On Journal’s Multidisciplinary,Interdisciplinarity and Anticipatory Character

Definitions

It is necessary here to recapitulate the meaning of multidisciplinary, cross-disciplinary, interdisciplinary and transdisciplinary because many among us use all these as interchangeable words. Multidisciplinary refers to an approach in which two or more academic disciplines are used to explain or resolve a social problem. Here, each discipline, with its own methods, methodology, theory and analytical tools, is used for understanding the problem or resolving the problem.

Cross-disciplinary, differing from multidisciplinary, refers to an approach in which concepts, theories or methods from one discipline are applied to the problem of another discipline, often from a single discipline’s perspective. It is different from multidisciplinary disciplinary, as dependence on the techniques, theories and concepts of another discipline is not involved.

An interdisciplinary approach means understanding a problem as part of an altogether different field of knowledge that does not belong to any of the established disciplines (Barthes, 1977). At the same time, this knowledge field is hardly a discipline. For example, environmental science, women’s studies or Dalit studies. This is evidently different from the multidisciplinary and cross-disciplinary approaches.

The transdisciplinary approach is different from all these. It refers to scholars’ knowledge generation as co-produced with anybody, including the lay public, who do not have specialization or even formal education, which is a method transcending the narrow academic restrictions normally followed by research institutions. Needless to say, it is different from all the other terms mentioned above. Nevertheless, even the academics often use all these terms interchangeably and indiscriminately as loose buzzwords. This Journal expects its contributors to maintain terminologically accepted semantic consistency. In order to ensure this, we once published a detailed editorial on terminology itself.

Terminology

Coming up spontaneously and forming part of the knowledge creators’ communicative action, terms constituted a new language within the language. It gained currency among academics. Terms containing phonological and morphological information are based on syntactic rules for delineating concepts by means of definition. The syntactic structures of thought describing the formation of concepts are similar to those in a language. Terminology distinguishes itself from the relation of words to language, which is semantic, evolving, diachronic, syntagmatic, regional and unilingual communication. Despite all this, terms and words became interchangeable, making their semantic function imprecise. Indiscriminate rendering of terms of conceptual and theoretical signification made cross-disciplinary scientific communication ambiguous. Terms from one science became words with metaphorical or analogical functions in another science, upsetting scientific communication.

In the communication of higher-order knowledge, strikingly new knowledge, terminology becomes helpless, despite its being universal, independent of geo-cultural and topographical differences. Defining higher-order knowledge has been an extremely difficult or near impossible attempt. We can say that it is the outcome of higher-order cognition, which cannot be easily taught due to its non-amenability to communication, even through terminology. Higher-order knowledge is profoundly theoretical, irrespective of the domain it represents.

For Overcoming Barriers

One of the editorials in the Journal addressed the difficulty of communicating higher-order knowledge through technical language. Language is humanity’s primary and most informal medium for conveying ideas; yet it often proves inadequate for the complex functional responsibilities entrusted to it. Linguists have long acknowledged that language rarely succeeds in transmitting ideas with complete fidelity to the intentions of their original source. Bhartrhari, a famous early Sanskrit philosopher-linguist, explored this problem in considerable depth, as discussed by Matilal (1990). According to Bhartrhari, linguistic expression tends to obscure ideas by concealing their essence within the semantic world of words. When a listener penetrates this verbal enclosure and grasps the concealed core, the experience occurs as a sudden revelation or spoṭa (an explosion in the mind). At times, this hidden core relates to the absent cause underlying the expression, much like fire that remains unseen beneath layers of ash.

Mikhail Bakhtin (1895–1975) realized that utterances were not confined to words, that gestures, sighs, yawns, exclamations, laughter and all such forms of wordless utterances were rich in communicative power. Likewise, we mix informal language with semiotics in everyday communication. Semiotics is not entirely a non-verbal language. All of this fails in communicating higher-order knowledge. Despite the richness of these verbal and non-verbal modes of expression, they often remain inadequate for communicating higher-order knowledge with precision and completeness.

The semantic vagueness of words had seriously bothered the philosophers of language and logic in Renaissance Europe. Most scholars felt the formal language of algebra was suitable. William of Ockham (1285–1347 ce), an English Franciscan Friar, as their precursor, thought of a language capable of expressing higher-order knowledge in a language devoid of description (Gurukkal, 2019). This practice of presenting the core of knowledge in an irreducible minimum of symbols by following Ockham’s prescription is famous as using Ockham’s razor. Accordingly, scientists continue to follow mathematical modelling in communicating their discoveries.

