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The research takes into account the influence of emerging technology on organisational communication and home-based work behaviour in a new renewable energy company. The data collection in this mixed-methods case study involved all fifty staff members in semi-structured interviews, documentary analysis and direct observation of virtual work practice. Qualitative data were processed using NVivo software for the analysis of themes, and quantitative metrics quantified improvements in operations. Among such extraordinary capabilities is a notable 45% boost in operational productivity, 50% enhancement in customer responsiveness and a 35% drop in quality control noncompliance in response to the use of digital workflow tools by the likes of Microsoft Teams, WhatsApp Business, and in-house created ERP software. Digital transformation success is found by the study to require the coexistence of technology, human capabilities, and organizational traditions rather than technology adoption. From this study, it can be concluded that it brings concepts and avenues into the system to augment the advanced research in the interface of technology, which can happen in any form only through various causes. the research demonstrates that technology adoption processes are both influenced by external institutional pressures and internal socio-technical relations simultaneously. This study presents significant implications for small energy companies located in emerging markets in search of transforming digitally.

Almeida, F., Santos, J. D., & Monteiro, J. A. (2020). The challenges and opportunities in the digitalization of companies in a post-COVID-19 World. IEEE Engineering Management Review, 48(3), 97-103. Appelbaum, S. H. (1997). Socio‐technical systems theory: an intervention strategy for organizational development. Management decision, 35(6), 452-463. Cho, J., Choi, D., Yu, J., & Voida, S. (2024). Reinforcing and Reclaiming The Home: Co-speculating Future Technologies to Support Remote and Hybrid Work. In Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1-28). Daramola, G. O., Adewumi, A., Jacks, B. S., & Ajala, O. A. (2024). Conceptualizing communication efficiency in energy sector project management: the role of digital tools and agile practices. Engineering Science & Technology Journal, 5(4), 1487-1501. DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American sociological review, 48(2), 147-160. Farhi, F., Jeljeli, R., & Belarbi, A. (2022, November). Artificial intelligence in sustaining internal communication in corporate sector: The mediation of two-way communication perspective of PR. In 2022 International Arab Conference on Information Technology (ACIT) (pp. 1-7). IEEE. García‐Navarro, C., Pulido‐Martos, M., & Pérez‐Lozano, C. (2024). The study of engagement at work from the artificial intelligence perspective: A systematic review. Expert Systems, e13673. García-Orosa, B. (2019). 25 years of research in online organizational communication. Review article. Profesional de la información, 28(5). Geels, F. W. (2020). Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory. Technological Forecasting and Social Change, 152, 119894. Gholami, M. J., & Al Abdwani, T. (2024). The rise of thinking machines: A review of artificial intelligence in contemporary communication. Journal of Business, Communication & Technology, 1-15. Hassan, M. G., Akanmu, M. D., & Yusoff, R. Z. (2019). Technological integration and sustainable performance in manufacturing firms. Industrial Engineering, 9(8), 1639-1650. Hassan, S. S., Meisner, K., Krause, K., Bzhalava, L., & Moog, P. (2024). Is digitalization a source of innovation? Exploring the role of digital diffusion in SME innovation performance. Small Business Economics, 62(4), 1469-1491. James, O. O., Udeh, C. A., Daraojimba, C., Ogedengbe, D. E., Elufioye, O. A., & Samod, B. O. (2023). Digital