Discovering the relationship between student effort and ability for predicting the performance of technology-assisted learning in a mathematics after-school program
Abstract
This study explored the relationship between students’ math ability and effort in predicting 6th grade students’ performance in the Assessment and LEarning in Knowledge Spaces (ALEKS) system. The students were clustered into four groups by K-means: high ability high effort, high ability low effort, low ability high effort and low ability low effort. A one-way ANOVA indicated that student’s math posttest within the high ability, high effort group was significantly higher than other groups. An interaction was therefore observed between ability and effort. Further analysis revealed that math ability and effort had a multiplication impact on students’ math posttest. That is, expending effort improves student’s math posttest but how much progress in mathematics is achieved depends on the student’s math ability. Higher students’ math ability multiplies with effort in determining performance.
Publication Title
Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013
Recommended Citation
Xie, J., Huang, X., Hua, H., Wang, J., Tang, Q., Craig, S., Graesser, A., & Lin, K. (2013). Discovering the relationship between student effort and ability for predicting the performance of technology-assisted learning in a mathematics after-school program. Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013 Retrieved from https://digitalcommons.memphis.edu/facpubs/7733
