Journal of International Education and Practice

Detecting Student Inattention Using Deep Learning and Behavioral Analysis

2025-12-12T14:54:07+08:00

Student inattention in classrooms negatively impacts learning outcomes and academic performance, posing a significant challenge for educators. Traditional methods of monitoring engagement rely on subjective teacher observations, which can be inconsistent, labor-intensive, and prone to bias. To address these limitations, this paper presents an AI-driven framework that uses deep learning and behavioral analysis to detect student inattention in real time. The proposed system integrates computer vision techniques including facial expression recognition, posture analysis, head pose estimation, and eye-gaze analysis, employing convolutional neural networks (CNNs) to extract spatial features and recurrent neural networks (RNNs) to model temporal patterns. The framework was evaluated using annotated classroom video data collected from real teaching sessions, capturing natural student behavior under typical classroom conditions. Experimental results demonstrate that the proposed approach achieves high accuracy in distinguishing attentive from inattentive states, outperforming traditional machine learning baselines while maintaining real-time performance. Beyond detection, the system provides actionable insights for educators by highlighting patterns of disengagement across time and students. By combining CNN-based spatial analysis with RNN-based temporal modeling, the framework offers an objective, scalable, and practical solution for monitoring classroom engagement, enabling timely interventions, personalized instruction, and improved learning outcomes.

Conversation Breakdown and Institutional Discourse in Ghanaian ESL Classrooms: A Conversation Analytic Investigation

2025-12-19T09:49:29+08:00

This study responds to the growing pedagogical interest in optimizing communicative competence within English as a Second Language (ESL) classroom interaction by investigating a critical, yet under-explored, domain, the interactional trouble sources that initiate conversation breakdown. Grounded in a Conversation Analytical (CA) framework, the research methodology utilizes a hybrid approach: CA modeling for the micro-analysis of recorded data and content analysis for the qualitative interview data. The empirical base consists of 52 h of recorded ESL classroom discourse extracted from the Ghana Senior High School corpus of academic spoken English database collected by the researchers and research assistants, and augmented by interviews with practicing ESL teachers. A systematic analysis of the interactional sequences showed a pronounced presence of both etic (analyst-defined) and emic (participant-oriented) conversational trouble sources. The findings delineate six salient categories of trouble sources, namely, mishearing/non-hearing, vagueness, topic transition, information deficit, and lexical inappropriacy. These trouble sources demonstrably impeded interactional flow. Notably, the research establishes that the origins of these trouble sources are multi-layered, transcending mere surface-level linguistic (phonology, syntax, lexis) deficiencies to include institutional factors such as instructional ambiguity, procedural misalignments, disciplinary actions, and culturally situated vocabulary choices. This evidence mandates that future ESL research accord greater significance to the impact of institutional discourse (especially, classroom discourse) features as a primary generator of interactional trouble.

Community Engagement in Management of Public Secondary Schools: A Systematic Comparative Review of India and Tanzania

2026-01-06T13:45:39+08:00

This systematic review examines the role of community engagement as a governance mechanism in the management of government secondary schools in developing countries, with a comparative focus on India and Tanzania. The review synthesized evidence from 61 current and relevant peer‑reviewed literature sources published between 2015 and 2025, identified through systematic searches of ERIC, Scopus, Web of Science, UNESCO, and government repositories. The main focus was on exploring the contributions of community engagement in the management of government secondary schools in India and Tanzania. This helped recommend further studies on challenges and ways of community engagement in schools managed by the government. Using a thematic synthesis approach aligned with PRISMA principles, the review analyses patterns across governance structures, accountability mechanisms, and school‑level outcomes. Findings indicate that community engagement contributes to improved resource mobilization, enhanced transparency, better school facilities, and stronger school-community trust, while challenges include political interference, elite capture, and uneven stakeholder capacity. The key contribution of this review lies in its comparative governance of education in elementary government institutions, which demonstrates how differing decentralization architectures in India and Tanzania shape the effectiveness of community engagement. The study proposes a Community–State Partnership Framework to guide policy and practice, emphasizing that community engagement should complement rather than substitute for state responsibility in education governance.