Improving the Retention and Progression of Learners Through Intelligent Systems for Diagnosing Metacognitive Competencies – A Case Study in UK Further Education

Tej Samani, Ana Isabel Canhoto, Esin Yoruk

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Metacognitive competencies related to cognitive tasks have been
shown to predict learning outcomes. Less however is known about how metacognitive competencies can enhance the retention and progression of learners in Further Education. This study provides evidence from Performance Learning (PL)
and its intelligent system PLEX, PL’s proprietary technology, to show how learners’
self-reports on meta-cognitive dimensions can be used as predictors of learner
retention and progression within the learner’s course/s. The results confirm the
predictive potential of PLEX technology in early identification of metacognitive
competencies in learning and helps learners with developing effective remedies
to enhance their retention and progression levels.
Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
Subtitle of host publicationHuman Interaction, Emerging Technologies and Future Applications IV
EditorsTareq Ahram, Redha Taiar, Fabienne Groff
Place of PublicationSwitzerland
PublisherSpringer
Pages20-27
Number of pages8
Volume1378
ISBN (Electronic)978-3-030-74009-2
ISBN (Print)978-3-030-73270-7
DOIs
Publication statusE-pub ahead of print - 16 Apr 2021

Fingerprint Dive into the research topics of 'Improving the Retention and Progression of Learners Through Intelligent Systems for Diagnosing Metacognitive Competencies – A Case Study in UK Further Education'. Together they form a unique fingerprint.

Cite this