Programme overview
Introduction:
AI in education has moved faster than most school and university policies: students already use chatbots for homework and essays, teachers experiment with lesson generators, and leaders face questions on cheating, student data and child safety without an agreed position. This Core Concept course helps academic teams use generative AI for lesson planning, feedback and tutoring while redesigning assessment, reading learning analytics responsibly and setting safeguards for learners of every age. Participants leave with an Institutional AI in Education Adoption Plan covering classroom practice, assessment policy, staff AI literacy and governance.
Course Objectives:
- Design lessons, rubrics and formative feedback with generative AI tools while keeping pedagogical decisions with the teacher
- Redesign coursework and examinations so that assessment evidence stays valid when students have access to AI assistants
- Configure AI tutors and adaptive practice so that they support, rather than replace, learner reasoning at each age and stage
- Interpret learning analytics dashboards to flag at-risk students early and plan proportionate academic interventions
- Draft an institutional AI use policy covering student data privacy, age limits, child safety and acceptable use for staff and learners
- Plan staff AI literacy development and an institution-wide AI adoption roadmap with clear ownership and review points
Target Audience:
- School and university leaders responsible for teaching quality, academic policy and digital strategy
- Heads of department and programme leaders who own curriculum, coursework and examination design
- Faculty members and senior teachers who lead classroom practice and mentor colleagues
- Academic technology and e-learning staff who run learning platforms and evaluate classroom AI tools
- Student affairs, admissions and academic advising staff who manage learner support and records
- Quality assurance and academic integrity officers who handle misconduct cases and assessment regulations
Course Outline:
Day 1: Generative AI in Schools and Universities: Landscape and Readiness
- Chatbots, Intelligent Tutoring Systems and Adaptive Platforms in the Classroom
- Ouyang and Jiao Paradigms: AI-Directed, AI-Supported and AI-Empowered Learners
- Hallucination, Bias and Over-Reliance Risks for Students and Teachers
- Classroom and Campus AI Use Survey of Students, Teachers and Parents
- Institutional AI Readiness Scan: Infrastructure, Policy, Skills and Culture
Day 2: UNESCO Guidance and Competency Frameworks for Education
- UNESCO Guidance for Generative AI in Education and Research: Key Measures
- Age Limits for Independent Learner Conversations with Generative AI Platforms
- UNESCO AI Competency Framework for Teachers: Five Dimensions and Acquire, Deepen, Create
- UNESCO AI Competency Framework for Students: Understand, Apply, Create Progression
- Human-Centred Pedagogical Validation of Classroom AI Tools
Day 3: Teaching, Tutoring and Feedback with Generative AI
- Prompt Patterns for Lesson Plans, Worked Examples and Differentiated Worksheets
- Rubric Drafting and AI-Assisted Formative Feedback on Student Writing
- AI Tutor Configuration with Socratic Questioning and Guardrails
- Adaptive Practice Sequencing for Mixed-Ability Classes and Cohorts
- AI Support in Admissions Queries, Timetabling and Student Services Chat
Day 4: Academic Integrity, Learning Analytics and Safeguarding
- Assessment Redesign: Oral Defence, Process Portfolios and In-Class Authentic Tasks
- AI Detection Tool Limits and Fair Academic Misconduct Procedures
- Early-Warning Indicators from Attendance, Submissions and Platform Activity
- Student Data Privacy Impact Screening for Education Technology Procurement
- Child Safety Controls, Parental Consent and Content Filtering for Minors
Day 5: Case Work: Institutional AI in Education Adoption Plan
- Case Brief: A Secondary School and a University Faculty Facing AI-Assisted Coursework
- Acceptable Use Policy Drafting for Staff, Students and Parents
- Staff AI Literacy Pathway Mapped to Teacher Competency Levels
- Phased Adoption Roadmap with Pilot Classes, Evaluation Measures and Owners
- Adoption Plan Presentation to an Academic Leadership Panel
Skills You Will Gain:
- AI-Assisted Lesson Design
- Assessment Redesign
- AI Tutor Configuration
- Learning Analytics Interpretation
- Academic Integrity Case Handling
- Education Data Privacy Screening
- Child Safeguarding in Digital Learning
- Staff AI Literacy Planning
Why Attend This Course:
- Return with an Institutional AI in Education Adoption Plan ready for review by your academic leadership
- Settle staff and student uncertainty with a clear, workable position on permitted and prohibited AI use
- Reduce disputed misconduct cases by relying on assessment design rather than unreliable detection scores
- Exchange classroom and campus practice with educators from schools, colleges and universities in other systems
Conclusion:
Generative AI will be part of how students learn whether institutions plan for it or not. The course moves from the current classroom landscape and readiness, through the UNESCO guidance and competency frameworks, into practical lesson, feedback and tutoring work, and then to the integrity, analytics and safeguarding questions that decide whether adoption is trusted. The final day turns this into an Institutional AI in Education Adoption Plan that participants can take to their leadership, test with pilot classes and refine each term.