Engaged Learning

In the context of efforts to increase the number of engaged learners and, if possible, to nurture higher-order cognition in them (Mohanan & Mohanan 2024), the Journal editorial focused on the necessity by recalling the traditional practice of engaged learning.

It has been true across the ages that a curiosity-driven, self-directed, critical learner will spontaneously and joyously engage with original sources of knowledge. How to train the other learners has always been the central question in pedagogy and outcome-based education; the most systematized teaching and learning method guaranteeing differentially graded cognitive achievements for the largest number of learners is widely resorted to for surmounting the crisis (Anderson & Krathwohl, 2001). The Journal produced editorial as well as instructional material on it (Gurukkal, 2020a, 2020b, 2025; Rao, 2020).

In early India, systematic and analytical engagement with master texts constituted the core of advanced learning. Intellectual training largely depended on exercises such as defining, interpreting, expanding, commenting upon and summarizing authoritative texts. Such forms of textual engagement have long been recognized for their ability to transform students into active and reflective learners, with some of them eventually developing a passion for knowledge itself. Perhaps the best clinching evidence is the survival of the texts in the scholarly houses that were Gurukulas.

Across the world, traditional systems of higher learning were similarly rooted in sustained engagement with codified bodies of knowledge. Both early Indian and classical Graeco-Roman intellectual traditions attached great importance to learning through close interaction with foundational texts, reflecting a long continuity in the pedagogic practices of pre-modern societies. Engaged learning in knowledge fields like astronomy, healthcare and grammar in early India seems to indicate a pedagogic purpose. Debating is another method of engaged learning followed in early Indian, Chinese and Graeco-Roman traditions, very relevant today (Gurukkal, 2019). A self-motivated learner, under an inner compulsion urge, automatically debates, while others are required to debate under the teacher’s guidance through clarifications, corrections and encouragement until they become confident in self-guided debates. Mastering the art of reasoning and logic is fundamental to this learning experience of dialectics.

Production of New Knowledge

An editorial deals with the textual taxonomy of early Indian engaged learning practices. Master texts in astronomy, healthcare, grammar and philosophy were subjected to learners’ engagements, such as explanation (bhāṣyā), commentary/interpretation (vyākhya) and summary (sangraha). An explanatory version (bhāṣya) was essential since master texts are invariably theoretical. Needless to mention that the taxon successfully rendered the meaning differently but without losing the theory in the original text. However, a bhāṣya was not a mere reproduction of the content of the master text in different expressions. It was much more than what the taxon apparently and humbly makes us believe.

All the taxa were creative and critical engagements involving re-articulation of the master text, strikingly fresh illustrations, production of proofs, or presentation of new ideas. Often, they had led them to make original contributions to the knowledge concerned. These engagements, which were genuine cognitive encounters, often ended with the production of new knowledge. In this sense, the texts produced through engagement with master knowledge texts through the taxa finally came to be known as original texts of the authors themselves. In Sanskrit, Greek or Latin have spawned many translations and commentaries of master texts embodying original knowledge during pre-modern times have been convincingly explained from the angle of communication.

This teaching–learning device, grounded in a dynamic understanding of the cognitive process, has proved adaptable across diverse contexts of space and time. By being informed in advance about the intended learning outcomes, students are enabled to undertake a concurrent self-assessment of whether they are achieving the predetermined and graded cognitive gains associated with each course. In a similar manner, teachers can evaluate their own pedagogic effectiveness through a continuous assessment of student performance. Yet such mechanisms alone cannot overcome the prevailing crisis of quality in higher education. The only enduring solution lies in the democratization of passionate self-learning.

Theory as Higher-order Knowledge

Theory may be understood as a form of higher-order knowledge that transcends the immediate description of facts or events and seeks to identify their underlying principles, structures, relations and meanings. Unlike empirical information, which remains confined to particular instances, theory enables the human mind to move from the concrete to the abstract, from isolated observations to systematic understanding. It organizes experience into conceptual frameworks through which reality becomes intelligible, explainable and open to critical reflection. In this sense, theory is not merely an accumulation of ideas but a cognitive instrument that allows human beings to interpret the world in a deeper and more coherent manner.

