Translating Learning into Numbers: A Generic Framework for Learning Analytics

By Wolfgang Greller, Hendrik Drachsler. J. Educ. Technol. Soc., 2012

795 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d1bd219962defaeb326c3b51fb4fb1086c5b7b28

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Citations in the corpus

Enhancing socially shared regulation in collaborative learning groups: designing for CSCL regulation tools (2014, background): “For example, to deal with all of this information and make sense of it for both learner and teacher, learning analytics can be used (Greller and Drachsler 2012).”
A Systematic Review of Empirical Studies on Learning Analytics Dashboards: A Self-Regulated Learning Perspective (2020, background): “Within learning analytics, dashboards have received much attention as tools that can provide users with relevant insight, prompt user reﬂec-tion, and potentially inform interventions that are aimed at optimizing learning and the quality of the student experience [3].”
Are We There Yet? - A Systematic Literature Review on Chatbots in Education (2021, background): “Learning Analytics is defined as the research area that focuses on collecting traces that learners leave behind and using those traces to improve learning (Duval and Verbert, 2012; Greller and Drachsler, 2012).”
Learning Analytics for Learning Design: A Systematic Literature Review of Analytics-Driven Design to Enhance Learning (2019, background): “[40] Greller and Drachsler [41] identified six critical dimensions of leaning analytics that need to be covered by the design to ensure use of learning analytics in an “educationally beneficial way”.”
Privacy and analytics: it's a DELICATE issue a checklist for trusted learning analytics (2016, background): “Rapid moves and developments by enthusiasts have, however, slowed down recently due to rising concerns about the impact analytics has on individuals, their identity and integrity, as has already been identified early on by [2].”
Curriculum development for the workplace using Entrustable Professional Activities (EPAs): AMEE Guide No. 99 (2015, methodology): “Greller and Drachsler (2012) have identified five dimensions of learning analytics that may be operationalised for EPA-based competency curricula as in Table 9.”
MOOCs and the funnel of participation (2013, unknown): “One useful design framework for learning analytics [26] can be readily applied to a MOOC, but the terminology (e.”
Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education (2022, background): “An early framework suggested by [79] considers six dimensions of a LA: (1) stakeholders, (2) internal limitations (required competencies), (3) external limitations (conventions, norms, and time scale), (4) instruments, (5) data, and (6) objectives.”
In search for the most informative data for feedback generation: Learning analytics in a data-rich context (2015, background): “…close to a time when personalisation will become commonplace in learning”, although several researchers (García-Peñalvo, Conde, Alier, & Casany, 2011; Greller & Drachsler, 2012; Stiles, 2012) indicate that most institutions may not be ready to exploit the variety of available datasets for learning…”