Mastery Grids is an intelligent interface that provides access to different kinds of practice content for an introductory programming course. A distinctive feature of the interface is a parallel topic-level visualization of student progress and the progress of their peers. This contribution presents an extended version of the original system that features a fine-grained visualization of student knowledge on the level of the detailed concepts that are associated with the course. The student model is based on a Bayesian-network which is built using students performance history in the learning activities.
%0 Conference Paper
%1 citeulike:14346057
%A Pineda, Jordan B.
%A Guerra, Julio
%A Huang, Yun
%A Brusilovsky, Peter
%B Proceedings of the 22Nd International Conference on Intelligent User Interfaces Companion
%C New York, NY, USA
%D 2017
%I ACM
%K iui2017, open-student-model, social-comparison
%P 141--144
%R 10.1145/3030024.3038262
%T Concept-Level Knowledge Visualization For Supporting Self-Regulated Learning
%U http://dx.doi.org/10.1145/3030024.3038262
%X Mastery Grids is an intelligent interface that provides access to different kinds of practice content for an introductory programming course. A distinctive feature of the interface is a parallel topic-level visualization of student progress and the progress of their peers. This contribution presents an extended version of the original system that features a fine-grained visualization of student knowledge on the level of the detailed concepts that are associated with the course. The student model is based on a Bayesian-network which is built using students performance history in the learning activities.
%@ 978-1-4503-4893-5
@inproceedings{citeulike:14346057,
abstract = {{Mastery Grids is an intelligent interface that provides access to different kinds of practice content for an introductory programming course. A distinctive feature of the interface is a parallel topic-level visualization of student progress and the progress of their peers. This contribution presents an extended version of the original system that features a fine-grained visualization of student knowledge on the level of the detailed concepts that are associated with the course. The student model is based on a Bayesian-network which is built using students performance history in the learning activities.}},
added-at = {2017-11-15T17:02:25.000+0100},
address = {New York, NY, USA},
author = {Pineda, Jordan B. and Guerra, Julio and Huang, Yun and Brusilovsky, Peter},
biburl = {https://www.bibsonomy.org/bibtex/2a30c10eeb217f10cc70d33ba5074bc10/brusilovsky},
booktitle = {Proceedings of the 22Nd International Conference on Intelligent User Interfaces Companion},
citeulike-article-id = {14346057},
citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=3038262},
citeulike-linkout-1 = {http://dx.doi.org/10.1145/3030024.3038262},
doi = {10.1145/3030024.3038262},
interhash = {1043961db0cf64373ce6c02a65fc4f68},
intrahash = {a30c10eeb217f10cc70d33ba5074bc10},
isbn = {978-1-4503-4893-5},
keywords = {iui2017, open-student-model, social-comparison},
location = {Limassol, Cyprus},
pages = {141--144},
posted-at = {2017-04-28 03:09:47},
priority = {0},
publisher = {ACM},
series = {IUI '17 Companion},
timestamp = {2017-11-15T17:02:25.000+0100},
title = {{Concept-Level Knowledge Visualization For Supporting Self-Regulated Learning}},
url = {http://dx.doi.org/10.1145/3030024.3038262},
year = 2017
}