%0 Book Section %1 citeulike:12473758 %A Long, Yanjin %A Aleven, Vincent %B Artificial Intelligence in Education %D 2013 %E Lane, H. Chad %E Yacef, Kalina %E Mostow, Jack %E Pavlik, Philip %I Springer Berlin Heidelberg %K open-user-model self-assessment %P 219--228 %R 10.1007/978-3-642-39112-5_23 %T Supporting Students' Self-Regulated Learning with an Open Learner Model in a Linear Equation Tutor %U http://dx.doi.org/10.1007/978-3-642-39112-5_23 %V 7926 %X Self-assessment and study choice are two important metacognitive processes involved in Self-Regulated Learning. Yet not much empirical work has been conducted in ITSs to investigate how we can best support these two processes and improve students' learning outcomes. The present work redesigned an Open Learner Model (OLM) with three features aimed at supporting self-assessment (self-assessment prompts, delaying the update of the skill bars and progress information on the problem type level). We also added a problem selection feature. A 2x2 experiment with 62 7th graders using variations of an ITS for linear equation solving found that students who had access to the OLM performed significantly better on the post-test. To the best of our knowledge, the study is the first experimental study that shows an OLM enhances students' learning outcomes with an ITS. It also helps establish that self-assessment has key influence on student learning of problem solving tasks.

@incollection{citeulike:12473758, abstract = {{Self-assessment and study choice are two important metacognitive processes involved in Self-Regulated Learning. Yet not much empirical work has been conducted in ITSs to investigate how we can best support these two processes and improve students' learning outcomes. The present work redesigned an Open Learner Model (OLM) with three features aimed at supporting self-assessment (self-assessment prompts, delaying the update of the skill bars and progress information on the problem type level). We also added a problem selection feature. A 2x2 experiment with 62 7th graders using variations of an ITS for linear equation solving found that students who had access to the OLM performed significantly better on the post-test. To the best of our knowledge, the study is the first experimental study that shows an OLM enhances students' learning outcomes with an ITS. It also helps establish that self-assessment has key influence on student learning of problem solving tasks.}}, added-at = {2018-03-19T12:24:51.000+0100}, author = {Long, Yanjin and Aleven, Vincent}, biburl = {https://www.bibsonomy.org/bibtex/27df8e141a4961bd50134e0f1bd671b45/aho}, booktitle = {Artificial Intelligence in Education}, citeulike-article-id = {12473758}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-39112-5_23}, citeulike-linkout-1 = {http://link.springer.com/chapter/10.1007/978-3-642-39112-5_23}, comment = {QuizGuide-like OLS for self-selection of problems - the field of aAlgebra. Shows both examples and problems. Has some self-assessment. Shows OLM on two levels (group of problems) Experiment with 2 factors - OLM or no OLM, can they self-select problems or not Do better on post-test with OLM With PS they solved less problems (more efficient Self-assessment is reasonably reliable - correlates with post and pre tests No significant effect on study choice}, doi = {10.1007/978-3-642-39112-5_23}, editor = {Lane, H. Chad and Yacef, Kalina and Mostow, Jack and Pavlik, Philip}, interhash = {cb5155d514bae00d093a492660d4287a}, intrahash = {7df8e141a4961bd50134e0f1bd671b45}, keywords = {open-user-model self-assessment}, pages = {219--228}, posted-at = {2013-07-10 22:42:44}, priority = {2}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2018-03-19T12:24:51.000+0100}, title = {{Supporting Students' Self-Regulated Learning with an Open Learner Model in a Linear Equation Tutor}}, url = {http://dx.doi.org/10.1007/978-3-642-39112-5_23}, volume = 7926, year = 2013 }