Document Type : Research Paper
Authors
1 M. A. in Educational Research, Kharazmi University, Tehran, Iran.
2 Assistant Professor, Curriculum Planning Department, Kharazmi University, Tehran, Iran
Abstract
The purpose of this study was to investigate the effect of different levels of fines and difficulty of tests on the relationship between the ability and the score of individuals and determine the optimal penalties at different levels of ability according to their risk-taking attitude. In order to investigate the effect of different levels of penalties on the relationship between the ability and the score of individuals, the correlation between the ability and the score of individuals at different levels of penalties for different levels of ability was investigated and levels of penalties that lead to a maximum relationship between ability and the score of individuals in each level Ability was chosen as the optimal penalty levels for that ability level. In order to investigate the effect of the difficulty of the tests on the relationship between the ability and the score of individuals at the optimal penalties levels, the maximum correlation values at the optimal penalties levels at each level of ability in three tests (mathematics, education, and English) in mathematical discipline of 1395 according to the average difficulty of the tests compared. The results showed that both lack of penalties and high penalties reduced the correlation between the ability and the score. The optimal penalties levels in individuals with high abilities were higher than those with low ability and in general the optimal penalty for the whole individuals was higher than the normal value (0.33) (for all individuals in the math, education, and English tests Respectively minimum 40/0, 40/0 and 60/0). Also, if the average difficulty of the test questions is close to zero and the penalties are based on the levels of ability and with respect to the risk-taking attitude, the relationship between the ability and the score of the individuals is maximized.
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