transformation in the resource and energy sectors: A review of the impact of digital transformation on HR practices and strategies in the Nigerian renewable energy sector. Journal of Third World Economics, 1(1), 36–46. Josephs, N., Peng, S., & Crawford, F. W. (2022). Communication network dynamics in a large organizational hierarchy. arXiv preprint arXiv:2208.01208. Kelly, J. A. (2020). The New" Covid-19" Home Office Worker: Evolving Computer-Human Interactions and the Perceived Value of Workplace Technology. Technium Soc. Sci. J., 13, 575. Kohn, V., Frank, M., & Holten, R. (2023). How sociotechnical realignment and sentiments concerning remote work are related–insights from the COVID-19 pandemic. Business & Information Systems Engineering, 65(3), 259-276. Kwiotkowska, A. (2024). Creating organizational resilience through digital transformation and dynamic capabilities: Findings from fs/QCA analysis on the example of Polish CHP plants. Sustainability, 16, 6266. Lakhwani, M., Dastane, O., Satar, N. S. M., & Johari, Z. (2020). The impact of technology adoption on organizational productivity. The Journal of Industrial Distribution & Business, 11(4), 7-18. Lawrence, T. B., & Suddaby, R. (2006). 1.6 institutions and institutional work (Vol. 2, pp. 215-254). The Sage handbook of organization studies. Maroufkhani, P., Desouza, K. C., Perrons, R. K., & Iranmanesh, M. (2022). Digital transformation in the resource and energy sectors: A systematic review. Resources Policy, 76, 102622. Melin, U., Sarkar, P. K., & Young, L. W. (2020). To couple or not to couple: A case study of institutional legitimacy relating to SaaS applications in two universities. Information Technology & People, 33(4), 1149-1173. Mengova, E., & Green, D. (2023). The role of innovation and technology in renewable energy. The International Journal of Environmental Sustainability, 19(2), 17-41. Nkomo, L., & Kalisz, D. (2023). Establishing organisational resilience through developing a strategic framework for digital transformation. Digital Transformation and Society, 2(4), 403-426. Scott, W. R. (2008). Institutions and organizations: Ideas and interests. Sage Publications. Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting: An examination of the psychological situation and defences of a work group in relation to the social structure and technological content of the work system. Human relations, 4(1), 3-38. Usman, F. O., Ani, E. C., Ebirim, W., Montero, D. J. P., Olu-lawal, K. A., & Ninduwezuor-Ehiobu, N. (2024). Integrating renewable energy solutions in the manufacturing industry: challenges and opportunities: a review. Engineering Science & Technology Journal, 5(3), 674-703.

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Despite nationwide efforts to address post-pandemic learning loss, limited research has explored how remedial programs like Catch-Up Fridays are perceived and implemented at the school level. This study assessed student satisfaction with the Catch-Up Fridays program in a public school in the Philippines. Using a survey research design, it gathered quantitative data from 121 stratified randomly selected students and qualitative insights from student and teacher interviews. Validated instruments and a combination of descriptive statistics and thematic analysis ensured reliable and in-depth findings. Results showed that students were generally satisfied with the program, citing clear instruction, engaging reading activities, and alignment with academic goals. Teachers viewed the initiative as a valuable tool to support learners with academic gaps. Both groups emphasized the need for improved support systems, clearer policies, and stronger stakeholder collaboration. Recommendations were provided to strengthen implementation and ensure long-term program sustainability.

