-assessment and ungrading could increase intrinsic motivation and reduce the desire to rely on AI for coursework, especially when such coursework requires personalized details from students. Thus, we propose that the emergence of ChatGPT and the continued evolution of AI poses an exciting challenge for higher education - to refocus students on work that is personally meaningful, and accomplishable only by humans.

Wang, X., Gong, Z., Wang, G., Jia, J., Xu, Y., Zhao, J., Fan, Q., Wu, S., Hu, W., & Li, X.

ChatGPT, a language model developed by OpenAI, uses a 175 billion parameter Transformer architecture for natural language processing tasks. This study aimed to compare the knowledge and interpretation ability of ChatGPT with those of medical students in China by administering the Chinese National Medical Licensing Examination (NMLE) to both ChatGPT and medical students. We evaluated the performance of ChatGPT in three years' worth of the NMLE, which consists of four units. At the same time, the exam results were compared to those of medical students who had studied for five years at medical colleges. ChatGPT's performance was lower than that of the medical students, and ChatGPT's correct answer rate was related to the year in which the exam questions were released. ChatGPT's knowledge and interpretation ability for the NMLE were not yet comparable to those of medical students in China. It is probable that these abilities will improve through deep learning. [ABSTRACT FROM AUTHOR]Copyright of Journal of Medical Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study explores university students’ perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education, focusing on familiarity, their willingness to engage, potential benefts and challenges, and efective integration. A survey of 399 undergraduate and postgraduate students from various disciplines in Hong Kong revealed a generally positive attitude towards GenAI in teaching and learning. Students recognized the potential for personalized learning support, writing and brainstorming assistance, and research and analysis capabilities. However, concerns about accuracy, privacy, ethical issues, and the impact on personal development, career prospects, and societal values were also expressed. According to John Biggs’ 3P model, student perceptions signifcantly infuence learning approaches and outcomes. By understanding students’ perceptions, educators and policymakers can tailor GenAI technologies to address needs and concerns while promoting efective learning outcomes. Insights from this study can inform policy development around the integration of GenAI technologies into higher education. By understanding students’ perceptions and addressing their concerns, policymakers can create well-informed guidelines and strategies for the responsible and efective implementation of GenAI tools, ultimately enhancing teaching and learning experiences in higher education.

International Journal of Educational Technology in Higher Education

Author's note: This article was written by the ChatGPT chatbot, in response to prompts from MK. Graph: Figure 1 Four depictions of "how artificial intelligence and chatbots might be used for cheating in college", as envisioned by the AI-powered DALL-E 2 image generator (OpenAI). ChatGPT is a cutting-edge AI chatbot technology that uses natural language processing and machine learning to enable users to have conversational interactions with a virtual assistant. [Extracted from the article]Copyright of Cellular & Molecular Bioengineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study presents a corpus analysis of academic integrity policies from Higher Education Institutions (HEIs) worldwide, exploring how they address the issues posed by technological threats, such as Automated Paraphrasing Tools and generative-artificial intelligence tools, such as ChatGPT. The analysis of 142 policies conducted in November and December 2022, and May 2023 reveals a gap regarding the mention of AI and associated technologies in the available academic integrity policies. Despite the growing prevalence of these tools in the 6-month period since the release of ChatGPT, no HEIs had produced revised academic integrity policies. Content analysis of 53 guidance documents produced by HEIs suggests an overall positive focus of Gen AI tools, yet advises caution. This study suggests a modification to Bretag et al.’s (Int J Educ Integr 7, 2011) exemplary academic integrity model, introducing “Technological Explicitness� — emphasizing the need to include explicit guidelines about new technologies in academic integrity policies. These results underscore the urgent need for HEIs to revise their academic integrity policies, considering the evolving landscape of AI and its implications for academic integrity. This paper argues for a multifaceted approach to deal with the issues of integrating technology, education, policy reform, and assessment restructuring to navigate these challenges while upholding academic integrity. [ABSTRACT FROM AUTHOR]Copyright of Higher Education Policy is the property of Palgrave Macmillan Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The recent development of AI Chatbot - specifically ChatGPT - has gained dramatic attention from users as evident by ongoing discussion among the education fraternity. We argue that prior to making any conclusion, it is important to understand how ChatGPT is being used in higher education across the globe. This paper makes a significant contribution by systematically reviewing the global literature on the use of ChatGPT in higher education using PRISMA guidelines. We included 69 studies in the analysis based on inclusion and exclusion criteria. We presented the scope of published literature in three aspects: (i) contextual, (ii) methodological, and (iii) disciplinary. Most of the studies have been carried out in HICs (n = 53; 77%) representing the field of higher education (n = 37; 54%) without specifying the discipline, while only a few studies were based on empirical data (n = 19; 27%). The findings based on included studies reveal that ChatGPT serves as a convenient tool to assist teachers, students, and researchers in various tasks. While the specific uses vary, the underlying motivation remains consistent: seeking personal benefits and reducing academic burdens. Teachers use it for personal and professional learning and resource generation while students use it as personal tutors for various learning purposes. However, concerns related to accuracy, reliability, academic integrity, and potential negative effects on cognitive and social development were consistently highlighted in many studies. To address these concerns, we have proposed a comprehensive framework for universities along with directions for future research in higher education as an optimal response.

The OpenAI's ChatGPT-3, or Chat Generative Pre-Trained Transformer was released in November 2022 without significant warning, and has taken higher education by storm since. The artificial intelligence (AI) -powered chatbot has caused alarm for practitioners seeking to detect authenticity of student work. Whereas some educational doomsayers predict the end of education in its current form, we propose an alternate early view. We identify in this commentary a position where educators can leverage AI like ChatGPT to build supportive learning environments for students who have cultivated good character. Such students know how to use ChatGPT for good, and can engage effectively with the ChatGPT application. In building our ChatGPT argument, we acknowledge the existing literature on plagiarism and academic integrity, and consider leadership as a root support mechanism, character development as an antidote, and authentic assessment as an enabler. In doing so, we highlight that while ChatGPT - like papermills, and degree factories before it - can be used to cheat on university exams, it can also be used to support deeper learning and better learning outcomes for students. In doing so, we offer a commentary that offers opportunities for practitioners, and research potential for scholars.

Journal of University Teaching & Learning Practice

PurposeThis paper aims to present a systematic literature review and bibliometric analysis of research papers published on chat generative pre-trained transformer (ChatGPT), an OpenAI-developed large-scale generative language model. The study's objective is to provide a comprehensive assessment of the present status of research on ChatGPT and identify current trends and themes in the literature.Design/methodology/approachA total of 328 research article data was extracted from Scopus for bibliometric analysis, to investigate publishing trends, productive countries and keyword analysis around the topic and 34 relevant research publications were selected for an in-depth systematic literature review.FindingsThe findings indicate that ChatGPT research is still in its early stages, with the current emphasis on applications such as natural language processing and understanding, dialogue systems, speech processing and recognition, learning systems, chatbots and response generation. The USA is at the forefront of publishing on this topic and new keywords, e.g. "patient care", "medical", "higher education" and so on are emerging themes around the topic.Research limitations/implicationsThese findings underscore the importance of ongoing research and development to address these limitations and ensure that ChatGPT is used responsibly and ethically. While systematic review research on ChatGPT heralds exciting opportunities, it also demands a careful understanding of its nuances to harness its potential effectively.Originality/valueOverall, this study provides a valuable resource for researchers and practitioners interested in ChatGPT at this early stage and helps to identify the grey areas around this topic.

The aim of this project was to understand student perspectives on generative artificial intelligence (GAI) technologies such as Chat generative Pre-Trained Transformer (ChatGPT), in order to inform changes to the University of Liverpool Academic Integrity code of practice. The survey for this study was created by a library student team and vetted through focus groups. A total of 2555 students participated in the survey. Results showed that only 7% of students who responded had not heard of any GAI technologies, whilst over half had used or considered using these for academic purposes. The majority of students (54.1%) were supportive or somewhat supportive of using tools such as Grammarly, but 70.4% were unsupportive or somewhat unsupportive towards students using tools such as ChatGPT to write their whole essay. Students who had higher levels of confidence in their academic writing were less likely to use or consider using them for academic purposes, and were also less likely to be supportive of other students using them. Most students (41.1%) also thought there should be a university wide policy on when these technologies are or are not appropriate to use. The results of this research suggest that students require clear policies on the use of GAI and that these technologies should not be banned from university, but consideration must be made to ensure different groups of students have equal access to the technologies.

Academics' perceptions of ChatGPT-generated written outputs: A practical application of Turing's Imitation Game.

Artificial intelligence (AI) technology, such as Chat Generative Pre-trained Transformer (ChatGPT), is evolving quickly and having a significant impact on the higher education sector. Although the impact of ChatGPT on academic integrity processes is a key concern, little is known about whether academics can reliably recognise texts that have been generated by AI. This qualitative study applies Turing's Imitation Game to investigate 16 education academics' perceptions of two pairs of texts written by either ChatGPT or a human. Pairs of texts, written in response to the same task, were used as the stimulus for interviews that probed academics' perceptions of text authorship and the textual features that were important in their decision-making. Results indicated academics were only able to identify AI-generated texts half of the time, highlighting the sophistication of contemporary generative AI technology. Academics perceived the following categories as important for their decision-making: voice, word usage, structure, task achievement and flow. All five categories of decision-making were variously used to rationalise both accurate and inaccurate decisions about text authorship. The implications of these results are discussed with a particular focus on what strategies can be applied to support academics more effectively as they manage the ongoing challenge of AI in higher education.Implications for practice or policy:center dot Experienced academics may be unable to distinguish between texts written by contemporary generative AI technology and humans.center dot Academics are uncertain about the current capabilities of generative AI and need support in redesigning assessments that succeed in providing robust evidence of student achievement of learning outcomes.center dot Institutions must assess the adequacy of their assessment designs, AI use policies, and AI-related procedures to enhance students' capacity for effective and ethical use of generative AI technology.

Economics students' behavioural intention and usage of ChatGPT in higher education: A hybrid structural equation modelling-artificial neural network approach.

The Chat Generative Pre-Trained Transformer, popularly referred to as ChatGPT, is an AI-based technology with the potential to revolutionise conventional teaching and learning in higher education institutions (HEIs). However, it remains unclear which factors influence the behavioural intentions and the actual usage of ChatGPT among economics students in Ghanaian HEIs. In pursuit of this goal, we employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) to gain a better understanding of the antecedents influencing the behavioural intentions and actual usage of ChatGPT among economics students. The study surveyed 306 Ghanaian students enrolled in economics at a public university. These students were aware of the existence of ChatGPT applications. We applied a hybrid analytical approach, combining structural equation modelling and artificial neural network (SEM-ANN), to elucidate the causal relationships between variables believed to impact perceived trust, intentions, and actual usage. The results showed that design and interactivity have a significant impact on perceived trust. Similarly, perceived trust, social influence, performance expectancy, hedonic motivation, and habits drive behavioural intentions. Among the various factors influencing behavioural intentions, hedonic motivation emerged as the most dominant. Moreover, behavioural intentions and facilitating conditions significantly drive students' actual use of the ChatGPT. Nevertheless, ethics is not a significant factor in perceived trust, and effort expectancy does not affect behavioral intention. These findings, however, offer theoretical and practical contributions that can serve as guide for a thoughtful and responsible integration of AI-based tools as a future strategy to enhance education accessibility and inclusivity opportunities

The evolution of natural language processing techniques has led to the development of advanced conversational tools such as ChatGPT, capable of assisting users with a variety of activities. Media attention has centered on ChatGPT's potential impact, policy implications, and ethical ramifications, particularly in the context of education. As such tools become more accessible, students across the globe may use them to assist with their homework. However, it is still unclear whether ChatGPT's performance is advanced enough to pose a serious risk of plagiarism. We fill this gap by evaluating ChatGPT on two introductory and two advanced university-level courses. We find that ChatGPT receives near-perfect grades on the majority of questions in the introductory courses but has not yet reached the level of sophistication required to pass in advanced courses. Moreover, adding a few full stops or typos may fool a machine learning algorithm designed to detect ChatGPT-generated text. These findings suggest that, at least for some courses, current artificial intelligence tools pose a real threat that can no longer be overlooked by educational institutions.

