حسین کرمی

Formative writing assessment can help writing instructors to explore weaknesses and strengths of language learners’ writing performances. The current research aimed to explore firstly writing attributes and secondly examine their reciprocal contribution to one another. To achieve such an objective, the participants (N=200) were asked to write about two different topics. One writing sample before treatment was considered as the pre-test and the other after the treatment was considered as the post-test writing sample. Having scrutinized the pre-writing samples, five raters extracted the writing attributes which appeared in pre-test and post-test writing samples. Results indicate that there is a statistically significant difference among the participants’ performances in terms of using writing attributes. The results can be advantageous for both instructors and syllabus designers to provide pedagogical materials which identify particular frailties and notify them about the more troublesome points to concentrate on in the classroom so as to arrange effective education.

Measurement has been ubiquitous in all areas of education for at least a century. Various methods have been suggested to examine the fairness of education tests especially in high-stakes contexts. The present study has adopted the newly proposed ecological approach to differential item functioning (DIF) to investigate the fairness of the Iranian nationwide university entrance exam. To this end, the actual data from an administration of the test were obtained and analyzed through both traditional logistic regression and latent class analysis (LCA) techniques. The initial DIF analysis through logistic regression revealed that 19 items (out of 70) showed either uniform or non-uniform DIF. Further examination of the sample through LCA showed that the sample is not homogeneous. LCA class enumeration revealed that three classes can be identified in the sample. DIF analysis for separate latent classes showed that three serious differences in the number of DIF items identified in each latent class ranging from zero items in latent class 3 to 43 items in latent class 2. The inclusion of the covariates in the model also showed that latent class membership could be significantly predicted from high school GPA, field of study, and acceptance quota. It is argued that the fairness of the test might be under question. The implications of the findings for the validity of the test are discussed in detail.

This study aimed to investigate the effect of task type (i.e., sentence fill-in/sentence writing) and word type (i.e., real/ pseudo) on initial learning and retention of 10 word meanings, taking the predictions of Involvement Load Hypothesis (ILH) and Technique Feature Analysis (TFA) into account. Participants were 59 intermediate-level EFL learners from eight intact classes. Each intact class was randomly assigned to one of the four learning conditions: 1) sentence fill-in with real words, 2) sentence writing with real words, 3) sentence fill-in with pseudowords, and 4) sentence writing with pseudowords. Initial learning was measured by administering a meaning recall test immediately after the tasks and medium-term retention was measured by administering the same test with rearranged items one week after the tasks phase. The results of a mixed between-within subjects ANOVA did not show any significant interaction effect between test time and learning condition. Furthermore, the main effect for learning condition was not statistically significant but there was a significant main effect for test time, suggesting that participants’ scores dropped significantly from the immediate posttest to the delayed posttest. The findings of two independent-samples t-tests failed to show any significant difference between the immediate and delayed posttest scores of the participants who received either sentence fill-in or sentence writing tasks. However, some tentative findings demonstrated that those participants who were assigned to the sentence writing task achieved higher scores on the posttests. This finding indicates that TFA has probably more predictive power than ILH and it also provides some evidence in favor of the heavier weight of the evaluation component of the ILH when compared to its search component.