UGC MALAVIYA MISSION TEACHER TRAINING CENTRE · SAVITRIBAI PHULE PUNE UNIVERSITY
Unlocking the Potential of AI for
Teaching, Learning & Evaluation
A Three-Hour Professional Development Workshop for Higher Education Teachers
Resource Person: Dr. N. A. Reddy
Dept. of Education, North-Eastern Hill University (NEHU), Shillong
10 October 2026
Part 3
SESSION ROADMAP
How We Will Spend Our Three Hours
Session Roadmap
1
0:00 – 0:20
Opening & Orientation
Welcome, learning outcomes, and a quick self-assessment of participants' current AI use.
0:20 – 1:00
Setting the Context
Why AI, why now; the AI landscape for education; NEP 2020 and UGC policy signals.
1:00 – 1:50
Dimension 1 – Teaching
AI for content creation, differentiation, lesson design — tools, journals, books.
1:50 – 2:00
Short Break
Tea break.
2:00 – 2:45
Dimensions 2 & 3 – Learning & Evaluation
Adaptive learning, tutoring systems, AI-assisted assessment — tools, journals, books.
2:45 – 3:00
Ethics, Practice & Action Plan
Responsible use, hands-on toolkit, group discussion, and a personal action plan.
LEARNING OUTCOMES
By the End of This Workshop, Participants Will Be Able To
Learning Outcomes
2
1 Explain
LEARNING OUTCOME
Explain the core capabilities of AI relevant to higher education — generative, adaptive, and analytic — in plain language.
2 Apply
LEARNING OUTCOME
Apply at least two AI tools to a real teaching task: content creation, lesson planning, or material design.
3 Design
LEARNING OUTCOME
Design a personalized or adaptive learning activity that responds to individual learner needs.
4 Evaluate
LEARNING OUTCOME
Evaluate the use of AI for assessment — automated grading, feedback, and academic-integrity safeguards.
5 Critique
LEARNING OUTCOME
Critique the ethical, privacy, and bias implications of AI adoption in their own institutional context.
6 Plan
LEARNING OUTCOME
Draft a personal action plan for integrating one AI practice into their teaching within the next month.
00
FOUNDATIONS
Setting the Context
Why artificial intelligence matters for Indian higher education right now.
Foundations
3
FOUNDATIONS
Why AI, Why Now
Foundations
4
40+
Countries have issued national AI-in-education guidance since 2023
2020
NEP 2020 explicitly calls for technology-enabled, personalized learning
1:40+
Typical teacher–student ratio in Indian HE that AI-assisted workflows can ease
24×7
Availability of AI tutoring and feedback support outside class hours
Three converging pressures are pushing AI onto every faculty development agenda:
1
Workload pressure
Rising class sizes and administrative load leave less time for individual attention to students.
2
Learner diversity
First-generation learners, multilingual classrooms, and varied prior knowledge demand differentiation at scale.
3
Policy momentum
NEP 2020, UGC, and AICTE guidance actively encourage responsible technology integration.
FOUNDATIONS
The AI Landscape for Education
Foundations
5
Generative AI
TEXT · IMAGE · AUDIO
Large language models that draft, explain, summarize, and create content on request — e.g. ChatGPT, Claude, Gemini.
Adaptive & ML Systems
PERSONALIZATION
Algorithms that adjust content difficulty and sequencing to an individual learner's performance in real time.
Intelligent Tutoring
GUIDED PRACTICE
Systems that simulate one-on-one tutoring, offering hints, questions, and step-by-step scaffolding.
Learning Analytics
DATA & DASHBOARDS
AI that mines engagement and performance data to flag at-risk learners and surface teaching insights.
Automated Assessment
GRADING & FEEDBACK
Natural-language processing that scores responses and generates rubric-aligned feedback at scale.
Conversational Agents
24×7 SUPPORT
Chat-based assistants that answer learner queries, coach revision, and extend office hours virtually.
FOUNDATIONS
India's Policy Context: NEP 2020 & UGC Guidance
Foundations
6
NEP
NEP 2020 — Technology-Enabled Personalization
Calls for a National Educational Technology Forum and encourages AI, adaptive software, and blended models to support individualized learning pathways.
