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This study scrutinized the impact of Web 2.0 on the language achievement and self-regulated learning of Iranian EFL learners in online language courses. A mixed-methods approach was employed to leverage the Learning Management System (LMS) alongside WhatsApp as a supplementary tool in the experimental group. In the quantitative segment conducted over a three-month semester, an experimental design was implemented involving 24 Iranian male and female students from the Iran Language Institute (ILI). These participants were divided into two coeducational online classes: LMS and WhatsApp were utilized in the experimental group (n=12), while the control group (n=12) solely employed LMS. Quantitative data were gathered using the Oxford Placement Test (OPT), the Language Learning Self-Regulated Scale, and pre-test and post-test assessments. Concurrently, the qualitative phase entailed interviews with 8 participants, aimed at capturing nuanced insights into the advantages and disadvantages of utilizing WhatsApp alongside LMS for online learning. The quantitative outcomes revealed a notable impact on language achievement and self-regulated learning among EFL learners in the experimental group, emphasizing WhatsApp's supplementary role. Furthermore, qualitative findings shed light on the multifaceted aspects of employing WhatsApp in conjunction with LMS, unveiling both its merits and drawbacks. The implications for online EFL classes are substantial, offering valuable insights into optimizing digital platforms for enhanced language learning experiences.

It is assumed that web-based dynamic assessment will continue to thrive and have a profound role in pedagogy. In this regard, explanatory sequential mixed-methods design was selected to consider the effect of web-based dynamic assessment on learners' autonomy. To this end, a sample of 60 male EFL learners at high school were chosen at non-random and categorized into two groups of web-based dynamic assessment and the control group based on the convenience sampling method. the learners’ autonomy questionnaire was used as a data gathering tool for pretest and posttest in autonomy. The high school students exposed to web-based DA via a designed web based on the level and requirements of the students in grammar, however, the learners in the control group learned the grammar by the traditional or conventional method of instruction. Based on the results of Mann-Whitney U test, the learners’ autonomy means scores in web-based DA increased in comparison to those of the control group. The platform and methods employed in this study produce results that are encouraging for the field of language instruction and could produce motivational outcomes in the future. The pedagogical implications of the study

This study aimed to examine the impact of Group Dynamic Assessment (G-DA) on the listening comprehension of Iranian intermediate EFL learners. To this purpose, through the Preliminary English Test (PET) 140 Iranian EFL female learners in four English Language Institutes of Ahvaz, Iran, were tested, and 80 of them were selected as the sample of the study using convenience sampling. They were taught through group dynamic assessment. After the pretest and treatment sessions, the participants were given the listening comprehension post-test and the resultant scores were statistically analyzed to detect their development from pretest to post-test. The obtained results revealed that Group Dynamic Assessment (G-DA) had a positive impact on the participants’ listening comprehension. This finding implies that EFL teachers may need to consider the positive impact of dynamic assessment on EFL learners’ listening comprehension improvement and provide them with more opportunities to interact. They may also need to create a change in the traditional models of listening comprehension assessment which emphasize psychometric quantification of students' performances

Modern teaching practices emphasize learner autonomy and learner-centered approaches to language learning. Such teaching methods require corresponding assessment approaches. Self-assessment is viewed as an assessment mode which matches modern learner-centered teaching methodologies. However, the validity and reliability of self-assessments are not yet conclusively established. This study aimed to provide validity and reliability evidence for self-assessments among Iranian EFL university learners. The Common European Framework of Reference (CEFR) Self-Assessment Grid was translated into Persian and was given to a sample of Iranian undergraduate students of English. A C-Test battery containing four passages was used as a criterion for concurrent validation. Self-assessments of university EFL learners were examined for internal consistency and test-retest reliability. Findings showed that while self-assessments are highly reliable they lack validity as evidenced with low correlations between components of self-assessment grid and the C-Test. The implications of the study for the application of self-assessments in foreign language education are discussed.

Cognitive diagnostic models (CDMs) have received sustained attention in educational settings because they can be used to operationalize formative assessment to provide diagnostic feedback and inform instruction. A large number of CDMs have been developed over the past few years. An important component of all CDMs is a Q-matrix that specifies a particular hypothesis about the relationship between each test item and its required attributes. The purpose of this study was to construct and validate a Q-matrix for the reading comprehension section of the Islamic Azad University English Proficiency Test (IAUEPT), as an advanced English placement test designed to measure language ability of Ph.D. candidates who tend to pursue their studies in the IAU. To achieve this, using item responses of 1152 candidates to twenty items of the reading section of the test, an initial Q-matrix was constructed based on theories and models of second/foreign language (L2) reading comprehension, previous applications of CDMs on L2 reading comprehension, and brainstorming and consensus of five content experts. Then, the initial Q-matrix was empirically validated using the method proposed by de la Torre and Chiu (2016) and checking mesa plots, and heatmap plot. Five attributes were derived for the reading comprehension section: vocabulary, grammar, making an inference, understanding specific information, and identifying explicit information. Finally, the analysis of the Generalized Deterministic Inputs, Noisy “and” Gate (GDINA) regarding absolute fit at item- and test-level as well as three residual-based statistics showed the accuracy of the Q-matrix and a perfect model-data fit.

