### Abstract

This study explored the relationship between students’ math ability and effort in predicting 6^{th} 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.

Original language | English (US) |
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Title of host publication | Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013 |

Editors | Sidney K. D'Mello, Rafael A. Calvo, Andrew Olney |

Publisher | International Educational Data Mining Society |

ISBN (Electronic) | 9780983952527 |

State | Published - Jan 1 2013 |

Event | 6th International Conference on Educational Data Mining, EDM 2013 - Memphis, United States Duration: Jul 6 2013 → Jul 9 2013 |

### Publication series

Name | Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013 |
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### Conference

Conference | 6th International Conference on Educational Data Mining, EDM 2013 |
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Country | United States |

City | Memphis |

Period | 7/6/13 → 7/9/13 |

### Fingerprint

### Keywords

- After-school program
- ALEKS
- Effort
- Math ability
- Math performance

### ASJC Scopus subject areas

- Computer Science Applications
- Information Systems

### Cite this

*Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013*(Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013). International Educational Data Mining Society.

**Discovering the relationship between student effort and ability for predicting the performance of technology-assisted learning in a mathematics after-school program.** / Xie, Jun; Huang, Xudong; Hua, Henry; Wang, Jin; Tang, Quan; Craig, Scotty; Graesser, Arthur C.; Lin, King Ip; Hu, Xiangen.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013.*Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013, International Educational Data Mining Society, 6th International Conference on Educational Data Mining, EDM 2013, Memphis, United States, 7/6/13.

}

TY - GEN

T1 - Discovering the relationship between student effort and ability for predicting the performance of technology-assisted learning in a mathematics after-school program

AU - Xie, Jun

AU - Huang, Xudong

AU - Hua, Henry

AU - Wang, Jin

AU - Tang, Quan

AU - Craig, Scotty

AU - Graesser, Arthur C.

AU - Lin, King Ip

AU - Hu, Xiangen

PY - 2013/1/1

Y1 - 2013/1/1

N2 - 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.

AB - 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.

KW - After-school program

KW - ALEKS

KW - Effort

KW - Math ability

KW - Math performance

UR - http://www.scopus.com/inward/record.url?scp=85072306176&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85072306176&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85072306176

T3 - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013

BT - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013

A2 - D'Mello, Sidney K.

A2 - Calvo, Rafael A.

A2 - Olney, Andrew

PB - International Educational Data Mining Society

ER -