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Agile-Blended Learning as a Metropolitan Teaching Approach

  • Conference paper
  • First Online:
Blended Learning : Lessons Learned and Ways Forward (ICBL 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13978))

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Abstract

This paper proposes a novel pedagogical approach, named Agile-Blended Learning (AB learning), designed for individuals residing in metropolitan areas who have a multitude of commitments, including long working hours and familial obligations, and who prefer utilizing technology for learning. Learners in metropolitan areas require flexibility, personalized learning, and possess a strong inclination towards self-management of their learning process. The AB learning approach consists of four fundamental features: flexibility, collaboration, learner autonomy, and technology mediation. AB learning offers flexibility in various areas, such as time, spatial delivery, study mode, pace, course design, learning activities, and learning materials. As a crucial component of AB learning, collaborative learning emphasizes both peer-to-peer collaboration and collaboration between learners and teachers throughout the learning process. Additionally, learners are provided with a high degree of autonomy when planning, designing, and implementing their learning, including in terms of time, space, content, and learning modes. Finally, AB learning incorporates a broad range of technologies to enhance flexibility and personalized learning. The use of educational technologies not only enriches learners’ experiences but also improves their digital literacy.

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Correspondence to Kam Cheong Li .

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Li, K.C. (2023). Agile-Blended Learning as a Metropolitan Teaching Approach. In: Li, C., Cheung, S.K.S., Wang, F.L., Lu, A., Kwok, L.F. (eds) Blended Learning : Lessons Learned and Ways Forward . ICBL 2023. Lecture Notes in Computer Science, vol 13978. Springer, Cham. https://doi.org/10.1007/978-3-031-35731-2_2

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  • DOI: https://doi.org/10.1007/978-3-031-35731-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35730-5

  • Online ISBN: 978-3-031-35731-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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