International Journal of Multidisciplinary Department
Leading Students in the Classroom: Similarities and Differences Between English and Music Teachers
Abstract
Effective classroom leadership plays a key role in supporting student learning across all subjects, though its practice varies according to each discipline’s unique demands. This article explores how English and music teachers lead their classrooms, identifying both commonalities and distinctions. Based on a narrative review of research on classroom management, teacher leadership, and subject-specific teaching methods, the analysis reveals that while both groups use similar foundational strategies—such as setting clear expectations, building relationships, maintaining consistent routines, and designing engaging lessons—they differ in significant ways. These differences include the main focus of student engagement, reliance on nonverbal and auditory signals, patterns of student interaction and grouping, methods of feedback, and overall classroom structure. The findings offer insights for teacher training, instructional coaching, and broader educational leadership practices.
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Barriers to Artificial Intelligence Adoption for Cybersecurity in Small and Medium Scale Enterprises
Abstract
Artificial intelligence (AI) offers small and medium scale enterprises (SMEs) a potentially transformative route to stronger cybersecurity, yet adoption among such firms continues to lag markedly behind that of larger organisations. This study examines the barriers that hinder AI adoption for cybersecurity among SMEs, conceptualised across three functional barrier dimensions drawn from Innovation Resistance Theory: the value barrier (cost and return-on-investment uncertainty), the usage barrier (knowledge and skills gaps), and the risk barrier (governance and trust-related concerns). Anchored on Innovation Resistance Theory, the study formulated three objectives, three research questions and three corresponding hypotheses. A descriptive survey design was adopted, involving 220 purposively sampled owner-managers and information technology personnel of registered SMEs. Data were analysed using descriptive statistics and multiple linear regression at the 0.05 level of significance. Findings show that the value, usage and risk barriers each exert a statistically significant negative influence on the extent of AI adoption for cybersecurity, jointly explaining a substantial proportion of variance in adoption outcomes, with the usage (knowledge and skills) barrier emerging as the strongest predictor. The study concludes that AI adoption resistance among SMEs is best understood as a multi-dimensional, rational response to genuine resource and knowledge constraints rather than mere technological conservatism. Recommendations are offered for SME operators, policymakers and educational institutions engaged in digital capacity-building.
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Artificial Intelligence-Assisted Literary Pedagogy and its Influence on Students' Critical Thinking, Engagement, and Interpretive Skills in English Literature Classrooms
Abstract
The integration of Artificial Intelligence (AI) in education is transforming teaching and learning practices, particularly in language and literature classrooms. This study examines the influence of AI-assisted literary pedagogy on students' critical thinking, engagement, and interpretive skills in English literature classrooms. AI-powered tools—such as intelligent tutoring systems, text analysis applications, and adaptive learning platforms—are increasingly being used to support personalized learning experiences and enhance students' interaction with literary texts. The study adopts a mixed-method approach to investigate how AI-supported instructional strategies impact students' ability to analyze themes, interpret literary devices, and engage meaningfully with texts. It also explores how AI fosters collaborative learning, immediate feedback, and deeper comprehension, thereby promoting higher-order thinking skills. However, the research further considers challenges associated with the use of AI in literary pedagogy, including over-reliance on technology, reduced human interaction, and ethical concerns related to academic integrity. The findings of this study provide valuable insights for educators, curriculum designers, and policymakers on effectively integrating AI into literature instruction to improve students' cognitive and interpretive outcomes. This study contributes to the growing discourse on technology-enhanced learning and its implications for 21st-century education.