Applying Learning Analytics to Support Instruction

The Society for Learning Analytics Research (SOLAR) defines learning analytics as the collection, analysis and reporting of data about learners and their contexts for the purposes of understanding and optimizing learning and the environments in which it occurs. In this chapter, we present four case...

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Bibliographische Detailangaben
Veröffentlicht in:Score Reporting Research and Applications S. 126 - 144
Hauptverfasser: Feng, Mingyu, Krumm, Andrew, Grover, Shuchi
Format: Buchkapitel
Sprache:Englisch
Veröffentlicht: Routledge 2019
Ausgabe:1
Schlagworte:
Common Wrong Answers
Productive Persistence
Educational Data Mining
Zealand Primary School Teachers
Data Intensive Analyses
Heat Map Analyses
Large Scale Efficacy Trial
Applying Learning Analytics
MFT
Information Visualization
Professional Development
General Diagnostic Model
Online Learning System
Research Practice Partnership
Unsupervised Machine Learning
Von Davier
CT
Homework Review
Collect Student Performance Data
LA
Administrative Data Systems
Digital Learning Environments
Data Intensive Research
Improve Learning Environments
Large Scale Testing Programs
ISBN:9780815353393, 9780815353409, 0815353391, 0815353405
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Beschreibung
Zusammenfassung:The Society for Learning Analytics Research (SOLAR) defines learning analytics as the collection, analysis and reporting of data about learners and their contexts for the purposes of understanding and optimizing learning and the environments in which it occurs. In this chapter, we present four case studies where analytics were used to make sense of data from a variety of technologies to discover and interpret student learning processes and measure students' performances. Data products were developed for practitioners in an effort to inform their instructional practices and to identify areas and strategies for improvement. The case studies vary in context, subjects, focal constructs, analytical approaches, format of data collected, and student learning tasks. The context of the studies ranges from middle school to community college students. The constructs being measured in these case studies include both learning outcomes and learning processes. The data being analyzed ranges from traditional log data of student's individually working in learning systems, to more open-ended programming process data, to speech data of students who worked collaboratively with peers. This chapter examines how the needs of practitioners shaped the work, the processes undertaken to develop data products, and the ways in which data products were ultimately used by stakeholders.
ISBN:9780815353393
9780815353409
0815353391
0815353405
DOI:10.4324/9781351136501-12