UGC
UGC Guidelines on Generative AI in Higher Education
Recommends institutional AI-use policies, faculty capacity-building, and academic-integrity safeguards alongside adoption.
MMTTC
Malaviya Mission Teacher Training Centres
Positioned as the nodal faculty-development mechanism for building AI literacy and responsible-use competence nationally.
NAAC
NAAC / Accreditation Signals
Increasingly reference innovation in teaching-learning processes, including technology and AI-enabled practice, in quality indicators.
FOUNDATIONS
Our Framework for Today: Three Pillars
Foundations
7
1
Teaching
How AI supports the educator — content creation, differentiation, lesson design.
2
Learning
How AI supports the learner — adaptive pathways, tutoring, analytics, inclusion.
3
Evaluation
How AI supports assessment — grading, feedback, integrity, rubric design.
Each pillar covers: what changes · best AI tools · key journals · essential books · a real classroom snapshot.
01
DIMENSION ONE
AI for Teaching
Empowering the educator: content, differentiation, and design.
Dimension One
8
DIMENSION 1 · TEACHING
What AI Changes in Teaching
Dimension 1 · Teaching
9
1
From blank page to first draft
AI turns a topic outline into lecture notes, slide content, or handouts in minutes — freeing time for refinement, not creation from scratch.
2
From one-size-fits-all to differentiated
The same concept can be regenerated at multiple reading levels or formats for a mixed-ability classroom.
3
From static to interactive material
Quizzes, simulations, and multimedia explainers can be produced alongside traditional notes.
4
From individual effort to co-creation
AI acts as a drafting partner for lesson plans and curriculum mapping, with the teacher retaining editorial judgment.
DIMENSION 1 · TEACHING
AI for Content & Lecture Creation
Dimension 1 · Teaching
10
✎
Draft lecture notes & explanations
Generate a structured first draft from a syllabus topic, then edit for accuracy and local examples.
▤
Build slide decks from an outline
AI slide generators turn bullet outlines into designed presentations, which teachers then refine.
♪
Produce audio/video explainers
Text-to-speech and video-summary tools convert notes into short multimedia recaps for revision.
Practice tip: Always fact-check AI-generated content against your own subject expertise before sharing it — treat AI as a drafting assistant, never the final authority.
DIMENSION 1 · TEACHING
AI for Differentiated Instruction
Dimension 1 · Teaching
11
A
Levelled reading passages
Regenerate the same content at simplified, grade-level, and advanced reading levels for one classroom.
B
Multilingual explanations
Translate and localize material for multilingual classrooms while preserving disciplinary terminology.
C
Scaffolded practice sets
Generate graded problem sets — easy to challenging — tailored to a learner's current mastery.
D
Support for diverse needs
Adapt pacing, format, and vocabulary for learners with disabilities or varied first languages.
DIMENSION 1 · TEACHING
AI for Lesson Planning & Curriculum Design
Dimension 1 · Teaching
12
1
Define outcomes
State the learning outcome and prior knowledge assumed.
→
2
Draft with AI
Ask for an activity sequence, timing, and assessment ideas.
→
3
Localize & verify
Add local examples, check accuracy, align to syllabus.
→
4
Map to curriculum
Cross-check coverage against the full course map for gaps.
AI is strongest at generating options and structure quickly — the teacher remains the final decision-maker on pedagogy and sequencing.
DIMENSION 1 · TEACHING
Best AI Tools for Teaching
Dimension 1 · Teaching
13
ChatGPT / GPT-5
GENERAL-PURPOSE
Drafting explanations, lecture notes, rubrics, and brainstorming activities quickly.
Claude
GENERAL-PURPOSE
Long-document analysis, careful reasoning, and Socratic-style explanation drafting.
MagicSchool AI
TEACHER SUITE
Purpose-built tools for lesson plans, rubrics, IEP support, and differentiated worksheets.
Curipod
INTERACTIVE LESSONS
Generates interactive, discussion-driven lesson slides from a single topic prompt.
Diffit
DIFFERENTIATION
Turns any text or topic into levelled reading passages and matched activities.
Canva Magic Studio
VISUAL DESIGN
AI-assisted slide, poster, and handout design from text prompts or outlines.
