@inproceedings{aefd2af5b8d342d4b80d974dd479c9b2,
title = "Comparing representations for learner models in interactive simulations",
abstract = "Providing adaptive support in Exploratory Learning Environments is necessary but challenging due to the unstructured nature of interactions. This is especially the case for complex simulations such as the DC Circuit Construction Kit used in this work. To deal with this complexity, we evaluate alternative representations that capture different levels of detail in student interactions. Our results show that these representations can be effectively used in the user modeling framework proposed in [2], including behavior discovery and user classification, for student assessment and providing real-time support. We discuss trade-offs between high and low levels of detail in the tested interaction representations in terms of their ability to evaluate learning and inform feedback.",
keywords = "Clustering, Educational data mining, Exploratory learning environments, Interactive simulations, User modeling",
author = "Cristina Conati and Lauren Fratamico and Samad Kardan and Ido Roll",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 17th International Conference on Artificial Intelligence in Education, AIED 2015 ; Conference date: 22-06-2015 Through 26-06-2015",
year = "2015",
doi = "10.1007/978-3-319-19773-9_8",
language = "الإنجليزيّة",
isbn = "9783319197722",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "74--83",
editor = "Cristina Conati and Neil Heffernan and Antonija Mitrovic and {Felisa Verdejo}, M.",
booktitle = "Artificial Intelligence in Education - 17th International Conference, AIED 2015, Proceedings",
}