Introduction: Open-source generative artificial intelligence (AI) applications are fast-transforming access to information and allow students to prepare assignments and offer quite accurate responses to a wide range of exam questions which are routinely used in assessments of students across the board including undergraduate dental students. This study aims to evaluate the performance of Chat Generative Pre-trained Transformer (ChatGPT), a generative AI-based application, on a wide range of assessments used in contemporary healthcare education and discusses the implications for undergraduate dental education.Materials and Methods: This was an exploratory study investigating the accuracy of ChatGPT to attempt a range of recognised assessments in healthcare education curricula. A total of 50 independent items encompassing 50 different learning outcomes (n = 10 per item) were developed by the research team. These included 10 separate items based on each of the five commonly used question formats including multiple-choice questions (MCQs); short-answer questions (SAQs); short essay questions (SEQs); single true/false questions; and fill in the blanks items. Chat GPT was used to attempt each of these 50 questions. In addition, ChatGPT was used to generate reflective reports based on multisource feedback; research methodology; and critical appraisal of the literature.Results: ChatGPT application provided accurate responses to majority of knowledge-based assessments based on MCQs, SAQs, SEQs, true/false and fill in the blanks items. However, it was only able to answer text-based questions and did not allow processing of questions based on images. Responses generated to written assignments were also satisfactory apart from those for critical appraisal of literature. Word count was the key limitation observed in outputs generated by the free version of ChatGPT.Conclusion: Notwithstanding their current limitations, generative AI-based applications have the potential to revolutionise virtual learning. Instead of treating it as a threat, healthcare educators need to adapt teaching and assessments in medical and dental education to the benefits of the learners while mitigating against dishonest use of AI-based technology.

Background: This study examined pharmacy students' knowledge and attitudes to artificial intelligence (AI) and ChatGPT. Methods: A survey was conducted with 258 fourth-year pharmacy students at Kitasato University, Japan, assessing their AI knowledge, ChatGPT impressions, and literacy regarding its appropriate use. Data were analysed descriptively, and participants were divided into two groups based on ChatGPT awareness for further analysis. Results: A total of 113 students (43.7%) participated, with 19.5% having prior ChatGPT experience, 4.4% were unaware, and 42.5% could describe it. General AI terms like "machine learning" were more familiar (83.2%) than specific ones like "natural language processing" (2.6%). Positive impressions of ChatGPT included 65.5% finding it efficient and 50.4% mentioning enhanced comprehension. However, only 3.5% correctly identified all inappropriate purposes, and 24.8% selected all precautions for its use. The 48 participants (42.5%) who described ChatGPT and had higher AI knowledge showed more correct answers than the other group (65 participants, 57.5%). Conclusion: Students with AI knowledge and the ability to describe ChatGPT demonstrated a better understanding of its appropriate usage. Educating students on AI fundamentals helps them utilise AI tools like ChatGPT effectively. This study offers valuable insights on ChatGPT among pharmacy students, with implications for responsible AI usage and education.

In November 2022, the public release of ChatGPT, an artificial intelligence (AI)-based natural language model, was a groundbreaking point in many sectors of human life and education was not the exception. We describe how ChatGPT was integrated in an undergraduate course for an International Relations program in a private Mexican university. Under an action research methodology, we introduced this novel instrument in a course on Future Studies. Students were evaluated on their ability to explain to ChatGPT several discipline-specific methods and to make the AI implement these methods step by step. After six such activities, the outcomes evidenced that the students not only learned how to use the new AI tool and deepen their understanding of prospective methods, but also strengthened three soft or transversal competencies: communication, critical thinking, and logical and methodical reasoning. These results are promising in the framework of Skills for Industry 4.0 and Education for Sustainable Development; even more, they demonstrate how ChatGPT created an opportunity for the students to strengthen, and for the professor to assess, time-tested competencies. This is a call-to action for faculty and educational institutions to incorporate AI in their instructional design, not only to prepare our graduates for professional environments where they will collaborate with these technologies but also to enhance the quality and relevance of higher education in the digital age. Therefore, this work contributes to the growing body of research on how Artificial Intelligence (AI) can be used in higher education settings to enhance learning experiences and outcomes.

Lopez-Chila, R., Llerena-Izquierdo, J., Sumba-Nacipucha, N., & Cueva-Estrada, J.

Since its origin in the 1950s, artificial intelligence (AI) has evolved from technological to educational applications. AI is emerging as an essential tool in education. Its integration into education promises the personalization and the globalization of learning. Despite its potential, it is crucial to consider its ethical challenges and uses. This bibliometric study sought to understand the current state of AI in higher education in order to provide a basis for future research. A bibliometric analysis was conducted between 2017 and 2023, using the Scopus database. The query was performed on 23 October 2023 and focused on titles, keywords, and abstracts. A total of 870 articles were found, and their metadata were analyzed after removing incorrect data. VOSviewer software was used to visualize the similarities, and the publications were studied by country, authors, and collaborations. A steady growth in AI studies in higher education was found, highlighting areas such as computer science and social sciences. China and the United States led in production and citations. Keywords such as "artificial intelligence", "chatgpt", and "machine learning" indicated trends and areas of interest.

Maintaining the integrity of the South African university: The impact of CHATGPT on plagiarism and scholarly writing.

Recent advancements in artificial intelligence (AI) have reignited discussions about the value of the university and its role in producing and facilitating knowledge. The invention of ChatGPT has led to differing responses in the academy, with some welcoming its abilities and others fearing that it may undermine what schools and universities do, calling it "apocalyptic" (Green 2022). These aspects impact the integrity of the academy and are therefore a fundamental contribution to the debate. The impact, as well as the perceived impact, of AI on teaching and learning in higher education has been consistently documented in popular media. Therefore, the aim of this article is to understand the impact of ChatGPT on plagiarism and scholarly writing. It contributes to the under-researched academic discourse of generative artificial intelligence and teaching and learning by garnering the views of three established professors in South Africa. The findings from this qualitative endeavour demonstrate that, for these professors, these kinds of technology are welcome, and students need to be taught how to engage with them rather than vilifying them. Much of the responsibility rests on the lecturers and the university to create a teaching and learning environment that allows for these technologies to enter the classroom, especially in the way we assess.

Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D., Mohammed, A. H., Hassan, B. A. R., Wayyes, A. M., Farhan, S. S., Khatib, S. E., Rahal, M., Sahban, A., Abdelaziz, D. H., Mansour, N. O., Alzayer, R., Khalil, R., Fekih-Romdhane, F., Hallit, R., Hallit, S., & Sallam, M.

Artificial intelligence models, like ChatGPT, have the potential to revolutionize higher education when implemented properly. This study aimed to investigate the factors influencing university students' attitudes and usage of ChatGPT in Arab countries. The survey instrument "TAME-ChatGPT" was administered to 2240 participants from Iraq, Kuwait, Egypt, Lebanon, and Jordan. Of those, 46.8% heard of ChatGPT, and 52.6% used it before the study. The results indicated that a positive attitude and usage of ChatGPT were determined by factors like ease of use, positive attitude towards technology, social influence, perceived usefulness, behavioral/cognitive influences, low perceived risks, and low anxiety. Confirmatory factor analysis indicated the adequacy of the "TAME-ChatGPT" constructs. Multivariate analysis demonstrated that the attitude towards ChatGPT usage was significantly influenced by country of residence, age, university type, and recent academic performance. This study validated "TAME-ChatGPT" as a useful tool for assessing ChatGPT adoption among university students. The successful integration of ChatGPT in higher education relies on the perceived ease of use, perceived usefulness, positive attitude towards technology, social influence, behavioral/cognitive elements, low anxiety, and minimal perceived risks. Policies for ChatGPT adoption in higher education should be tailored to individual contexts, considering the variations in student attitudes observed in this study.

Generative artificial intelligence: University student awareness, experience, and confidence in use across disciplines.

The global higher education sector has been significantly disrupted by the proliferation of generative artificial intelligence tools such as ChatGPT, especially in relation to its implications for assessment. However, few studies to date have explored student perspectives on these tools. This article reports on one of the first large-scale quantitative studies of student views on generative artificial intelligence at an Australian university (n = 1,135). When the survey was conducted, most students had low knowledge, experience, and confidence in using these tools. These results varied across disciplines and across some student sub-groups, such as mature-age students and international students. Confidence appeared to increase with experience, although the data also revealed a portion of students that have never used these tools yet still felt confident in using them. In exploring these results, this article aims to shed new light on this fast-evolving landscape and inform the future direction of supporting students to engage with generative artificial intelligence tools appropriately.

Journal of University Teaching & Learning Practice

The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of using ChatGPT in higher education, and discusses the potential risks and rewards of these tools. The paper also considers the difficulties of detecting and preventing academic dishonesty, and suggests strategies that universities can adopt to ensure ethical and responsible use of these tools. These strategies include developing policies and procedures, providing training and support, and using various methods to detect and prevent cheating. The paper concludes that while the use of AI in higher education presents both opportunities and challenges, universities can effectively address these concerns by taking a proactive and ethical approach to the use of these tools.

Innovations in Education and Teaching International

Artificial intelligence (AI) technologies have the potential to completely transform how we teach and learn in higher education. ChatGPT, a language model developed by OpenAI, is one such tool that can deliver individualized recommendations to students, increase collaboration and communication, and improve student learning results. However, there are some obstacles to overcome, such as ethical concerns and implementation issues. This study reviews related work on the use of artificial intelligence in education, with a focus on ChatGPT and its possible applications in higher education. It also examines the benefits and drawbacks of adopting ChatGPT in higher education, as well as implementation advice. Finally, the report discusses future directions for ChatGPT research in higher education. According to the findings of this paper, ChatGPT represents a significant opportunity for higher education institutions to improve the quality and accessibility of education; however, its implementation must be approached with caution and a clear understanding of the opportunities and challenges involved.

Applying a modified technology acceptance model to explain higher education students' usage of ChatGPT: A serial multiple mediation model with knowledge sharing as a moderator.

Generative artificial intelligence (AI), such as ChatGPT, has taken the world by storm, especially in the education sector, because of its capacity to produce responses that are contextually relevant and appear to imitate human language. This has increased concerns from both scholars and practitioners regarding the potential impacts of ChatGPT on students' learning. However, research on higher education students' adoption of ChatGPT is still scant. Drawing on the modified technology acceptance model (TAM) and a sample of 1389 higher education students recruited in 11 universities in Vietnam with a stratified random sampling approach, the findings of this study indicated that effort expectancy not only directly affected students' actual usage of ChatGPT, but also serially indirectly increased their actual use of ChatGPT through performance expectancy and intentions to use ChatGPT. Additionally, knowledge sharing was found to significantly increase higher education students' transformation from having the intention to use ChatGPT to actual users of ChatGPT. The theoretical and managerial implications of this are discussed in this paper in order to gain benefits and manage the potential threats from this new technology.

The International Journal of Management Education

Time to revisit existing student's performance evaluation approach in higher education sector in a new era of ChatGPT - A case study.

Artificial intelligence-based tools are rapidly revolutionizing the field of higher education, yet to be explored in terms of their impact on existing higher education institutions' (HEIs) practices adopted for continuous learning improvement, given the sparsity of the literature and empirical experiments in undergraduate degree programs. After the entry of ChatGPT -a conversational artificial intelligence (AI) tool that uses a deep learning model to generate human-like text response based on provided input-it has become crucial for HEIs to be exposed to the implications of AI-based tools on students' learning outcomes, commonly measured using an assessment-based approach to improve program quality, teaching effectiveness, and other learning support. An empirical study has been conducted to test the ChatGPT capability of solving a variety of assignments (from different level courses of undergraduate degree programs) to compare its performance with the highest scored student(s). Further, the ChatGPT-generated assignments were tested using the best-known tools for plagiarism detection to determine whether they could pass the academic integrity tests, including Turnitin, GPTZero, and Copyleaks. The study reported the limitations of the Bot and highlighted the implications of the newly launched AI-based ChatGPT in academia, which calls for HEIs' managers and regulators to revisit their existing practices used to monitor students' learning progress and improve their educational programs.

Large Language Models (LLMs) and conversational-style generative artificial intelligence (AI) are causing major disruption to higher education pedagogy. The emergence of tools like ChatGPT has raised concerns about plagiarism detection but also presents opportunities for educators to leverage AI to build supportive learning environments. In this commentary, we explore the potential of AI-augmented teaching and learning practice in higher education, discussing both the productive affordances and challenges associated with these technologies. We offer instructional advice for writing instructional text to guide the generation of quality outputs from AI models, as well as a case study to illustrate using AI for assessment design. Ultimately, we suggest that AI should be seen as one tool among many that can be used to enhance teaching and learning outcomes in higher education.

Journal of University Teaching & Learning Practice

Can ChatGPT pass graduate-level instructional design assignments? Potential implications of artificial intelligence in education and a call to action.

This article investigates an artificial intelligence language model, ChatGPT, and its ability to complete graduate-level instructional design assignments. The approach subjected ChatGPT to a needs, task, and learner analysis for a 12th-grade media literacy module and benchmarked its performance by expert evaluation and measurements via grading rubrics. Initial results show ChatGPT's ability to write graduate-level instructional design assignments but with some challenges and frustration in the bot's ability to customize for location and school-specifics. Key benefits of the findings include new ways to challenge instructional design students, faculty customization of future assignments, and the potential of AI as a collaboration tool in the instructional design and educational process.

