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Objective: The involvement load hypothesis posits that the higher the involvement load of a task, the more effective it will be in improving students’ lexical learning. It does not differentiate between the different components of involvement load (need, search, and evaluation). Nor does it assume that the type of words to be learnt has any role in the effectiveness of tasks with different involvement load indices. This study compared the effect of the components of task involvement load on the comprehension, production, and retention of concrete and abstract words. Methods: Sixty upper-intermediate students were assigned to two groups. One group received a task in which the search component was dominant, the other group received a task (with the same overall involvement index) in which search was not present, and the evaluation component was the determining factor of task difficulty. A pretest, posttest, control group design (quasi-experimental method of research) was used to address the research questions. Results: One-way MANOVA results on the immediate posttest were in line with ILH predictions, showing no significant differences between tasks with equal involvement indices. On the other hand, the delayed posttest results showed that in case of receptive knowledge, there was a meaningful difference between abstract and concrete vocabulary, and the search group outperformed the evaluation group. However, the results of the productive posttest showed that the evaluation group outperformed the search group in abstract words. Conclusions: The findings can have significant implications for language learners, teachers, materials designers, and researchers.

Since the emphasis of the studies has shifted from a teacher-centered approach to a learner-centered one, researchers have discovered the significance of variables originating inside learners during the learning process. The present study was an attempt to focus on self-efficacy and strategy use as two learners’ variables. The purpose of this study was to investigate whether there is any relationship between EFL learners’ self-efficacy, strategy use, and grammar performance. In addition, it aimed to find out whether there is any difference between high self-efficacious learners and low self-efficacious learners in strategy use and grammar performance. To conduct the study, a non-experimental correlational design was used and thirty-five participants consisting of males and females studying English language teaching were selected randomly out of all the sophomores. Two questionnaires and a test were the main instruments in gathering data. Based on the results of the questionnaire, they were divided into two groups of high and low by using a normal distribution curve. As a result of running several data analysis tests, the findings of the present study revealed a significant relationship between EFL learners’ self-efficacy, strategy use, and their performance on a grammar test. Furthermore, it was illustrated that high self-efficacious learners performed better than low self-efficacious ones on the grammar test and grammar strategy use questionnaire.

Using Kane's interpretive argument model and Messick's validity argument approach, this study rigorously examined faculty and PhD candidate’s perspectives on PhD admission interviews in Iranian universities. We interviewed 10 professors and PhD interviewees which provided comprehensive insight into nuanced perspectives. We conducted rigorous content analysis to identify prevalent themes, forming a strong foundation for our analysis. This study emphasizes the vital requirement for standardized evaluation criteria, robust support systems, and an enhanced interview process to ensure fair and inclusive admission systems. Additionally, our development of guidelines based on Toulmin's reasoning model underscores the originality of our contribution and its potential to benefit stakeholders and the Ministry of Science, Research, and Technology (MSRT) in Iran. The findings highlighted the importance of standardized criteria, support, and a stronger interview process for fairness and inclusivity in selecting PhD candidates. Faculty stressed clear guidelines to remove subjectivity, while candidates voiced concerns about unclear expectations and proposed added support like mentoring and preparation programs. Based on Toulmin's reasoning model, the study crafted validity argument guidelines for this context. As a result, these proposed changes will impact stakeholders and the MSRT by enhancing the PhD candidate evaluation process and ensuring a fairness and inclusivity. This study provides valuable insights to improve PhD admission procedures at Iranian universities by integrating standardized criteria, enhancing support mechanisms, and fostering fairness in decision-making.

Construct-irrelevant variance is considered as a major threat to validity which indicates the existence of additional unrelated variables that distort the meaning of test scores and cause the test to be biased. Differential item functioning (DIF) analysis is an important technique in examining the validity and fairness of educational tests. Concerning the importance of test fairness in large-scale exams, this study aimed to (1) detect gender DIF in the reading comprehension section of the B2 First exam using the Rasch model and Mantel-Haenszel method, and (2) investigate the comparability of results from the two DIF detection techniques. To this end, the reading section of the B2 First exam was administered to 207 undergraduate students of English as a foreign language (EFL). After checking the fit of the data to the Rasch model, the results of the Rasch model-based DIF analysis showed the presence of two items indicating DIF, whereas the results of Mantel-Haenszel showed that there were three gender-DIF items.

Cloze tests are commonly used in language testing as a quick measure of overall language ability or reading comprehension. A problem for the analysis of cloze tests with item response theory models is that cloze test items are locally dependent. This leads to the violation of the conditional or local independence assumption of IRT models. In this study, a new modeling strategy is suggested to circumvent the problem of local item dependence in cloze tests. This strategy involves identifying locally dependent items in the first step and combining them into polytomous items in the second step. Finally, partial credit model is applied to the combination of dichotomous and polytomous items. Our findings showed that the new strategy results in a better model-data fit than the dichotomous model where dependence is ignored but with a lower reliability. Results also indicated that the person and item parameters from the two models highly correlate. The findings are discussed in light of the literature on managing local dependence in educational tests.