Abejo, J. R. A., Malatag, X. Y. M., & Maneja, C. B. (2024). Evaluating the impact of ‘Catch-Up Friday’ on senior high school students’ reading proficiency level and perspective. American Journal of Interdisciplinary Research and Innovation, 3(3), 42-50. https://doi.org/10.54536/ajiri.v3i3.3332 Adholiya A., Adholiya S., & Kanja R. (2021). ICT services effect on students’ satisfaction for library services. A study on students of technical degree colleges of Udaipur. Pacific Business Review International, 14(3), 132-141. Andrade, H. (2019). A critical review of research on student self-assessment. Frontiers in Education, 4, 87. https://doi.org/10.3389/feduc.2019.00087 Balbin, L. B. A., Alota, A. V., & Lapada, A. A. (2024). Students’ perception, motivation, and engagement in the implementation of Catch-Up Friday Program. DMMMSU Research and Extension Journal, 8, 62–81. https://doi.org/10.62960/dmmmsu.v8i.52 Cardino Jr, J. M., & Cruz, R. A. O. D. (2020). Understanding of learning styles and teaching strategies towards improving the teaching and learning of mathematics. LUMAT: International Journal on Math, Science and Technology Education, 8(1), 19-43. https://doi.org/10.31129/LUMAT.8.1.1348 Cosio, M. G. (2024, February 1). Beyond the bell: Uncovering the challenges of implementing Catch-up Fridays. SunStar Pampanga, p. 10. https://www.pressreader.com/philippines/sunstar- pampanga/20240201/281741274306677 Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. https://spada.uns.ac.id/pluginfile.php/510378/mod_resource/content/1/creswell.pdf Cruz, R. O. D., & Ausa, M. A. M. (2025). Instant Reader Program: A Tool to Enhance Reading Skills Among Primary Pupils. JEE (Journal of English Education), 11(1), 38-68. https://doi.org/10.30606/jee.v11i1.3594 Culduz, M. (2023). The impact of educational leadership in improving the learning experience. In Promoting crisis management and creative problem-solving skills in educational leadership (pp. 168–189). IGI Global. https://doi.org/10.4018/978-1-6684-8332-9.ch008 Department of Education. (2023). State of literacy in the Philippines: Challenges and interventions. Department of Education. Department of Education. (2024a). DepEd Order No. 013, s. 2023: Adoption of the National Learning Recovery Program (NLRP). Department of Education. Department of Education. (2024b). DepEd Memorandum No. 001, s. 2024: Implementation of Catch-Up Fridays. Department of Education. https://www.deped.gov.ph/wp-content/uploads/DM_s2024_001.pdf DepEd. (2023). DepEd Memorandum No. 54, s. 2023: Pilot implementation of the MATATAG Curriculum. Department of Education. https://www.deped.gov.ph/wp-content/uploads/DM_s2023_054.pdf Delos Reyes, F. J. F., & Caballes, D. G. (2021). A review on the school-based learning activity sheet towards improvement of instructional material. International Journal of Scientific and Research Publications, 11(8), 200–204. https://doi.org/10.29322/IJSRP.11.08.2021.p11627 De Leon, M.LT., & Ortega-Dela Cruz, R. A. (2024). Web-Based Instruction on Improving the Students’ Academic Performance in Music and Arts Education. Scientia Paedagogica Experimentalis, 61 (1), 69-102. https://doi.org/10.57028/S61-069-Z1054 Farkas, W., & Jang, B. G. (2019). Designing, implementing, and evaluating a school-based literacy program for adolescent learners with reading difficulties: A mixed-methods study. Reading & Writing Quarterly, 35(4), 305–321. https://doi.org/10.1080/10573569.2018.1541770 Gonio, Y. G., & Bauyot, M. M. (2025). Evaluating the implementation of Catch-up Fridays in public elementary schools: An administrative insight. International Journal of Multidisciplinary Educational Research and Innovation, 3(1). https://ejournals.ph/article.php?id=26135 LaBad, R., & Alindo, J. B. (2025). Perceptions of learners on reading enhancement during Catch-Up Fridays. Zenodo, 1, 24–31. https://doi.org/10.5281/zenodo.14621217 Lopez, M.K.R.R., & Ortega-Dela Cruz, R.A. (2022). Gallery