As artificial intelligence proliferates, so do associated hopes and fears. This study explores such tensions within South African higher education following ChatGPT's launch, analyzing perceived threats alongside opportunities for responsibly harnessing benefits. Adopting a socio-technical framework recognizing technology's interdependence with social systems, it investigates institutional uncertainties regarding unchecked AI adoption. Whilst findings reveal significant concerns about impartiality, critical faculties and employment impacts, evidence also indicates artificial intelligence, if transparently governed, could enrich scholarship. However, effectively leveraging such opportunities necessitates updated policies fostering accountable assimilation rather than reactionary resistance. Through a systematic literature analysis, this study contends that conceptualizing tools like ChatGPT as amplifying rather than automating academia's technical capacities, with protocols ensuring human oversight, provides the most constructive paradigm. Rather than technologies threatening academics' relevance, an agile, ethical integration strategy upholding rigorous pedagogical, research and assessment standards while expanding inclusion and insight is advocated. The conclusions caution against vilifying innovation but urge policymakers to foster frameworks transparently aligning artificial intelligence's trajectory with academic integrity. Ultimately, the socio-technical approach promoted underscores technological disruption's potential, if governed accountably, to strengthen rather than undermine scholarly excellence.

Does ChatGPT play a double-edged sword role in the field of higher education? An in-depth exploration of the factors affecting student performance.

The application of generative artificial intelligence in the field of education has been receiving increasing attention, with the performance of chatbot ChatGPT being particularly prominent. This study aims to explore in depth the performance impact on higher education students utilizing ChatGPT. To this end, we conducted a survey on 448 university students and employed the partial-least squares (PLS) method of structural equation modeling for data analysis. The results indicate that all eight hypothetical paths posited in this study were supported, and surprisingly, the hypothesis that technology characteristics have a direct effect on performance impact was supported. Moreover, the study found that overall quality is a crucial factor determining performance impact. Overall quality indirectly affects performance impact through task-technology fit, technology characteristics, and compatibility, among which the mediating effect of compatibility is most significant, followed by technology characteristics. This study offers practical recommendations for students on the proper use of ChatGPT during the learning process and assists developers in enhancing the services of the ChatGPT system.

The recent high performance of ChatGPT on several standardized academic tests has thrust the topic of artificial intelligence (AI) into the mainstream conversation about the future of education. As deep learning is poised to shift the teaching paradigm, it is essential to have a clear understanding of its effects on the current education system to ensure sustainable development and deployment of AI-driven technologies at schools and universities. This research aims to investigate the potential impact of AI on education through review and analysis of the existing literature across three major axes: applications, advantages, and challenges. Our review focuses on the use of artificial intelligence in collaborative teacher-student learning, intelligent tutoring systems, automated assessment, and personalized learning. We also report on the potential negative aspects, ethical issues, and possible future routes for AI implementation in education. Ultimately, we find that the only way forward is to embrace the new technology, while implementing guardrails to prevent its abuse.

Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S.

ChatGPT is revolutionizing the field of higher education by leveraging deep learning models to generate human-like content. However, its integration into academic settings raises concerns regarding academic integrity, plagiarism detection, and the potential impact on critical thinking skills. This article presents a study that adopts a thing ethnography approach to understand ChatGPT's perspective on the challenges and opportunities it represents for higher education. The research explores the potential benefits and limitations of ChatGPT, as well as mitigation strategies for addressing the identified challenges. Findings emphasize the urgent need for clear policies, guidelines, and frameworks to responsibly integrate ChatGPT in higher education. It also highlights the need for empirical research to understand user experiences and perceptions. The findings provide insights that can guide future research efforts in understanding the implications of ChatGPT and similar Artificial Intelligence (AI) systems in higher education. The study concludes by highlighting the importance of thing ethnography as an innovative approach for engaging with intelligent AI systems and calls for further research to explore best practices and strategies in utilizing Generative AI for educational purposes.

The purpose of this study was to determine university students' experiences with the use of ChatGPT in online courses. The sample consisted of 84 associate degree students from a state university in Turkey. A multi-method approach was used in the study. Although quantitative data were collected using the Chatbot Usability Scale, qualitative data were collected using a semi-structured interview form that we developed. The data were analysed using descriptive and content analysis methods. According to the findings, ChatGPT exhibits advantages such as a user-friendly interface and fast, concise, relevant responses. Moreover, emphasizing its contribution to the learning process, the information provided was sufficient and topic-oriented. The understandability of the chatbot's functions and the clarity of their communication were emphasized. However, there are disadvantages such as performance issues, frequency of errors and the risk of providing misleading information. Concerns have also been raised about the potential difficulties chatbots may face in ambiguous conversations and providing insufficient information on privacy issues. In conclusion, ChatGPT is recognised as a potentially valuable tool in education based on positive usability impressions; however, more research is needed for its safe use.Implications for practice or policy center dot Based on positive usability impressions, students and instructors can use ChatGPT to support educational activities.center dot ChatGPT can promote and enhance students' personalised learning experiences.center dot ChatGPT can be used in all higher education courses.center dot Users should be cautious about the accuracy and reliability of the answers provided by ChatGPT.center dot Decision-makers should take precautions against risks such as privacy, ethics, confidentiality and security that may arise from using artificial intelligence in education.

BackgroundThe transformative potential of artificial intelligence (AI) in higher education is evident, with conversational models like ChatGPT poised to reshape teaching and assessment methods. The rapid evolution of AI models requires a continuous evaluation. AI-based models can offer personalized learning experiences but raises accuracy concerns. MCQs are widely used for competency assessment. The aim of this study was to evaluate ChatGPT performance in medical microbiology MCQs compared to the students' performance.MethodsThe study employed an 80-MCQ dataset from a 2021 medical microbiology exam at the University of Jordan Doctor of Dental Surgery (DDS) Medical Microbiology 2 course. The exam contained 40 midterm and 40 final MCQs, authored by a single instructor without copyright issues. The MCQs were categorized based on the revised Bloom's Taxonomy into four categories: Remember, Understand, Analyze, or Evaluate. Metrics, including facility index and discriminative efficiency, were derived from 153 midterm and 154 final exam DDS student performances. ChatGPT 3.5 was used to answer questions, and responses were assessed for correctness and clarity by two independent raters.ResultsChatGPT 3.5 correctly answered 64 out of 80 medical microbiology MCQs (80%) but scored below the student average (80.5/100 vs. 86.21/100). Incorrect ChatGPT responses were more common in MCQs with longer choices (p = 0.025). ChatGPT 3.5 performance varied across cognitive domains: Remember (88.5% correct), Understand (82.4% correct), Analyze (75% correct), Evaluate (72% correct), with no statistically significant differences (p = 0.492). Correct ChatGPT responses received statistically significant higher average clarity and correctness scores compared to incorrect responses.ConclusionThe study findings emphasized the need for ongoing refinement and evaluation of ChatGPT performance. ChatGPT 3.5 showed the potential to correctly and clearly answer medical microbiology MCQs; nevertheless, its performance was below-bar compared to the students. Variability in ChatGPT performance in different cognitive domains should be considered in future studies. The study insights could contribute to the ongoing evaluation of the AI-based models' role in educational assessment and to augment the traditional methods in higher education.

Development of an assessment scale for measurement of usability and user experience characteristics of Bing Chat conversational AI.

After the introduction of the ChatGPT conversational artificial intelligence (CAI) tool in November 2022, there has been a rapidly growing interest in the use of such tools in higher education. While the educational uses of some other information technology (IT) tools (including collaboration and communication tools, learning management systems, chatbots, and videoconferencing tools) have been frequently evaluated regarding technology acceptance and usability attributes of those technologies, similar evaluations of CAI tools and services like ChatGPT, Bing Chat, and Bard have only recently started to appear in the scholarly literature. In our study, we present a newly developed set of assessment scales that are related to the usability and user experiences of CAI tools when used by university students, as well as the results of evaluation of these assessment scales specifically regarding the CAI Bing Chat tool (i.e., Microsoft Copilot). The following scales were developed and evaluated using a convenience sample (N = 126) of higher education students: Perceived Usefulness, General Usability, Learnability, System Reliability, Visual Design and Navigation, Information Quality, Information Display, Cognitive Involvement, Design Appeal, Trust, Personification, Risk Perception, and Intention to Use. For most of the aforementioned scales, internal consistency (Cronbach alpha) was in the range from satisfactory to good, which implies their potential usefulness for further studies of related attributes of CAI tools. A stepwise linear regression revealed that the most influential predictors of Intention to Use Bing Chat (or ChatGPT) in the future were the usability variable Perceived Usefulness and two user experience variables-Trust and Design Appeal. Also, our study revealed that students' perceptions of various specific usability and user experience characteristics of Bing Chat were predominantly positive. The evaluated assessment scales could be beneficial in further research that would include other CAI tools like ChatGPT/GPT-4 and Bard.

Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review of the literature.

This study examines the role of ChatGPT as a writing assistant in academia through a systematic literature review of the 30 most relevant articles. Since its release in November 2022, ChatGPT has become the most debated topic among scholars and is also being used by many users from different fields. Many articles, reviews, blogs, and opinion essays have been published in which the potential role of ChatGPT as a writing assistant is discussed. For this systematic review, 550 articles published six months after ChatGPT’s release (December 2022 to May 2023) were collected based on specific keywords, and the final 30 most relevant articles were finalized through PRISMA flowchart. The analyzed literature identifies different opinions and scenarios associated with using ChatGPT as a writing assistant and how to interact with it. Findings show that artificial intelligence (AI) in education is a part of the ongoing development process, and its latest chatbot, ChatGPT is a part of it. Therefore, the education process, particularly academic writing, has both opportunities and challenges in adopting ChatGPT as a writing assistant. The need is to understand its role as an aid and facilitator for both the learners and instructors, as chatbots are relatively beneficial devices to facilitate, create ease and support the academic process. However, academia should revisit and update students’ and teachers’ training, policies, and assessment ways in writing courses for academic integrity and originality, like plagiarism issues, AI-generated assignments, online/home-based exams, and auto-correction challenges. © 2023 by authors; licensee CEDTECH by Bastas.

Purpose: This research was developed to identify artificial intelligence (AI) opportunities and challenges in higher education. Design/methodology/approach: This qualitative research was developed using the six-step thematic analysis method (Braun and Clark, 2006). Participants in this study were AI PhD students from Tehran University in 2022–2023. Purposive sampling was used to select the participants; a total of 15 AI PhD students, who were experts in this field, were selected and interviews were conducted. Findings: The authors considered the opportunities that AI creates for higher education in eight secondary subthemes (for faculty members, for students, in the teaching and learning process, for assessment, the development of educational structures, the development of research structures, the development of management structures and the development of academic culture). Correspondingly, The authors identified and categorized the challenges that AI creates for higher education. Research limitations/implications: Concerning the intended research, several limitations are significant. First, the statistical population was limited, and only people with characteristics such as being PhD students, studying at Tehran University and being experts in AI could be considered the statistical population. Second, caution should be exercised when generalizing the results due to the limited statistical population (PhD students from Tehran University). Third, the problem of accessing some students due to their participation in research grants, academic immigration, etc. Originality/value: The innovation of the current research is that the authors identified the opportunities and challenges that AI creates for higher education at different levels. The findings of this study also contribute to the enrichment of existing knowledge in the field regarding the effects of AI on the future of higher education, as researchers need more understanding of AI developments in the future of higher education. © 2023, Emerald Publishing Limited.

de Vicente-Yague-Jara, M.-I., Lopez-Marti­nez, O., Navarro-Navarro, V., & Cuellar-Santiago, F.

The main objective of the research is to study the creative potential of Artificial Intelligence (AI) for writing skills in an educational context. The research aims to provide evidence on the use of AI and contribute to its integration in the classroom as a support for the teaching-learning process. Two types of research designs were established: a descriptive and comparative non-experimental quantitative research, and a quasi-experimental pretest-posttest study. The sample consisted of 20 AI systems and 193 university students who were given Games 2 and 3 of the Spanish PIC-A test (“Creative Imagination Test for Adults�). The students repeated the games, assisted by ChatGPT, to compare the possible improvement of their productions. The findings reveal statistically significant differences between the AIs and the students in the indicators of fluency, flexibility, and narrative originality in Game 2. Furthermore, significant differences are found between students’ pre-test and post-test scores in fluency, flexibility, and narrative originality in Game 2 and in fluency in Game 3. Finally, the assistance provided by AI in writing tasks and verbal creativity is highlighted, and this should be considered in language teaching; in any case, AI cannot replace human intelligence and creativity. © 2023, Oxbridge Publishing House Ltd. All rights reserved.

