Call for Papers
Telangana Journal of Higher Education (TJHE)
ISSN 3108-0693 (Online) | ISSN 3139-292X (Print) | ISSN-L 3108-0693 (Linking ISSN)
Volume 2, Number 2 (July – December 2026)
Call for Papers
Submission Deadline: 15 October 2026
THEME
Artificial Intelligence and Higher Education
Artificial intelligence has moved, with remarkable alacrity, from the margins of experimental research into the into the mainstream university life. It now shapes how students search for information, read, think and write. It influences how teachers design courses, set assignments and respond to student work. It also affects how institutions admit students, advise them, manage workload, allocate resources and make decisions. Tools that once belonged mainly in specialist laboratories are now present, often quietly, in lecture halls, libraries, research groups and administrative offices, in India and around the world.
This themed issue of Telangana Journal of Higher Education (TJHE) invites original scholarship that takes this moment seriously. Our aim is not to endorse AI uncritically or to reject it outright, but to understand it in proper perspective. We encourage contributions that ask, with precision and intellectual rigour, what AI is doing to the university and what the university ought to do in response. We are especially interested in work that holds together both sides of the story—opportunity and risk—and that attends carefully to the Indian context while remaining in conversation with international debates.
The opportunities offered by AI are immense. Adaptive learning systems can personalise support for students in ways that no single teacher can manage alone. Automated feedback can speed up revision cycles and allow human teachers to spend more time on mentoring, discussion and careful judgement. Translation and language technologies can reduce barriers in India’s multilingual classrooms and support students who work across several languages. Discovery tools can help scholars in modestly resourced institutions to find and use large bodies of research. Assistive technologies can support learners with disabilities and long-term health conditions. For first-generation students, for those in remote regions and for those studying in under-resourced contexts, well-designed AI systems may open doors that were long closed.
The challenges, however, are equally real and undeniable. AI systems are designed and trained by particular people, using particular data and assumptions. This raises basic questions—whose values and viewpoints shape these tools, and whose do not? When algorithms influence reading lists, search results and citation patterns, certain kinds of knowledge may be highlighted while others are conveniently pushed aside. Because AI systems learn from historical data, they often reproduce existing inequalities of gender, caste, class, language, disability and region. Used without proper scrutiny, they may strengthen the very exclusions they claim to eliminate.
AI also poses practical and ethical questions in everyday academic life. In the classroom, it unsettles familiar ideas of authorship, originality and academic honesty. In university governance, it causes concerns about surveillance, consent, constant monitoring and an excessive reliance on numerical metrics. In research, it raises issues of access, bias and dependence on proprietary platforms, especially for institutions with limited resources. In a country like India, where connectivity and infrastructure remain uneven, these tensions and trade-offs become especially pronounced.
This issue of TJHE therefore invites sustained, critical and constructive inquiry into how AI can be governed and used responsibly and productively within higher education. We welcome work that examines AI in teaching and learning, in research and knowledge production, in institutional planning and administration, and in the wider public role of universities. Historical, theoretical, empirical and practice-based studies are all welcome, as are interdisciplinary approaches that cross established academic boundaries.
Above all, we seek writing that remains with the complexity of the present rather than rushing to simple verdicts. The goal is to open a careful, context-aware conversation about the place of AI in higher education, and to consider what the university ought to be in an age of machine learning, automated decision systems, data-driven governance, ubiquitous surveillance, predictive analytics, generative media, algorithmic management, platform monopolies, and relentless technological change.