Walk technique in enhancing reading comprehension and oral English language proficiency of junior high school students. Waikato Journal of Education, 27(3), 57–71. https://doi.org/10.15663/wje.v27i3.813 Maawa, P. K. L., & Cruz, R. O. D. (2019). Remedial and Corrective Feedback Strategies for Improving Students' English Language Proficiency. International Journal of Language Education, 3(1), 1-11. https://doi.org/10.26858/ijole.v1i1.7794 McLeod, S. (2024). Thematic analysis: A step-by-step guide. Simply Psychology. https://doi.org/10.13140/RG.2.2.13084.71048 Martinez, C., & Torres, J. (2020). Peer-assisted learning strategies in Philippine secondary schools. Philippine Journal of Developmental Education, 44(3), 101–117. Metu, A. (2024). A literature review of student engagement in learning experiences. https://doi.org/10.13140/RG.2.2.17426.98243 Nabor, L.G., & Ortega-Dela Cruz, R.A. (2022). Project 555: A silent reading intervention towards an improved reading comprehension in English. Journal of English Education, 7 (2), 36-50. Nobles, L. M. A. G., & Cruz, R. O. D. (2020). Making connections: A Metacognitive Teaching Strategy in Enhancing Students’ Reading Comprehension. Journal of English Education, 5(1), 49-61. OECD. (2023). PISA 2022 results: Learning loss and recovery. Organisation for Economic Co-operation and Development. https://doi.org/10.1787/23f07c74-en Ortega-Dela Cruz, R.A. (2020). Pedagogical practice preferences among generational groups of learners: Towards effective twenty-first century higher education. Journal of University Teaching & Learning Practice, 17 (5), 1-19. https://ro.uow.edu.au/jutlp/vol17/iss5/6/ Pacana, R. O., & Cabaguing, A. M. (2024). Transformative teaching practices: The lived experiences of educators in the Catch-Up Fridays program. International Journal of Research and Innovation in Social Science, 8(8), 4744–4756. https://doi.org/10.47772/IJRISS.2024.8080361 Palines, K. M. E., Moreno, J. M. U., Tatlonghari, A. G., & Ortega-Dela Cruz, R. A. (2025). Integrating information and communication technologies to enhance high school students’ research capabilities. Journal of Educational Research and Practice, 15 (1), 1–12. https://doi.org/10.5590/JERAP.2025.15.1952 Perez, R. C., & Cruz, R. A. O. D. (2024). Effect of seminar on teaching on the performance of teachers in higher education. Pan-African Journal of Education and Social Sciences, 5(1), 112-119. Philippine News Agency. (2023, June 16). Addressing effects of Covid-19 among Filipino learners. Philippine News Agency. https://www.pna.gov.ph/opinion/pieces/704-addressing-effects-of-covid-19-among-filipino-learners Requillo, D. A. C., Flores, L. C., Almagro, R., Gonio, Y., et al. (2024). Implementation of Catch-Up Fridays: A case study on teachers’ experiences at the Davao del Norte Division. Asian Journal of Education and Social Studies, 50(8), 1–15. https://doi.org/10.9734/ajess/2024/v50i81547 Reyes, J. M., & Villanueva, E. L. (2019). Digital reading interventions for Filipino learners: A review of literacy platforms. Education Technology Review, 11(1), 33–47. Rominimbang, A. M., Rominimbang, N. S., & Barrera, K. I. B. (2024). Exploring teacher's effective strategies in Catch-Up Fridays in addressing reading gap. Randwick International of Education and Linguistics Science Journal, 5(3), 1144–1154. Saro, J. M., Barol, A. O., Glodobe, A. L., Grana, F. S., & Billuga, N. (2024). Catch-Up Friday: Improving the reading proficiency levels and perspectives of Grade 10 students. American Journal of Education and Technology, 3(2), 12–23. https://doi.org/10.54536/ajet.v3i2.2533 Torres, R. A. O., & Ortega-Dela Cruz, R. A. (2022). Remote Learning: Challenges and Opportunities for Educators and Students in the New Normal. Anatolian Journal of Education, 7(1), 83-92. https://doi.org/10.29333/aje.2022.717a Torres, R. A. O., & Ortega-Dela Cruz, R. A. (2024). Facilitating Learning of Generation Z Learners towards Effective Remote English Language Learning. Theory and Practice of Second Language Acquisition, 10(2), 1-18. https://doi.org/10.31261/TAPSLA.15616 UNESCO. (2022). The global learning crisis: Addressing learning losses post-COVID-19. