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Volume 19 No 7 (2021)
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The Expected Loss Optimization Framework for Active Learning for Ranking
Lisa Gopal
Abstract
Students participate in activities including reading, writing, discussions, and problem-solving that encourage
analysis, synthesis, and assessment of the course material as part of the active learning process. Active learning
is encouraged through a variety of strategies, including problem-based learning, case studies, simulations, and
cooperative learning. The number and calibre of the provided paired constraints, as well as the training data,
have a significant impact on the ranking model's quality. It is an instructional strategy that places the onus of
learning on the students.
Keywords
Active Learning, Loss Optimization Framework, Encourage Analysis
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