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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
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Williamson, David M.; Bauer, Malcolm; Steinberg, Linda S.; Mislevy, Robert J.; Behrens, John T.; DeMark, Sarah F. – International Journal of Testing, 2004
In computer-based interactive environments meant to support learning, students must bring a wide range of relevant knowledge, skills, and abilities to bear jointly as they solve meaningful problems in a learning domain. To function effectively as an assessment, a computer system must additionally be able to evoke and interpret observable evidence…
Descriptors: Computer Assisted Testing, Psychometrics, Task Analysis, Performance Based Assessment