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000381259 UNICEF. (2023). COVID-19 and education: The impact on children’s learning. United Nations International Children's Fund. https://www.unicef.org/reports/covid-19-and-education-2023 Vlachopoulos, D., & Makri, A. (2024). A systematic literature review on authentic assessment in higher education: Best practices for the development of 21st century skills, and policy considerations. Studies in Educational Evaluation, 83, Article 101425. https://doi.org/10.1016/j.stueduc.2024.101425 Wambui, D. A. (2024). The impact of project-based learning on developing critical thinking and problem-solving skills. Research Output Journal of Education, 3(3), 51–56. https://www.researchgate.net/publication/383553743 World Bank. (2021). The state of global learning poverty: 2021 update. World Bank. https://doi.org/10.1596/978-1-4648-1761-9 Yasnitsky, A. (2014). Vygotsky, Lev. In D. C. Phillips (Ed.), Encyclopedia of educational theory and philosophy (pp. 843–845). SAGE Publications, Inc. https://doi.org/10.4135/9781483346229

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This study examines mental illness and healing practices among ethnic groups in Nigeria, focusing on cultural beliefs, traditional healing methods, and their implications for mental health outcomes. Using a mixed-methods approach, the study combined quantitative surveys (N = 300) and qualitative interviews (n = 50) to explore perceptions of mental illness, utilization of healing practices, and the potential for integrating traditional and modern mental health care. Descriptive statistics revealed that 65% of participants attributed mental illness to supernatural causes, while 70% preferred traditional healing practices such as herbal remedies and spiritual rituals. Inferential statistical analyses, including chi-square tests and one-way ANOVA, demonstrated significant associations between ethnicity and perceptions of mental illness (χ²(4, N = 300) = 12.45, p < 0.05) as well as differences in the utilization of traditional healing practices across ethnic groups (F(2, 297) = 8.32, p < 0.01). Qualitative findings highlighted themes such as cultural explanations of mental illness, the role of traditional healing practices, and challenges to integrating traditional and modern care. The study underscores the need for culturally sensitive mental health interventions that address the unique beliefs and practices of Nigeria's diverse ethnic groups.

Abbo, C. (2011). Profiles and outcome of traditional healing practices for severe mental illnesses in two districts of Eastern Uganda. Global Health Action, 4(1), 7117. Abdulmalik, J., Olayiwola, S., Docrat, S., & Lund, C. (2016). Mental health systems in Nigeria: A review of the literature. International Journal of Mental Health Systems, 10(1), 1-9. Abdulmalik, J., Olayiwola, S., & Docrat, S. (2020). Cultural beliefs and mental health service utilization in Northern Nigeria. International Journal of Mental Health Systems, 14(1), 1-10. Adebowale, T. O., Ogunlesi, A. O., & Adeyemo, F. O. (2020). Cultural beliefs and mental health stigma in Nigeria: A community-based study. Journal of Mental Health and Cultural Diversity, 12(3), 45-58. Adewuya, A. O., & Makanjuola, R. O. (2008). Social distance towards people with mental illness in southwestern Nigeria. Australian & New Zealand Journal of Psychiatry, 42(5), 389-395. Adholiya, A. & Adholiya, S. (2018). Technology driven child mindlessness: A study on children mental prosperity, and social connections in digital era, Unnati : The Business Journal, 6(2), 128 - 133. Aina, O. F. (2004). Mental illness and cultural issues in West African films: Implications for orthodox psychiatric