DIMENSION 1 · TEACHING
Key Journals — AI in Teaching
Dimension 1 · Teaching
14
British Journal of Educational Technology (BJET)
Wiley · technology-enhanced pedagogy
Computers & Education
Elsevier · flagship EdTech research journal
Computers and Education: Artificial Intelligence
Elsevier · AI-specific companion journal
Educational Technology Research & Development
Springer / AECT · design and development studies
Journal of Computer Assisted Learning
Wiley · technology-supported instruction
Education and Information Technologies
Springer · broad EdTech and AI applications
DIMENSION 1 · TEACHING
Essential Books — AI in Teaching
Dimension 1 · Teaching
15
Teaching with AI: A Practical Guide
José Antonio Bowen & C. Edward Watson · Johns Hopkins University Press
Artificial Intelligence in Education: Promises and Implications for Teaching and Learning
Wayne Holmes, Maya Bialik & Charles Fadel · Center for Curriculum Redesign
The AI Classroom
Dan Fitzpatrick & Amanda Fox · IntelligentED
Handbook of Artificial Intelligence in Education
Edited by Benedict du Boulay, Antonija Mitrovic & Kalina Yacef · Edward Elgar
DIMENSION 1 · TEACHING
Classroom Snapshot: An AI-Assisted Teaching Workflow
Dimension 1 · Teaching
16
1
Prompt
"Draft a 40-min lesson on osmosis for BSc first-years, with 2 real-world examples."
→
2
Draft
AI returns structured notes, an analogy, and 3 discussion questions.
→
3
Edit
Teacher swaps in a locally relevant example and checks accuracy.
→
4
Deliver
Lesson delivered; AI-generated exit-ticket quiz used for quick recall check.
DIMENSION 1 · TEACHING
Issues & Challenges in Teaching
Dimension 1 · Teaching
17
1
Fact-checking burden
AI-generated notes and explanations can be confidently wrong; verifying every claim against subject expertise adds real time back in.
2
Time investment to learn tools
Evaluating, selecting, and learning new AI tools competes with an already full teaching and research workload.
3
Uneven access to premium tools
Free tiers cap usage and quality; institutions without licences risk a two-tier teaching experience.
4
Risk of eroding design skill
Leaning on AI for every draft can quietly weaken a teacher’s own lesson-design and subject-explanation skills over time.
DIMENSION 1 · TEACHING
Tips & Suggestions for Teaching
Dimension 1 · Teaching
18
✎
Start with one recurring task
Pilot AI on a single lecture, worksheet, or rubric before rolling it out across a whole course.
▤
Always verify before sharing
Treat AI output as a first draft only — check facts, examples, and framing against your own expertise.
♪
Prefer free or institutional tools first
Use vetted, institutionally approved tools before paid options, to keep material accessible to every colleague.
Suggestion: Keep a personal library of prompts and edited outputs that worked well — it turns each lesson into a reusable template for the next.
02
DIMENSION TWO
AI for Learning
Empowering the learner: adaptive pathways, tutoring, and inclusion.
Dimension Two
17
DIMENSION 2 · LEARNING
What AI Changes in Learning
Dimension 2 · Learning
20
1
From fixed pace to adaptive pace
Content difficulty and sequencing adjust automatically to each learner's demonstrated mastery.
2
From scarce tutoring to on-demand support
AI tutoring extends one-on-one style guidance beyond limited office hours.
3
From intuition to evidence
Learning analytics surface engagement patterns and at-risk signals earlier than manual tracking.
4
From exclusion to accessibility
AI-generated captions, translations, and alternative formats widen access for diverse learners.
DIMENSION 2 · LEARNING
Adaptive & Personalized Learning Pathways
Dimension 2 · Learning
21
→
Diagnostic entry points
A short adaptive quiz places each learner at an appropriate starting difficulty.
↔
Dynamic sequencing
The system reorders or repeats topics based on ongoing performance, not a fixed syllabus order.
✓
Mastery-based progression
Learners advance only after demonstrating competence, reducing gaps that compound over a term.
DIMENSION 2 · LEARNING
Intelligent Tutoring Systems & AI Learning Companions
Dimension 2 · Learning
22
?