Media coverage suggests that ChatGPT can pass examinations based on multiple choice questions (MCQs), including those used to qualify doctors, lawyers, scientists etc. This poses a potential risk to the integrity of those examinations. We reviewed current research evidence regarding the performance of ChatGPT on MCQ-based examinations in higher education, along with recommendations for how educators might address challenges and benefits arising from these data. 53 studies were included, covering 114 question sets, totalling 49014 MCQs. Free versions of ChatGPT based upon GPT-3/3.5 performed better than random guessing but failed most examinations, performing significantly worse than the average human student. GPT-4 passed most examinations with a performance that was on a par with human subjects. These findings indicate that all summative MCQ-based assessments should be conducted under secure conditions with restricted access to ChatGPT and similar tools, particularly those examinations which assess foundational knowledge. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

The release of ChatGPT has sparked significant academic integrity concerns in higher education. However, some commentators have pointed out that generative artificial intelligence (AI) tools such as ChatGPT can enhance student learning, and consequently, academics should adapt their teaching and assessment practices to embrace the new reality of living, working, and studying in a world where AI is freely available. Despite this important debate, there has been very little academic literature published on ChatGPT and other generative AI tools. This article uses content analysis to examine news articles (N=100) about how ChatGPT is disrupting higher education, concentrating specifically on Australia, New Zealand, the United States, and the United Kingdom. It explores several key themes, including university responses, academic integrity concerns, the limitations and weaknesses of AI tool outputs, and opportunities for student learning. The data reveals mixed public discussion and university responses, with a focus mainly on academic integrity concerns and opportunities for innovative assessment design. There has also been a lack of public discussion about the potential for ChatGPT to enhance participation and success for students from disadvantaged backgrounds. Similarly, the student voice is poorly represented in media articles to date. This article considers these trends and the impact of AI tools on student learning at university. © 2023. Miriam Sullivan, Andrew Kelly, and Paul McLaughlan.

AI-based tools such as ChatGPT and GPT-4 are currently changing the university landscape and in many places, the consequences for future forms of teaching and examination are already being discussed. In order to create an empirical basis for this, a nationwide survey of students was carried out in order to analyse the use and possible characteristics of AI-based tools that are important to students. The aim of the quantitative study is to be able to draw conclusions about how students use such AI tools. A total of more than 6300 students across Germany took part in the anonymous survey. The results of this quantitative analysis make it clear that almost two-thirds of the students surveyed use or have used AI-based tools as part of their studies. In this context, almost half of the students explicitly mention ChatGPT or GPT-4 as a tool they use. Students of engineering sciences, mathematics and natural sciences use AI-based tools most frequently. A differentiated examination of the usage behaviour makes it clear that students use AI-based tools in a variety of ways. Clarifying questions of understanding and explaining subject-specific concepts are the most relevant reasons for use in this context. © 2023, The Author(s).

Humanities and Social Sciences Communications

Not quite eye to A.I.: Student and teacher perspectives on the use of generative artificial intelligence in the writing process.

Generative artificial intelligence (GenAI) can be used to author academic texts at a similar level to what humans are capable of, causing concern about its misuse in education. Addressing the role of GenAI in teaching and learning has become an urgent task. This study reports the results of a survey comparing educators' (n = 68) and university students' (n = 158) perceptions on the appropriate use of GenAI in the writing process. The survey included representations of user prompts and output from ChatGPT, a GenAI chatbot, for each of six tasks of the writing process (brainstorming, outlining, writing, revising, feedback, and evaluating). Survey respondents were asked to differentiate between various uses of GenAI for these tasks, which were divided between student and teacher use. Results indicate minor disagreement between students and teachers on acceptable use of GenAI tools in the writing process, as well as classroom and institutional-level lack of preparedness for GenAI. These results imply the need for explicit guidelines and teacher professional development on the use of GenAI in educational contexts. This study can contribute to evidence-based guidelines on the integration of GenAI in teaching and learning.

International Journal of Educational Technology in Higher Education

The artificial intelligence chatbot ChatGPT was used to answer questions from final exams administered in two general chemistry courses, including questions with closed-response format and with open-response format. For closed-response questions, ChatGPT was very capable at identifying the concept even when the question included a great deal of chemical symbolism. However, ChatGPT's success at solving problems was only 44%, a value well below the class average of 69%. On open-response questions, ChatGPT's responses displayed strong language processing ability with higher performance on questions that could be solved with more generalizable information compared to questions that required specific skills, especially when those topics or skills were primarily found in lecture. Incorrect responses and flawed explanations were often logically sound and would be persuasive to a novice. The chatbot is currently ill-equipped to provide reliable answers or explanations to students for many representative exam questions, but a potential use is to create assignments in which students analyze and improve ChatGPT's responses.

Comparing the performance of college chemistry students with ChatGPT for calculations involving acids and bases.

Clark, T. M., Anderson, E., Dickson-Karn, N. M., Soltanirad, C., & Tafini, N.

Student performance on open-response calculations involving acid and base solutions before and after instruction in general chemistry and analytical chemistry courses was compared with the output from the artificial intelligence chatbot ChatGPT. Applying a theoretical model of expertise for problem solving that includes problem conceptualization, problem strategy, and solution, it is found that students errors following instruction primarily involved problem conceptualization and the misapplication of heuristics like the Henderson-Hasselbalch equation When the same problems were used as input to ChatGPT the responses were comparable to worked examples found in general chemistry textbooks in terms of length and detail and usually displayed strong problem conceptualization. Response accuracy of the chatbot varied greatly for different topics, being best for calculations of pH for a strong acid or strong base and much lower for more complex problems involving titrations or aqueous salts. Chatbot and student errors differed in that the chatbot did not misapply heuristics but did make mathematical errors uncommon for students. The variability in the correctness of ChatGPT's responses and the nature of its errors vis-à-vis students will influence its potential use as an instructional resource for calculations involving acids and bases.

The world has evolved dramatically in the last several decades and continues to do so. ChatGPT has sparked intense speculation and interest among academic stakeholders about how this emerging technology will transform higher education. In particular, there is ambiguity among researchers and teaching professionals on how to deal with the integration of natural language processing models (e.g., ChatGPT) practically and ethically. The use of ChatGPT is an emerging area of interest that presently lacks the perspective of students on this new technology. Thus, an exploratory study design was applied as a methodological frame to investigate the problem empirically. Semi-structured interview data was gathered from current university students to thematically analyze the phenomenon. The thematic analysis revealed three themes: (1) support for autonomous learning, (2) digital and artificial tutoring, and (3) academic misconduct and ethical considerations. The article presents theoretical and managerial implications and advances the discussion about natural language processing models in higher education. Moreover, the study contributes to the body of knowledge by closing a theoretical gap in the literature on how university students utilize artificial chatbots for and during their studies. © 2023 by the authors

International Journal of Information and Education Technology

The integration of technology in education has become ever more prioritized since the COVID-19 pandemic. Chat Generative Pre-Trained Transformer (ChatGPT) is an artificial intelligence technology that generates conversational interactions to user prompts. The trained model can answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. The functionality of ChatGPT in answering chemistry assessment questions requires investigation to ascertain its potential impact on learning and assessment. Two chemistry-focused modules in year 1 and year 2 of a pharmaceutical science program are used to study and evaluate ChatGPT-generated responses in relation to the end-of-year exam assessments. For questions that focused on knowledge and understanding with “describe� and “discuss� verbs, the ChatGPT generated responses. For questions that focused on application of knowledge and interpretation with nontext information, the ChatGPT technology reached a limitation. A further analysis of the quality of responses is reported in this study. ChatGPT is not considered a high-risk technology tool in relation to cheating. Similar to the COVID-19 disruption, ChatGPT is expected to provide a catalyst for educational discussions on academic integrity and assessment design. © 2023 The Authors. Published by American Chemical Society and Division of Chemical Education, Inc.

Purpose: The paper aims to evaluate the ways ChatGPT is going to disrupt tourism education and research. Design/methodology/approach: This is a conceptual paper. Findings: ChatGPT has the potential to revolutionize tourism education and research because it can do what students and researchers should do, namely, generate text (assignments and research papers). Universities will need to reevaluate their teaching and assessment strategies and incorporate generative language models in teaching. Publishers will need to be more receptive toward manuscripts that are partially generated by artificial intelligence. In the future, digital teachers and research assistants will take over many of the cognitive tasks of tourism educators and researchers. Originality/value: To the authors’ best knowledge, this is one of the first academic papers that investigates the implications of ChatGPT to tourism education and research. © 2023, Stanislav Ivanov and Mohammad Soliman.

This academic research explores the opportunities and challenges of using Chat Generative Pre-trained Transformer (ChatGPT) in the English Language Teaching (ELT) in a university in Oman. Recent researches have proven that ChatGPT provides various benefits and opportunities in education. Students can gain from different problem-solving scenarios provided by ChatGPT. Moreover, teachers will be freed from heavy marking-load allowing them to spend more time on lesson planning (Hong, 2023). The study aims to find out the possible prospects and challenges of employing ChatGPT in the teaching and learning of English, which naturally influence research and educational policy making as well. The study adopted qualitative methods for data collection and analysis, using literature review and semi-structured interviews. The findings show that the use of ChatGPT in ELT has been much more beneficial and promising, as evidenced by the limited research available. However, there are potential risks associated with over-reliance on ChatGPT and the need for appropriate training and guidance for teachers and students. The study suggests that further research is needed to explore the full potential of ChatGPT in ELT and to address the challenges associated with its. © 2023 by University of Niš, Serbia.

The Journal of Teaching English for Specific and Academic Purposes

(1) Background: AI (artificial intelligence) chatbots have been widely applied. ChatGPT could enhance individual learning capabilities and clinical reasoning skills and facilitate students' understanding of complex concepts in healthcare education. There is currently less emphasis on its application in nursing education. The application of ChatGPT in nursing education needs to be verified. (2) Methods: A descriptive study was used to analyze the scores of ChatGPT on the registered nurse license exam (RNLE) in 2022~2023, and to explore the response and explanations of ChatGPT. The process of data measurement encompassed input sourcing, encoding methods, and statistical analysis. (3) Results: ChatGPT promptly responded within seconds. The average score of four exams was around 51.6 to 63.75 by ChatGPT, and it passed the RNLE in 2022 1st and 2023 2nd. However, ChatGPT may generate misleading or inaccurate explanations, or it could lead to hallucination; confusion or misunderstanding about complicated scenarios; and languages bias. (4) Conclusions: ChatGPT may have the potential to assist with nursing education because of its advantages. It is recommended to integrate ChatGPT into different nursing courses, to assess its limitations and effectiveness through a variety of tools and methods.

French, F., Levi, D., Maczo, C., Simonaityte, A., Triantafyllidis, S., & Varda, G.

Educators and students have shown significant interest in the potential for generative artificial intelligence (AI) technologies to support student learning outcomes, for example, by offering personalized experiences, 24 h conversational assistance, text editing and help with problem-solving. We review contemporary perspectives on the value of AI as a tool in an educational context and describe our recent research with undergraduate students, discussing why and how we integrated OpenAI tools ChatGPT and Dall-E into the curriculum during the 2022–2023 academic year. A small cohort of games programming students in the School of Computing and Digital Media at London Metropolitan University was given a research and development assignment that explicitly required them to engage with OpenAI. They were tasked with evaluating OpenAI tools in the context of game development, demonstrating a working solution and reporting on their findings. We present five case studies that showcase some of the outputs from the students and we discuss their work. This mode of assessment was both productive and popular, mapping to students’ interests and helping to refine their skills in programming, problem-solving, critical reflection and exploratory design. © 2023 by the authors.

This research explored the potential of artificial intelligence (AI)-assisted learning using ChatGPT in an engineering course at a university in South-east Asia. The study investigated the benefits and challenges that students may encounter when utilising ChatGPT-3.5 as a learning tool. This research developed an AI-assisted learning flow that empowers learners and lecturers to integrate ChatGPT into their teaching and learning processes. The flow was subsequently used to validate and assess a variety of exercises, tutorial tasks and assessment-like questions for the course under study. Introducing a self-rating system allowed the study to facilitate users in assessing the generative responses. The findings indicate that ChatGPT has significant potential to assist students; however, there is a necessity for training and offering guidance to students on effective interactions with ChatGPT. The study contributes to the evidence of the potential of AI-assisted learning and identifies areas for future research in refining the use of AI tools to better support students' educational journey. Implications for practice or policy • Educators and administrators could review the usage of ChatGPT in an engineering technology course and study the implications of generative AI tools in higher education. • Academics could adapt and modify the proposed AI-assisted learning flow in this paper to suit their classroom. • Students can review and adopt the proposed AI-assisted learning flow in this paper for their studies. • Researchers could follow up on the application of ChatGPT in teaching and learning: teaching quality and student experience, academic integrity and assessment design. © Articles published in the Australasian Journal of Educational Technology (AJET) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant AJET right of first publication under CC BY-NC-ND 4.0.

ChatGPT (GPT-3.5) as an assistant tool in microbial pathogenesis studies in Sweden: A cross-sectional comparative study.

ChatGPT (GPT-3.5) has entered higher education and there is a need to determine how to use it effectively. This descriptive study compared the ability of GPT-3.5 and teachers to answer questions from dental students and construct detailed intended learning outcomes. When analyzed according to a Likert scale, we found that GPT-3.5 answered the questions from dental students in a similar or even more elaborate way compared to the answers that had previously been provided by a teacher. GPT-3.5 was also asked to construct detailed intended learning outcomes for a course in microbial pathogenesis, and when these were analyzed according to a Likert scale they were, to a large degree, found irrelevant. Since students are using GPT-3.5, it is important that instructors learn how to make the best use of it both to be able to advise students and to benefit from its potential. 2023 Korea Health Personnel Licensing Examination Institute This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Journal of Educational Evaluation for Health Professions

Was this title generated by ChatGPT? Considerations for artificial intelligence text-generation software programs for chemists and chemistry educators.

