Computer-assisted language learning

The rich and still expanding literature on TBLT is helping to mature both its theoretical conceptualization and practical implementation in foreign and second language education. Similarly, computer-assisted language learning (CALL) has grown as a field, with the use and integration of technology in the classroom continuing to increase and will continue to play an important role in this maturation process. The present study, hence, reports on an empirical study that investigated the effects of CALL-mediated TBLT on the perceived self- efficacy of Iranian university non-English major EFL students. Through non-probability and convenience sampling, two intact freshmen classes were chosen and randomly assigned as the experimental and the control group. During the treatment sessions, the students in the experimental group received instruction in a CALL-mediated TBLT format, while the control group received no CALL-mediated TBLT instruction but underwent only a task- based instruction on reading without the mediation of CALL. A univariate analysis of covariance (ANCOVA) was run, while controlling for pre-intervention scores as the covariate. A significant effect was found for CALL-mediated TBLT (F = 81.450, p = .000, partial eta squared =.504), suggesting CALL-mediated TBLT had a positive effect on the self-efficacy perceptions of the students in the experimental group .

Web-quests are internet-based technology applications in which groups of students follow a specific set of steps toward the completion of a final project on a specific subject or a multi-disciplinary subject. The present study aimed to investigate the impacts of using web-quests on learning vocabulary by Iranian pre-university students. The sample of the study consisted of 72 students assigned into two groups. One of the groups represented the control group, and included 23 students; the other group represented the experimental group and comprised 49 students. The two groups were chosen from a population of pre-university students in Chadegan, Isfahan, Iran. The web-quest strategy was used in teaching the experimental group, while the traditional method was used with the control group in the second term of the school year 2015-2016. An Oxford Placement Test (OPT), a vocabulary pretest, a vocabulary posttest, and an attitude questionnaire were the data elicitation tools employed in this study. The collected data were analyzed using independent-samples t test, which was used to determine the existence of possible significant differences between the groups both before and after the instruction. The results indicated that there were statistically significant differences between both groups in favor of the experimental group. The conclusion, thus, could be that the students in the experimental group, who used the web-quest resources for learning vocabulary, performed significantly better than the students in the control group, who learnt vocabulary through traditional method of learning vocabulary. Finally, questionnaire data analyzed via one-sample t test indicated that the experimental group learners had a positive attitude towards the treatment they experienced in the experiment.

The growing popularity of language-learning apps among language learners has highlighted the need for rigorous evaluation of their efficacy in second language acquisition (SLA). This study combined quantitative measures to comprehensively understand the effectiveness of the Busuu app in improving the productive vocabulary of Iranian intermediate EFL learners with qualitative data from in-depth interviews to explore their perceptions and experiences while using the app. Forty-three learners (17 males and 26 females with a mean age of 27.53) were selected to assess the effectiveness of the Busuu app on learners’ productive vocabulary knowledge. Among them,15 participants (all female with a mean age of 29.40) agreed to be interviewed after the Busuu study to gain insights into learners’ perceptions and experiences with app-based learning. A pretest-posttest design using the LEX30 task, a standardized productive vocabulary assessment tool, was conducted before and after the Busuu study to evaluate participants’ productive vocabulary knowledge. Paired samples t-tests revealed no significant improvement in participants’ productive vocabulary knowledge. Nonetheless, the number of responses produced in the posttest was higher than in the pretest. According to the interview data, users rated vocabulary as the most favored feature of the app, while restricted access to premium content was noted as the least favored. Most participants acknowledged that the app exceeded their initial expectations before installing it. Additionally, improving vocabulary knowledge was the users’ primary expectation from utilizing the app. Furthermore, approximately all participants found the app beneficial for language learning. However, most of them reported low levels of enjoyment during app usage. The results can contribute to understanding what needs to be done to upgrade the quality and potential of the Bussu app, how the app can better support EFL learners in effectively activating their lexical knowledge, and what the users’ experiences and expectations from a language-learning app are.

Artificial Intelligence (AI) is increasingly transforming the landscape of education, particularly within the domain of language learning, as evidenced by a growing body of research published in computer-assisted language learning (CALL) journals. These studies have examined the application of various AI technologies, including natural language processing (NLP), AI-driven educational platforms, automatic speech recognition, and chatbots, in facilitating language acquisition. The present study investigated the perceptions of 386 Iranian high school EFL students, utilizing the Students’ Perceived EFL Teacher Support Scale to evaluate the impact of AI-powered speaking assistance technologies, educational level, and learning setting on perceived teacher support. The findings revealed a tri-factorial structure underlying EFL teacher support, highlighting the compatibility of AI technologies with traditional pedagogical methods. This suggests that the integration of AI-powered tools into classroom instruction can enhance the overall effectiveness of language teaching and learning. To ensure optimal outcomes, educators are encouraged to strategically incorporate AI within pedagogically sound frameworks that maintain human-centered support. The study offers important implications for sustaining and enhancing teacher support in technology-enriched learning environments and underscores the need for further empirical research in this evolving area of applied linguistics and educational technology.

The emergence of technological advances dramatically changed the status of foreign language teaching forever, making computer-assisted language learning (CALL) into a key area in foreign language teaching and later a distinct academic discipline at higher education level. The present study describes the intended curriculum of a two-year post-graduate technology-enhanced language teaching program launched at Al-Zahra University, a women’s university in Tehran, Iran, as well as the national context within which the program was developed. It begins with a background on the significance of technology in education followed by a brief history of education in Iran. The main part of the paper describes the intended curriculum of the program from different perspectives including the aims and rationales, significance of the program, student profile (who takes it) and sources of the M.A. admission examination, abilities intended for graduates, courses of the program, syllabus and recommended readings, and assessment of the course outcomes. The paper finally concludes by discussing what is not included in the curriculum as well as the implications for teacher educators and suggestions for further research.