Higher learning in all advanced intellectual traditions has therefore attached special importance to theory. Whether in philosophy, science, social thought, aesthetics or political reflection, theory represents the capacity to engage with knowledge beyond its surface appearance. It enables comparison, classification, generalization, critique and prediction. Theoretical knowledge also possesses a reflexive dimension: it not only explains objects and processes but interrogates the assumptions, methods and categories through which knowledge itself is produced. For this reason, theory occupies a central place in higher education, where the objective is not simply the transmission of information or technical skills, but the cultivation of analytical, critical and creative modes of thought.

Theorizing is a cognitive practice involving comparison, critical reflection, creative inference and constructive abstraction. A learner who cannot theorize may reproduce theoretical vocabulary, yet remain unable to use theory creatively, critically or contextually. If one is able to sensibly apply a theory, it demonstrates the faculty for deeper analysis and creative reflection. Theory can function as a meaningful framework of comprehension only when the learner acquires the intellectual disposition and analytical competence necessary for theoretical thinking itself.

A constant request to the authors during the peer review process of the Journal has been to be theoretical. Hardly does it elicit any successful response in practice. Most authors seem to believe that being theoretical is optional. Some of them draw a blank about what theory means and how it matters. Still, most articles thus follow the style of plain narration bereft of causation and generalization. In fact, the simple method of analytical narration is enough because it amounts to explanatory discussion with logical or empirical proof.

Even if one is not able to theorize, it is important to use one or more theories as a framework of comprehension and a logical foundation for interpretation. It presupposes the faculty to think conceptually, establish relations, recognize abstractions and critically examine the assumptions underlying knowledge. Without the ability to theorize, the use of theory degenerates into mere citation detached from genuine understanding. The legitimacy of theory in interpretation, therefore, depends not only on familiarity with theoretical texts but also on the actual intellectual ability to discover conceptual connections between theory and empirical reality.

Knowledge Economy

An editorial has explained at length what the knowledge economy means, how it works, and what consequences, and has illustrated all the implications thereof in an anticipatory editorial article. Nevertheless, we have to prepare the youth for the future, which is in the hands of the knowledge economy, widely instituted as part of the global capitalist system. The knowledge economy demands a greater focus on science, digital/information technology, engineering and mathematics at all levels of education as basic, essential literacy for innovation. Most jobs in the knowledge economy require skill sets in information technology and related fields.

Actually, the knowledge economy demands proficiency in high-impact technical expertise for jobs in the new global competitive world. Both in the academic and industrial sectors, postgraduates are expected to demonstrate competence to undertake original and potentially groundbreaking research leading to the production of new knowledge and to be inevitably innovative. Today, scientists, technologists, entrepreneurs and industry experts form a single community. Every basic science is constrained to be technology-oriented. Such science-tech hybrid areas like nanoscience and nanotechnology, grapheme engineering, brain-computer interface objects and several related fields, like microbiology, genomics, biotechnology, artificial intelligence (AI), robotics, bioinformatics and others, are examples. Corporates the world over need science-tech graduates from innovative faculty in plenty for their research establishments. Courses giving more weightage to the cognitive benefits of conceptual understanding and application are important too.

Students must be capable of demonstrating critical thinking (the faculty to discern the underlying and fundamental about anything, that is, the faculty to discover), communication skills (the ability to be articulate in the knowledge language, that is, the language of technical terms, algorithms and algebraic equations), multidisciplinary adaptability (mandatorily good acquaintance with the basics of cognate disciplines, and desirably of other sciences as well) enabling collaboration, and creativity (the faculty to innovate). Operational skills in digital technologies such as robotics, AI, machine learning, augmented reality, big data and real-time analytics, Bitcoin and Blockchain have to supplement the competencies.

The Digital Turn

The Journal, through editorials and articles, has focused on the question of the digital turn in higher education, which marks a profound transformation in the ways knowledge is produced, accessed, shared and evaluated. Digital technologies have altered the relationship between teachers, students, institutions and knowledge systems by enabling access to global information networks, virtual classrooms, open educational resources, web libraries, AI tools and collaborative research platforms. The traditional model of higher education, centred on the physical campus and the classroom, is increasingly being supplemented by hybrid modes of learning.

