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Saar, Merike; Rodríguez-Triana, María Jesús; Prieto, Luis P. – Journal of Learning Analytics, 2022
Data-informed decision-making in teachers' practice, now recommended by different teacher inquiry models and policy documents, implies deep practice change for many teachers. However, not much is known about how teachers perceive the different steps that analytics-informed teacher inquiry entails. This paper presents the results of a study into…
Descriptors: Learning Analytics, Evidence Based Practice, Data, Decision Making
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De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
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Zhang Yingbin; Paquette, Luc; Baker, Ryan S.; Ocumpaugh, Jaclyn; Bosch, Nigel; Biswas, Gautam; Munshi, Anabil – Journal of Learning Analytics, 2021
Confusion may benefit learning when it is resolved or partially resolved. Metacognitive strategies (MS) may help learners to resolve confusion when it occurs during learning and problem solving. This study examined the relationship between confusion and MS that students evoked in Betty's Brain, a computer-based learning-by-modelling environment…
Descriptors: Metacognition, Brain, Grade 6, Emotional Response
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Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gasevic, Dragan – Journal of Learning Analytics, 2021
The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust in data and difficulties in scaling LA. This paper presents a study that investigated areas of distrust and threats to trustworthy LA through a series of consultations with teaching staff and…
Descriptors: Learning Analytics, Program Implementation, Trust (Psychology), Higher Education
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Crossley, Scott A.; Karumbaiah, Shamya; Ocumpaugh, Jaclyn; Labrum, Matthew J.; Baker, Ryan S. – Journal of Learning Analytics, 2020
This study builds on prior research by leveraging natural language processing (NLP), click-stream analyses, and survey data to predict students' mathematics success and math identity (namely, self-concept, interest, and value of mathematics). Specifically, we combine NLP tools designed to measure lexical sophistication, text cohesion, and…
Descriptors: Elementary School Mathematics, Blended Learning, Self Concept, Audience Response Systems
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McCoy, Chase; Shih, Patrick C. – Journal of Learning Analytics, 2016
Educational data science (EDS) is an emerging, interdisciplinary research domain that seeks to improve educational assessment, teaching, and student learning through data analytics. Teachers have been portrayed in the EDS literature as users of pre-constructed data dashboards in educational technologies, with little consideration given to them as…
Descriptors: Case Studies, Semi Structured Interviews, Educational Research, Data Collection