Iranian Journal of Language Teaching Research
Volume:11 Issue: 3, Dec 2023

Second language education is a complex field that is continually evolving, shaped by the changes in teaching and learning contexts that have emerged over the past several decades. It would not be an exaggeration to say that these changes are predominantly driven by shifts in technology, shifts in educational approaches and philosophies, and shifts in societal and sociocultural perspectives, and each of them have brought with them different influences that have led second language education to where it is today. Amidst the numerous elements that contribute to its complexity, one factor that has become increasingly significant is social justice. This article provides an in-depth discussion on social justice in the context of second language teaching and learning, and how it has been impacted by technological developments, highlighting the affordances of technology

This paper explores the implications of ChatGPT for language teaching through the lens of Paulo Freire's critical pedagogy. A review of recent research on ChatGPT reveals promising opportunities for personalised and interactive learning, but also risks of propagating cultural bias, plagiarism and passive learning. Freire's concepts of 'banking' versus empowering, dialogic education provide a relevant framework for analysis. While recognising the potential of ChatGPT, a Freirean perspective suggests that efforts are needed to ensure that its integration serves goals of equity, social justice and the development of critical consciousness, not just efficiency. Suggested strategies include developing students' AI literacy, co-creating localised learning scenarios, promoting learner agency, ensuring access, and establishing ethical guidelines. Guided by Freire's ideals, ChatGPT has the potential to play a transformative role in language education. This conceptual analysis enriches our understanding of the implications of AI for language pedagogy and suggests an ethical way forward.

Drawing on duoethnography, the teacher researchers in the present study interacted with the relevant literature, engaged in dialogs, and shared artifacts to examine their knowledge, beliefs, and practices regarding fairness and justice considerations in technology-enhanced language classroom assessment. Under the domain of knowledge, they conceptualized fairness and justice and identified their components. Within beliefs, the difference between high-stakes and low-stakes assessments, the significance of students’ perceptions, and the role of computer literacy in relation to fairness and justice in technologyenhanced classroom assessment were debated. To operationalize their knowledge and beliefs, the researchers inspected their assessment practices during and following COVID-19. They agreed that fairness was distinct from justice in that the former pertained to test internal characteristics and its administration procedures while the latter referred to test external consequences at a broader social level. They believed that fairness and justice were equally important in high-stakes and lowstakes assessments, and students’ perceptions were valuable sources of feedback regarding fair and just classroom assessments. Moreover, the teachers argued that computer literacy cannot yet be considered an aspect of language ability. Finally, it was revealed that although their practice regarding fairness and justice was affected by the pandemic, they learned valuable lessons (e.g., combining online and paper assessment modalities and giving oral exams) in this respect for the future. The findings imply that language teachers should theoretically adopt a clear conception of fairness and justice while being practically prepared for future developments (e.g., technological advances) and unexpected circumstances (e.g., a pandemic).

The emergence of generative artificial intelligence (GenAI) text generator tools and the potential challenges for higher education (HE) have characterised informal academic discussion on multiple fora. Specifically examining the case of English medium instruction (EMI) assessment academic integrity, this study sought to explore this conundrum by conceptualising threats and possible recommendations to counter these by creating a problem-solution matrix for key stakeholders considering the scarce academic literature available. An exploratory Delphi technique was employed as a way of generating ideas, gauging expert perspectives, and establishing consensus based on the premise of wisdom-of-(expert)-crowds. In the data collection stage, this new use of the mixed-methods methodology in the field included iterative Delphi questionnaire rounds and concurrent focus group sessions with a panel of 26 international experts. Quantitative and qualitative data were analysed using descriptive statistics and thematic analysis, respectively. The resulting GenAI and EMI Assessment Problem-Solution Matrix is an empirically informed instrument for key stakeholders in EMI HE that exemplifies a range of GenAI-induced issues and recommendations as to how to proceed going forward in EMI HE pedagogical settings. This contributes to the field in line with broader theoretical assessment principles, particularly with those seeking to mitigate inequitable practices. Further contextual matters pertaining to social justice were highlighted, such as the effects of the massification and commodification of HE on the role of assessment in both EMI didactic contexts and others. The findings here take a step towards addressing the gaps identified but also represent a means of sparking much-needed further discussion in both extant literature and praxis.

Technology is here to stay and transfer our entire lives, including modes of communication and education. Its deep impact on our educational lives during the COVID-19 pandemic which forced education everywhere to go online cannot be denied. Technology-Mediated Language Learning (TMLL) otherwise known as Computer- Assisted Language Learning (CALL) in its various realizations (online and offline) has been a common, but limited, practice in many educational encounters for a few decades. Its recent, more widespread use on a global scale has brought to the fore less-attended but thornier issues such as social justice. This paper takes social justice in TMLL as the starting point and attempts to outline social (in)justice issues addressed in published papers on this topic from 2015 to 2023 (4 years before the pandemic up to now). To this end, relevant articles (following the inclusion/exclusion criteria) were identified (N = 16) and examined meticulously in terms of utilized data collection tools, social justice issues addressed, as well as theoretical and pedagogical implications. The review uncovers that more attention has been drawn to social justice issues in online classes after the pandemic compared to the pre-pandemic period. The studies further signify the prominent role of language teachers in promoting social justice, highlight the widening digital gap between learners, and bring to spotlight hegemonies and governing power influencing social media content.

Language Testing and Assessment: A Comprehensive Guide by Estaji and Ghiasvand (2022) constitutes a quintessential example of an instructive and informative textbook for English as a Foreign Language (EFL) students eager to navigate the subtleties of assessment in language education. The book opens new horizons for students and reinforces their assessment insights by unraveling the models, theories, notions, and practical considerations of language testing and assessment. The book is divided into 14 chapters and features critical and research-oriented content that could lay the groundwork for