Researchers led by Nishat Tabassum of Pabna University of Science and Technology, working with colleagues from Comilla University, surveyed students at three major public institutions: the University of Dhaka, Rajshahi University, and Pabna University of Science and Technology. Using stratified random sampling, they collected responses from 150 students at each university, drawn evenly from engineering, science, social sciences, arts, and humanities faculties. The respondents, 52.2 percent male and 47.8 percent female and mostly between 18 and 25 years old, answered a structured questionnaire administered through a web survey, with the resulting data analyzed using IBM SPSS Statistics 20 and Excel.

The intellectual scaffolding of the study rests on three theories. Technological determinism, rooted in the work of sociologist Thorstein Veblen, holds that technological innovation drives social change and reshapes institutions, often faster than those institutions can adapt. Skill mismatch theory describes the gap that emerges when workers’ competencies diverge from labor market demands, whether through horizontal mismatch between education and job requirements, vertical mismatch of overqualification, or skills obsolescence caused by rapid technological turnover. Labor market theory, meanwhile, frames how shifts in the supply and demand for particular skills translate into changes in wages and employment levels. Together, the researchers argue, these frameworks explain why students expect AI to transform their careers and why they fear the education system is not keeping pace.

The headline finding is cautiously optimistic: across all three universities, a majority of students believe AI will generate more employment opportunities than it eliminates in their fields. Rajshahi University students expressed the greatest optimism, with 55.3 percent agreeing that AI will expand job opportunities, followed by PUST at 52.7 percent and Dhaka University at 43.3 percent. This pattern echoes a growing international literature suggesting that AI’s effect on employment is better characterized as job shifting than mass job loss, as automation displaces routine tasks while creating new occupations that demand advanced cognitive, digital, and socio-emotional capabilities.

Beneath that optimism, however, lies a deep vein of anxiety and institutional criticism. More than half of the students at every university surveyed agreed that AI-driven change would produce a skills mismatch, with agreement peaking at 62 percent at Rajshahi University. Even more telling, 70.7 percent of all respondents believed a gap exists between the skills they are currently learning and the skills required for AI-related jobs. And when asked whether their institutions were actively updating curricula to include AI-relevant skills, 62.7 percent disagreed overall, with dissatisfaction reaching 70 percent at Dhaka University and 69.3 percent at PUST. Only at Rajshahi University did a comparatively larger share, 37.3 percent, believe their curriculum was being meaningfully refreshed.

The study also documented institutional variation in how much AI education students are actually receiving. Rajshahi University reported the best integration, with 48.7 percent of students saying they receive adequate AI education in their programs, against 38.6 percent who disagreed. At Dhaka University the picture was more divided, with 48.6 percent disagreeing that their AI education was sufficient, and at PUST a majority, 50.6 percent, said their programs were not preparing them adequately. Correspondingly, only 12.7 percent of Dhaka students and 14.7 percent of PUST students rated the availability of AI-related courses and training at their institutions positively, compared with 24 percent at Rajshahi University. The researchers note that AI course integration appears greatest in engineering faculties and weakest in the sciences across all three institutions.

Gender and geography shaped perceptions in subtle ways. Female students at Dhaka University and PUST reported higher familiarity with AI than their male peers, at 75.6 percent and 88.4 percent agreement respectively on the relevance of AI to their fields, while at Rajshahi University males reported greater familiarity and a sizable share of female respondents, 19.4 percent, remained neutral, a pattern the authors suggest may reflect unequal access to AI-focused learning opportunities. Regional dynamics were equally revealing: Dhaka University students, situated in the capital with greater industry exposure, were the least fearful of job loss, with 56.7 percent disagreeing that AI would cause significant job losses, while roughly half of PUST and Rajshahi students expressed such fears, a disparity the researchers attribute to uneven access to technological infrastructure and employment networks outside Dhaka.

