AI in Education: A Shortcut for Students???

Use of AI by Students. What needs to be done: and quickly

AI tools, such as advanced language models and coding assistants, have become powerful resources for university students, enabling them to complete assignments, write papers, and solve complex problems, especially in STEM fields. Recent statistics from 2025 indicate that 68% of teachers now rely on AI detection tools to combat academic dishonesty, with student discipline rates for AI-related plagiarism rising from 48% in 2022-23 to 64% in 2024-24 (Source: AI Plagiarism Statistics 2025). However, the use of AI raises significant challenges for educational institutions, particularly in classifying AI-generated papers as plagiarism, given the difficulty in distinguishing them from human work. In developing countries, these challenges are amplified by limited access to technology, uneven digital infrastructure, and the need for faculty training. Universities need to quickly adapt and make best use of the power that AI offers.

Completing assignments without understanding the underlying concepts

AI tools offer significant benefits for students assistance with complex problem-solving, and efficiency in completing assignments. In STEM fields, AI can assist with data analysis, simulations, coding and writing academic style papers. However, over-reliance on AI risks undermining critical thinking, understanding deeper concepts behind each subject, originality, and skill development, which are core essence of education.

AI as Learning Platform

For students in developing countries, AI can bridge gaps in access to quality resources, offering affordable tutoring and research support. A 2024 study on AI in education noted an 80% accuracy rate for AI programs providing recommendations to students, particularly in self-paced digital learning, based on data from 1,170 Ugandan students (Source: AI in Education Statistics)

Challenges with Academic Integrity

It is very difficult to detect AI-generated content, as it often mimics human writing styles. Traditional plagiarism detection tools like Turnitin may struggle to identify AI-generated text, with recent articles highlighting the limitations of AI-detection tools and the need for new assessment strategies (Source: EDUCAUSE Review - Academic Integrity in the Age of AI). This issue is particularly acute in developing countries e.g. Pakistan, Uganda etc where limited faculty training and outdated assessment methods exacerbate the challenge. Cultural attitudes toward academic integrity may also vary, with some students viewing AI use as a shortcut rather than a learning tool, as noted in a 2023 systematic review on AI and academic integrity (Source: ScienceDirect - Reassessing Academic Integrity in the Age of AI).

Socioeconomic and Infrastructure Barriers

Unequal access to technology creates disparities in AI adoption, favoring urban or affluent students. Many universities lack the resources to invest in AI infrastructure or train faculty, with a 2019 systematic review noting the lack of educational perspectives in AI research (Source: International Journal of Educational Technology in Higher Education). However, opportunities exist to leverage affordable AI tools, such as open-source platforms, to democratize education. Recent UNESCO guidance emphasizes AI’s role in addressing inequalities in access to knowledge, particularly in developing countries (Source: UNESCO - Artificial Intelligence in Education).

Future Implications

AI tools are expected to become more sophisticated, potentially automating entire workflows in STEM and other fields. A 2025 study on generative AI in higher education highlights the need for universities to prepare a future generation of AI-literate students, with policies focusing on academic integrity and equity (Source: ScienceDirect - Generative AI in Higher Education). Without adaptation, universities risk producing graduates who lack critical skills, as employers increasingly value AI-augmented problem-solving. In developing countries, failure to integrate AI could widen the global education gap, leaving students less competitive in a tech-driven job market.

How to Transform

Universities can leverage AI as a collaborative tool, focusing on skills like critical thinking, ethical AI use, and creativity (Source: UNESCO - AI Competency Frameworks). Transformation strategy is divided into short-term (2-3 years) and long-term (5-10 years), with a focus on developing countries;

Short-Term Recommendations (2-3 Years)

Develop Clear AI Policies. Establish policies on AI use, specifying what is allowed and what constitutes plagiarism, communicated through syllabi and workshops. Collaborate with regulatory bodies like HEC for standardized national guidelines.

Integrate AI in assignments / papers. Clearly indicate what tasks are acceptable through AI and what concepts students are expected to learn / understand Redesign assignments, academic papers

Invest in AI Detection Tools. Acquire AI-specific tools to identify AI-generated content and train faculty on their use.Explore free or open-source tools for cost-effectiveness.

Educate Students on AI Ethics. Integrate modules on AI ethics and academic integrity into curricula, using local languages. Ensure accessibility for all students through local workshops.

Enhance Faculty Training. Train faculty on designing AI-resistant assignments and integrating AI into teaching, using online platforms like Coursera. Leverage existing university infrastructure for training.

Improve Infrastructure. Invest in internet connectivity and AI tools in university labs, partnering with governments and NGOs for funding. Use digital programs and promote mobile-based AI tools.

Promote Affordable AI Tools Encourage use of free or low-cost AI tools, developing mobile-based solutions for accessibility. Focus on tools that support local languages and needs.

Long-Term Recommendations (5-10 Years)

Curriculum Redesign. Redesign curricula to incorporate AI, emphasizing understanding the concepts, critical thinking and creativity. Ensure relevance to local challenges like manufacturing, agriculture and healthcare.

Research and Development. Establish AI research centers, collaborating with tech companies for tailored educational tools. Use govt funding and international grants for local research.

Policy Frameworks. Develop national or regional AI education frameworks, involving stakeholders from government and industry. Advocate for a national AI education strategy.

International Collaboration. Foster partnerships with global universities and participate in international AI education forums. Seek funding and support from UNESCO and other organizations.

Equity and Access. Work towards closing the digital divide, developing open-source AI tools for affordability. Expand rural infrastructure through government and international aid.

Continuous Assessment and Adaptation. Regularly review and update AI policies based on feedback, using AI data to inform strategies. Involve local communities and parents to build trust and understanding.

Conclusion

AI’s integration into education is inevitable, and universities in developing countries like Pakistan must adapt to harness its potential while addressing plagiarism and ensuring knowledge development by students. Short-term actions should focus on policy development, faculty training, and infrastructure improvements, while long-term strategies should aim for curriculum reform, research, and equitable access. By embracing AI as a collaborative tool and prioritizing critical thinking, universities can prepare students for an AI-driven future while maintaining academic integrity. The recommendations are in no way conclusive. This write up is aimed at generating a discussion on this important topic and all suggestions are as good as mine!!