Generative artificial intelligence (GAI) is here; now what? In this commentary, we discuss the potential impacts of GAI text-based systems for the chemistry community. The recent launch of ChatGPT, a free GAI text-based system by OpenAI, has sparked concerns regarding academic integrity and student assessment across all educational levels. However, the capabilities of these systems will impact more than the teaching and learning of chemistry; GAI systems can serve students, faculty, and administrators for teaching and learning, research, and professional activities. Herein we explore various ways students and faculty might use GAI systems, identify potential benefits and risks, and consider equity and accessibility issues. We hope to inspire productive discussions on leveraging GAI technology's capabilities while recognizing its limitations. © 2023 American Chemical Society and Division of Chemical Education, Inc.

AI-enabled medical education: Threads of change, promising futures, and risky realities across four potential future worlds.

Knopp, M. I., Warm, E. J., Weber, D., Kelleher, M., Kinnear, B., Schumacher, D. J., Santen, S. A., Mendonca, E., & Turner, L.

Background: The rapid trajectory of artificial intelligence (AI) development and advancement is quickly outpacing society's ability to determine its future role. As AI continues to transform various aspects of our lives, one critical question arises for medical education: what will be the nature of education, teaching, and learning in a future world where the acquisition, retention, and application of knowledge in the traditional sense are fundamentally altered by AI? Objective: The purpose of this perspective is to plan for the intersection of health care and medical education in the future. Methods: We used GPT-4 and scenario-based strategic planning techniques to craft 4 hypothetical future worlds influenced by AI's integration into health care and medical education. This method, used by organizations such as Shell and the Accreditation Council for Graduate Medical Education, assesses readiness for alternative futures and effectively manages uncertainty, risk, and opportunity. The detailed scenarios provide insights into potential environments the medical profession may face and lay the foundation for hypothesis generation and idea-building regarding responsible AI implementation. Results: The following 4 worlds were created using OpenAI’s GPT model: AI Harmony, AI conflict, The world of Ecological Balance, and Existential Risk. Risks include disinformation and misinformation, loss of privacy, widening inequity, erosion of human autonomy, and ethical dilemmas. Benefits involve improved efficiency, personalized interventions, enhanced collaboration, early detection, and accelerated research. Conclusions: To ensure responsible AI use, the authors suggest focusing on 3 key areas: developing a robust ethical framework, fostering interdisciplinary collaboration, and investing in education and training. A strong ethical framework emphasizes patient safety, privacy, and autonomy while promoting equity and inclusivity. Interdisciplinary collaboration encourages cooperation among various experts in developing and implementing AI technologies, ensuring that they address the complex needs and challenges in health care and medical education. Investing in education and training prepares professionals and trainees with necessary skills and knowledge to effectively use and critically evaluate AI technologies. The integration of AI in health care and medical education presents a critical juncture between transformative advancements and significant risks. By working together to address both immediate and long-term risks and consequences, we can ensure that AI integration leads to a more equitable, sustainable, and prosperous future for both health care and medical education. As we engage with AI technologies, our collective actions will ultimately determine the state of the future of health care and medical education to harness AI's power while ensuring the safety and well-being of humanity. © 2023 JMIR Publications Inc.

Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. G., Wahyuni, S., & Octavia, A.

This paper examines the determinants that drive ChatGPT use in learning among Indonesian Higher Education Institutions (HEIs) students. A proposed model based on the unified theory of acceptance and use of technology model-2 (UTAUT2) was used in the context of the study. A pilot study was done prior to the main data collection to examine the reliability of the instrument. For the structural model assessment, 1117 responses were analyzed through Partial Least Square Structural Equation Modeling (PLS-SEM) and Importance-Performance Analysis (IPMA). Most hypotheses are confirmed by the significant results reported through the PLS-SEM. The strongest determinant of Behavioral Intention (BI) to use ChatGPT in learning was Facilitating Conditions (FC). ChatGPT use (GPTU) was most significantly predicted by BI. However, one hypothesis was not supported; the insignificant role of Effort Expectancy (EE) on BI was revealed. Through IPMA, FC had the most significant importance for BI, while BI was the most important determinant for GPTU. Besides, BI obtains the highest performance in the IPMA procedure. This study addresses a UTAUT model by evaluating ChatGPT acceptance and use among HEIs students in Indonesia. Findings could facilitate policymakers with insights into the determinants and initiate effective and efficient policies to improve artificial intelligence use in education, specifically ChatGPT. © 2023 The Author(s)

Exploring artificial intelligence in the Nigerian medical educational space: An online cross-sectional study of perceptions, risks and benefits among students and lecturers from ten universities.

Oluwadiya, K. S., Adeoti, A. O., Agodirin, S. O., Nottidge, T. E., Usman, M. I., Gali, M. B., Onyemaechi, N. O., Ramat, A. M., Adedire, A., & Zakari, L. Y.

Background: The impact of artificial intelligence (AI) has been compared to that of the Internet and printing, evoking both apprehension and anticipation in an uncertain world. Objective: This study aimed to explore the perceptions of medical students and faculty members from ten universities across Nigeria regarding AI. Methods: Using Google Forms and WhatsApp, a cross-sectional online survey was administered to clinical year medical students and their lecturers from ten medical schools representing all the six geopolitical zones of Nigeria. Results: The survey received 1003 responses, of which 708 (70.7%) were from students and 294 (29.3%) were from lecturers. Both groups displayed an average level of knowledge, with students (Median:4, range -5 to 12) significantly outperforming lecturers (Median:3, range -5 to 15). Social media (61.2%) was the most common form of first contact with AI. Participants demonstrated a favourable attitude towards AI, with a median score of 6.8 out of 10. Grammar checkers (62.3%) were the most commonly reported AI tool used, while ChatGPT (43.6%) was the most frequently mentioned dedicated AI tool. Students were significantly more likely than lecturers to have used AI tools in the past but <5% of both groups had received prior AI training. Excitement about the potential of AI slightly outweighed concerns regarding future risks. A significantly higher proportion of students compared to lecturers believed that AI could dehumanise health care (70.6% vs. 60.8%), render physicians redundant (57.6% vs. 34.7%), diminish physicians' skills (79.3% vs. 71.3%) and ultimately harm patients (28.6% vs. 20.6%). Conclusion: The simultaneous fascination and apprehension with AI observed among both lecturers and students in our study mirrors the global trend. This finding was particularly evident in students who, despite possessing greater knowledge of AI compared to their lecturers, did not exhibit a corresponding reduction in their fear of AI. © 2023 Nigerian Postgraduate Medical Journal.

Aim/Purpose The purpose of this article is to provide an overview and analysis of the emerg ing research landscape surrounding the integration of ChatGPT into education. The main problem appears to be that this is a new, rapidly developing research area for which there is no comprehensive synthesis of the current literature. The aim of the article is to fill this gap by conducting a timely bibliometric study to map publication trends, influential works, themes, and opportunities, thus representing the growth and structure of ChatGPT educational research. Background This article addresses the issue of the lack of a comprehensive synthesis of the new research on ChatGPT in education by conducting a bibliometric analysis. Specifically, the authors use statistical and network analysis techniques to examine the patterns of publication, citation, and keywords and map the growth, contributions, themes, structure, and opportunities in this evolving field. The bibliometric approach provides a comprehensive, evidence-based overview of the current state of the literature to uncover trends and gaps and help researchers improve their understanding of appropriate and effective applications of ChatGPT in educational contexts. Methodology The authors used bibliometric analysis as the primary method to summarize the new research on ChatGPT in education. We searched the database of the Web of Science Core Collection to find 51 relevant documents from 2023 that included ChatGPT in the title and were classified as ‘educational research.’ The sample consisted of these 51 documents, including articles, early access articles, editorials, reviews, and letters. Statistical techniques examined publication, citation, and keyword patterns. Network analysis visualized citation and cooccurrence networks to reveal intellectual structure. The multifaceted bibliometric approach allowed a comprehensive study of the sample from a productive, conceptual, and intellectual perspective. Contribution This article conducts comprehensive bibliometric analysis of this emerging re search area and synthesizes publication, citation, and keyword data to map the growth and structure of the literature. The results reveal important trends, such as the rapid growth of publications since the release of ChatGPT, initial authorship patterns, the focus on higher education applications, and distinct research clusters around pedagogical, ethical, and assessment issues. Visualizing citation networks identifies seminal studies while mapping co-occurrence clarifies conceptual relationships between topics. The comparative analysis highlights the differences between document types, topics, and time periods. Knowledge mapping highlights gaps in the literature, such as lack of focus on K-12 contexts, and highlights opportunities for further research. Findings Key findings from this bibliometric analysis of the emerging research landscape surrounding ChatGPT integration in education include the following: • Since ChatGPT was released in late 2022, the number of releases has increased significantly, indicating rapid growth in this emerging space. • The most cited authors initially came primarily from Anthropic, but over time, the citations spread throughout the research community. • The topics focused primarily on higher education applications, with a clear focus on pedagogical strategies, ethical risks, and implications for assessment. • Citation networks visualized seminal studies, while the co-occurrence of keywords clarified conceptual connections. • Gaps such as applications in the K-12 context were uncovered, and opportunities for further research were highlighted. • The literature is rapidly evolving and requires ongoing monitoring of the development of this field. In general, the analysis presents the productivity, contributors, themes, structure, and opportunities in this emerging area around the integration of ChatGPT in education based on current scientific evidence. The key findings focus on the growing early interest, gaps and developments that can provide insight for researchers and educators. Recommendations Practitioners should carefully integrate ChatGPT into education based on new for Practitioners evidence, carefully assess contextual applicability, and proactively develop guide lines for ethical and equitable implementation. Ongoing advice, impact monitoring, and research partnerships are crucial to informing best practices. Educators must be vigilant for risks such as privacy, student well-being, and competence impairment while staying abreast of advances in knowledge to dynamically adapt integration strategies. The introduction should empower diverse learners through measured, integrative approaches based on continuous contextual analysis and ethical principles. Recommendations This article recommends that researchers conduct more studies in under- for Researchers researched contexts, use multiple methods to capture nuanced impacts, increase focus on responsible integration strategies, develop tailored assessments, conduct interdisciplinary collaborations, monitor long-term adoption, mix with interactive explain and publish open access technologies, help guide adoption pathways through actionable studies, and synthesize the exponentially growing literature through updated systematic reviews. Impact on Society The rapid publication growth and prevailing optimism suggest that the integration of ChatGPT into education will accelerate, increasing the need for rigorous research that guides ethical, responsible innovations that avoid risks and improve outcomes in all educational contexts. The findings have broader implications for guiding adoption trajectories through ongoing evidence synthesis and expanded investigations in under-researched areas to address knowledge gaps. Ultimately, continued monitoring and updated guidance are critical to ensure that ChatGPT’s educational penetration progresses carefully by maximizing benefits and minimizing harms in rapidly evolving AI-powered learning ecosystems. Future Research Based on the basic mapping provided by this paper, recommended research directions include longitudinal impact studies, research tailored to underresearched contexts such as K-12, qualitative research to capture stakeholder perspectives, development and testing of AI-calibrated assessments as well as explorations that combine conversational and interactive learning technologies, updated systematic reviews, and co-designed implementation research that explain pedagogical strategies that ethically unlock learning potential while mitigating risks in diverse educational environments. Such multilayered tracking can provide critical insights to guide context-specific, responsible ChatGPT integration and monitor impact within rapidly evolving AI-powered education ecosystems. © (2023), (Informing Science Institute). All Rights Reserved.

Journal of Information Technology Education: Innovations in Practice

Is the education system prepared for the irruption of artificial intelligence? A study on the perceptions of students of primary education degree from a dual perspective: Current pupils and future teachers.

The recent irruption of ChatGPT, a powerful chatbot that uses a “Chat Generative Pretrained Transformer� language model, could revolutionize education worldwide since it can greatly affect the competence development that students need to achieve for their professional future. The aim of this work is to assess the level of knowledge of ChatGPT and the perception of its possibilities of use in education by students studying the Primary Education Degree at the University of León (Spain) from a double perspective: as students and future teachers, respectively. For this purpose, a descriptive, cross-sectional, non-experimental, and quantitative research design was carried out, with the design and elaboration of a questionnaire. The questionnaire data were statistically processed by calculating relative frequencies. The main results highlight that students have a positive perception of ChatGPT use, with potential applications in education, and do not perceive it as a threat to the deterioration of the educational system as long as the sources of the data generated by the tool are verified. In addition, as students and future teachers, they need more knowledge about the operation of ChatGPT to ensure its correct use and maintain the quality of the education system. Thus, to overcome ChatGPT irruption in education, digital literacy is crucial at all educational levels. © 2023 by the authors.

