ArticleSN computer science2022
"This Student Needs to Stay Back": To What Degree Would Instructors Rely on the Recommendation of Learning Analytics?
Article in SN computer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed, 2 citations in OpenAlex.
No citing paper in PubMed yet.
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Authors and funding
3 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Learning analytics (LA) systems are becoming a new source of advice for instructors. Using LA provides new insights into learning behaviours and occurring problems about learners. Educational platforms collect a wide range of data while learners use them, for example, time spent on the platform, passed exams, and completed tasks and provide recommendations in terms of predicted learning success based on LA. In turn, LA might increase efficiency and objectivity in the grading process. In this paper, we examine how instructors react to the platform's automatic recommendations and to which extent they consider them when judging learners. Drawing on an adaptive choice-based experimental research design and a sample of 372 instructors, we analyze whether and to what degree instructors are influenced by the provided data and recommendations of an unknown LA system. In a follow-up study with 95 teachers, we describe the differences in the use of data between learners and the influence of early warning systems. All in all, we show the influence of automatic evaluation on teachers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.