Where students agreed almost unanimously was on the enduring value of human skills. Majorities at all three institutions, ranging from 66.7 percent at Rajshahi to 73.3 percent at PUST, said jobs requiring creativity and emotional intelligence are less likely to be automated. Even more striking, between 73.3 and 84 percent of students at the three universities said AI knowledge is key to future career success. Yet this awareness did not translate into confidence: 52.7 percent of Dhaka University students took a neutral stance on their own ability to adapt to AI-driven change, compared with far lower neutrality and higher confidence at PUST, where 50.7 percent agreed they could adapt, and Rajshahi, where 55.3 percent did so.

The demand signal from students could hardly be clearer. Around 81 percent of PUST students and 82 percent of Rajshahi students, along with 72 percent of Dhaka students, called for more practical AI training in their curricula, and similar majorities wanted more hands-on AI experience and stronger collaboration between universities and industry. Confidence in government action was notably weaker: a net negative assessment of policy effectiveness emerged, with 44 percent of respondents disagreeing that government initiatives were addressing AI-era skills mismatches, against just 30 percent agreeing. This skepticism persists despite Bangladesh’s National Strategy for Artificial Intelligence, launched in 2020, and a National AI Policy adopted in 2024, suggesting a perceived gap between policy formulation and implementation on the ground.

The authors conclude that without deliberate intervention, the promise of AI-driven development in Bangladesh may remain unrealized. They recommend embedding foundation AI courses across all faculties, not just engineering; organizing workshops, seminars, and guest lectures with AI professionals to expose students to real-world applications; aligning university curricula with national AI policies; investing in faculty training and the infrastructure needed for AI teaching and research; and fostering continuous learning habits among students so their skills remain relevant throughout their careers. For a country where nearly 34 percent of young people are considered tech-savvy and the youth population is expanding rapidly, the stakes are considerable. The study suggests that Bangladesh’s students have already made up their minds about AI: they see it as an opportunity, but one their universities have not yet equipped them to seize.

Subject of Research: University students' perceptions of artificial intelligence's impact on job prospects and skill mismatch in Bangladesh

Article Title: Understanding university students’ perspective on artificial intelligence and its influence on job prospects and skills in Bangladesh

Article References: Tabassum, N., Ferdous, J., Hossain, M. S., & Haque, T. (2026). Understanding university students’ perspective on artificial intelligence and its influence on job prospects and skills in Bangladesh. Discover Global Society, 4(1), Article 237. https://doi.org/10.1007/s44282-026-00413-7

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00413-7

Keywords: artificial intelligence, Bangladesh, university students, job prospects, skill mismatch, higher education, curriculum reform, labor market, AI literacy, employment, public universities, workforce readiness

The research team, led by Helen Maginnis and Agata Oliwa as joint first authors, with Lucy McKay of the charity Medics for Rare Disease and Duncan Cole of Cardiff University School of Medicine among the senior investigators, designed a cross-sectional online survey of 28 items. The questionnaire was adapted from an earlier instrument developed at University Hospitals Leuven and distributed with the help of student networks, including Students for Global Health and the National Student Association for Medical Research, to students at 35 medical schools accredited by the General Medical Council. The survey measured both self-assessed knowledge and awareness of rare disease and an objective knowledge test, alongside questions about educational experience and exposure to people living with rare conditions.

In total, 253 responses were recorded from undergraduate and graduate-entry medical students, of which 126 fully completed responses from 27 medical schools were suitable for analysis. Respondents spanned all years of medical study, although the majority, 79 percent, were in years one to four or undertaking an intercalated degree. The numbers provide a snapshot rather than a census, but the breadth of participating institutions lends weight to the central finding: rare disease education in the UK undergraduate curriculum is patchy, inconsistent and, by the students’ own assessment, frequently inadequate.

The headline figures are striking. The median self-assessed knowledge of rare disease among respondents was just 3 out of 10, indicating that even students who chose to answer a survey on the topic rated their own understanding as low. Objective knowledge, measured with a fifteen-point test, yielded a median score of 9, suggesting a partial but incomplete command of core concepts. More troubling than the raw scores, however, was the trajectory: there was no consistent improvement in self-assessed knowledge, self-assessed awareness or objective test performance as students advanced through their degrees. Whatever learning does occur appears scattered rather than cumulative, dissipated across a curriculum that rarely returns to the topic in a structured way.