Public access to artificial intelligence, and specifically to ChatGPT, is presenting challenges in the professional training of occupational therapists. In this context, this essay aims to describe the impact of artificial intelligence, with an emphasis on ChatGPT, on the training of occupational therapists and proposes strategies to integrate these technologies into higher education from an integrative, ethical perspective, in line with the values and principles of academic integrity. While this tool can be used to provide theoretical knowledge and enhance content learning, it also poses a risk for dishonest behaviors in the academic realm. Therefore, it is essential that educators understand its use and promote experiential methodologies that encourage creativity, critical thinking, and reflection. The challenge lies in the implementation of policies and strategies that promote the development of professional skills and the ethical and effective use of these technologies in training future occupational therapists, such as declaring its use in written works, modeling by teachers, and integration into training methodologies. © 2023 Universidade Federal de Sao Carlos. All rights reserved.

War of the chatbots: Bard, Bing Chat, ChatGPT, Ernie and beyond. The new AI gold rush and its impact on higher education.

Developments in the chatbot space have been accelerating at breakneck speed since late November 2022. Every day, there appears to be a plethora of news. A war of competitor chatbots is raging amidst an AI arms race and gold rush. These rapid developments impact higher education, as millions of students and academics have started using bots like ChatGPT, Bing Chat, Bard, Ernie and others for a large variety of purposes. In this article, we select some of the most promising chatbots in the English and Chinese-language spaces and provide their corporate backgrounds and brief histories. Following an up-to-date review of the Chinese and English-language academic literature, we describe our comparative method and systematically compare selected chatbots across a multi-disciplinary test relevant to higher education. The results of our test show that there are currently no A-students and no B-students in this bot cohort, despite all publicised and sensationalist claims to the contrary. The much-vaunted AI is not yet that intelligent, it would appear. GPT-4 and its predecessor did best, whilst Bing Chat and Bard were akin to at-risk students with F-grade averages. We conclude our article with four types of recommendations for key stakeholders in higher education: (1) faculty in terms of assessment and (2) teaching & learning, (3) students and (4) higher education institutions. © 2023. Jurgen Rudolph, Shannon Tan and Samson Tan.

The use of artificial intelligence (AI) in education is becoming increasingly prevalent, and its encroachment and impact on online education and assessment is a topic of interest to researchers and lecturers. ChatGPT is one such AI model that has been trained on a large corpus of text data to generate human-like responses to questions and prompts. Using the theory of disruptive innovation as a foundation for our argument, this conceptual article explores the potential and possible disruption of ChatGPT in online assessment. This article also considers the ethical and pedagogical implications of using ChatGPT, particularly in relation to online assessment in distance education. While the use of AI in online assessment presents a myriad of limitations and possibilities, it is crucial to approach its use with caution and consider the ethical implications of academic integrity for online assessment. This article aims to contribute to the ongoing discussion and debate around the use of AI in online higher education and assessment, highlighting the need for continued research and critical evaluation of its impact. © 2023 by authors.

Online Journal of Communication and Media Technologies

Investigating marker accuracy in differentiating between university scripts written by students and those produced using ChatGPT.

Hassoulas, A., Powell, N., Roberts, L., Umla-Runge, K., Gray, L., & Coffey, M. J.

The introduction of OpenAI's ChatGPT has widely been considered a turning point for assessment in higher education. Whilst we find ourselves on the precipice of a profoundly disruptive technology, generative artificial intelligence (AI) is here to stay. At present, institutions around the world are considering how best to respond to such new and emerging tools, ranging from outright bans to re-evaluating assessment strategies. In evaluating the extent of the problem that these tools pose to the marking of assessments, a study was designed to investigate marker accuracy in differentiating between scripts prepared by students and those produced using generative AI. A survey containing undergraduate reflective writing scripts and postgraduate extended essays was administered to markers at a medical school in Wales, UK. The markers were asked to assess the scripts on writing style and content, and to indicate whether they believed the scripts to have been produced by students or ChatGPT. Of the 34 markers recruited, only 23% and 19% were able to correctly identify the ChatGPT undergraduate and postgraduate scripts, respectively. A significant effect of suspected script authorship was found for script content, X²(4, n=34) = 10.41, p<0.05, suggesting that written content holds clues as to how markers assign authorship. We recommend consideration be given to how generative AI can be responsibly integrated into assessment strategies and expanding our definition of what constitutes academic misconduct in light of this new technology. © 2023. Athanasios Hassoulas, Ned Powell, Lindsay Roberts, Katja Umla-Runge, Laurence Gray and Marcus J Coffey.

ChatGPT and Generative AI: Possibilities for Its contribution to lesson planning, critical thinking and openness in teacher education.

Although artificial intelligence (AI) has been part of our lives for some time, the launch of the Generative Pretrained Transformer (ChatGPT) has given it renewed attention. While most of these debates are about higher education in general, this article focuses on schoolteacher education and teacher training. This research aimed to determine the contribution of generative AI tools such as ChatGPT in lesson planning, critical thinking and openness in education. The research used a qualitative approach and document analysis following an interpretative paradigm. The findings reveal that generative language models such as ChatGPT can provide specific materials and support mechanisms, such as lesson plans, to schoolteachers and student teachers. It also showed that ChatGPT has levelled the playing field by opening access to lesson plans to all teachers. However, to unleash their full potential for education, it is crucial to approach these models with caution and critically evaluate their limitations and potential biases, understanding that they are tools to support teaching and learning and do not replace teachers. The study’s contribution lies in ChatGPT-generated lesson plans’ implications and the enhancement of critical thinking for teacher education, and it also underscores the need for further research to explore best practices for integrating ChatGPT in lesson planning. © 2023 by the authors.

Educational design principles of using AI chatbot that supports self-regulated learning in education: Goal setting, feedback, and personalization.

The invention of ChatGPT and generative AI technologies presents educators with significant challenges, as concerns arise regarding students potentially exploiting these tools unethically, misrepresenting their work, or gaining academic merits without active participation in the learning process. To effectively navigate this shift, it is crucial to embrace AI as a contemporary educational trend and establish pedagogical principles for properly utilizing emerging technologies like ChatGPT to promote self-regulation. Rather than suppressing AI-driven tools, educators should foster collaborations among stakeholders, including educators, instructional designers, AI researchers, and developers. This paper proposes three key pedagogical principles for integrating AI chatbots in classrooms, informed by Zimmerman’s Self-Regulated Learning (SRL) framework and Judgment of Learning (JOL). We argue that the current conceptualization of AI chatbots in education is inadequate, so we advocate for the incorporation of goal setting (prompting), self-assessment and feedback, and personalization as three essential educational principles. First, we propose that teaching prompting is important for developing students’ SRL. Second, configuring reverse prompting in the AI chatbot’s capability will help to guide students’ SRL and monitoring for understanding. Third, developing a data-driven mechanism that enables an AI chatbot to provide learning analytics helps learners to reflect on learning and develop SRL strategies. By bringing in Zimmerman’s SRL framework with JOL, we aim to provide educators with guidelines for implementing AI in teaching and learning contexts, with a focus on promoting students’ self-regulation in higher education through AI-assisted pedagogy and instructional design. © 2023 by the authors.

Gupta, R., Park, J. B., Herzog, I., Yosufi, N., Mangan, A., Firouzbakht, P. K., & Mailey, B. A.

Background: The recent introduction of Generative Pre-trained Transformer (GPT)-4 has demonstrated the potential to be a superior version of ChatGPT-3.5. According to many, GPT-4 is seen as a more reliable and creative version of GPT-3.5. Objective: In conjugation with our prior manuscript, we wanted to determine if GPT-4 could be exploited as an instrument for plastic surgery graduate medical education by evaluating its performance on the Plastic Surgery Inservice Training Examination (PSITE). Methods: Sample assessment questions from the 2022 PSITE were obtained from the American Council of Academic Plastic Surgeons website and manually inputted into GPT-4. Responses by GPT-4 were qualified using the properties of natural coherence. Incorrect answers were stratified into the consequent categories: informational, logical, or explicit fallacy. Results: From a total of 242 questions, GPT-4 provided correct answers for 187, resulting in a 77.3% accuracy rate. Logical reasoning was utilized in 95.0% of questions, internal information in 98.3%, and external information in 97.5%. Upon separating the questions based on incorrect and correct responses, a statistically significant difference was identified in GPT-4's application of logical reasoning. Conclusion: GPT-4 has shown to be more accurate and reliable for plastic surgery resident education when compared to GPT-3.5. Users should look to utilize the tool to enhance their educational curriculum. Those who adopt the use of such models may be better equipped to deliver high-quality care to their patients. © 2023 British Association of Plastic, Reconstructive and Aesthetic Surgeons

Journal of Plastic, Reconstructive & Aesthetic Surgery

The latest AI language modules can produce original, high quality full short-form (300-word) Physics essays within seconds. These technologies such as ChatGPT and davinci-003 are freely available to anyone with an internet connection. In this work, we present evidence of AI generated short-form essays achieving First-Class grades on an essay writing assessment from an accredited, current university Physics module. The assessment requires students answer five open-ended questions with a short, 300-word essay each. Fifty AI answers were generated to create ten submissions that were independently marked by five separate markers. The AI generated submissions achieved an average mark of 71 ± 2 % , in strong agreement with the current module average of 71 ± 5 % . A typical AI submission would therefore most-likely be awarded a First Class, the highest classification available at UK universities. Plagiarism detection software returned a plagiarism score between 2 ± 1 % (Grammarly) and 7 ± 2 % (TurnitIn). We argue that these results indicate that current natural language processing AI represent a significant threat to the fidelity of short-form essays as an assessment method in Physics courses. © 2023 The Author(s). Published by IOP Publishing Ltd

Thanh, B. N., Vo, D. T. H., Nhat, M. N., Pham, T. T. T., Trung, H. T., & Xuan, S. H.

In this study, we introduce a framework designed to help educators assess the effectiveness of popular generative artificial intelligence (AI) tools in solving authentic assessments. We employed Bloom’s taxonomy as a guiding principle to create authentic assessments that evaluate the capabilities of generative AI tools. We applied this framework to assess the abilities of ChatGPT-4, ChatGPT-3.5, Google Bard and Microsoft Bing in solving authentic assessments in economics. We found that generative AI tools perform very well at the lower levels of Bloom's taxonomy while still maintaining a decent level of performance at the higher levels, with “create� being the weakest level of performance. Interestingly, these tools are better able to address numeric-based questions than text-based ones. Moreover, all the generative AI tools exhibit weaknesses in building arguments based on theoretical frameworks, maintaining the coherence of different arguments and providing appropriate references. Our study provides educators with a framework to assess the capabilities of generative AI tools, enabling them to make more informed decisions regarding assessments and learning activities. Our findings demand a strategic reimagining of educational goals and assessments, emphasising higher cognitive skills and calling for a concerted effort to enhance the capabilities of educators in preparing students for a rapidly transforming professional environment. Implications for practice or policy • Our proposed framework enables educators to systematically evaluate the capabilities of widely used generative AI tools in assessments and assist them in the assessment design process. • Tertiary institutions should re-evaluate and redesign programmes and course learning outcomes. The new focus on learning outcomes should address the higher levels of educational goals of Bloom’s taxonomy, specifically the “create� level. © Articles published in the Australasian Journal of Educational Technology (AJET) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant AJET right of first publication under CC BY-NC-ND 4.0.

Academic integrity has been challenged by artificial intelligence algorithms in teaching institutions, including those providing nuclear medicine training. The GPT 3.5–powered ChatGPT chatbot released in late November 2022 has emerged as an immediate threat to academic and scientific writing. Methods: Both examinations and written assignments for nuclear medicine courses were tested using ChatGPT. Included was a mix of core theory subjects offered in the second and third years of the nuclear medicine science course. Long-answer–style questions (8 subjects) and calculation-style questions (2 subjects) were included for examinations. ChatGPT was also used to produce responses to authentic writing tasks (6 subjects). ChatGPT responses were evaluated by Turnitin plagiarism-detection software for similarity and artificial intelligence scores, scored against standardized rubrics, and compared with the mean performance of student cohorts. Results: ChatGPT powered by GPT 3.5 performed poorly in the 2 calculation examinations (overall, 31.7% compared with 67.3% for students), with particularly poor performance in complex-style questions. ChatGPT failed each of 6 written tasks (overall, 38.9% compared with 67.2% for students), with worsening performance corresponding to increasing writing and research expectations in the third year. In the 8 examinations, ChatGPT performed better than students for general or early subjects but poorly for advanced and specific subjects (overall, 51% compared with 57.4% for students). Conclusion: Although ChatGPT poses a risk to academic integrity, its usefulness as a cheating tool can be constrained by higher-order taxonomies. Unfortunately, the constraints to higher-order learning and skill development also undermine potential applications of ChatGPT for enhancing learning. There are several potential applications of ChatGPT for teaching nuclear medicine students. COPYRIGHT © 2023 by the Society of Nuclear Medicine and Molecular Imaging.

