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Evaluating test-taking motivation based on process data and its influence on academic performance
Jimei Ding1, Ting Li2, Yuan Liu3
1Faculty of Psychology, Southwest University, Chongqing, China.
A new behavioral effort measure, derived from process data, effectively assesses students' test-taking motivation (TTM). This novel approach correlates with traditional measures and predicts academic performance better than existing methods.
Area of Science:
- Educational Psychology
- Assessment and Measurement
- Learning Sciences
Background:
- Understanding student test-taking motivation (TTM) is crucial in large-scale assessments.
- Traditional measures like self-reported effort and response time effort (RTE) have limitations.
- Existing methods often fail to capture situational influences on TTM during testing.
Purpose of the Study:
- To introduce and validate a novel concept of behavioral effort for assessing TTM.
- To address the limitations of traditional TTM measures.
- To evaluate the predictive validity of behavioral effort on academic performance.
Main Methods:
- Utilized process data from the Programme for International Student Assessment (PISA) 2018 (N=2853).
- Developed a "behavioral effort" metric from student interaction data.
- Validated behavioral effort against self-reported measures and RTE.
- Employed multilevel analysis to predict academic performance.
Main Results:
- Behavioral effort demonstrated a strong positive correlation with traditional TTM measures (self-report and RTE).
- Behavioral effort significantly predicted academic performance.
- The effect size of behavioral effort on performance surpassed that of traditional measures.
Conclusions:
- Behavioral effort, extracted from process data, offers a robust and valid method for assessing TTM.
- This new metric provides a more effective predictor of academic performance than conventional approaches.
- The findings highlight the utility of process data in understanding student motivation and achievement.
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