The present study scrutinized the probable significant correlation between Iranian language learners’ emotional intelligence (EQ) and reading proficiency. Moreover, the significant predicting role of the participants’ EQ for their reading comprehension proficiency was investigated. To this end, 196 Iranian B.A. English language teaching students at Islamic Azad university of Neyshabur attended the study. They formed unequal proportion of gender. The study followed a quantitative descriptive design, in which the significant correlation between the variables and the significant predicting role of EQ were investigated. As the normality of data was proved through Kolmogrow-smirnow test, the parametric statistical analyses, including descriptive statistics, Pearson correlation coefficient, independent sample T-test, and linear regression analyses were employed. The data collection instruments were an ETS TOEFL reading comprehension test and Bar On’s (1997) inventory of emotional quotient. The findings demonstrated significant positive correlation coefficients between the participants’ reading proficiency and overall EQ as well as most of its subcategories. Three highest positive significant correlation coefficients were seen among the participants’ reading proficiency level, happiness, problem-solving, and emotional self-awareness successively. The results of linear regression analysis also reflected that EQ significantly predicted the participants’ reading proficiency. No significant differences were found between the genders concerning EQ. The findings laid emphasis on the influential importance of psychological non-linguistic factors in improving linguistic competence of language learners. Language teachers should be acutely conscious of the highly influential role of psychological paradigms in boosting language learning process of language learners.

The documentation of test takers’ achievements has been accomplished through large-scale assessments to find general information about students’ language ability. To remove subjectivity, Cognitive Diagnostic Assessment (CDA) has recently played a crucial role in perceiving candidates’ latent attribute patterns to find multi-diagnostic information rather than single proficiency classification. However, there are some gaps in the literature about in detail investigation of test takers’ listening comprehension language ability in responding to placement test items of a public English language center. The present study aims to validate an English placement test at a language center through a retrofitting process. In an exploratory mixed-method design, 449 participants from the same language center, including 274 females and 175 males, were selected. The performance of randomly selected participants in a language center placement test was analyzed by applying the GDINA model from R-studio packages, to detect Differential Item Functioning (DIF). Results of the study revealed DIF in some items since there is some bias in test items. The implication of this study is to provide meaningful interpretations of respondents’ attributes and improve teaching and learning by finding the strengths and weaknesses of candidates. For this purpose, the findings derived from the result of the study can raise the awareness of test developers in preparing unbiased items for the placement test, and at the same time, assist test-takers to become more critical of their English language achievements. It is also helpful for materials developers to become aware of developing materials free from bias.

Language testing and assessment has grown in popularity and gained significance in the last few decades, and there is a rising need for assessment literate stakeholders in the field of language education. As teachers play a major role in assessing students, there is a need to make sure they have the right level of assessment knowledge and skills to accomplish their duties as assessors. The present study sought to develop and validate an assessment literacy test. To this end, a thirty-five scenario-based Language Assessment Literacy Test (LALT) was developed based on the seven standards covered by the Standards for Teacher Competence in Educational Assessment of Students (1990). Construct validity of the test was investigated by collecting data from 168 Iranian EFL teachers. To investigate the validity of the measure, tests of reliability, item difficulty, and item discrimination were carried out. The test was then subjected to EFA (Exploratory Factor Analysis whose results showed a seven-factor solution for the test items. The implications of the study for EFL teachers, language testers, teacher trainers, and curriculum developers are discussed.

Predicting students’ performance in a course is one of the major aims of educational data mining systems. In the present study, two and three-layer artificial neural networks (ANN) and neuro-fuzzy systems (NFS) were used to predict Iranian EFL learners’ final scores and compare them with scores given by their instructor. Sixty-six students’ scores in an English reading comprehension course comprising of five sub-scores of midterm (out of 40), quiz (out of 60), final (out of 50), class participation (out of 5) and bonus (out of 2) were used for training the systems. Two and three-layer ANNs and an NFS were trained to predict students’ final scores using training data. Researchers compared the students’ final scores given by their instructor and those achieved through the ANNs and NFS. The results showed that the NFS could predict and deliver scores that were closer to the linear sum of students’ scores. Moreover, three-layer ANN had a better performance than the two-layer ANN. According to these results, data mining techniques could deliver an accurate estimate of students' abilities in a particular course.