Students have the freedom to access lectures from leading universities across the world, participate in international research collaborations, and engage with that transcends linguistic and geographical barriers. Digital platforms have enabled new pedagogic practices such as flipped classrooms, adaptive learning systems, data-driven student assessment and interactive simulations. This radical transformation has forced universities to restructure curricula and institutional governance systems using digital automation and AI-powered tools. The Journal did focus on the social, ethical and philosophical questions perturbed by consequences like the shallowness of the affordable learners due to the reckless use of generative AI-powered tools as an alternative to real learning, while the poor are deprival of all the technology’s positive advantages. Unequal access to digital infrastructure, devices and connectivity continues to reproduce existing social inequalities. Concerns regarding data privacy, surveillance, algorithmic bias and the erosion of critical human interaction have been central to several articles. Editorials have been probing the question of whether institutions should ban or democratize such AI-powered interactive tools and whether the faculty should compete or collaboration with the tools.

Digital technologies have accounted for the onset of a fundamental change in the perception, appreciation and sensibility in all branches of knowledge. Today, every discipline has it today identified with the prefix ‘computational’ or ‘digital’ irrespective of the domain. We have digital sciences, digital social sciences and digital humanities. Computer analytics (involving statistical tools, mathematical models and algorithms) distinguishes the digital sciences and digital social sciences.

Digital Sciences

Digital sciences refer to the broad domain of scientific knowledge and research that is shaped, enabled or transformed by digital technologies, computational systems and data-intensive methods. It encompasses the use of advanced computing, AI, machine learning, simulation, modelling, digital instrumentation and big data analytics in the production, organization and application of scientific knowledge. Across disciplines such as physics, biology, chemistry, environmental science, medicine, engineering and astronomy, digital technologies have fundamentally altered the ways in which scientific observation, experimentation, analysis and communication are carried out. Scientific inquiry today increasingly depends on computational capacities capable of processing vast amounts of data, simulating complex systems, and identifying patterns beyond the reach of conventional methods.

More significantly, digital sciences represent a new epistemic condition in which computation itself becomes central to scientific reasoning and discovery (Floridi, 2014). Scientific knowledge is no longer confined to laboratory observation alone, but increasingly emerges through digitally mediated environments such as virtual simulations, algorithmic modelling, sensor networks and interconnected research infrastructures. This transformation has accelerated interdisciplinary research and global scientific collaboration while simultaneously raising important ethical and philosophical questions concerning data ownership, algorithmic reliability, technological dependence and the social consequences of automated decision-making. Thus, digital sciences signify not merely the digitization of science, but the emergence of new forms of scientific thinking, experimentation and knowledge production in the digital age.

Digital Social Sciences

Digital social sciences refer to the application of digital technologies, computational methods and data-driven approaches to the study of society, human behaviour, institutions, culture and social relations (Ackland, 2013). The rapid expansion of digital communication platforms, social media, online transactions, mobile technologies and digital governance systems has generated enormous volumes of data concerning contemporary social life. Digital social sciences seek to analyze these emerging forms of data through methods such as computational analysis, network analysis, digital ethnography, big data analytics, geospatial mapping and AI-assisted research. By combining traditional social science concerns with digital tools, the field enables researchers to study social processes at scales and speeds previously unimaginable (Lupton, 2015).

At the same time, digital social sciences is not merely a technical extension of conventional social research. It also involves critical reflection on how digital technologies themselves are reshaping society, politics, economy, identity, labour, communication and power relations. Questions relating to surveillance, digital inequality, algorithmic governance, data privacy, misinformation, platform capitalism and the transformation of democratic processes have become central concerns of contemporary social inquiry. The field, therefore, demands an interdisciplinary approach that combines sociological, political, economic, anthropological and philosophical perspectives with computational competence. In this sense, digital social sciences represent both a methodological innovation and a new domain of critical understanding necessary for interpreting social life in the digital age.

