1. Education & AI
High level discussion points relating ‘techniques / tools’ to possible ‘projects’

2. Reinforcement Learning & Sequential Decision Making
Choose sequence of questions, tasks or modes to optimize an individual's learning progress
Provide encouraging prompts or reminders at beneficial times to optimize engagement
Frictionless assessment, constantly monitor what a student answers correctly or incorrectly and realtime update an estimate of their knowledge.

3. Computer Vision & Speech Recognition
Assessing students' concentration / frustration / stress-levels via facial expressions
Speech recognition and synthesis to coach public speaking and teach languages

4. Generative Models – Bayes / Markov etc.
Produce many novel exercises from few examples or rough templates
Generate encouraging feedback messages for students
Automatically produce quizzes from a knowledge base (e.g. Wikipedia Page → Quiz)
New creative tools for art and literature classes

5. Natural Language Processing
Conversational interfaces for interactive tutoring (Siri for Students)
Automated marking of short answer questions or essays
Answering students' free-form questions

6. Recommendation Systems & Topic Modelling
Recommend course material based on similar or successful students' choices
Automatically recommend revision material based on incorrectly answered questions
Realtime rank students' aptitude
Adaptively rank and match questions and homework by difficulty
Adaptively categorize material by topic and style
Match students and material by style and need
Match students to peer learning groups by style and need
Match students with teachers or tutors by style and need

7. Clustering / Exploratory Analysis
Group students by how they learn
Identify early-warning signs of under-performance
Understand how schools, classrooms and teachers relate to each other
Analyse course material for good structure and coverage of topics

8. No really AI
But definitely still in scope 

9. Analytics & Reporting
Realtime reports on student, classroom and school performance
Tracking of positive / negative indicators over time

10. Data Visualisation Explorable visualisations of student journeys
Present student changes over time
Present interactions with different teachers and topics.

11. Operations Research
Optimal scheduling for classrooms, teachers, sports equipment or other resources.

12. Personalised Learning
Some final discussion points

13. Learner Profiles
Use clustering to identify groups of similar students and hidden patterns
Make recommendations for intervention based on past evidence
Alert on early-warning signs or large changes

14. Personal Learning
Recommend follow-on material based on past interest and performance (e.g. Netflix recommendations for homework)

15. Competency Based Progression
Interactive tutoring (e.g. Siri for Students)
Question answering and Search (e.g. Google your textbook)
Facilitate peer learning by automatically matching students with peers at similar (or different) levels
Frictionless assessment, constantly monitor what a student answers correctly or incorrectly and real-time update an estimate of their knowledge.

16. Flexible learning environments
Automatically and dynamically schedule and allocate resources based on recent data