Theme: Artificial Intelligence and Higher Education
Sub-Themes (indicative, not exhaustive)
1. Generative AI and academic integrity in student work
2. Rethinking assessment for AI-assisted learning environments
3. Adaptive and personalised learning models through AI
4. AI tutoring systems and equitable learning support
5. Automated feedback and formative assessment tools in universities
6. AI in admissions, scholarships, and student selection processes
7. Predictive analytics and student retention strategies in higher education
8. Learning analytics dashboards and meaningful student support
9. Privacy, consent, and data dignity on campus
10. Algorithmic bias and exclusion in Indian higher education
11. Fairness audits for educational AI tools and platforms
12. AI for multilingual and Indian-language higher education
13. Machine translation and cross-lingual academic collaboration
14. Language hierarchies, English dominance, and AI interventions
15. Research integrity in the age of generative systems
16. AI-assisted literature review and knowledge discovery practices
17. Citation patterns, recommendation systems, and invisible knowledge biases
18. AI in laboratories, studios, and field-based research
19. AI for research design, data analysis, and visualisation
20. Accessibility tools for students with disabilities and chronic health issues
21. Inclusive AI design for various learner needs
22. Teacher training for responsible pedagogical use of AI
23. Faculty development and critical AI literacy programmes
24. Academic leadership training for AI-era decision-making
25. University libraries and AI-driven discovery tools
26. Library catalogues, search algorithms, and epistemic justice
27. Open educational resources and AI-assisted content creation and consumption
28. Quality assurance for AI-generated learning materials
29. Institutional AI policies and academic freedom safeguards
30. National and state AI governance frameworks for universities
31. NEP 2020 and AI-enabled higher education reform
32. Accreditation, quality assurance, and AI-based evaluation systems
33. Edtech platforms, vendor contracts, and proprietary AI dependence
34. Public-private partnerships around AI in higher education
35. The digital divide and unequal AI access across regions
36. AI infrastructure planning for under-resourced campuses
37. Low-cost, low-bandwidth AI solutions for Indian universities
38. Student voice, participation, and campus debate on AI
39. Surveillance, monitoring, and the ethics of dashboards
40. Attendance tracking, proctoring, and everyday surveillance practices
41. Governance by metrics versus academic and collegial judgement
42. Comparative AI adoption across central, state, and private universities
43. AI in open and distance learning institutions and MOOCs
44. AI and opportunities for first-generation and marginalised learners
45. Rural and remote learners in an AI-mediated ecosystem
46. AI for regional languages, dialects, and local knowledges
47. Sustainable and green approaches to campus AI infrastructure
48. Philosophy of knowledge in the machine age
49. Human judgement, craft, and machine assistance in scholarship
50. Embedding AI ethics across disciplines and curricula
51. Teaching ethical reasoning about data, algorithms, and automation
52. Intellectual property and AI-generated scholarship and courseware
53. Authorship norms, acknowledgment, and credit in AI-assisted work
54. Explainability and transparency in educational AI systems
55. Contestability, appeal, and redress in AI-based decisions
56. AI-driven timetabling and administrative decision-making
57. Workload allocation, scheduling, and algorithmic management of staff
58. Career services and AI-powered employability and placement tools
59. Labour market forecasting, skilling, re-skilling and AI-informed programme design
60. AI and the future of examinations and invigilation
61. Remote proctoring, integrity tools, and student trust
62. Detecting AI content: promise, limits, and misuse
63. Institutional guidelines for legitimate AI use in coursework
64. Global South perspectives on AI in academia and policy
65. South-South collaborations on educational AI research and practice
66. India’s AI talent pipeline and university curriculum reform
67. Centres of excellence for AI and higher education studies
68. Industry partnerships and AI research funding arrangements
69. Conflicts of interest in university-industry AI collaboration
70. Academic labour and automation of routine academic tasks
71. AI, casualisation, and new pressures on faculty work
72. Critical AI literacy for scholars, administrators, and citizens
73. Public engagement, media narratives, and AI in higher education
74. Governance structures for campus-wide AI steering and oversight
75. Ethics committees and review mechanisms for AI deployments
76. University archives, digitisation, and AI-driven heritage preservation
77. AI for alumni relations, fundraising, and institutional branding
78. Cross-border AI regulations and implications for international students
79. Comparative analysis of global AI-in-education guidelines
80. Reimagining the university in an AI-saturated world
These sub-themes are offered as prompts for reflection rather than as prescribed titles. Authors may pursue a single thread, weave several together, or advance arguments that open new ground within the wider theme of artificial intelligence and higher education.
Important Submission Details
Contributors may please note
- Multiple submissions will not be considered. Each contributor, together with any co-authors, should submit only one article.
- The number of authors, including the corresponding author, must not exceed three.
- The ideal manuscript length lies between 3,000 and 8,000 words.
- All submissions will be screened for similarity and AI-generated content. Where either measure exceeds 15 per cent, the submission will be rejected.
- Authors who have published in either of the previous two issues of TJHE are requested to wait until the following issue before submitting new work.
- TJHE observes British English and APA Style, 7th edition.
- For more information, please consult the Submission Guidelines: https://tgche.ac.in/telangana-journal-of-higher-education-tjhe/
The Editor
Telangana Journal of Higher Education (TJHE)
Telangana Council of Higher Education (TGCHE)
JNAFAU Building, Mahaveer Marg, Masab Tank
Hyderabad 500028, Telangana, India
Email: editor.tjhe@tgche.ac.in