Socratic questioning, not answer-giving
The strongest tutoring tools guide learners with questions rather than handing over finished answers.
↻
Immediate, targeted feedback
Learners get feedback within seconds of attempting a problem, while the reasoning is still fresh.
☉
Available beyond class hours
Extends support to evenings, weekends, and exam periods when faculty are not reachable.
Caution: Tutoring bots can still produce confident but incorrect explanations — build in periodic teacher spot-checks of AI-tutor transcripts.
DIMENSION 2 · LEARNING
AI for Learning Analytics & Inclusive Access
Dimension 2 · Learning
23
▣
Engagement dashboards
Track participation, time-on-task, and submission patterns across a whole cohort at a glance.
⚠
Early-warning signals
Flag learners whose engagement or performance is dropping, before a mid-term crisis.
♿
Accessibility support
Auto-captioning, screen-reader-friendly formats, and read-aloud tools widen participation.
⊕
Multilingual inclusion
Real-time translation helps learners engage with content in their language of comfort.
DIMENSION 2 · LEARNING
Best AI Tools for Learning
Dimension 2 · Learning
24
Khanmigo (Khan Academy)
AI TUTOR
Socratic-style tutoring across subjects, widely studied for measurable learning gains.
SchoolAI
LEARNING SPACES
Teacher-created chat "sidekicks" for guided practice with progress tracking.
Century Tech
ADAPTIVE PLATFORM
AI-driven adaptive pathways with real-time analytics for teachers and learners.
ALEKS
MASTERY LEARNING
Adaptive assessment and learning, especially strong in mathematics and sciences.
Coursera Coach
COURSE-EMBEDDED TUTOR
In-course AI tutor that answers questions and explains concepts within MOOCs.
Duolingo Max
LANGUAGE LEARNING
AI role-play and explanation features layered onto adaptive language practice.
DIMENSION 2 · LEARNING
Key Journals — AI & Learning
Dimension 2 · Learning
25
International Journal of Artificial Intelligence in Education
Springer / IAIED · the field's flagship journal
IEEE Transactions on Learning Technologies
IEEE · technical learning-systems research
The Internet and Higher Education
Elsevier · online and technology-mediated learning
Journal of Educational Computing Research
Sage · computing and learning outcomes
Distance Education
Taylor & Francis · open, distance & digital learning
Interactive Learning Environments
Taylor & Francis · adaptive and interactive systems
DIMENSION 2 · LEARNING
Essential Books — AI & Learning
Dimension 2 · Learning
26
How People Learn II: Learners, Contexts, and Cultures
National Academies of Sciences, Engineering, and Medicine · National Academies Press
Learning Analytics Explained
Niall Sclater · Routledge
Intelligence Unleashed: An Argument for AI in Education
Rose Luckin, Wayne Holmes, Mark Griffiths & Laurie B. Forcier · Pearson
The Ethics of Artificial Intelligence in Education
Edited by Wayne Holmes & Ilkka Tuomi · Routledge
DIMENSION 2 · LEARNING
Learner Snapshot: An AI-Supported Study Journey
Dimension 2 · Learning
27
1
Diagnose
Short adaptive quiz reveals gaps in a foundational topic.
→
2
Practice
AI tutor offers guided questions at the learner's level.
→
3
Reflect
Learner explains reasoning back to the tutor to check understanding.
→
4
Progress
System unlocks the next topic once mastery is demonstrated.
DIMENSION 2 · LEARNING
Issues & Challenges in Learning
Dimension 2 · Learning
28
1
Confidently wrong tutoring
AI tutors can explain an incorrect answer just as confidently as a correct one, so unsupervised use can embed misconceptions.
2
Over-reliance on ready answers
Learners who default to asking AI for finished answers risk skipping the struggle that builds real understanding.
3
Uneven access outside class
Adaptive platforms assume a device and reliable connectivity that not every learner has at home.
4
Learner data privacy
Analytics and tutoring platforms collect fine-grained learner data that needs clear consent and safeguards.
DIMENSION 2 · LEARNING
Tips & Suggestions for Learning
Dimension 2 · Learning
29
✎
Build in periodic spot-checks
Sample AI-tutor transcripts regularly to catch confident errors before they spread across a cohort.
