Problems Faced by High School Teachers During Digital Classroom Interaction in the COVID-19 Pandemic Period
Authors-Reseela K. K
Keyword-Digital classroom, high school teachers, online learning, ICT, teacher difficulties, COVID-19.
Abstract-The COVID-19 pandemic compelled schools to shift from conventional face-to-face teaching to digital and online classroom interaction. This article examines the problems experienced by high school teachers during this transition, with particular reference to Kozhikode district, Kerala. The study adopted a descriptive survey design. The dissertation reports a sample of high school teachers selected through stratified random sampling with representation based on gender, locale, and type of management. Data were collected using a questionnaire developed and standardized by the investigator, and percentage analysis was used for interpretation. The reported problem areas included academic, administrative, curricular and co-curricular, and parental dimensions. The findings indicate that teachers experienced difficulties related to network connectivity, conti-nuity of learning, delayed feedback, limited face-to-face communication, group work, online assessment, cyber-related risks, excessive screen use, and the additional time required for digital teaching. The article concludes that teacher training, reliable digital infrastructure, technical sup-port, time management, and sustained teacher–student communication are necessary for effective digital classroom interaction.
Doi-[https://zenodo.org/records/22975943]
Cinema as Constitution: The Courtroom Narrative of Tamil film Jai Bhim
Authors-Dr. Aniket Parmar
Keyword-Jai Bhim, B. R. Ambedkar, habeas corpus, Article 21, Dalit cinema, constitutional justice, custo-dial violence, caste, Irular community.
Abstract-T. J. Gnanavel's Tamil film Jai Bhim (2021) functions as a powerful cinematic enactment of Dr. B. R. Ambedkar's constitutional and legal philosophy. The film's deployment of habeas corpus, Article 21 of the Indian Constitution, and its dramatisation of custodial atrocity together translate Ambedkar's written guarantees of liberty into lived, affective experience. The film constitutes a jurisprudential argument about the distance between constitutional promise and ground reality, showing how marginalised communities can reclaim the Constitution as a living instrument of liberation. Drawing on Ambedkar's primary writings, the Indian Constitution, and scholarship from film studies, Dalit Studies, and constitutional law, this paper argues that the courtroom in Jai Bhim serves as an Ambedkarite arena where law is restored to its proper function as a tool of social transformation.
Digital Discourse and Contemporary English: A Linguistic Study of Social Media Communication
Authors-Dr. Hema. S, Dr. Neeti Roy
Keyword-Digital Discourse, Social Media Linguistics, Language Change, Computer-Mediated Communi-cation, Multimodality
Abstract-While social media sites are today's principal venues for written English usage, the impact of social media on language is only partially acknowledged. The present research analyzes how digital platforms affect modern English through investigating 10,000 posts on Twitter/X, Insta-gram, and TikTok, published between 2021 and 2026. The study utilizes a sequential mixed-method research design combining corpus linguistics and quantitative research with critical discourse analysis. The research findings include a 34.2% increase in the use of hybrid lexical units, a 40.1% decrease in the mean length of sentences, and a 41.3% increase in multimodal pragmatic elements (emojis, hashtags). Comparative platform analysis demonstrates that differ-ent digital platforms cultivate specific registers: TikTok is associated with emotionally-loaded and positionally-driven language; Instagram provides a space for cultivated identity-related lan-guage, whereas Twitter/X remains more informational and intertextual in character.
Doi-[http://doi.org/10.5281/zenodo.23095766]
The Influence of Social Media Language on Modern English Communication: A Linguistic Analysis
Authors-Dr V. V. Malinee, Mrs. D. Deepikadevi
Keyword-Social Media Linguistics, Digital Communication, Lexical Innovation, Syntactic Simplification, Multimodal Pragmatics, Corpus Analysis, English Language Evolution, Sociolinguistics
Abstract-The current research paper aims at providing an extensive linguistic analysis of how the advent of social media has impacted modern-day English communication practices. Using the method-ology which relies on both quantitative corpus analysis and qualitative discourse analysis, this study investigates the changes in lexical innovation, syntactic simplicity, and multimodal prag-matic markers that took place on Twitter, Instagram, and TikTok. It is revealed that there are considerable changes in the way lexical items are created, syntactic simplicity measures, and pragmatic markers usage compared to the traditional way of communication prior to digital times. It is shown that Twitter possesses a higher rate of abbreviations and acronyms, Instagram has a higher number of emoji usage, and TikTok is the main platform which creates hybrid lexical formations and multimodal discourse. The study proves that the usage of social media content in English occupies the largest share in global digital communication.
