All Journals

Language Teaching Research Quarterly

European Journal of Studies in Management and Business

International Journal of Behavior Studies in Organizations

Studies in Educational Management

New Challenges in Accounting and Finance

Language Testing in Focus: An International Journal

Marketing and Branding Research

Individual Differences in Language Education: An International Journal 

Feedback Research in Second Language 

Management Issues in Healthcare System

Language Teacher Education Research

Artificial Intelligence Knowledge Development

<span style="font-size: 10.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: Calibri; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: FA; mso-bidi-font-weight: bold;">Small and Medium-Sized Enterprises (SMEs) continue to encounter significant obstacles in securing finance, often due to information asymmetry, limited credit histories, and inadequate collateral. Developments in Financial Technology (FinTech) have reshaped capital access by enhancing information exchange, reducing transaction costs, and introducing alternative financing models. This study offers a systematic review of empirical research on FinTech and SME financial inclusion between 2008 and 2025, using scientific methods such as PRISMA, PSALSAR, Biblioshiny, and Bibliometrix in RStudio. The findings indicate a relatively recent and fragmented body of literature, with a concentration of studies in China, Indonesia, and other emerging economies. Evidence consistently supports FinTech&rsquo;s contribution to mitigating financing barriers, particularly in developing contexts. Nonetheless, notable limitations remain, such as a dependence on secondary data, restricted geographic scope, and a scarcity of longitudinal analyses. The paper identifies these gaps and proposes directions for future research to better understand how FinTech can foster sustainable and inclusive financing for SMEs in diverse economic environments.

mbrq.2026.37.01.pdf

Review Article

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Fintech and SME Financial Inclusion: A Systematic Literature Review and Bibliometric Analysis

This study investigates the relationship between leader-member exchange and work engagement among emergency care setting nurses, considering the mediating role of humor at work. Through a causal quantitative approach, 301 employees in Emergency care settings were chosen from five hospitals at random using a simple random procedure. Three validated scales were used in this study to measure the study variables and establish a structural equation model.&nbsp; The findings reveal that Leader-Member exchange positively affects nurses' work engagement and Humor at work. But the humor on work engagement is not significantly related to work engagement. Therefore, the effects of leader-member exchange and work engagement, while humor mediates them, were not significant. The study demonstrates that leader-member exchange has a significant, direct, positive impact on both nurses&rsquo; work engagement and workplace humor. While workplace humor does not mediate this relationship, the findings highlight that direct relational leadership is the primary driver of nursing engagement. For hospital administrators in emergency care settings, this suggests a need to prioritize supervisors&rsquo; relational behaviors. Cultivating high-quality leader-member exchange directly improves the work environment and boosts nurses&rsquo; engagement, ultimately leading to more effective healthcare management and better patient outcomes.

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Original Research 

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Humor, Leader-Member Exchange, and Work Engagement: A Mediation Analysis Among Nurses in Emergency Care Settings

In the dynamic and increasingly diverse healthcare environment, career adaptability is a recognized predictor of work engagement. This study investigated the mediating effect of cultural intelligence as an underlying mechanism on the relationship among nursing professionals. Primary data were collected from a sample of nurses (N=271) using validated self-report questionnaires that assessed the three focal constructs: career adaptability, cultural intelligence, and work engagement. To test the proposed hypotheses and examine the structural relationships among the variables, Structural Equation Modeling (SEM) was utilized. The findings revealed a significant positive direct relationship between career adaptability and work engagement. Crucially, the analysis confirmed that cultural intelligence exerts a significant mediating effect on this relationship: career adaptability positively predicts cultural intelligence, which, in turn, enhances work engagement. Highly adaptable nurses are better equipped to develop cultural intelligence, thereby improving their overall work engagement. Healthcare administrators should prioritize professional development programs that foster both career adaptability and cultural intelligence to sustain nurse engagement and improve patient care. Cultivating these critical psychosocial resources can effectively sustain nurses&rsquo; work engagement, reduce turnover intentions, and ultimately improve patient care outcomes in diverse healthcare settings.

mihs.2025.11.04.pdf

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Nurses’ Career Adaptability and Work Engagement: The Mediating Role of Cultural Intelligence

<span style="font-size: 10.0pt; font-family: 'Cambria',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Calibri; letter-spacing: -.15pt; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold; mso-bidi-font-style: italic;">Although the findings of teaching method studies conducted to date have offered insights into the positive influence of novel teaching strategies on improving students&rsquo; academic performance, there is no conclusive evidence addressing the effect of integrated teaching methods on pupil&rsquo;s academic self-efficacy, academic engagement, and academic performance. This study compares the differential effects of employing an integrated teaching method on enhancing primary school students&rsquo; academic attitudes. To set the scene, 40 6th-grade students were randomly assigned to two groups: an experimental group trained using the integrated teaching method (n = 20) and a control group that stuck to the traditional teaching method (n = 20). The participating groups took Jinks and Morgan&rsquo;s academic self-efficacy, Fredricks and Blumenfield&rsquo;s academic engagement, and teacher-made academic performance pretests. Having completed 8 sessions of integrated teaching, students took the aforementioned tests as posttests. The data analysis demonstrated the effectiveness of the integrated teaching method in increasing the variables, as the participants in the control group outperformed them. The findings of the study act as a driving force for potential educational implications which are discussed in detail.

