Understanding the value of Large Language Models for higher education. An online survey study
Before agreeing to participate in the study, it is important that you read the following explanation.

Title of research: Understanding the value of Large Language Models for higher education. An online survey study. This research is conducted by Dr. Olya Kudina as the Principal Investigator (PI).

Researchers: Olya Kudina, Assistant Professor, Department of Values, Technology and Innovation, Section Ethics/Philosophy of Technology, Delft University of Technology, NL

Project duration: February 2023 – February 2025

Purpose of the research: The purpose of the study is to gain an understanding of the extent and nature of use by the students of Large Language Models (LLMs) (e.g. ChatGPT) in the context of higher education. The study is in the form of an open-ended qualitative questionnaire on the web-based interface of Google Forms (i.e. online survey). The results of the study will contribute to an empirically informed philosophical analysis that aims to outline (1) a developmental perspective of the value of education and how it can be adapted to critically appropriate the use of LLMs, (2) develop several response strategies for the higher education settings, and (3) generate recommendations for a more responsible design and societal introduction of LLMs.

Confidentiality and data managementThroughout the online questionnaire, we will collect the abstract data on your demographics for gaining an awareness on the pool of respondents (i.e. age range, the level of study and field of study), as well as your qualitative answers to the questions. We will not collect personally identifiable information (e.g. your name, email address, IP address, etc.) to ensure a privacy-sensitive and confidential report of the data. To facilitate this within the Google forms, the settings have been set to work without Google sign-in and without any collection of the personally identifiable information within the questionnaire. All the collected data will thus be by default anonymous. Your aggregated data and qualitative responses, being anonymous, may be used for research and publications and shared with other researchers for the purposes of this project.  Therefore, please, do not provide any personally identifiable information in your responses (e.g. your name) to comply with the data protection procedures for this study.

For the project duration (until February 2024), your anonymous data will be stored on the SURFdrive cloud storage. The anonymous data will be available to the researchers in this project with organizational login access. The data are stored in the Netherlands. After the project, the anonymous data will be transferred to the 4TU.Center for Research Data as a data repository for a period of 10 years. The anonymous data will have open access. The data is stored in the Netherlands and complies with the international Data Seal of Approval standard.  

Explanation of procedures: To qualify for the study, you must be at least 18 years old, be fluent in English and be a higher education student (undergraduate/bachelor's, graduate/master's or postgraduate/PhD student). When you first follow the link to the online survey, you will be asked to fill in this Informed Consent form digitally by reading this Information Sheet and answering the Informed Consent questions. Only if you complete the informed consent form and agree to the proposed statements will you have access to the questionnaire.

If you agree to participate in the study, you will be invited to answer a series of questions describing your experiences with Large Language Models in the context of your studies. The questions will ask you to narrate your experiences and provide suggestions and ideas regarding the potential integration of LLMs in higher education or debate its desirability. The estimated duration of answering the questions ranges from several minutes to 10-15 minutes, depending on the person. 

RisksThe main risks of participating in the study are linked to the incidental revealing of your personally identifiable information in the filling out of the qualitative questions in the survey. This risk will be mitigated by manually filtering in and coding the qualitative data, removing any personally identifiable information should it be filled in. The data interception and reidentification risks are thus minimal. Participation in the study is otherwise safe for you.

Withdrawal without prejudice: Taking part in the study is voluntary. You are free to withdraw consent or discontinue the study at any time, without prejudice from the researchers.

Questions: Any questions concerning this LLM study and/or in the case of issues due to the research can be directed to the PI, Olya Kudina, either in person or via o.kudina@tudelft.nl.

After reading the explanation of the study above, please, answer the following questions by ticking the “Yes” or “No” before proceeding to the questions. If you disagree with at least one of the statements below, please, select the "No" option.
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I have read the foregoing information, or it has been read to me. I voluntarily consent to be a participant in this study. I understand that I can refuse to answer questions and I can withdraw from the study at any time, without having to give a reason. I understand that taking part in the study involves answering qualitative open-ended questionnaire. 

I understand that taking part in the study involves the risk of the interception of my anonymous data during the processing and storage of the information provided by me to complete this study. I furthermore understand that the researchers have minimized the risks by using only anonymous data that cannot be linked back to me and taking the appropriate measures of storage and access control to secure the data during and after the project. 

I understand that the anonymous information I provide may be used for publications and other research related activities (e.g., reports, website, blogs, etc.). I understand that after the end of the project (February 28, 2025), the anonymous information I provide will become publicly accessible to verify the research results and to potentially enable others to re-use the data for future research and learning.

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