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Understanding when students are active-in-thinking through modeling-in-context.

, , , , and . Br. J. Educ. Technol., 50 (5): 2346-2364 (2019)

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Automated Speech Act Categorization of Chat Utterances in Virtual Internships., , , and . EDM, International Educational Data Mining Society (IEDMS), (2018)NeRoSim: A System for Measuring and Interpreting Semantic Textual Similarity., , , , , , and . SemEval@NAACL-HLT, page 164-171. The Association for Computer Linguistics, (2015)Effect of Domain Corpus Size and LSA Vector Dimension: A Study in Assessing Student Generated Short Texts in Virtual Internships Without Participant Data., , and . FLAIRS, page 179-184. AAAI Press, (2019)DTSim at SemEval-2016 Task 1: Semantic Similarity Model Including Multi-Level Alignment and Vector-Based Compositional Semantics., , , and . SemEval@NAACL-HLT, page 640-644. The Association for Computer Linguistics, (2016)Supporting Distributed Search in Virtual Worlds., , , , and . HCI (26), volume 8029 of Lecture Notes in Computer Science, page 395-404. Springer, (2013)Supporting data collection in virtual worlds., , , and . VRST, page 193-194. ACM, (2012)Safeguarding Web Surfing with URL Blacklisting., , and . ITNG, page 157-162. IEEE Computer Society, (2015)Modeling Classifiers for Virtual Internships Without Participant Data., , , , and . EDM, International Educational Data Mining Society (IEDMS), (2017)Assessing Student-Generated Design Justifications in Virtual Engineering Internships., , , , and . EDM, page 496-501. International Educational Data Mining Society (IEDMS), (2016)Markov Analysis of Students' Professional Skills in Virtual Internships., , , , and . FLAIRS, page 116-121. AAAI Press, (2017)