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Nathan Mentzer; Wonki Lee; Andrew Jackson; Scott Bartholomew – International Journal of Technology and Design Education, 2024
Adaptive comparative judgment (ACJ) has been widely used to evaluate classroom artifacts with reliability and validity. In the ACJ experience we examined, students were provided a pair of images related to backpack design. For each pair, students were required to select which image could help them ideate better. Then, they were prompted to provide…
Descriptors: Evaluative Thinking, Design, Engineering Education, Evaluation Methods
Shi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics