منصور توکلی

Adaptive teaching addresses students’ diversity and their immediate learning needs. Particularly, in the high-interactive context of English teaching, fostering adaptive teaching in teacher professional development programs not only stimulates teacher change at the micro level, but also facilitates implementing the organizational and curricular innovations imposed by authorities at the macro level. The current English teaching literature lacks a measure for evaluating and fostering adaptive teaching within higher education. Hence, within the present study, the Interconnected Model of Teacher Professional Growth (IMTPG) was adapted and validated as a measure for evaluating and fostering teacher adaptability for 183 international English teachers in higher education. Structural Equation Modelling (SEM) was employed for validating two different enactment and reflection links in the original IMTPG, and the final adapted IMTPG for adaptive teaching (At-IMTPG) was proposed. The AT-IMTPG can be applied for evaluating how adaptive English teachers are, seeking to resolve the problem of implementing educational innovations by English teachers in higher education. It can also be used to design teacher professional growth programs for fostering adaptive teaching within English teaching higher education. Such a change in the classroom level is hoped to be translated into an educational change in English teaching higher education.

 Task sequencing (TS) has been a focus of empirical investigations in task-based language teaching (TBLT). Previous studies on TS failed to represent classroom contexts because they did not provide learners with corrective feedback (CF). This study aimed to address this gap by examining the combined effects of TS and CF on writing complexity, accuracy, and fluency (CAF). To do so, 113 upper-intermediate EFL learners were selected and divided into two groups. Participants took a pretest at the beginning of the study. Each group performed two three-task sets in simple-to-complex(S-C) or complex-to-simple(C-S) order. In each group, the errors in the first set of tasks were given CF by error codes (ECs), while the errors in the second set were only underlined. Participants in both groups were asked to revise their texts based on the provided CF and take a posttest at the end of the study. Multivariate analysis of variance (MANOVA) was run to analyze the pretest and posttest data. The results showed that the group performing tasks in S-C order and receiving ECs outperformed the others. Findings supported the SSARC (Stabilize, Simplify, Automatize, Reconstruct, Complexify) model. The study has implications for material development.

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.

This study investigated the effectiveness of two different scopes of corrective feedback on enhancing the complexity, accuracy, and fluency of L2 written productions among 150 intermediate EFL learners participating in intact online courses. The corrective feedback scope includes highly focused and comprehensive feedback delivered via digital platforms in synchronous and asynchronous formats. Participants were divided into five groups: synchronous highly focused feedback, synchronous comprehensive feedback, asynchronous highly focused feedback, asynchronous comprehensive feedback, and a control group receiving corrective feedback via traditional methods, characterized by the indiscriminate identification and marking of all errors. Results across the feedback groups regarding their impact on complexity, accuracy, and fluency in EFL learners' written productions indicated a significant effect on accuracy, while complexity and fluency showed no significant differences based on feedback scope and delivery modality. The results of this study have several important implications for educators, material developers, and policymakers in the field of language education. For teachers, adopting synchronous feedback strategies could significantly enhance the accuracy and complexity of students' written work.

The study, which has been derived from a larger project, examined how effective ChatGPT, compared to human raters, is for scoring writing tasks when tasks were arranged from simple to complex or vice versa. In so doing, a correlational design was employed. The participants were 113 EFL learners. Two sets of writing tasks were customized based on the SSARC (simplify, stabilize, automatize, reconstruct, complexify) model. The participants were divided into two groups. They took a pre-test and did tasks in two different orders. The tasks were rectified by the researcher and returned to them later. The participants enhanced their text based on comments on tasks. After that, they took a posttest. Human raters and ChatGPT scored the pretests and posttests.  A Pearson Correlation test was run to obtain the correlation between a human rater and ChatGPT. The results indicated a strong positive correlation between scores assessed by human raters and those by ChatGPT when tasks were arranged from simple to complex (r = 968, p > 05) or complex to simple (r = 860, p > 05). These findings suggest that ChatGPT can be an effective tool for writing assessments. Suggestions for further research are discussed.