▤
Ask learners to explain back
Have learners restate the AI tutor’s reasoning in their own words — it keeps understanding, not just answers, the goal.
♪
Offer low-bandwidth alternatives
Pair adaptive tools with offline or print options so access outside class does not depend on connectivity.
Suggestion: Set clear, shared norms with learners on which AI tools are approved and how their data will be used and protected.
03
DIMENSION THREE
AI for Evaluation
Empowering assessment: grading, feedback, and integrity.
Dimension Three
26
DIMENSION 3 · EVALUATION
What AI Changes in Evaluation
Dimension 3 · Evaluation
31
1
From delayed to immediate feedback
Learners can receive rubric-aligned feedback within minutes rather than weeks.
2
From sampling to scale
AI-assisted grading makes it feasible to give detailed feedback on every submission, not just a sample.
3
From suspicion to verification
AI-text detectors and process-based assessment design help address integrity concerns directly.
4
From ad hoc to structured rubrics
AI assists in drafting clear, criterion-referenced rubrics and question banks.
DIMENSION 3 · EVALUATION
Automated Assessment & AI-Assisted Grading
Dimension 3 · Evaluation
32
✓
Objective-item scoring
MCQs, short numeric answers, and structured responses can be graded instantly and consistently.
✍
Essay & open-response support
NLP tools score against a rubric and draft first-pass feedback for teacher review, not final grades.
⚖
Consistency across graders
AI can flag inter-rater discrepancies when multiple teachers grade the same assignment.
Principle: AI-assisted grading should support, not replace, teacher judgment on high-stakes assessments — always retain human sign-off.
DIMENSION 3 · EVALUATION
AI for Formative Feedback at Scale
Dimension 3 · Evaluation
33
↻
Draft-stage feedback
Learners get structured comments on drafts before final submission, encouraging revision.
≡
Rubric-anchored comments
Feedback is generated against explicit criteria, keeping it specific rather than generic.
◎
Personalized next steps
AI suggests targeted practice based on the specific gaps identified in a learner's submission.
DIMENSION 3 · EVALUATION
AI, Academic Integrity & Plagiarism Detection
Dimension 3 · Evaluation
34
✓
AI-text and similarity detection
Institutional tools flag likely AI-generated or copied text for human review — not automatic penalty.
✎
Process-visible assessment design
Oral defenses, drafts-with-history, and in-class components make the learning process visible.
⚖
Clear institutional AI-use policy
Explicit guidance on permitted AI use per assignment reduces ambiguity and disputes.
DIMENSION 3 · EVALUATION
Best AI Tools for Evaluation
Dimension 3 · Evaluation
35
Gradescope
AI-ASSISTED GRADING
Groups similar answers for consistent, fast grading of handwritten and typed work.
Turnitin
INTEGRITY & AI DETECTION
Similarity checking plus AI-writing indicators to support academic-integrity review.
Quillionz
QUESTION GENERATION
Generates question banks from source text for quizzes and practice tests.
Formative
REAL-TIME FEEDBACK
Live, auto-scored formative checks with instant class-wide response tracking.
Grammarly
WRITING FEEDBACK
Sentence-level writing feedback that supports revision before formal submission.
ChatGPT / Claude (rubric mode)
RUBRIC & ITEM DRAFTING
Drafts criterion-referenced rubrics and item banks for teacher review and refinement.
DIMENSION 3 · EVALUATION
Key Journals — AI & Assessment
Dimension 3 · Evaluation
36
Assessment & Evaluation in Higher Education
Taylor & Francis · leading HE assessment journal
Educational Assessment, Evaluation and Accountability
Springer · assessment systems and policy
Studies in Educational Evaluation
Elsevier · evaluation methodology and practice
Higher Education Research & Development
Taylor & Francis · HE pedagogy and assessment
Language Testing
Sage · relevant for AI in language assessment
Journal of Computer Assisted Learning
Wiley · technology-based assessment studies
DIMENSION 3 · EVALUATION
Essential Books — AI & Assessment
Dimension 3 · Evaluation
37
Machine Scoring of Student Essays: Truth and Consequences
Edited by Patricia Freitag Ericsson & Richard Haswell · Utah State University Press
Automated Essay Scoring
Beata Beigman Klebanov & Nitin Madnani · Morgan & Claypool / Springer
Assessment and Learning
Edited by John Gardner · Sage
Handbook of Formative Assessment in the Disciplines
Edited by Heidi L. Andrade, Robin D. Tierney & Aukje Anna Smit · Routledge
DIMENSION 3 · EVALUATION
Evaluation Snapshot: Redesigning an Assessment with AI
Dimension 3 · Evaluation
38
1
Draft rubric
AI proposes a criterion-referenced rubric from the learning outcomes.
