1. Machine Learning in the Classroom
Maher Selim, PhD.
Machine learning Postdoctoral Fellow
Professor Wenying Feng research group
Trent University

2. Machine Learning
Machine learning is using the data to automates analysis and building analytical model.
Learn from data, machine learning using computers to find hidden pattern without being explicitly programmed.
Machine learning works especially well in prediction and classification.

3. Collecting Data from students behaviours
Machine Learning
Kotsiantis, Sotiris B. "Use of machine learning techniques for educational proposes: a decision support system for forecasting students’ grades." Artificial Intelligence Review 37.4 (2012):
Collecting Data from students behaviours

4. Machine Learning in Education
Scheduling Grading Organization Recommendation
IBM’s Chalapathy Neti vision of Smart Classrooms
By Michael Davison

5. Scheduling
Scheduling algorithms search for an optimal and adapted teaching policy for helping students to learn more efficiently.
Existing Platforms
NewClassrooms uses learning analytics to schedule personalized math learning experiences.
By Tom Vander Ark
By Michael Davison

6. Grading
Grading systems that assess and score student responses to assessments and computer assignments at large scale, either automatically or via peer grading
Existing Platforms
Grading systems that assess and score student responses to assessments and computer assignments at large scale, either automatically:
Pearson’s WriteToLearn and Turnitin’s Lightside can score essays and detect plagiarism.
By Michael Davison

7. Organization
Content analytics that organize and optimize content items like assessments, textbook sections, lecture videos, etc.
Existing Platforms
Content analytics that organize and optimize content modules:
Gooru , IBM Watson Content Analytics
Jenzabar and IBM SPSS helps HigherEd institutions predict enrollment, improve financial aid, boost retention, and enhancing campus security.
By Michael Davison

8. Recommendation
Learning analytics that build statistical models of student knowledge to provide computerized and personalized feedback on learning the students’ progress and their instructors
Active learning and experimental design, which adaptively select assessments and other learning resources for each student individually to enhance learning efficiency
Existing Platforms
Adaptive learning systems: DreamBox, ALEKS, Reasoning Mind, Knewton
Game-based learning: ST Math, Mangahigh
By Michael Davison

9. The Future Machine Learning in Education
Bill Gates: A.I. will make our lives 'more productive and creative'

10. Discussions What can Machine Learning do to make education more
productive and creative?”