sem.2026.19.03.pdf

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Effect of Integrated Teaching Method on Elementary Students’ Academic Self-Efficacy, Academic Engagement, and Academic Performance

As an L2 learner and teacher, you have often asked yourself why some students acquire a second language (L2) more successfully than others. On the other hand, other students seem to find difficulty with similar material. You might have noticed that some students are quick to engage with a task while others appear to disengage. How can language learning be structured in the face of these diverse responses? You might further question why the L2 acquisition of speaking or grammar (for example) is so easily taught through tasks, while the L2 acquisition of writing or listening comprehension seems resistant to this approach. These questions lie at the heart of teachers, learners, researchers, and policy makers who wish to improve L2 education. Nonetheless, there are two main aspects of L2 learning: Individual Differences (IDs) and Task-Based Language Teaching (TBLT). First, IDs are broadly defined as thepersonal characteristics that make learners differ from one another in how they approach and succeed in language learning (Skehan, 1989).

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Book Review

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Book Review: Individual Differences and Task-Based Language Teaching (2024), Edited by Shaofeng Li (John Benjamins)

Individual Differences in the AI and Digital Era: The Impact of ChatGPT and Beyond

Guest Editors:
Zhisheng (Edward) Wen 
The Hong Kong Polytechnic University - CPCE, Hong Kong SAR, China

Richard L. Sparks
Mt. St. Joseph University, USA

Hassan Mohebbi 
European Knowledge Development Institute, Turkey


Special Issue

For a long time, motivation and anxiety, as traits of individual differences (IDs), have been understood as significant factors in learning a second language (L2) successfully. Scholars conceptualized these two traits as learners&rsquo; internal traits. In this article, we, as the authors, use sociocultural theory (SCT) to revisit these traits and reconceptualize them. Therefore, we argue that these traits are not merely unchanged qualities; instead, they are the outcome of a learner&rsquo;s engagement in a socially meaningful practice during the L2 learning process. Meanwhile, current research findings show that other factors, such as linguistic aptitude, L1 literacy, and L2 metalinguistic skills, play a part in L2 learning. These factors are not only applicable to a traditional classroom environment, but we believe that with the emergence of AI-mediated learning tools, such as chatbots, adaptive learning platforms, and AI tutors, they can be used as scaffolding techniques for learners&rsquo; participation. We further argue that if AI tools are used systematically to meet learners&rsquo; needs, they can enhance learning processes, and this can reduce L2 anxiety and increase motivation. A sociocultural perspective, therefore, provides a productive way to understand how motivation and anxiety unfold in AI-mediated language learning, while remaining attentive to the linguistic resources that adult learners bring with them.

idle.2025.03.05.pdf

Perspective Article

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Reconceptualizing Individual Differences through the Lens of Sociocultural Theory in AI-Mediated Language Learning

The rapid development of Large Language Models (LLMs) has offered new opportunities for personalized education while raising concerns about bias amplification, equity gaps, and the digital divide. This quasi-experimental study explores LLM applications in high school Computer Science (CS) education, focusing on bias mitigation and bridging to higher education. A sample of 616 students from a key high school in northern China was randomly assigned to an experimental group (LLM personalized instruction, n=308) or a control group (traditional instruction, n=308). The 8-week intervention built CS skills through progressive tasks from basic syntax to comprehensive projects, aligned with university domains (e.g., ACM CS2023). Methods integrated UNESCO (2025) and OECD (2025) guidelines, emphasizing low-bandwidth solutions and bias mitigation strategies such as prompt engineering and multi-model comparison. Data analysis combined quantitative approaches (t-tests, ANOVA, bridging index) and qualitative NVivo thematic coding to assess performance gains, subgroup equity, and bias indicators (MAB and MDB). Results showed significant improvements in the LLM group (p&lt;0.05), with a 15% average bridging index and 80%&plusmn;5% bias mitigation rate. However, urban-rural and gender biases still require further optimization. This study provides empirical insights into responsible LLM use in education and proposes policy frameworks and model optimization (unified super models vs. mixture of experts) to advance global equity and ethical AI integration.

idle.2025.03.04.pdf

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Personalized Applications of Large Language Models in Pre-University Computer Science Education: Bridging Global Equity, Mitigating Bias, and Addressing Structural Challenges

There is a growing concern that the increased efficiency of using Generative Artificial Intelligence (GAI) text in the completion of educational tasks related to English language learning may come at the cost of whether or not students develop real language proficiency. This study investigated the perceptions and usage patterns of ten English-majored university students - whose English proficiency levels ranged from A2 to C1 (as designated by The Common European Framework of Reference for Languages - CEFR) - in their use of ChatGPT and other AI tools for coursework and self-study. Findings from interviews revealed notable individual differences. However, while all students acknowledged improved efficiency through GAI use, their perceived impact on language proficiency varied. Some A2 or B1 learners used GAI for speaking practices. Other students, particularly C1-level, perceived AI generated text as a tool for improving efficiency rather than language proficiency. These findings highlight the need to distinguish proficiency from efficiency and account for individual differences. Implications are made for a pedagogy that includes GAI-integrated language instruction.

