Learning workflow using learner-generated digital media (LGDM) assignments.

Citation:
2017
Issue Date:
2017-12-10
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With the implementation of Learner-Generated Digital Media (LGDM) as an assessment tool (Reyna et al., 2017), students are increasingly becoming co-creators of content in Higher Education. To implement digital media assessments, educators require an understanding of the different media types and the skills involved in the effective production. This understanding will enable them to effectively allocate student workload and marks for the task. It will also inform the design of marking rubrics that assess digital media as part of communication skills. The digital media type and its complexity will define if the task should be individual or group work. If group work is required, a strategy such as a peer review needs to be implemented to ensure every member of the group contributes. Additionally, if educators understand digital media types and the skills required to produce LGDM, they can scaffold student digital media literacy across curricula. This research proposes a Learning Workflow for Digital Media Assignments (LWDMA) based on two theoretical underpinnings: the Digital Media Literacies Framework (DMLF)(Reyna et al., 2017); and the concept of digital technologies as Technological Proxies (TPs) in the learning process (Hanham et al., 2014). The DMLF proposed three domains (conceptual, functional, and audio-visual) which need to be mastered to produce effective LGDM. In contrast, TP theory identifies digital technologies as agents performing important tasks on behalf of the user. Currently, this project is collecting data that will inform the validity of the LWDMA.
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