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Exploring Datafication for Teaching and Learning Development: A Higher Education Perspective
Abstract
The scale, magnitude, and diversity of higher education teaching/learning and higher education institutions (HEIs) have resulted in corresponding diverse datafication representations. Contrary to conventional datafication, where the objective is profitability (e.g., adopting facial recognition for improved policing), the datafication of HEIs should be analysed, understood, and interpreted for its unique diversity, practice, and consequences. The result of the COVID-19 pandemic has forced a paradigm shift from conventional/traditional classroom-based teaching to online teaching, which has resulted in enhanced data collection. Taking a post-digital perspective on modern practices in higher education literature, this chapter argues for an organic view, in which the datafication must consider the aspects of teaching, learning, and educational context that are absent in digital data. The findings from the discussion lead to the conclusion that datafication can complement expert judgement in HEIs when informed by the unification of pedagogy and technology.
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