Digital Humanities

Digital humanities and liberal arts, consisting of philosophy, ethics, jurisprudence, literature, political history and fine arts, apply computational tools and methodology for pursuing basic research questions and organizing knowledge relating to contextualization, historicization, rhetorical narration and critical interpretation (Schreibman et al., 2004). Hence, computational analytics of the genre, text, subtext, hypertext and context of thoughts, arts, artefacts and culture is the distinctive feature of the domain. Be it differences, departures, recurrences, regularities or uniformities—they are tracked with unprecedented accuracy across the bewildering data pools, thanks to Blockchain technology. This is not mere quantification of the measurable attributes, but a precise assessment even of subtle nuances and niceties.

Digital humanities refer to a multidisciplinary field of knowledge that brings together the methods of the humanities with the tools and technologies of the digital world. It involves the use of computational techniques, digital archives, data visualization, AI, text mining, mapping technologies and multimedia platforms for the study, preservation, interpretation and dissemination of human culture, history, language, literature, philosophy and the arts. The field is not confined to the mere digitization of texts or manuscripts; rather, it seeks to transform the ways in which humanities knowledge is produced, analyzed and communicated. By integrating computational methods with humanistic inquiry, digital humanities open new possibilities for examining large bodies of texts, tracing historical patterns, visualizing cultural networks, and creating interactive forms of scholarship.

At a deeper level, digital humanities represent a significant epistemic shift in the humanities themselves. It encourages collaborative and interdisciplinary research involving historians, literary scholars, linguists, archivists, computer scientists, designers and data analysts. The field also raises important theoretical and ethical questions concerning authorship, interpretation, digital preservation, access to knowledge, algorithmic bias and the politics of data. In societies marked by linguistic and cultural diversity, digital humanities can play an important role in preserving endangered archives, vernacular traditions, oral histories and regional knowledge systems through digital platforms. Thus, digital humanities are not simply about technology in the humanities; it is about reimagining the future of humanistic knowledge in the age of digital transformation.

Digital technologies’ extensive penetration into all forms of knowledge is resulting in the growth of digital innovation itself as an amazing field. Through a process of redefinition and reconceptualization, the digital innovation field is emerging as an all-encompassing field. Engaging in cross-disciplinary research in the digital innovation field, technologists are integrating and redesigning their resources for future innovations, which are predictably all the more path-breaking.

Anticipatory Dimension

There are several anticipatory notes published in the Journals. Only two prominent instances are repeated here as representative cases. An article in three parts, which the chief editor wrote, is the lengthiest one that demonstrates the Journal’s anticipatory function. It was a considered response to the COVID-induced virtual mode of teaching and learning, which many in the higher education sector took as a pandemic-caused deterioration. Similarly, many communists thought that the pandemic would lead the whole world to a peaceful but historic transition from capitalism to the life of communes. Sociologists like Manuel Castells had already argued that the nation-state would be bypassed by showing that an alternative economy was possible (Castells et al., 2017). Zizek (2020), a famous Slovenian Neo-Marxist critical theorist and public intellectual, as a strong proponent of this view, extensively talked and wrote about the transition involving the death of capitalism, urbanism and nation states.

In anticipation, the Journal, through the article, stated that the COVID-induced virtual mode was not just a technological alternative to the actual teaching–learning system. The Journal anticipated that the virtual would not go away with the pandemic. Capable of reshaping many of the established educational practices and their environments, it would bring about a series of transformations in the concept of higher education institutions, clientele and practices. A change in the concepts of competence, outcomes, teaching, learning, evaluation, quality, access, equity and excellence is likely. Competence will be e-competence, outcome will be computational, teaching will be information and communication technology-linked, evaluation will be online-based, quality will be e-competency-related, access will be technology-dependent, and equity will be mere rhetoric. Further, under COVID-19-induced flexibility and wide choice, impairing institutional requirements and administrative procedures would make higher education much more personalized and self-directed. Those portions of the published article relevant to the higher education sector are reproduced below:

Post-COVID-19 changes on campus would be mainly behavioural, such as physical distancing, mask wearing and sanitizing. These will be insisted upon in classrooms, libraries, laboratories, canteens and other places, like common spaces, but more as a set of new routines. At the same time, there are certain matters most likely to be followed seriously. A new time schedule, opportunities to gain work experience under the scheme of earn while you learn, chances to do various courses enhancing employability, postgraduate programmes in cross-disciplinary fields, and the expansion of life-related research. Many students aiming to go abroad for higher studies would be encouraged to continue their higher studies in the state itself due to COVID-19-induced restrictions on mobility and the global recognition of Kerala’s health security. Students from within the country, too, would like to pursue their studies in the state, thanks to its dignity of showing equal care for all. This would lead to the appointment of many new teachers in different fields.

