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Direct linkWang, Hao-Chuan; Chang, Chun-Yen; Li, Tsai-Yen – Computers & Education, 2008
The work aims to improve the assessment of creative problem-solving in science education by employing language technologies and computational-statistical machine learning methods to grade students' natural language responses automatically. To evaluate constructs like creative problem-solving with validity, open-ended questions that elicit…
Descriptors: Interrater Reliability, Earth Science, Problem Solving, Grading
