Deep learning evaluation in vocational teacher education: Conducted on the principles of authentic and dialogical collaborative knowledge construction

Sanna Ruhalahti, Helena Aarnio, Heli Ruokamo

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The vocational education system is being challenged to achieve a greater amount of deep learning. To facilitate the inclusion of more deep learning in the teaching and learning process, curriculum restructuring is required. This article reports the results of a study that investigated the kind of authentic and dialogical collaborative knowledge construction toward which the DIANA model (Dialogical Authentic Netlearning Activity) directs vocational student teachers (n=76). The results indicate that using authenticity as the basis for a learning process enabled individual study circles (f=19) to define questions that were meaningful to them but mainly directed the learners toward superficial learning-oriented activities. Notably, despite engaging primarily in superficial learning-oriented activities, the results indicate that dialogical collaborative knowledge construction still directed the learners toward deep learning, demonstrating how learning changed and was enriched during the process. The framework re-designed for evaluating superficial and deep learning will facilitate the examination of vocational teacher education learning activities in the future.
Original languageEnglish
Pages (from-to)22-47
JournalNordic Journal of Vocational Education and Training
Volume8
Issue number2
DOIs
Publication statusPublished - 2018
MoEC publication typeA1 Journal article-refereed

Field of science

  • General education

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