practice. Medical Humanities, 30(1), 23-26. Ayonrinde, O. A., Gureje, O., & Lawal, R. A. (2020). Psychiatric research in Nigeria: Bridging the gap. The Lancet Psychiatry, 7(5), 387-388. Ayonrinde, O. A., Gureje, O., & Lawal, R. A. (2022). Cultural beliefs and mental health outcomes in Sub-Saharan Africa: A systematic review. The Lancet Psychiatry, 9(5), 387-398. Gureje, O., Lasebikan, V. O., Ephraim-Oluwanuga, O., Olley, B. O., & Kola, L. (2006). Community study of knowledge of and attitude to mental illness in Nigeria. The British Journal of Psychiatry, 188(4), 436-441. Makanjuola, R. O., Adewuya, A. O., & Ola, B. A. (2019). Traditional healing practices for mental illness in Southwest Nigeria: A qualitative study. Journal of Ethnopharmacology, 235, 328-335. Okeke, C. I., Mokuolu, B. O., & Aje, A. (2018). Traditional healing practices and mental health in Nigeria: A review. African Journal of Psychiatry, 21(3), 1-7. Okeke, C. I., Mokuolu, B. O., & Aje, A. (2021). Cultural explanations of mental illness and help-seeking behaviors among the Igbo ethnic group in Nigeria. African Journal of Psychiatry, 24(2), 112-125. Okeke, C. I., Mokuolu, B. O., & Aje, A. (2021). Traditional healing practices for mental illness among the Igbo ethnic group in Nigeria. African Journal of Traditional, Complementary, and Alternative Medicines, 18(2), 45-56. Ola, B. A., Morakinyo, O., & Adewuya, A. O. (2016). Traditional healers’ perceptions of mental illness in Lagos, Nigeria. Transcultural Psychiatry, 53(4), 434-454. Ola, B. A., Morakinyo, O., & Adewuya, A. O. (2019). Perceptions of mental illness among the Yoruba ethnic group in Southwest Nigeria. Transcultural Psychiatry, 56(4), 789-803 Oshodi, Y. O., Abdulmalik, J., Ola, B., James, B. O., & Bonetto, C. (2019). Traditional healers’ experiences of mental health care in Lagos, Nigeria. International Journal of Culture and Mental Health, 12(2), 123-134. Sorketti, E. A., Zuraida, N. Z., & Habil, M. H. (2013). The integration of traditional healing practices in mental health care in Malaysia. International Journal of Social Psychiatry ,59(4), 352-361. Sorketti, E. A., Zuraida, N. Z., & Habil, M. H. (2020). Integration of traditional healing practices with modern mental health care in Sub-Saharan Africa. International Journal of Social Psychiatry, 66(5), 456-464. World Health Organization [WHO]. (2021). Mental health in low and middle-income countries. Retrieved from https://www.who.int/mental_health/en/

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Artificial intelligence (AI) has emerged as a transformative force in higher education marketing, offering unprecedented opportunities for personalization and targeted communication. Yet, its adoption raises ethical questions regarding transparency, privacy, and trust. This study investigates student perceptions of ethics and personalization in AI-driven advertising using survey data from 400 students across diverse demographics, disciplines, and institutions in India. Employing descriptive, chi-square, correlation, and regression analyses, the study reveals three key insights. First, exposure to AI-driven campaigns is significant but uneven, with emails, chatbots, and Google apps dominating over mobile ads and social media. Second, ethical perceptions are strongly influenced by perceived effectiveness and outcomes (β = 0.664, p < 0.001), while engagement does not significantly predict ethical acceptance. Third, ethical trust and effectiveness are closely intertwined, confirming an outcome-dependent model of digital ethics. The findings highlight the need for higher education institutions to adopt transparent, personalized, and outcome-oriented strategies that foster trust and inclusivity. The study contributes to theory by extending engagement and ethics frameworks to AI-enabled marketing, and to practice by offering actionable recommendations for responsible institutional adoption of AI in higher education.

Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. Proceedings of the Conference on Fairness, Accountability and Transparency, 81, 149–159. Bhutoria, A. (2022). Personalized learning and artificial intelligence in education: A review of literature and directions for future research. Education and Information Technologies, 27, 5351–5370. https://doi.org/10.1007/s10639-021-10811-y Bryson, J. (2019). The past decade and future of AI’s impact on society. ACM Transactions on Human-Robot Interaction, 7(1), 7. https://doi.org/10.1145/3313762 Christians, C. G., Fackler, M., Richardson, K., Kreshel, P. J., & Woods, R. T. (2020). Media ethics: Cases and moral reasoning (11th ed.). Routledge. Choudhury, N., & Pattnaik, S. (2020). Emerging trends of e-marketing in education sector in India. International Journal of Innovative Technology and Exploring Engineering, 9(2), 420–425. Crompton, H., Burke, D., Gregory, K., & Gräbe, C. (2021). The use of artificial intelligence in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100012. https://doi.org/10.1016/j.caeai.2021.100012 Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 Dwivedi, Y. K., Hughes, D. L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 EDUCAUSE. (2025). 2025 Horizon report: Teaching and learning edition. EDUCAUSE. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5 Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5–14. https://doi.org/10.1177/0008125619864925 Holmes, W., Luckin, R. (2022). Ethics of AI in education: Reimagining learning and teaching. Learning, Media and Technology, 47(1), 1–15. https://doi.org/10.1080/17439884.2022.2063823 Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., & Shum, S. B., et al. (2022). Ethics of AI in education: Towards a community-wide framework. British Journal of Educational Technology, 53(3), 518–537. https://doi.org/10.1111/bjet.13102 Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2 Kapoor, K., Dwivedi, Y. K., Piercy, N. F., & Rana, N. P. (2022). Advances in digital and social media marketing: A review and research agenda. Journal of Business Research, 146, 341–354. https://doi.org/10.1016/j.jbusres.2022.03.009 Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage AI along the consumer journey. Journal of Advertising Research, 58(3), 263–267. https://doi.org/10.2501/JAR-2018-035 Langan, R., Cowley, S., Nguyen, C., Bandara, W., et al. (2023). The state of artificial intelligence in marketing: A review and research agenda. Australasian Marketing Journal, 31(3), 227–245. https://doi.org/10.1177/18393349231163582 Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69–96. https://doi.org/10.1509/jm.15.0420 Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson. Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 1–21. https://doi.org/10.1177/2053951716679679 OECD. (2019). Artificial intelligence in society. OECD Publishing. https://doi.org/10.1787/eedfee77-en Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 22. https://doi.org/10.1186/s41039-017-0062-8 Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity. Shukla, A., & Tripathi, R. (2021). AI in higher education marketing: Ethics and personalization. International Journal of Innovative Science and Research Technology, 6(4), 377–383. Siau, K., & Wang, W. (2018). Building trust in artificial intelligence, machine learning, and robotics. Cutter Business Technology Journal, 31(2), 47–53. Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of artificial intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.09.008 Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 Wang, Y., Hong, J., & Pavlou, P. A. (2022). Privacy assurance in online platforms: An experimental analysis of information transparency and personalized targeting. Information Systems Research, 33(1), 27–49. https://doi.org/10.1287/isre.2021.1057 Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97–121. https://doi.org/10.1509/jm.15.0413 Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0

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Teaching in rural Rajasthan can easily become routine, turning learning into boring drills that have little to do with students’ real lives. NEP 2020 has nurtured this problem with a solution of making is eco-conscious and based on IKS(Indian Knowledge System). An eco-centric English for Specific Purposes (ESP) syllabus breaks this pattern by linking language learning to the environment, work skills, and culture of rural areas. Instead of treating English as just another school subject, it presents the language as a tool for everyday communication about land, water, crafts, animal care, small businesses, and local government topics that matter to students and their future. The reasons for this approach are threefold. First, learning becomes more interesting and motivating when English is used for practical tasks like selling crops, promoting eco-tourism, or recording traditional knowledge. Second, it helps students find jobs by teaching the kinds of writing and speaking needed at work, such as making enquiries, writing reports or manuals, and handling business letters. Third, it builds awareness of the environment, giving learners the words and ideas they need to talk about sustainability and community issues. This paper describes how to create such an eco-centric ESP syllabus based on careful research and the real needs of students in Girwa district of Rajasthan. It explains how textbooks can be developed, how teaching methods can focus on learners, and how teachers can be trained and students assessed to make English education more useful and engaging in rural Rajasthan.