Post-pandemic higher education would be influenced by the pandemic itself. Research fields might be either directly or indirectly related to the pandemic crisis and its consequences. Scientific research will have an added focus on the knowledge universe of the virus itself. The COVID-19 vaccine is the object of sustained engagement the world over today. The pandemic is going to be the central theme of research in the liberal arts, humanities and social sciences too, focused through the lens of disciplines, genres, and their unending combinations, interfaces and transcendence. Most of these would receive the global economy’s patronage, but only until the pandemic phases out as a passing phenomenon. Software and hardware industries, on their own, responding to the COVID-19 situation of virtual education, would push research in technology and product design engineering for inventing new tools.

A few research domains, both macro and micro, separately and in combination, would predictably last as the potential source of techno-capitalist knowledge industry. The combination of the macro and the micro has already been there for knowing the macro through extrapolation, as in the case of geology and cosmology. Under the patronage of the knowledge industry, cosmology has been receiving a lot of patronage for quite some time, by fits and starts. Plasma high-energy physics, mainly shockwave hypersonic velocity research, has been another area of the macro—micro combine receiving the techno-capitalist industry’s patronage. Similarly, the macro is being explored in terms of non-classical mechanics and impact physics through new means of measurement. Such science-tech hybrid areas focusing on the microspace of nanometres and the time of milliseconds, instead of the macrospace and infinite time, are receiving the industry’s attention.

Most advanced research in these fields is being carried out in the huge transnational research establishments of corporates. As already pointed out earlier, more specialized research on aspects of self-replicating particles, grapheme engineering, the designing of nanotech sensors, transmitters, brain-computer interface objects and others, is in progress there. Several related fields of techno-capitalist interest, like microbiology, genomics, biotechnology, nanotechnology, AI, robotics, bioinformatics and others, are already there in some of our higher education institutions. Under the pandemic emergency environment of centralized and bureaucratized control, many of the areas of corporate interest would be pushed into the higher education curricula, with a view to developing human resources in rare fields. Corporates would need science-tech graduates with innovative faculties in plenty for them to choose the best to work at low cost in their research establishments.

It would be increasingly recognized that the developing world of poor-quality higher education is rich in students of innovativeness. Since picking and training them as such being costly, the developing countries would be more and more encouraged to uniformly redesign their higher education to serve the purpose. Such redesigning and homogenizing reforms have already been in progress everywhere, including India. Disciplines will increasingly draw closer to one another in the wake of the emergence of more and more cross-disciplinary areas of knowledge. Blurring of disciplinary borders in higher education will demand cross-disciplinary literacy among teachers and adaptability among students. The growth of the sciences through narrow specializations, which in their turn becoming sub-disciplines of added rigidity, will be forced to break disciplinary silos and allow flexibility of choice in specialization across disciplines. Specialization giving precedence to parts over the whole impeding holistic understanding will phase out. This is because of the corporate-industrial interest in the opening up of knowledge fields of application at the interface of disciplines or their convergence.

What is striking about the Indian context is the rare demographic situation of having the world’s highest population ratio of youngsters. Out of the country’s total population of about 1.32 billion, over 65% are below the age of 35, and above 50% are in the age group of 18–23. About 140 million youngsters are in the age group of 17–20. As estimated by the International Labour Organization, India today has 116 million youth in the age group of 20–24, a strength that exceeds the Chinese youth population by 22 million. Today, the average age of an Indian is 29 years, while it is 37 for China, 40 for the USA, 47 for Europe and 48 for Japan. It is extremely important for the nation to judiciously design effective strategies for equipping the youth to be at their best with competencies of the twenty-first century in order to reap the benefits of this demographic dividend.

Let us hope that our premier institutions might succeed in equipping a microscopic minority among the brilliant youth for the technology of the twenty-first century. We cannot be sure of their global competitiveness. Nevertheless, we may only export them for want of a domestic market. It is, therefore, essential for us to develop our own standards of higher education and research questions by coming to terms with the crucial problems that we encounter at the national, regional and local levels. Knowledge, generated beyond disciplines and across their interfaces, strikingly new, regenerative and converging, has to be our focus. It cuts across wide-ranging domains of knowledge, from material sciences and manufacturing technology to natural sciences, ecology, biotechnology and healthcare. We should try to equip our brilliant youth for the production of new knowledge belonging to the interface of multiple domains of science and technology, which helps us better understanding of the local and national problems.