ChatGPT, an Artificial Intelligence (AI) powered chatbot, has caused a stir in the Higher Education landscape, with fears of plagiarism and a disruption of the student-teacher relationship that has formed the bedrock of teaching. ChatGPT-3 and now four have been reported to pass many exams, including medical, law, and engineering. Overwhelming concerns from academics about students using these generative AI tools to work on their assessments is alarming. These AI tools are here to stay. Teachers should not treat AI as 'the enemy', and instead find ways to work with it for the betterment of learning outcomes for students. Working with AI can mean transforming teaching and the AIed-teacher relationship, resulting in positive outcomes and learning experiences for teachers and students. © 2023, North American Business Press. All rights reserved.

Journal of Higher Education Theory and Practice

Challenges and opportunities of AI-assisted learning: A systematic literature review on the impact of ChatGPT usage in higher education.

Vargas-Murillo, A. R., de la Asuncion Pari-Bedoya, I. N. M., & de Jesus Guevara-Soto, F.

In recent years, ChatGPT has become a noteworthy subject in the educational field due to the popularity it gained among students all over the world. Applications such as text creation, data processing, and curriculum development, among other applications, prove that ChatGPT is one of the most advanced chatbots available, albeit it posing a series of challenges that prevents students from developing their critical thinking skills in some cases. In this sense, this study’s objective is to analyze the current literature regarding the use of ChatGPT in higher education. The study questions its usage, the overall impact it has on education, and the challenges and opportunities of artificial intelligence- (AI) assisted learning, all within the research area of digital education. For this, a systematic literature review (SLR) was conducted across multiple journal databases, analyzing the articles found and filtering them with the use of specific criteria. The results of this analysis afforded the conclusion that that ChatGPT can potentially enhance both academic- and librarian-related processes, although it is important to reconsider the ethics of using technology such as this. This is because this kind of AI technology also has the potential to modify the way people take on different jobs, tasks, and processes at an academic level, for which the correct and responsible use of ChatGPT needs to be assessed in the field of higher education. © Authors.

International Journal of Learning, Teaching and Educational Research

The emergence of ChatGPT has challenged academic integrity in teaching institutions, including those providing nuclear medicine training. Although previous evaluations of ChatGPT have suggested a limited scope for academic writing, the March 2023 release of generative pretrained transformer (GPT)-4 promises enhanced capabilities that require evaluation. Methods: Examinations (final and calculation) and written assignments for nuclear medicine subjects were tested using GPT-3.5 and GPT-4. GPT-3.5 and GPT-4 responses were evaluated by Turnitin software for artificial intelligence scores, marked against standardized rubrics, and compared with the mean performance of student cohorts. Results: ChatGPT powered by GPT-3.5 performed poorly in calculation examinations (31.4%), compared with GPT-4 (59.1%). GPT-3.5 failed each of 3 written tasks (39.9%), whereas GPT-4 passed each task (56.3%). Conclusion: Although GPT-3.5 poses a minimal risk to academic integrity, its usefulness as a cheating tool can be significantly enhanced by GPT-4 but remains prone to hallucination and fabrication. © 2023 Society of Nuclear Medicine Inc.. All rights reserved.

Generative artificial intelligence: University student awareness, experience, and confidence in use across disciplines.

The global higher education sector has been significantly disrupted by the proliferation of generative artificial intelligence tools such as ChatGPT, especially in relation to its implications for assessment. However, few studies to date have explored student perspectives on these tools. This article reports on one of the first large-scale quantitative studies of student views on generative artificial intelligence at an Australian university (n = 1,135). When the survey was conducted, most students had low knowledge, experience, and confidence in using these tools. These results varied across disciplines and across some student sub-groups, such as mature-age students and international students. Confidence appeared to increase with experience, although the data also revealed a portion of students that have never used these tools yet still felt confident in using them. In exploring these results, this article aims to shed new light on this fast-evolving landscape and inform the future direction of supporting students to engage with generative artificial intelligence tools appropriately. Practitioner Notes 1. Students need to be explicitly taught how to use generative artificial intelligence tools appropriately. 2. Learning activities that build student skills in using generative artificial intelligence should be embedded into curricula. 3. The ways in which students learn how to use generative artificial intelligence will need to vary based on the needs of each disciplinary area. 4. Student reports of self-confidence in using generative artificial intelligence may be overstated. 5. Assessment tasks need to be redesigned to reduce the academic integrity risks associated with using generative artificial intelligence. © 2023, University of Wollongong. All rights reserved.

Journal of University Teaching and Learning Practice

AI-Supported academic advising: Exploring ChatGPT's current state and future potential toward student empowerment.

Artificial intelligence (AI), once a phenomenon primarily in the world of science fiction, has evolved rapidly in recent years, steadily infiltrating into our daily lives. ChatGPT, a freely accessible AI-powered large language model designed to generate human-like text responses to users, has been utilized in several areas, such as the healthcare industry, to facilitate interactive dissemination of information and decision-making. Academic advising has been essential in promoting success among university students, particularly those from disadvantaged backgrounds. Unfortunately, however, student advising has been marred with problems, with the availability and accessibility of adequate advising being among the hurdles. The current study explores how AI-powered tools like ChatGPT might serve to make academic advising more accessible, efficient, or effective. The authors compiled a list of questions frequently asked by current and prospective students in a teacher education bachelor’s degree program in the United States. Then, the questions were typed into the free version of ChatGPT, and the answers generated were explored and evaluated for their content and delivery. ChatGPT generated surprisingly high-quality answers, written in an authoritative yet supportive tone, and it was particularly adept at addressing general and open-ended career-related questions, such as career outlook, in a clear, comprehensive, and supportive manner using plain language. We argue that AI-powered tools, such as ChatGPT, may complement but not necessarily replace human academic advisers and that these tools may very well serve to promote educational equity by empowering individuals from a wide range of backgrounds with the means to initiate effective methods of seeking academic advice. © 2023 by the authors.

The latest development of Generative Artificial Intelligence (GenAI), particularly ChatGPT, has drawn the attention of educational researchers and practitioners. We have witnessed many innovative uses of ChatGPT in STEM classrooms. However, studies regarding students’ perceptions of ChatGPT as a virtual tutoring tool in STEM education are rare. The current study investigated undergraduate students’ perceptions of using ChatGPT in a physics class as an assistant tool for addressing physics questions. Specifically, the study examined the accuracy of ChatGPT in answering physics questions, the relationship between students’ ChatGPT trust levels and answer accuracy, and the influence of trust on students’ perceptions of ChatGPT. Our finding indicates that despite the inaccuracy of GenAI in question answering, most students trust its ability to provide correct answers. Trust in GenAI is also associated with students’ perceptions of GenAI. In addition, this study sheds light on students’ misconceptions toward GenAI and provides suggestions for future considerations in AI literacy teaching and research. © 2023, The Author(s).

International Journal of Educational Technology in Higher Education

The latest technologies, such as Artificial Intelligence (AI), have emerged as pivotal tools for fostering creativity, aiding in the development of novel and interactive pedagogical methods, and catalysing innovation within the educational process. The integration of technology into education opens avenues for creative expression and the cultivation of creative skills among students. Investigating the cognitive styles of educators is imperative for adapting instructional strategies, as divergent modes of thinking can impact the efficacy of teaching and facilitate the customization of approaches in pedagogy. In this article, the predominant type of thinking among student teachers is investigated, the average level of creativity is determined, and the potential influence of employing an innovative method - ChatGPT - on the creative abilities of future educators is explored. The study sample consisted of (450) university teachers at three universities, Udmurt State University (Izhevsk, Russia), Peoples' Friendship University of Russia (Moscow, Russia), and Beijing Institute of Technology (Beijing, China). Participants were invited to participate in two assessments: J. Bruner's test on thinking styles, and a proprietary questionnaire designed to gather additional insights into the perception and influence of ChatGPT on creative potential. This research employed a quantitative approach. The study revealed that 70% of the surveyed student teachers exhibited a sign-oriented type of thinking. The experimental findings indicated a moderate level of creativity among these students. Only 28% of the participants demonstrated a high degree of creativity. In contrast, educators who utilized the developed programme exhibited a higher level of creative ability and better performance compared to teachers in the control group. This suggests that the incorporation of ChatGPT in education exerts a positive influence on enhancing educators' outcomes when compared to conventional teaching methods. The practical significance of this study lies in its contribution to expanding knowledge about the impact of ChatGPT on the development of creative potential. It underscores the importance of employing contemporary information and communication technologies in the preparation of future teachers. © 2023 Society for Research and Knowledge Management. All rights reserved.

International Journal of Learning, Teaching and Educational Research

Background:Artificial intelligence (AI) holds potential in improving medical education and healthcare delivery. ChatGPT is a state-of-the-art natural language processing AI model which has shown impressive capabilities, scoring in the top percentiles on numerous standardized examinations, including the Uniform Bar Exam and Scholastic Aptitude Test. The goal of this study was to evaluate ChatGPT performance on the Orthopaedic In-Training Examination (OITE), an assessment of medical knowledge for orthopedic residents.Methods:OITE 2020, 2021, and 2022 questions without images were inputted into ChatGPT version 3.5 and version 4 (GPT-4) with zero prompting. The performance of ChatGPT was evaluated as a percentage of correct responses and compared with the national average of orthopedic surgery residents at each postgraduate year (PGY) level. ChatGPT was asked to provide a source for its answer, which was categorized as being a journal article, book, or website, and if the source could be verified. Impact factor for the journal cited was also recorded.Results:ChatGPT answered 196 of 360 answers correctly (54.3%), corresponding to a PGY-1 level. ChatGPT cited a verifiable source in 47.2% of questions, with an average median journal impact factor of 5.4. GPT-4 answered 265 of 360 questions correctly (73.6%), corresponding to the average performance of a PGY-5 and exceeding the corresponding passing score for the American Board of Orthopaedic Surgery Part I Examination of 67%. GPT-4 cited a verifiable source in 87.9% of questions, with an average median journal impact factor of 5.2.Conclusions:ChatGPT performed above the average PGY-1 level and GPT-4 performed better than the average PGY-5 level, showing major improvement. Further investigation is needed to determine how successive versions of ChatGPT would perform and how to optimize this technology to improve medical education.Clinical Relevance:AI has the potential to aid in medical education and healthcare delivery. © Lippincott Williams & Wilkins.

The Journal of Bone and Joint Surgery, Open Access

Factors influencing students' intention to adopt and use ChatGPT in higher education: A study in the Vietnamese context.

ChatGPT, an extensively recognised language model created by OpenAI, has gained significant prominence across various industries, particularly in education. This study aimed to investigate the factors that influence students' intentions to adopt and utilise ChatGPT for their academic studies. The study used a Structural Equation Model (SEM) for analysing the data gathered from 108 participants, comprising both undergraduate and postgraduate students enrolled in public and private universities in Vietnam. The findings indicated that students' inclination to adopt ChatGPT (referred to as adoption intention or AI) was influenced by their perception of its user-friendliness (PEU). However, the perceived usefulness (PU) of ChatGPT did not have a direct impact on students' adoption intention; instead, it had an indirect influence through personalisation (with a positive effect) and interactivity (with a negative effect). Importantly, there was no significant indirect effect of PU on AI mediated by perceived trust and perceived intelligence. This study is one of the initial empirical inquiries into ChatGPT adoption within an Asian context, providing valuable insights in this emerging area of research. As the use of ChatGPT by students becomes increasingly inevitable, educational institutions should carefully consider integrating it into the assessment process. It is crucial to design assessments that encourage responsible usage of ChatGPT, preserving students' critical thinking abilities and creativity in their assessment writing. Moving forward, educators will play a pivotal role by offering clear guidelines and instructions that set out the appropriate and ethical use of artificial intelligence tools in the assessments. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

An artificial intelligence-based chatbot, ChatGPT, was launched in November 2022 and is capable of generating cohesive and informative human-like responses to user input. This rapid review of the literature aims to enrich our understanding of ChatGPT's capabilities across subject domains, how it can be used in education, and potential issues raised by researchers during the first three months of its release (i.e., December 2022 to February 2023). A search of the relevant databases and Google Scholar yielded 50 articles for content analysis (i.e., open coding, axial coding, and selective coding). The findings of this review suggest that ChatGPT's performance varied across subject domains, ranging from outstanding (e.g., economics) and satisfactory (e.g., programming) to unsatisfactory (e.g., mathematics). Although ChatGPT has the potential to serve as an assistant for instructors (e.g., to generate course materials and provide suggestions) and a virtual tutor for students (e.g., to answer questions and facilitate collaboration), there were challenges associated with its use (e.g., generating incorrect or fake information and bypassing plagiarism detectors). Immediate action should be taken to update the assessment methods and institutional policies in schools and universities. Instructor training and student education are also essential to respond to the impact of ChatGPT on the educational environment. © 2023 by the author.

