Achievement Goal Impacts Students' Preferences for “Personalized Problems” in Computer-Adaptive Tests1

Abstract

The contemporary development of psychometric theories and information technologies enables students to work on algorithm-based personalized tests in classroom settings. This study aims to investigate the relationship between students' achievement goals and what they prefer as “personalized problems” in computer-adaptive tests. We theoretically contrast achievement goals with developing competency through mastery and demonstrating competency through performance goals. We asked elementary and secondary school students to work on a computer-adaptive test and to complete questionnaires about what they prefer as “personalized problems” in computer-adaptive tests. The results revealed that while mastery goals positively predicted preference for challenging problems, performance goals positively predicted preference for problems that guaranteed students’ success. Moreover, only the preference for challenging problems positively predicted the intention to take computer-adaptive tests in the future. These results suggest that simply introducing a computer-adaptive test into the classroom may not be effective. We discuss how educational technologies should be integrated into human teaching activities.