Difference between revisions of "Course on Artificial Intelligence and Education"
Gurumurthy (talk | contribs) (Created page with "=== Objectives === # Develop a critical understanding of AI # Explore possible role for AI in school education # Assess challenges and risks from AI in education # === Agend...") |
Gurumurthy (talk | contribs) |
||
| Line 6: | Line 6: | ||
=== Agenda === | === Agenda === | ||
| + | |||
| + | Why AI in education? | ||
| + | |||
| + | Jose Van Dyjck - “real-time data about individual learning processes help instructors monitor students’ progress and allow for corrective feedback. Personalized data allegedly provide unprecedented insights into how individual students learn and what kind of tutoring they need. And aggregated data about learning behavior provide the input for individual ‘adaptive learning’ schemes (Higher Education in a Networked World: European Responses to U.S. MOOCs) | ||
| + | |||
| + | AI is seen as having the potential to assist teachers in efficiently and effectively managing multi-level/multi-grade classrooms, by judging learning levels of individual students, and allowing automated development of customised educational content adapted to each student’s class and learning level. Assessing work done by a student on each part/page of the learning material, for example, would allow real-time feedback on student performance to help the teacher appropriately tailor her guidance to the child. (Making AI work for Indian Education, IT for Change) | ||
=== Resources === | === Resources === | ||
Revision as of 11:29, 24 October 2019
Objectives
- Develop a critical understanding of AI
- Explore possible role for AI in school education
- Assess challenges and risks from AI in education
Agenda
Why AI in education?
Jose Van Dyjck - “real-time data about individual learning processes help instructors monitor students’ progress and allow for corrective feedback. Personalized data allegedly provide unprecedented insights into how individual students learn and what kind of tutoring they need. And aggregated data about learning behavior provide the input for individual ‘adaptive learning’ schemes (Higher Education in a Networked World: European Responses to U.S. MOOCs)
AI is seen as having the potential to assist teachers in efficiently and effectively managing multi-level/multi-grade classrooms, by judging learning levels of individual students, and allowing automated development of customised educational content adapted to each student’s class and learning level. Assessing work done by a student on each part/page of the learning material, for example, would allow real-time feedback on student performance to help the teacher appropriately tailor her guidance to the child. (Making AI work for Indian Education, IT for Change)