Doi-[http://doi.org/10.5281/zenodo.23099164]
Explainable Machine Learning for Student Performance Prediction in Higher Education
Authors-Shilpa K
Keyword-Academic Risk Prediction; Learning Analytics; XGBoost; Explainable Artificial Intelligence; Student Performance; Higher Education
Abstract-In higher education the early identification of students who are at risk of academic underperformance is crucial to deliver timely and targeted academic support. In this study, an Adaptive Multi-Modal Learning Analytics Framework (AMLAF) is proposed that combines academic, behavioural, institutional, learning preference and perceptual variables for predicting student academic risk. Explanability analysis with SHAP and LIME revealed that previous academic performance, study behavior, mentoring, institutional support and engagement of students were relevant factors that influence the model predictions. Results showed that the multi modal features engineered using these features were used to train Random Forest, XGBoost and LSTM models, with the latter model proving to be the most accurate. XGBoost with test accuracy of 99.47%, AUC-ROC of 0.9992 and 99.59% mean cross validation accuracy was the best performing model that was observed. The model got 7 false negative predictions and 1 false positive prediction in the test set, and had a recall of 98% and an F1 score of 99% for the at-risk class. The simulated XGBoost–LSTM ensemble obtained an accuracy of 96.75%, which is the same as XGBoost to show no performance improvement over XGBoost alone. LSTM obtained an accuracy of 81.06%, while the simulated XGBoost–LSTM ensemble obtained an accuracy of 96.75%, showing no improvement over XGBoost alone. The results show the first application to supporting early identification of academic risk and evidence based student support planning through multi modal learning analytics, of which explainable is one.
Doi-[https://doi.org/10.5281/zenodo.23160425]
Artificial Intelligence and the Future of Teacher Education: Pedagogical Innovations, Professional Competence, and Ethical Challenges
Authors-Dr G. Kokila Selva Kumari
Keyword-artificial intelligence, teacher education, generative AI, AI literacy, teacher professional develop-ment, pedagogical innovation, educational ethics
Abstract-Artificial intelligence (AI) is increasingly influencing educational practices, creating new possi-bilities and challenges for teacher education. Its applications extend beyond automated content generation to lesson planning, instructional design, assessment, personalised learning, reflective practice, and professional development. These developments require teacher education institu-tions to reconsider how prospective and practising teachers acquire pedagogical knowledge, exercise professional judgement, and prepare learners for an AI-mediated educational environ-ment. This article examines the implications of AI for teacher education through a thematic syn-thesis of published research and policy frameworks. The discussion is organised around five interconnected themes that examine the role of artificial intelligence in shaping the future of teacher education. These include the use of AI to support pedagogical innovation and improve instructional practices; the development of AI competence among prospective and practising teachers; the changing nature of assessment, feedback, and professional learning; the ethical, epistemological, and institutional challenges associated with AI adoption; and the strategies required to integrate AI responsibly into teacher education programmes. Together, these themes provide a basis for understanding how AI can enhance teaching and learning while addressing the professional, ethical, and institutional considerations necessary for its effective implementa-tion. Research reviews indicate that AI can support instructional planning, feedback, resource development, and professional learning, although the strength and sustainability of these benefits depend on the design of learning activities and the preparation of teachers. Concerns relating to inaccurate outputs, algorithmic bias, privacy, academic integrity, unequal access, and overde-pendence on automated systems remain important. The article argues that active AI integration requires more than technical familiarity. Teacher education should develop the capacity to evalu-ate AI-generated information, design pedagogically appropriate learning experiences, protect learner interests, and retain human responsibility for educational decisions. It proposes a human-centred framework for integrating AI literacy, pedagogical competence, ethical judgement, reflec-tive practice, and institutional support into teacher preparation. The article concludes that AI should strengthen teachers' professional capacity rather than diminish their agency, relationships with learners, or responsibility for educational quality.
Doi-[https://doi.org/10.5281/zenodo.23336496]
Workplace Diversity, Inclusion, and Organizational Effectiveness: An Empirical Study
Authors-Dr.Raghi.P.Nair, Dr.Prita Davidson
Keyword-Workplace Diversity, Inclusion Climate, Organizational Effectiveness, PLS-SEM, Employee Commitment
Abstract-This research explores the interrelationship among workplace diversity, inclusion climate, and organizational effectiveness with the help of the survey of 347 employees working in various industries. Based on the principles of social identity theory and optimal distinctiveness theory, this research hypothesizes that the dimensions of diversity (gender, age, and education) would have an indirect influence on organizational effectiveness via the mediating variable of inclusion climate. It is found out with the help of PLS-SEM model that inclusion climate plays an im-portant role in this process since, on its own, demographic diversity does not predict any effec-tiveness outcome; however, together with inclusion practices, it improves organizational com-mitment and employee retention. This study is important since it highlights the point that inclu-sion cannot be seen as an optional component but rather a necessity for achieving performance improvement through diversity.
Doi-[https://doi.org/10.5281/zenodo.23731197]