DaVID — A Model of Data Visualization for the Instructional Design

Menezes, Douglas; Florencio, Diogo Lima; Silva, Renato Ely Domingues; Nunes, Isabel Dillmann; Schiel, Ulrich; Aquino, Marcus Salerno de

doi:10.1109/icalt.2017.97

Cited by 3 publications

(2 citation statements)

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“…Only 30% of the publications discussed instances of LD improvements brought about by LA in actual courses in higher education. For example: ‘improvements were made in the HLAN through the addition of new reinforcement activities before the practical exercises, with the objective of eliminating the critical points and, consequently, to obtain better results’ (de Menezes et al, 2017, p. 5).…”

Section: Resultsmentioning

confidence: 99%

“…The authors provided evaluation of the implemented LA tools (12 papers). Often such evaluation was based on the analysis of students' learning outcomes (de Menezes et al, 2017; Ozdemir et al, 2019; Yang et al, 2021). In addition, student engagement (Yang et al, 2021), cognitive engagement (de Leng & Pawelka, 2020), student retention (Rienties et al, 2016), student satisfaction (Rienties et al, 2016), academic advising and student self‐reflection (Ozdemir et al, 2019) were examined.…”

Section: Resultsmentioning

confidence: 99%

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Learning analytics driven improvements in learning design in higher education: A systematic literature review

Drugova,

Zhuravleva,

Zakharova

et al. 2023

Computer Assisted Learning

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BackgroundDriven by the ongoing need to provide high‐quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear.ObjectivesThis study is aimed to evaluate the maturity of research discussing LA‐driven LD improvements in higher education.MethodsThe systematic review analyses 49 empirical papers, assesses their quality and suggests further research directions. The review elaborates on methodological (research questions, strategy and methods, LA‐LD integration theoretical backgrounds) and substantial (LA‐driven LD improvements, types of data used, LA software development) features of the papers.Results and ConclusionsThe findings demonstrated the lack of theoretical alignment between LA and LD, with research tending towards user experience studies. The most frequently used research strategy was a case study; experiments were very rare. Researchers predominantly used parsing for collecting data and AI methods for analysing it; mostly used data types related to registering learners' engagement with learning activities as well as resources and tools provided in digital learning environments.TakeawaysThe research area discussing LA‐driven LD improvements still has a way to go before attaining the level of full maturity. Only a third of the papers reported actual LA‐driven LD improvements; moreover, only three papers measured their effectiveness. The presented LA software was mostly at the beta or implementation stages and did not assess the impact of using this software.

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Section: Resultsmentioning

confidence: 99%