Name
Abstract | ||
|---|---|---|
Intelligent tutoring systems have been developed to help students learn independently. However, students who are poor self-regulated learners often struggle to use these systems because they lack the skills necessary to learn independently. The field of psychology has extensively studied self-regulated learning and can provide strategies to improve learning, however few of these include the use of technology. The present proposal reviews three elements of self-regulated learning (motivational beliefs, help-seeking behavior, and meta-cognitive self-monitoring) that are essential to intelligent tutoring systems. Future research is suggested, which address each element in order to develop self-regulated learning strategies in students while they are engaged in learning mathematics within an intelligent tutoring system. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19773-9_128 | ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015 |
Field | DocType | Volume |
Intelligent tutoring system,Computer science,Knowledge management,Educational data mining | Conference | 9112 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kim M. Kelly | 1 | 20 | 4.40 |
| Neil T. Heffernan | 2 | 1087 | 135.49 |