Abatan, O. L. (2012). The folklorist as teacher: Towards the use of story telling pedagogy. V, 125–130. Chandlia, H. (2012). Teaching English literature in the present context. In S. Goyal (Ed.), Reflections on English language teaching. Jain Vishwa Bharti Institute (Deemed University). Dudley-Evans, T., & St. John, M. J. (1998). Developments in English for specific purposes: A multi-disciplinary approach. Cambridge University Press. Dudley-Evans, T. (2001). Editorial. English for Specific Purposes, 20(4), 311–312. https://doi.org/10.1016/S0889-4906(01)00028-6 Integrating English language teaching with environmental sustainability: A comprehensive review of pedagogical strategies and global impacts. (2025). Review Article. Preprint available on ResearchGate. Jordan, R. R. (1987). English for academic purposes: A guide and resource book for teachers. Cambridge University Press. Kazazoğlu, S. (2025). Environmental education through eco-literacy: Integrating sustainability into English language teaching. Sustainability, 17(5), Article 2156. https://doi.org/10.3390/su17052156

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Accurate prediction of student academic performance is essential for early intervention and personalized support in educational settings. This study investigates the application of machine learning-based feature selection techniques to identify the most influential factors affecting student outcomes. By leveraging recursive feature elimination (RFE) and correlation analysis, we reduce data dimensionality and enhance model interpretability without compromising prediction accuracy. Several classification algorithms including Decision Trees, Support Vector Machines, and Logistic Regression were employed to evaluate the impact of feature selection on model performance. Experimental results demonstrate that carefully selected features significantly improve predictive accuracy and model efficiency, providing valuable insights for educators and policymakers.

Mustapha, S. S. (2023). Predictive analysis of students' learning performance using data mining techniques: A comparative study of feature selection methods. Applied System Innovation, 6(1), 1-20. Patel, H. I., & Patel, D. (2024). Exploratory data analysis and feature selection for predictive modeling of student academic performance using a proposed dataset. International Journal of Engineering Trends and Technology, 72(1), 45-56. Ramaswami, M., & Bhaskaran, R. (2009). A study on feature selection techniques in educational data mining. arXiv preprint arXiv:0912.3924. Roy, K., & Farid, D. M. (2024). An adaptive feature selection algorithm for student performance prediction. IEEE Access, 12, 12345-12356. Zaffar, M., Hashmani, M. A., & Savita, K. S. (2018). A study of feature selection algorithms for predicting students academic performance. International Journal of Emerging Technologies in Learning, 13(10), 4-14. Liu, H., & Motoda, H. (2012). Feature Selection for Knowledge Discovery and Data Mining. Springer. Mustapha, S. S. (2023). Predictive analysis of students' learning performance using data mining techniques: A comparative study of feature selection methods. Applied System Innovation, 6(1), 1-20. Patel, H. I., & Patel, D. (2024). Exploratory data analysis and feature selection for predictive modeling of student academic performance using a proposed dataset. International Journal of Engineering Trends and Technology, 72(1), 45-56. Ramaswami, M., & Bhaskaran, R. (2009). A study on feature selection techniques in educational data mining. arXiv preprint arXiv:0912.3924. Roy, K., & Farid, D. M. (2024). An adaptive feature selection algorithm for student performance prediction. IEEE Access, 12, 12345-12356. Zaffar, M., Hashmani, M. A., & Savita, K. S. (2018). A study of feature selection algorithms for predicting students academic performance. International Journal of Emerging Technologies in Learning, 13(10), 4-14. Shahiri, A. M., Husain, W., & Rashid, N. A. (2015). A review on predicting student's performance using data mining techniques. Procedia Computer Science, 72, 414–422. Ramaswami, M., & Bhaskaran, R. (2009). A study on feature selection techniques in educational data mining. arXiv preprint arXiv:0912.3924. Zaffar, M., Hashmani, M. A., Savita, K. S., et al. (2018). A study of feature selection algorithms for predicting students academic performance. International Journal of Emerging Technologies in Learning.