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The Holistic Framework for the Integration of Learning Analytics to Decision-Making Process in the Context of Stakeholder Theory
Abstract
Success in any process hinges on well-made decisions, but evaluating the effectiveness of these decisions can be challenging. Utilizing evidence-based decision-making enables informed choices based on data and experimental results, particularly in learning environments. Learning analytics—comprising static and dynamic data from learners—enhances decision-making and the overall learning process. All stakeholders, including learners, teachers, instructional designers, researchers, and administrators, should stay updated on trends in learning analytics to make effective decisions. This chapter presents a theoretical framework for using learning analytics in decision-making, framed within Stakeholder Theory. We will explore the intersection of assessment, learning analytics, and stakeholder theory, offering suggestions for its application in educational settings. This study aims to enrich literature on assessing and applying learning analytics from various stakeholder perspectives.
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