Focus on Personalized Collaborative Learning: What Can We Learn from the Indigenous Sámi Teachers’ Supplementary Study Program on Digital Learning Tools?

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Abstract

The aim of this study was to find ways to modernize Sámi language teaching and teaching in the Sámi language with digital technology. We realize the importance of digital technology in enhancing the sociocultural position of minority and Indigenous languages. However, the lack of teaching and learning material in the Sámi language is still challenging. Free digital teaching and learning tools could help produce and provide learners with multimodal learning material and new ways of learning. Moreover, competencies in the use of digital technology are an internationally accepted key element of teacher education. The Focus on the North–Digital Learning for Pre- and In-Service Teacher Education Project, funded by Norgesuniversitet in cooperation with the Sámi allaskuvla - Sámi University of Applied Sciences (SUAS) in Norway and the University of Lapland in Finland, aimed to address challenges affecting education in the Arctic educational context by creating a 15-credit (ECTS) course program with three courses on digital tools in education. SUAS practice schools are in Norway, Finland, and Sweden, so distance learning and teaching didactics were designed as the core of this project. Student teachers and in-service teachers at all education levels participated in the courses. The findings indicated that teachers’ and student teachers’ experiences of personalized collaborative learning in using digital teaching tools to support Sámi language teaching were remarkable in practice, as teachers gained access to tools for coping in a demanding educational context. Digitalization provides new ways to improve learning in a threatened language context.

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APA

Keskitalo, P., Frangou, S. M., & Chohan, I. (2019). Focus on Personalized Collaborative Learning: What Can We Learn from the Indigenous Sámi Teachers’ Supplementary Study Program on Digital Learning Tools? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11937 LNCS, pp. 675–684). Springer. https://doi.org/10.1007/978-3-030-35343-8_71

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