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Validating the Effectiveness of the Moodle Engagement Analytics Plugin to Predict Student Academic Performance., , , and . AMCIS, Association for Information Systems, (2015)Working Together in Learning Analytics Towards the Co-Creation of Value., , , and . J. Learn. Anal., (July 2019)Student perspectives on data provision and use: starting to unpack disciplinary differences., , , and . LAK, page 158-167. ACM, (2016)OnTask: Delivering Data-Informed, Personalized Learning Support Actions., , , , , , , , , and 4 other author(s). J. Learn. Anal., (December 2018)Evaluating the scaling of a LA tool through the lens of the SHEILA framework: A comparison of two cases from tinkerers to institutional adoption., , , and . Internet High. Educ., (2020)Empowering Instructors Through Customizable Collection and Analyses of Actionable Information., , , , and . PCLA@LAK, volume 1590 of CEUR Workshop Proceedings, page 3-9. CEUR-WS.org, (2016)Knowledge Acquisition for Learning Analytics: Comparing Teacher-Derived, Algorithm-Derived, and Hybrid Models in the Moodle Engagement Analytics Plugin., , , , and . PKAW, volume 9806 of Lecture Notes in Computer Science, page 183-197. Springer, (2016)Perceived benefits and barriers of a prototype early alert system to detect engagement and support 'at-risk' students: The teacher perspective., , , and . Comput. Educ., (2020)