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Cui, Ying; Guo, Qi; Leighton, Jacqueline P.; Chu, Man-Wai – International Journal of Testing, 2020
This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…
Descriptors: Inferences, Artificial Intelligence, Data Analysis, Computer Assisted Testing
Zlatkin-Troitschanskaia, Olga; Kuhn, Christiane; Brückner, Sebastian; Leighton, Jacqueline P. – International Journal of Testing, 2019
Teaching performance can be assessed validly only if the assessment involves an appropriate, authentic representation of real-life teaching practices. Different skills interact in coordinating teachers' actions in different classroom situations. Based on the evidence-centered design model, we developed a technology-based assessment framework that…
Descriptors: Computer Assisted Testing, Teacher Effectiveness, Teaching Skills, Reflection