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Titlebook: Assessment Analytics in Education; Designs, Methods and Muhittin Sahin,Dirk Ifenthaler Book 2024 The Editor(s) (if applicable) and The Auth

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Jessica J. M. Telleria,Bruce Sangeorzana to the present day. The second part identifies two major hurdles for learning analytics to overcome, the development of clear methodology to interpret new assessments and the political process of having these interpretations accepted by stakeholders in the educational system. The chapter concludes
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Eva Umoh Asomugha,Adam T. Grothels between students and assessment tasks, the dynamically calculated scores for both sides were discussed in the context of assessment analytics. Elo rating facilitates the simultaneous estimation of both learner skill and task difficulty, offering an approach for dynamically recalculating and upda
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First Metatarsophalangeal Joint Arthrodesisried out for this purpose. In the first two meso cycles of the design-based research process, a student-facing assessment analytics dashboard was designed and developed as well as a testing module. The reflection and evaluation phases of the study are ongoing. In this study, the learner dashboard is
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https://doi.org/10.1007/978-3-030-62926-7development and administration process, hence, quality assurance. Based on the existing literature, we conceptualize a framework with five aspects of how process data can be used for assessment quality improvement. In addition, we set these aspects in the context of computer-based assessments in mul
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Thomas Jöllenbeck,Juliane Pietschmannss. In a more realistic setting, the labels are not fully known until the semester end and supervised learning models may then create learning bias when trained only using assessment data. Therefore, cluster analysis presents a promising approach through observing performance similarities between st
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