Dispositional Learning Analytics and Formative Assessment: An Inseparable Twinship

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Bibliographische Detailangaben
Titel: Dispositional Learning Analytics and Formative Assessment: An Inseparable Twinship
Sprache: English
Autoren: Dirk Tempelaar (ORCID 0000-0001-8156-4614), Bart Rienties, Bas Giesbers
Quelle: International Journal of Educational Technology in Higher Education. 2024 21.
Verfügbarkeit: BioMed Central, Ltd. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://www.springer.com/gp/biomedical-sciences
Peer Reviewed: Y
Page Count: 26
Publikationsdatum: 2024
Publikationsart: Journal Articles
Reports - Research
Descriptors: Learning Analytics, Formative Evaluation, Educational Innovation, Technology Uses in Education, Learning Processes, Tutorial Programs
DOI: 10.1186/s41239-024-00489-8
ISSN: 2365-9440
Abstract: Educational innovations, particularly those in online education and technology-enhanced learning, some accelerated by the recent pandemic, take centre stage in this journal. Examples include the resurgence of the flipped classroom methodology, supported by instructional technology, the utilization of formative assessment with technological assistance to provide effective learning feedback, and the integration of learning analytics within technology-enhanced learning. Despite empirical studies addressing these advancements individually, they tend to focus predominantly on the initial phase of learning feedback: where the learner currently stands. This paper contends that isolated depictions of formative assessment overlook the broader progress in technology-enhanced learning. Our contribution highlights the significance of dispositional learning analytics, which combines learning and learner data to offer insights into learners' current status, future trajectory, and methods to facilitate their advancement. We advocate for strengthening the integration of formative assessment data within learning analytics to fully harness their combined potential. An empirical study is presented to illustrate the predictive value of formative practice behaviour on module performance and explore the link between students' learning dispositions and their engagement with e-tutorials. By delineating student profiles based on practice behaviour and examining variations in learning dispositions, our aim is to enhance our comprehension of effectively supporting learners in technology-enhanced educational environments.
Abstractor: As Provided
Entry Date: 2024
Dokumentencode: EJ1443133
Datenbank: ERIC
Beschreibung
Abstract:Educational innovations, particularly those in online education and technology-enhanced learning, some accelerated by the recent pandemic, take centre stage in this journal. Examples include the resurgence of the flipped classroom methodology, supported by instructional technology, the utilization of formative assessment with technological assistance to provide effective learning feedback, and the integration of learning analytics within technology-enhanced learning. Despite empirical studies addressing these advancements individually, they tend to focus predominantly on the initial phase of learning feedback: where the learner currently stands. This paper contends that isolated depictions of formative assessment overlook the broader progress in technology-enhanced learning. Our contribution highlights the significance of dispositional learning analytics, which combines learning and learner data to offer insights into learners' current status, future trajectory, and methods to facilitate their advancement. We advocate for strengthening the integration of formative assessment data within learning analytics to fully harness their combined potential. An empirical study is presented to illustrate the predictive value of formative practice behaviour on module performance and explore the link between students' learning dispositions and their engagement with e-tutorials. By delineating student profiles based on practice behaviour and examining variations in learning dispositions, our aim is to enhance our comprehension of effectively supporting learners in technology-enhanced educational environments.
ISSN:2365-9440
DOI:10.1186/s41239-024-00489-8