→
2
Refine
Teacher adjusts weightings and adds discipline-specific criteria.
→
3
Score & feedback
AI generates first-pass scores and comments; teacher reviews and finalizes.
→
4
Report
Class-level patterns inform the next teaching unit.
DIMENSION 3 · EVALUATION
Issues & Challenges in Evaluation
Dimension 3 · Evaluation
39
1
Imperfect AI-text detection
Similarity and AI-writing detectors produce false positives and negatives, so flags need human judgment, not automatic penalties.
2
Risk to teacher judgment
Automating grading and feedback can quietly sideline the teacher’s own judgment on high-stakes decisions.
3
Bias in rubrics and scoring
AI scoring models trained on unrepresentative data can systematically favour certain writing styles or backgrounds.
4
Learner trust and anxiety
Undisclosed AI-assisted grading can raise fairness concerns and anxiety among students if not communicated clearly.
DIMENSION 3 · EVALUATION
Tips & Suggestions for Evaluation
Dimension 3 · Evaluation
40
✎
Keep human sign-off on high stakes
Let AI draft scores and comments, but require a teacher to review and finalize every high-stakes grade.
▤
Pair detection with visible process
Combine similarity checks with drafts-with-history and oral components so the learning process stays visible.
♪
Pilot on low-stakes tasks first
Trial AI-assisted grading on formative work before extending it to exams or final assessments.
Suggestion: Publish a clear, simple AI-use policy for each assignment so learners know exactly what is and is not permitted.
04
CROSS-CUTTING
Responsible Adoption
Ethics, privacy, and building faculty capability — across all three pillars.
Cross-Cutting
35
CROSS-CUTTING
Ethics, Bias & Responsible AI Use
Cross-Cutting
42
⚖
Algorithmic bias
AI models trained on skewed data can disadvantage particular groups of learners — review outputs critically.
◈
Over-reliance risk
Excessive dependence on AI can erode learners' own reasoning and writing skills if unchecked.
✎
Transparency with learners
Disclose when and how AI is used in teaching materials, tutoring, or grading.
✓
Human-in-the-loop by default
Every high-stakes AI output — grade, feedback, or content — passes through teacher judgment before use.
CROSS-CUTTING
Data Privacy & Institutional Safeguards
Cross-Cutting
43
☷
Learner data minimization
Avoid entering identifiable student information into public AI tools without institutional approval.
⚑
Institutional AI-use policy
Follow your institution's approved tool list and data-handling guidelines before classroom use.
✓
Consent & disclosure
Inform learners when their submissions may be processed by AI-based tools.
CROSS-CUTTING
Building Faculty AI Literacy: A Competency Ladder
Cross-Cutting
44
1
Aware
Understands what generative and adaptive AI can and cannot do.
→
2
Experimenting
Tries AI tools for low-stakes tasks: drafts, ideas, practice questions.
→
3
Integrating
Embeds AI routinely into lesson prep, feedback, or assessment design.
→
4
Leading
Mentors colleagues and shapes departmental AI-use policy.
05
WORKSHOP PRACTICE
From Insight to Practice
Hands-on tasks and discussion for the remaining session time.
Workshop Practice
39
WORKSHOP PRACTICE
Hands-On Activity for Today
Workshop Practice
46
1
Pick a real task
Choose one recurring task from your own course: a lecture, a worksheet, or a rubric.
2
Try one AI tool
Use a tool introduced today to draft a first version of that task, in pairs.
