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Mining for gold: Identifying content-related MOOC discussion threads across domains through linguistic modeling.

, , , and . Internet High. Educ., (2017)

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Getting Down to Details: Using Theories of Cognition and Learning to Inform Tangible User Interface Design., and . Interact. Comput., 25 (1): 1-20 (2013)Editorial: Nine elements for robust collaborative learning analytics: A constructive collaborative critique., , and . Int. J. Comput. Support. Collab. Learn., 18 (1): 1-9 (March 2023)Knowledge Construction Patterns in Online Conversation: A Statistical Discourse Analysis of a Role-Based Discussion Forum., and . CSCL, International Society of the Learning Sciences, (2011)Beyond First Encounters with Analytics: Questions, Techniques and Challenges in Instructors' Sensemaking., , and . LAK, page 344-353. ACM, (2021)Unpacking Instructors' Analytics Use: Two Distinct Profiles for Informing Teaching., , , and . LAK, page 528-534. ACM, (2022)Topic models to support instructors in MOOC forums., , and . LAK, page 610-611. ACM, (2017)Analytics for Learning and Becoming in Practice., , , , , , and . ICLS, International Society of the Learning Sciences, (2014)Bringing order to chaos in MOOC discussion forums with content-related thread identification., , and . LAK, page 188-197. ACM, (2016)Exploring How a Co-dependent Tangible Tool Design Supports Collaboration in a Tabletop Activity., , , and . GROUP, page 81-90. ACM, (2014)Humans and Machines Together: Improving Characterization of Large Scale Online Discussions through Dynamic Interrelated Post and Thread Categorization (DIPTiC)., , and . L@S, page 217-219. ACM, (2017)