Resolution-oriented, local-level, issue-based, interdisciplinary teaching and research, facilitating the convergence of science and technology, may be a viable alternative for us. Issues of local relevance can act as objects of convergence research, leading to new knowledge in science and technology, which will be inevitably innovative and far-reaching in its effects. Such a vision has a global standard, too, in terms of sustainable science and technology. On top of all, it is based on ethical postulates relating to social and environmental justice.

What could be the post-COVID residual in the domain of higher education is an important question. In India, the higher education sector would largely remain the same but will be centralized under a single regulatory authority, with the number of institutions highly reduced and made uniform through homogenization of curricula, academic programmes and learning outcomes as construed by experts in the corporate knowledge industry. A centrally monitored single online podcast of course material will be nationally imposed. Institutions would be funded selectively through ‘challenge mode’, pressurizing them to function as centrifuges, sifting out the best brains trained in high-power computing to work in corporate institutions of science-tech hybrid areas.

Higher education institutions in the country will compete to provide a teaching and learning environment appropriate for the production of enough graduates employable in the knowledge industry. Both the central government and the University Grants Commission have already begun attempts to centralize academic decision-making, as is evident in the proposal for homogenizing curricula, reduction of the number of publicly funded institutions, and cuts in the funds made available to the existing institutions. Downsizing the entire sector, including the reduction of teaching posts, has been part of the educational policy of the Ministry of Human Resource Development ever since the General Agreement on Trade in Services. COVID-19-induced dependence of education on the online mode provides a good pretext for implementing.

Indian higher education, not dependent on foreign students, will be the least affected by the international supply-chain disruption caused by the pandemic. Demographically favourable from the demand side, Indian higher education institutions would hardly face any scarcity of students and, hence, any revenue fall. At the same time, the teaching/learning mode is redefined due to dependence on virtual classrooms and online transactions, and the cost will be less. However, private institutions forging ahead by investing in technological infrastructure and sophisticated educational tools might charge heavily.

Generation Alpha

Another notable anticipatory editorial relates to Generation Alpha, popularly called Gen Alpha. It is relevant to reproduce here several ideas and even expressions published in the Journal. The question of how we design higher education for Gen Alpha, those born after 2010, demands urgent attention, since they would soon enter institutions of higher education offering a pattern of learning utterly unsuitable to them. It is a ponderous paradox that we are shaping the educational futures of Gen Alpha with little knowledge about the cognitive worlds, learning habits and aspirations.

Gen Alpha is the seniors of screen-age children. Raised on liquid crystal display monitors, smartphones, tablets and algorithm-driven platforms, their sensibilities have been shaped long before their entry into higher education institutions. The learning process of Gen Alpha has never been linear, slow or exclusively textual. They would be looking for institutional support for personalized, self-paced and self-directed education. But we are yet to understand Gen Alpha’s learning styles, perceptions and expectations.

The emergence of AI marks a decisive rupture in this already fragile system. Educators now face the unprecedented challenge of designing curricula and teaching strategies for Gen Alpha. Teachers who lack competence in AI-powered tools and virtual learning environments will increasingly find themselves ineffective, regardless of their disciplinary expertise. AI-driven adaptive learning platforms offer what Gen Alpha requires. This shift would compel universities to rethink their academic enterprises at a speed and scale never experienced before. Institutions that fail to adapt will not merely stagnate but give way to the takeover by alternative, hyper-connected models better aligned with Generation Alpha’s expectations.

Teachers who are prepared to learn from and work with AI will move beyond present limitations. AI is likely to become a collaborator in the pursuit of knowledge, creativity and meaning rather than a mere substitute for human effort. Competing with the speed of AI is futile; what truly matters is the ability to raise questions that lie beyond the reach of algorithms. AI may detect patterns with remarkable efficiency, but only human judgement can interpret them with depth, nuance and vision. The future of higher education, therefore, rests on a thoughtful partnership between professors and intelligent systems. It is going to be a central challenge for higher education in the near future.