3
Critique & refine
Edit the AI draft for accuracy, tone, and fit with your learners — note what you changed and why.
4
Share back
Each pair shares one insight — a win, a limitation, or a surprise — with the larger group.
WORKSHOP PRACTICE
Quick-Start AI Toolkit: Top 10 Cheat Sheet
Workshop Practice
47
1. ChatGPT / Claude
TEACHING
Drafting, explaining, rubric and question generation.
2. MagicSchool AI
TEACHING
Teacher-specific lesson and worksheet suite.
3. Canva Magic Studio
TEACHING
Slide and handout design from text prompts.
4. Khanmigo
LEARNING
Socratic AI tutor for guided practice.
5. Century Tech / ALEKS
LEARNING
Adaptive, mastery-based learning pathways.
6. Coursera Coach
LEARNING
In-course AI tutor for MOOC-style content.
7. Gradescope
EVALUATION
AI-assisted grading at scale, with consistency checks.
8. Turnitin
EVALUATION
Integrity checking and AI-writing indicators.
9. Quillionz
EVALUATION
Question-bank generation from source material.
WORKSHOP PRACTICE
Group Discussion Prompts
Workshop Practice
48
?
Where does AI help most in your context?
Which of the three pillars — teaching, learning, or evaluation — has the most immediate need in your department?
?
What is one risk you want to guard against?
Bias, over-reliance, privacy, or integrity — which concerns you most, and why?
?
What would responsible adoption look like?
What institutional policy or personal practice would make AI use in your course more responsible?
RESOURCE BANK
Consolidated Resource Bank: Top Journals
Resource Bank
49
British Journal of Educational Technology
Teaching · Wiley
Computers & Education
Teaching · Elsevier
Intl. Journal of Artificial Intelligence in Education
Learning · Springer / IAIED
IEEE Transactions on Learning Technologies
Learning · IEEE
Assessment & Evaluation in Higher Education
Evaluation · Taylor & Francis
Studies in Educational Evaluation
Evaluation · Elsevier
Education and Information Technologies
Cross-cutting · Springer
Computers and Education: Artificial Intelligence
Cross-cutting · Elsevier
RESOURCE BANK
Consolidated Resource Bank: Top Books
Resource Bank
50
Teaching with AI — Bowen & Watson
Teaching · Johns Hopkins University Press
Artificial Intelligence in Education — Holmes, Bialik & Fadel
Foundations · Center for Curriculum Redesign
Intelligence Unleashed — Luckin, Holmes, Griffiths & Forcier
Learning · Pearson
Learning Analytics Explained — Sclater
Learning · Routledge
Automated Essay Scoring — Beigman Klebanov & Madnani
Evaluation · Springer
The Ethics of Artificial Intelligence in Education — Holmes & Tuomi (Eds.)
Cross-cutting · Routledge
ACTION PLAN
Your Monday Morning Checklist
Action Plan
51
✓
Pick one course and one task
Choose a single recurring task — not your whole course — to pilot an AI tool on.
✓
Check your institutional policy
Confirm what your institution currently permits before using any AI tool with student data.
✓
Try, review, and disclose
Use the tool, personally verify the output, and tell learners where AI was involved.
✓
Share what you learn
Bring your experience back to your department — responsible adoption spreads through peers, not mandates.
BRINGING IT TOGETHER
Overall Tips & Suggestions
Overall Takeaways
52
1
Start small, one task at a time
Across teaching, learning, and evaluation, pilot one tool on one recurring task before scaling adoption further.
2
Keep humans in the loop, always
Whatever the pillar, every high-stakes output — content, tutoring, or a grade — should pass through human judgment.
3
Follow institutional policy
Check your institution’s approved tool list and data-handling guidelines before using AI with student data.
4
Build literacy, then share it
Move up the competency ladder deliberately, and bring what you learn back to your department — adoption spreads through peers.
Thank You
Questions, reflections, and discussion
Dr. N. A. Reddy�Department of Education, North-Eastern Hill University (NEHU), Shillong�LinkedIn: linkedin.com/in/dr-naraginti-amareswaran-reddy-97308019�X (Twitter): @amareswaran
UGC-MMTTC, Savitribai Phule Pune University · 10 October 2026