It has been found from language assessment that the results were lower in terms of reliability compared to other aspects. Therefore, the development of a reliable model on English speaking skill assessment is very important and it will hopefully bring about English language teaching improvement. The objectives of this research were to study the steps and the components of a portfolio on English speaking skill assessment as well as to develop the English speaking skill assessment criteria for grade 6 students. The research methods used include a review of documents and interviews of nine experts on English language teaching and language assessment. The data was analysed using content analysis method. The results found that the component of the portfolio on English speaking skill assessment for grade 6 students comprises three parts: 1) Introduction 2) Contents and 3) Assessment criteria. There are 7 steps in using a portfolio in assessment: 1) planning 2) preparation for students 3) evidence collecting 4) progress monitoring 5) improvement of performance 6) reflection and 7) displaying the works. The tasks involved in English speaking skill assessment include interviewing, oral presentation, storytelling, making picture description. Analytic rating scale was applied as scoring criteria on vocabulary, syntax, cohesion, pronunciation ideational function and fluency.
Model specification issues on the cross-level two-way differential item functioning model were previously investigated by Patarapichayatham et al. (2009). Their study clarified that an incorrect model specification can easily lead to biased estimates of key parameters. The objective of this article is to provide further insights on the issue by specifically focusing on the impact of model selection strategies. Six model selection strategies were compared in this study. Through analyses of repeatedly simulated data, frequencies of each model being selected as the best model and parameter estimates were evaluated. As a result, it was found that the Bayesian information criterion (BIC) strategy tended to choose incomplete models more often than other strategies and led to more biased parameter estimates.
A variety of statistical methods is available for detecting Differential Item Functioning (DIF) in the Rasch model. Most of these methods consist of two approaches. The first is based on the comparison of the item parameters estimate pre-specified groups of subjects. The second is based on a comparison between all possible groups of subjects, regardless of person covariates. The purpose of this research is to compare the efficiency of Differential Item Functioning (DIF) detection between three methods: (1) Logistic regression based on classical test theory; (2) SIBTEST based on item response theory and (3) Raschtree based on modelbased recursive partitioning. Detection of DIF was collected through simulation. The first phase of the study revealed the advantages and disadvantages of these three methods from a literature review. The second phase of the research compared the efficiency of DIF detection using data simulation of four factors: type of item, number of DIF, test length and sample size.
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