Staying Relevant - The Evident Crisis in the Current Education System

The question arises: Is this enough? As the dominance of traditional education diminishes and learning happens outside formal environments, the debate about the right approach continues.

Countries such as China, the USA, India, the UK, and Japan are integrating AI education into schools, making it mandatory from an early age—only time will tell whether the initiative succeeds. Universities worldwide are also including it in their compulsory curriculum. Survey data by the Digital Education Council 2024 India- indicates that 86% of students in India have already adopted AI. This makes the government's move a welcome step. However, the lack of teachers or skilled AI learners to advance the process remains a significant challenge.

The report below aims to analyze the transitions in the higher education system, extending beyond traditional essay, report, thesis, dissertation, and article writing. The education sector is aiming to respond to AI misuse and tackle the challenge of evaluating college and university assignments. They are attempting to implement methods to assess originality that use primary research, verbal or credible defenses, real-time analysis, practical evidence, and supervised system logs to monitor students' actual work. 

With a huge surge in readership of unschooling articles and insights from notable writers like the late J. Holt, Peter Gray, and A. Rajkeins, who promote curiosity-based learning rather than a static timetable, this is a clear indication of the trend for an appetite for updates on unschooling and dropping out from the traditional methods (data from U.S. Department of Education, 2014-2024).

The positive aspect is that institutions are working to align the syllabus with current workplace demands. For example, firms such as Academic Mantra, Value Assignment Help, Job Suraksha and tech giants like ZOHO, IBM, Microsoft, Google, Amazon, and a few others are developing their own training modules to prepare the workforce for future projects.

Our experts do not advocate for abolishing the traditional school system. However, it is clear that a new approach is needed—one that enables humanity to coexist with AI. We all share the responsibility of safeguarding the future, yet our prospects seem to darken as AI usage increases. The declining IQ scores among Gen Z ( as per a recent report from The Times of India) should serve as a warning sign to us. The education sector must look beyond mere business interests, as the current system is gradually becoming obsolete.

The current research focuses on one of the systems described above for evaluating essays, theses, dissertations, articles, and reports.

The Crux: The primary research paradox no one is talking about

Primary Research Is Rising in Universities — and AI Is the Beneficiary

To beat AI dependency, universities are pushing students to do more primary research. But, knowingly or unknowingly, they are feeding the AI they’re trying to fight.

When we talk about AI intervention in education, the primary focus seems to be on one thing—preventing students from using AI. Mandatory Turnitin checks, academic integrity policies, AI content reports, and plagiarism detectors, institutional energy has been directed almost entirely at policing the output.

With the advent of AI, an entire category of academic assignments, including literature review, research summary, finding arguments from sources, and citing the sources, has become absolutely obsolete as a measure of a student’s capability. An AI tool can summarize forty articles in 10 seconds, identify contradictions across disciplines, and produce a referenced overview cleaner than most postgraduate students could manage in a week.

Across undergraduate, postgraduate, and doctoral programs, institutions have begun placing genuine weight on research participation, not just the research description. The literature review, as a standalone demonstration of research competence, is effectively reduced.

The expectation has shifted from interpreting existing knowledge to producing new knowledge:

Conventionally, most of the students acted as research interpreters, summarizing the existing knowledge through published literature and adding their viewpoints. This work can now be offloaded to AI tools, which can do it more efficiently. So why include it as an evaluation process at all?

The expectation is that students produce knowledge through primary research and create their own input data from accumulated raw data. Now, university professors place greater emphasis on primary research, including designing surveys, conducting interviews, gathering field responses, observing behaviors, and producing measurable evidence of their own. A survey conducted in the local market to study the consumer behavior is considered far more informative and valuable than summarizing the consumer behavior from pre-published articles. These kinds of projects are hyperlocal, imperfect, and entirely uneditable by an AI tool since they depend on a specific person in a specific place at a specific time. The specificity is increasingly the whole point. We at Value Assignment help by guiding our students on how to adopt genuine methods for data sourcing and use a credible targeted audience for maximum input towards their research.

Some Samples of our help for reference are added below :

The reading literature still matters, but it is no longer sufficient on its own and must be supported by primary research, since this is the only domain where human judgement and effort remain genuinely irreplaceable.

Rise in primary research observed across 14 different nations:

Value assignment help has seen a gradual increase in the number of students asking for primary research assistance through 2025 and into 2026. Since value assignment help is present across fourteen different nations, the thesis, dissertation, and research paper writing queries coming from the majority of these countries now include primary research component, a pattern that did not exist at this scale two years ago. While the search volume for the keyword “primary research” has decreased over the years, as depicted in the images appended below, the actual requirement of primary research in colleges has spiked.

Dr Abhijeet Rajkeins, editor-in-chief at Value Assignment Help, explains this counterintuitive data point in keyword research and actual spike. According to him, physical involvement in your research data becomes more important than online research, which explains why the search volume for research queries has decreased even when actual emphasis on primary research is increasing, not because fewer students are conducting it, but because it is now being assigned directly, without students needing to search.

What universities are asking for, practically speaking, is not dramatically different from what good research has always required.

What distinguishes a researcher now is the thing that can’t be prompted- going out in the sun, conducting the survey, gathering original data, sitting with the uncertainty of an open-ended query and producing something original.

The prime focus also shifts from theoretical knowledge to practical learning, as indicated by Delloitte’s 2025 higher education trends report. The report outlines that universities are shifting from theory-centric instruction towards competency-based, experimental, and workforce-aligned curriculum and assignments. However, there has been a notable contradictory trend as well. Universities have been notably, and in many cases, deliberately, slow to embrace AI tools with in their walls. A 2025 study conducted in the USA found that over 35% of the teachers opted out of embracing AI entirely, over future fears and job risks. In early 2026, more than 1000 teachers also signed an open letter to stop AI adoption in education, arguing that there is more value in rediscovering why human intelligence matters more than in accelerating its displacement. However, majority of LLMs are open-sourced, and their adoption in schools and colleges can’t be limited. More than 92% students are already using AI in some form, up from 66% in 2024. The methods adopted to gatekeep generative AI and what students are already doing is not an oversight. Institutions sense that something is at stake, but they have not yet fully articulated what they are actually protecting and why. 

A thought to ponder: Are teachers unknowingly feeding the system that might replace them?

Universities are trying to assert human irreplaceability. But in doing so, they may be unintentionally training the students to produce the one category of data AI needs most, and cannot generate itself. Currently, AI systems hallucinate because they lack real, grounded, human-gathered data, which produces false results. Universities respond by pushing students to collect primary data through surveys, interviews, observations, forms to produce “proof of work” for students. This data, when published in theses, dissertations, and research papers, enters the public domain, and AI systems use this data to make themselves better. This means that proof of work universities are demanding may be unintentionally the very fuel that makes the next generation of AI tools less dependent on hallucination and maybe even replace humans.

In barely three and a half years since AI entered the mainstream, institutions around the world have been scrambling to draw a clear line between human intelligence (output) and artificial intelligence (artificially generated output). But, the irony is that every method they devise to do so produces exactly the kind of grounded, human-gathered data that AI needs to erase that line entirely.

Education is no longer bound to conditions. It’s in abundance and accessible to all. So why try to keep it chained? We need to grow beyond small, mediocre changes, as we are not competing with an individual but with an industry in itself .

All our work and action should be driven by one objective: ‘We should make our students compete with AI, not be consumed by it’. Only then will there be a meaningful contribution to the generation waiting for us to make the right decision. We don’t have time and that time has already passed — it’s now or never.