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試演防止課題의 遂行時間과 檢査間隔이 再生量에 미치는 效果
金佐根 慶北大學校 師範大學 1983 敎育硏究誌 Vol.25 No.-
This study aimed to investigate the effects of the performance time of the distractor task and the test interval on the amount of free recall in Short-Term Memory. (STM) Sixty first-year students in middle school were randomly assigned to one of the four experimental groups as following conditions; (1) receiving 3-seconds of the distractor task to perform and 10-seconds of the test interval, (2) receiving 3-seconds of the distractor task to perform and 120-seconds of the test interval, (3) receiving 18-seconds of the distractor task to perform and 10-seconds of the test interval, and (4) receiving 18-seconds of the distractor task to perform and 120-seconds of the test interval. Projector type tachistoscope (TKK-208) was employed to present subjects with the tasks. The significance of obtained data was tested by the mixed design of 2×2×3(W) ANOVA, and the results were interpreted by one-or/and two-process theory. The conclusions obtained in this study are as follows; (1) the performance time of the distractor task has an effect on the amount of free recall in STM. (2) the test interval does net have an effect on the amount of free recall in STM. (3) the number of trials has an effect on the amount of free recall in STM. (4) the first or second order interaction effects of these variables are not found in this study.
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Characteristics of Item Parameter Estimation for the Multidimensional Item Response Theory (MIRT)
서동기,김좌근,김경태 한국심리학회 2015 한국심리학회지 일반 Vol.34 No.2
This study analyzes the three different estimation algorithms for recovering item parameters for the compensatory multidimensional IRT (MIRT) models. In particular, two- and four-dimensional models were investigated with different degrees of correlation between latent traits. The standards such as bias, standard error, and root mean square error were used to evaluate the recovery of item parameters for each program. The results indicated that in most conditions, Metropolis-Hasting Robbins-Monro (MH-RM) outperformed full information item factor analysis (FIIFA) and bivariate information item factor analysis (BIIFA) for a-parameters except for the independent and very low inter-trait correlation conditions where BIIFA outperformed the other algorithms. However, the MH-RM algorithm consistently produced the highest empirical standard errors compared to the other two methods for all conditions. FIIFA performed at a higher standard than BIIFA for a-parameters with moderately correlated latent traits. BIIFA is more suitable for a-parameters, especially when the levels of latent traits' independence or correlation are very low, and it is more suitable for d-parameters regardless of inter-trait correlations in the four-dimensional models. Overall, three estimation methods provided more accurate a- and d-parameter as the number of examinees increased, and less accurate a-parameter occurred as the inter-trait correlation increased. The inter-trait correlation condition did not have a dramatic impact on the recovery of d-parameter across all three algorithms.
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