idle.2025.03.03.pdf

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Efficiency ≠ Proficiency: College English as a Foreign Language Students’ Perceptions on the Use of Generative AI

The integration of artificial intelligence (AI) into task-based language teaching (TBLT) promises personalized learning at scale. Yet without grounding in the rich tradition of individual differences (IDs) research, AI risks reducing learners to simplified variables and substituting algorithmic accommodation for genuine cognitive engagement. This paper builds a bridge between established ID-TBLT research and emerging AI design. We critically synthesize how cognitive IDs (working memory, attentional control, language aptitude) and affective IDs (motivation, anxiety, enjoyment, boredom, and flow) interact with task complexity to shape L2 performance&mdash;acknowledging both established findings and persistent debates. From this synthesis, we articulate design challenges for AI-mediated TBLT, distinguishing what is technically feasible from what requires further research, and acknowledging inherent tensions (scaffolding vs. substitution, personalization vs. equity, detection vs. privacy, flow vs. instructional efficiency). We then extend this framework through Bui's (2026) longitudinal study of learner perceptions in AI-assisted speaking tasks, using empirical findings on learner adaptation and "prompt literacy" to illustrate and refine our design challenges. The result is a dual contribution: a systematic translation of ID-TBLT research into AI design challenges, and a refined, six-frontier research agenda for developing intelligent, adaptive TBLT systems that are cognitively grounded, affectively attuned, and ethically responsible.

idle.2025.03.02.pdf

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Individual Differences in Task-Based Language Teaching: A Critical Synthesis for AI-Mediated Learning Design

The rapid integration of generative AI into language education has exposed a dual challenge: a &ldquo;grounding gap&rdquo; in its cognitive shallowness, and a profound ethical peril that such technology may accommodate rather than empower learners. This editorial interrogates whether a bridge is possible. We argue that working memory (WM)&mdash;empirically central to language aptitude and learning&mdash;offers the most viable, if fraught, interface for such a bridge. We introduce the Cognitive Load&ndash;WM Interaction (CLWM) Matrix not as a solution, but as a critical heuristic and necessary safeguard. It is designed to enforce a key distinction: between AI that grounds learning by managing cognitive load and AI that bypasses cognitive effort. From this, we derive a dual-path risk-aware research agenda, focused on developing WM-aware pedagogical specifications and probing hybrid AI architectures. The conclusion is not a blueprint, but a condition: progress in AI must be subordinated to progress in understanding and protecting the human cognitive processes it seeks to engage.

idle.2025.03.01.pdf

Editorial

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Toward Cognitively Grounded AI: Can a Working Memory Interface Bridge Individual Differences and System Design?

Standardized testing has been increasingly criticized as a form of student evaluation due to its lack of focus on student individuality. In response, calls for authentic student assessment have encouraged educators, like Angela Stockman, to challenge traditional methods of student evaluation in favor of holistic approaches. Her book, The Writing Teacher&rsquo;s Guide to Pedagogical Documentation: Rethinking How We Assess Learners and Learning, extends those critiques; her intervention suggests pedagogical documentation of learning processes as a nuanced replacement for evaluating students. Stockman&rsquo;s 3-part book is a comprehensive framework for instructors looking to adopt a fresh perspective on student evaluation, offering a welcome change from traditional methods of assessment and instead emphasizing personal growth and student-centered learning.

frsl.2025.03.04.pdf

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The writing teacher’s guide to pedagogical documentation: Rethinking how we assess learners and learning by Angela Stockman

This study examines the influence of teachers&rsquo; behaviors on students&rsquo; foreign language speaking anxiety (FLSA) in Turkish middle school classrooms. Conducted with 55 students and two non-native English teachers over 14 weeks, the research included classroom observations, semi-structured interviews, and a foreign language anxiety scale. The findings reveal that teachers' behaviors have a moderately significant impact on students' anxiety levels, with positive behaviors reducing FLSA and negative behaviors exacerbating it. The results highlight discrepancies between teachers&rsquo; self-perceptions and their observed classroom practices, underscoring the need for greater teacher awareness of their impact on students&rsquo; learning experiences. This research contributes to the literature on FLSA by focusing on young learners in a Turkish context, emphasizing the importance of teacher attitudes and strategies in mitigating anxiety and fostering effective oral communication. The research took place in a Turkish state school classroom with 55 students and two non-native English language teachers over a period of 14 weeks. The findings concluded that teachers&rsquo; behaviours have an important impact, albeit small, on students' speaking anxiety levels, where positive behaviours decrease FLSA, while negative behaviours increase it. The outcomes also highlight a mismatch between teachers' self-perception and their classroom experiences.

ltf.2025.12.02.pdf

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The Influence of Teachers’ Behaviour on Learners’ Foreign Language Speaking Anxiety