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.
This meta-analysis investigated the strengths of the relationship between various types of motivations and accompanying future outcomes that individuals intend to change, based upon 337 effect sizes from 62 studies. Considerable variation exists within and between the effect sizes of the 14 types of motivations, ranging from a small negative effect size, r = −.13, I2 = 93.85% (k = 13), to a medium positive effect size, r = .38, I2 = 0.0% (k = 3). The following factors moderated some of the 14 summary effect sizes: (a) the type of assessment data (self-report vs. physical data); (b) the type of future outcomes (physical behavior, psychological state, and intellectual ability); (c) the use of a motivational intervention; (d) the use of a longitudinal design; and (e) the time period between the point that measured motivation and future outcomes. The moderating effects suggest that the effect size of motivations may fluctuate across various domains, while future outcomes may be almost unaffected or even affected negatively by particular types of motivations, although certain other types of motivations play positive roles.
Volume 65
Original Articles