The question of how generative AI tools, such as large language models and chatbots, can be leveraged ethically and effectively in education is ongoing. Given the critical role that writing plays in learning and assessment within educational institutions, it is of growing importance for educators to make thoughtful and informed decisions as to how and in what capacity generative AI tools should be leveraged to assist in the development of students' writing skills. This paper reports on two longitudinal studies. Study 1 examined learning outcomes of 48 university English as a new language (ENL) learners in a six-week long repeated measures quasi experimental design where the experimental group received writing feedback generated from ChatGPT (GPT-4) and the control group received feedback from their human tutor. Study 2 analyzed the perceptions of a different group of 43 ENLs who received feedback from both ChatGPT and their tutor. Results of study 1 showed no difference in learning outcomes between the two groups. Study 2 results revealed a near even split in preference for AI-generated or human-generated feedback, with clear advantages to both forms of feedback apparent from the data. The main implication of these studies is that the use of AI-generated feedback can likely be incorporated into ENL essay evaluation without affecting learning outcomes, although we recommend a blended approach that utilizes the strengths of both forms of feedback. The main contribution of this paper is in addressing generative AI as an automatic essay evaluator while incorporating learner perspectives. © 2023, The Author(s).

International Journal of Educational Technology in Higher Education

We present a wide-ranging interview with Stefan Popenici, a distinguished scholar and public speaker with extensive experience in higher education. Popenici’s research focuses on the impact of artificial intelligence (AI) on teaching, learning, quality assurance, and student engagement in higher education. The interview delves into the themes of his book, Artificial Intelligence and learning futures: Critical narratives of technology and imagination in higher education (2023), exploring the intersection of AI, intelligence, and societal issues such as eugenics and racism. Popenici critiques the power of tech titans and the belief in technology as a panacea, especially in higher education. The discussion also addresses the identity crisis in higher education, the potential of revisiting Humboldt’s 19th-century vision of the university, and the challenges and opportunities presented by the AI revolution. Popenici’s insights into the role of AI in assessment, graduate and academic employment, and the future of academic work are particularly illuminating. The interview concludes with Popenici’s reflections on his own educational journey and future plans. © 2023. Stefan Popenici, Jürgen Rudolph, Shannon Tan & Samson Tan.

Constructing and testing the psychometrics of an instrument to measure the attitudes, benefits, and threats associated with the use of artificial intelligence tools in higher education.

Under the acceleration in the body of information regarding AI technology and the paucity of instruments that assess the views and reactions of consumers, we have constructed this instrument to measure the attitudes, benefits, and threats (ABT) toward using Artificial Intelligence (AI) tools in higher education. Google Form was used in August of 2023 to collect data from students and teachers at higher education institutions in 11 Asian and African countries. After the ABT instrument obtained a sufficient score in content validity, additional statistical analyses were done. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed. This study included 503 participants who are familiar with AI tools. Over 56% have Bachelor's degrees and 35% have Master'd or Doctoral degrees. The most popular AI tool was ChatGPT. One model out of six models created for the factor structure of the 35 items that measure attitudes, benefits, and threats was chosen. The selected model provides the highest explained variance (55.6%). The CFA, using AMOS software, demonstrated that the fit indices were satisfactory for the adopted model. Attitude (15), benefits (6), and threats (14 items) are the three factors of the model. The CFA supports the EFA with the ABT three-factor structure model. The high factor loadings and communalities suggest that the factors are reliable and valid measures of the attitude, benefits, and threats toward AI tools among highly educated personnel. © 2023. Muayyad Ahmad, Fadwa Alhalaiqa and Maha Subih.

Usability and efficacy of artificial intelligence chatbots (ChatGPT) for health sciences students: Protocol for a crossover randomized controlled trial.

Veras, M., Dyer, J.-O., Rooney, M., Silva, P. G. B., Rutherford, D., & Kairy, D.

Background: The integration of artificial intelligence (AI) into health sciences students’ education holds significant importance. The rapid advancement of AI has opened new horizons in scientific writing and has the potential to reshape human-technology interactions. AI in education may impact critical thinking, leading to unintended consequences that need to be addressed. Understanding the implications of AI adoption in education is essential for ensuring its responsible and effective use, empowering health sciences students to navigate AI-driven technologies’ evolving field with essential knowledge and skills. Objective: This study aims to provide details on the study protocol and the methods used to investigate the usability and efficacy of ChatGPT, a large language model. The primary focus is on assessing its role as a supplementary learning tool for improving learning processes and outcomes among undergraduate health sciences students, with a specific emphasis on chronic diseases. Methods: This single-blinded, crossover, randomized, controlled trial is part of a broader mixed methods study, and the primary emphasis of this paper is on the quantitative component of the overall research. A total of 50 students will be recruited for this study. The alternative hypothesis posits that there will be a significant difference in learning outcomes and technology usability between students using ChatGPT (group A) and those using standard web-based tools (group B) to access resources and complete assignments. Participants will be allocated to sequence AB or BA in a 1:1 ratio using computer-generated randomization. Both arms include students’ participation in a writing assignment intervention, with a washout period of 21 days between interventions. The primary outcome is the measure of the technology usability and effectiveness of ChatGPT, whereas the secondary outcome is the measure of students’ perceptions and experiences with ChatGPT as a learning tool. Outcome data will be collected up to 24 hours after the interventions. Results: This study aims to understand the potential benefits and challenges of incorporating AI as an educational tool, particularly in the context of student learning. The findings are expected to identify critical areas that need attention and help educators develop a deeper understanding of AI’s impact on the educational field. By exploring the differences in the usability and efficacy between ChatGPT and conventional web-based tools, this study seeks to inform educators and students on the responsible integration of AI into academic settings, with a specific focus on health sciences education. Conclusions: By exploring the usability and efficacy of ChatGPT compared with conventional web-based tools, this study seeks to inform educators and students about the responsible integration of AI into academic settings. © 2023 The Author(s).

This study aims to develop an AI education policy for higher education by examining the perceptions and implications of text generative AI technologies. Data was collected from 457 students and 180 teachers and staff across various disciplines in Hong Kong universities, using both quantitative and qualitative research methods. Based on the findings, the study proposes an AI Ecological Education Policy Framework to address the multifaceted implications of AI integration in university teaching and learning. This framework is organized into three dimensions: Pedagogical, Governance, and Operational. The Pedagogical dimension concentrates on using AI to improve teaching and learning outcomes, while the Governance dimension tackles issues related to privacy, security, and accountability. The Operational dimension addresses matters concerning infrastructure and training. The framework fosters a nuanced understanding of the implications of AI integration in academic settings, ensuring that stakeholders are aware of their responsibilities and can take appropriate actions accordingly. © 2023, The Author(s).

International Journal of Educational Technology in Higher Education

Effects of a ChatGPT-based flipped learning guiding approach on learners’ courseware project performances and perceptions.

In recent decades, flipped learning has been adopted by teachers to improve learning achievement. However, it is challenging to provide all students with instant personalised guidance at the same time. To address this gap, based on Chat Generative Pre-trained Transformer (ChatGPT) and the learning scaffolding theory, I developed a ChatGPT-based flipped learning guiding approach (ChatGPT-FLGA) according to the analysis, design, development, implementation and evaluation model. To investigate the effectiveness of ChatGPT-FLGA, a quasi-experiment was conducted in the learning activities of a courseware project. One of two classes was randomly assigned to the experimental group, while the other was assigned to the control group. The students in both classes received flipped classroom instruction and conducted discussions through Tencent QQ applications, but only those in the experimental group learned with ChatGPT-FLGA. The results revealed that the ChatGPT-FLGA significantly improved students’ performance, self-efficacy, learning attitudes, intrinsic motivation and creative thinking. The research findings enrich the literature on ChatGPT in flipped classrooms by addressing the influence of ChatGPT-FLGA on students' performance and perceptions. Implications for practice or policy: • Teachers and universities should utilise ChatGPT as a tool for supporting students’ learning and promoting their problem-solving skills. • Course designers and academic staff can leverage ChatGPT-FLGA to enact student-centred pedagogical transformation in massive open online courses or flipped learning. • Course designers should master how to use ChatGPT-FLGA and its learning system, to foster learners’ self-regulated learning, help them promote online self-efficacy and overcome difficulties in learning motivation and creative thinking ability. © Articles published in the Australasian Journal of Educational Technology (AJET) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant AJET right of first publication under CC BY-NC-ND 4.0.

Incorporating artificial intelligence (AI) into education, specifically through generative chatbots, can transform teaching and learning for education professionals in both administrative and pedagogical ways. However, the ethical implications of using generative chatbots in education must be carefully considered. Ethical concerns about advanced chatbots have yet to be explored in the education sector. This short article introduces the ethical concerns associated with introducing platforms such as ChatGPT in education. The article outlines how handling sensitive student data by chatbots presents significant privacy challenges, thus requiring adherence to data protection regulations, which may not always be possible. It highlights the risk of algorithmic bias in chatbots, which could perpetuate societal biases, which can be problematic. The article also examines the balance between fostering student autonomy in learning and the potential impact on academic self-efficacy, noting the risk of over-reliance on AI for educational purposes. Plagiarism continues to emerge as a critical ethical concern, with AI-generated content threatening academic integrity. The article advocates for comprehensive measures to address these ethical issues, including clear policies, advanced plagiarism detection techniques, and innovative assessment methods. By addressing these ethical challenges, the article argues that educators, AI developers, policymakers, and students can fully harness the potential of chatbots in education, creating a more inclusive, empowering, and ethically sound educational future. Copyright © 2024 Williams.

Higher education continues to be confronted with significant learning and teaching challenges. Still reeling from the effects of the pandemic, the sector has grappled for the past year with the advent and impact of generative artificial intelligence (AI). Since the introduction of ChatGPT by OpenAI in November 2022, a growing number of studies have discussed AI models and their impacts and influence on higher education. However, the novelty of what we aim to do in a future paper, outlined in the current one, lies in the systematicity of our approach. There is yet to be a study in which a systematic search strategy is developed to critically review extant research longitudinally across all available generative AI chatbot models within higher education. This protocol paper identifies a prospective systematic approach to reviewing the emergent literature. In addition, this protocol paper documents the structural approach to facilitate a systematic literature review. We seek to offer a systematic approach to create an open-access resource to support future learning and teaching scholars to gain timely access to pre-examined literature on different forms of generative AI and their impact on higher education. This protocol paper, as such, offers an approach that can be used to initiate closer scrutiny of the metadata of articles published on AI models in higher education since its initiation in November 2022. We also suggest that the protocol presented in this paper be considered a relevant and rigorous approach for conducting systematic literature reviews in other domains. © 2023, Kaplan Singapore. All rights reserved.

ChatGPT's performance in German OB/GYN exams - Paving the way for AI-enhanced medical education and clinical practice.

Riedel, M., Kaefinger, K., Stuehrenberg, A., Ritter, V., Amann, N., Graf, A., Recker, F., Klein, E., Kiechle, M., Riedel, F., & Meyer, B.

Background: Chat Generative Pre-Trained Transformer (ChatGPT) is an artificial learning and large language model tool developed by OpenAI in 2022. It utilizes deep learning algorithms to process natural language and generate responses, which renders it suitable for conversational interfaces. ChatGPT’s potential to transform medical education and clinical practice is currently being explored, but its capabilities and limitations in this domain remain incompletely investigated. The present study aimed to assess ChatGPT’s performance in medical knowledge competency for problem assessment in obstetrics and gynecology (OB/GYN). Methods: Two datasets were established for analysis: questions (1) from OB/GYN course exams at a German university hospital and (2) from the German medical state licensing exams. In order to assess ChatGPT’s performance, questions were entered into the chat interface, and responses were documented. A quantitative analysis compared ChatGPT’s accuracy with that of medical students for different levels of difficulty and types of questions. Additionally, a qualitative analysis assessed the quality of ChatGPT’s responses regarding ease of understanding, conciseness, accuracy, completeness, and relevance. Non-obvious insights generated by ChatGPT were evaluated, and a density index of insights was established in order to quantify the tool’s ability to provide students with relevant and concise medical knowledge. Results: ChatGPT demonstrated consistent and comparable performance across both datasets. It provided correct responses at a rate comparable with that of medical students, thereby indicating its ability to handle a diverse spectrum of questions ranging from general knowledge to complex clinical case presentations. The tool’s accuracy was partly affected by question difficulty in the medical state exam dataset. Our qualitative assessment revealed that ChatGPT provided mostly accurate, complete, and relevant answers. ChatGPT additionally provided many non-obvious insights, especially in correctly answered questions, which indicates its potential for enhancing autonomous medical learning. Conclusion: ChatGPT has promise as a supplementary tool in medical education and clinical practice. Its ability to provide accurate and insightful responses showcases its adaptability to complex clinical scenarios. As AI technologies continue to evolve, ChatGPT and similar tools may contribute to more efficient and personalized learning experiences and assistance for health care providers. Copyright © 2023 Riedel, Kaefinger, Stuehrenberg, Ritter, Amann, Graf, Recker, Klein, Kiechle, Riedel and Meyer.