The study also probed what does seem to move the needle. Students with greater clinical exposure to people living with rare disease, and those with a personal connection to the rare disease community, reported higher self-assessed knowledge and awareness than their peers. Yet notably, neither form of experience translated into higher objective knowledge scores. This dissociation matters because it suggests that encountering rare disease in the clinic, however valuable for empathy and awareness, does not by itself build the transferable cognitive framework, such as an understanding of inheritance patterns, diagnostic delay, multidisciplinary coordination and the appropriate use of genomic and specialist services, that clinicians need to recognise and manage these conditions.

Preparedness for practice was similarly limited. Just over half of respondents reported receiving some rare disease education during their degree, but only one in five felt prepared to recognise or consider a rare disease in clinical practice. This gap between exposure and readiness echoes the lived experience of patients, who frequently describe years of uncertainty, multiple misdiagnoses and repeated referrals before a definitive diagnosis is reached. The so-called diagnostic odyssey that characterises rare disease is driven in part by a knowledge gap among healthcare professionals, and the RISE findings indicate that this gap begins forming well before graduation.

Encouragingly, the appetite for learning is there. Nearly three-quarters of students surveyed, 73.8 percent, expressed interest in further rare disease education, with lectures identified as the preferred mode of delivery. Free-text responses, analysed thematically, revealed the practical constraints that students believe stand in the way: curriculum overload and the sheer impracticality of memorising detailed information about thousands of individual disorders. Students are not asking to catalogue the entire Orphanet database. They are asking for a framework, a way of thinking about rarity, undiagnosed presentations and coordinated care that can be applied whatever the specific condition in front of them.

The authors argue that the findings point toward educational approaches that combine experiential learning with structured educational support. Clinical encounters and patient narratives can motivate and humanise the subject, but they need to be anchored by explicit teaching, formative assessment and curriculum time that is protected rather than incidental. The theoretical framing of the study draws on Experience-Based Learning and Transformative Learning Theory, both of which hold that meaningful clinical experiences must be processed and integrated through guided reflection and formal instruction if they are to produce durable, applicable knowledge. In other words, a memorable patient story is a beginning, not a curriculum.

The implications extend beyond the medical schools surveyed. The UK’s Rare Diseases Framework, and similar strategies internationally, have committed to faster diagnosis, better coordination of care and increased awareness among health professionals. Those commitments ultimately depend on the baseline training of the workforce. If a substantial proportion of graduating doctors do not feel prepared even to consider a rare diagnosis, then every downstream service, from specialist centres to genomic medicine alliances, inherits a population of clinicians who may not refer appropriately or early. The RISE study, funded by Medics for Rare Disease, provides a quantitative baseline against which curriculum reform can be measured, and its authors suggest that even modest, well-designed additions to undergraduate teaching, aligned with the knowledge and skills students themselves want, could meaningfully shorten the diagnostic journey for the estimated one in seventeen people whose lives are touched by a rare condition. The message from students themselves is unambiguous: they want this education, and the system that trains them now has the evidence to deliver it.

Subject of Research: Medical students' knowledge, experience and education regarding rare disease in the United Kingdom

Article Title: The Rare dISease Evaluation (RISE) study: a survey-based investigation of medical student experience and knowledge of rare disease in the UK

Article References: Maginnis, H., Oliwa, A., Classen, M., Adams, A., Alani, Z., Brooksbank, L., Mercer, C., Nikookam, Y., Pearson, M., Saw, A. M., Steele, A., McKay, L., & Cole, D. (2026). The Rare dISease Evaluation (RISE) study: a survey-based investigation of medical student experience and knowledge of rare disease in the UK. BMC Medical Education. https://doi.org/10.1186/s12909-026-10338-z

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10338-z

Keywords: rare disease, medical education, medical students, RISE study, undergraduate curriculum, UK medical schools, survey research, diagnostic odyssey, Medics for Rare Disease, health professional training, patient preparedness, curriculum reform