Report on the Role of Artificial Intelligence in Higher Education and Its Relation to Sustainable Development Goals

Introduction

The integration of artificial intelligence (AI) in higher education has sparked significant debate, particularly concerning academic integrity and the evolving nature of student learning. This report examines the current landscape of AI usage among university students, emphasizing the implications for Sustainable Development Goals (SDGs), notably Quality Education (SDG 4) and Reduced Inequalities (SDG 10).

Contextual Background

1. Impact of COVID-19 on Education Systems
   • School closures and lockdowns beginning in March 2020 disrupted traditional education pathways.
   • Cancellation of GCSEs and A-levels led to teacher-assessed grades, disproportionately benefiting well-performing private schools, highlighting inequality issues (SDG 10).
   • Universities adopted open-book, online assessments to accommodate remote learning, with 70% still utilizing online exams five years later.
2. Transition and Uncertainty in Assessment Methods
   • Variability in exam formats between and within universities created uncertainty for students.
   • Delayed communication regarding exam formats further complicated student preparedness.

AI Adoption in Higher Education

AI tools such as ChatGPT have become prevalent among students, not solely for cheating but also as aids in research and essay structuring. The adoption of AI reflects broader systemic challenges:

• Convenience and Efficiency: AI serves as a time-saving resource for students balancing academic and financial pressures (SDG 1 – No Poverty).
• Response to Educational Disruptions: The inconsistent assessment landscape post-COVID-19 has increased reliance on AI.
• Environmental Considerations: Concerns exist regarding the energy consumption of AI data centers, linking to Responsible Consumption and Production (SDG 12) and Climate Action (SDG 13).

Challenges and Recommendations

1. Addressing Academic Integrity
   • Universities must establish clear policies on AI usage, defining “proportionate” application in coursework and exams.
   • Consistent exam formats should be implemented to reduce uncertainty and discourage misuse of AI.
2. Supporting Student Well-being and Equity
   • Financial support systems should be enhanced to alleviate student debt burdens and allow more time for academic engagement (SDG 1 and SDG 4).
   • Efforts to reduce inequalities in educational access and outcomes must continue, especially for disadvantaged groups (SDG 10).
3. Promoting Sustainable AI Practices
   • Encourage development and use of energy-efficient AI technologies to minimize environmental impact.
   • Integrate sustainability education within curricula to raise awareness of AI’s ecological footprint (SDG 12 and SDG 13).

Conclusion

The evolving role of AI in higher education is intertwined with broader challenges in educational equity, assessment integrity, and sustainability. Addressing these issues aligns with multiple Sustainable Development Goals, particularly Quality Education (SDG 4), Reduced Inequalities (SDG 10), and Climate Action (SDG 13). Universities and policymakers must collaborate to create adaptive, fair, and sustainable educational environments that reflect the changing realities of student experiences and technological advancements.

Author

• Elsie McDowell, student and 2023 winner of the Hugo Young award (16-18 age category)

1. Sustainable Development Goals (SDGs) Addressed or Connected

1. SDG 4: Quality Education

   • The article discusses challenges in education caused by COVID-19 disruptions, exam cancellations, and the transition to online assessments.
   • Issues of equitable access to education and the impact of AI on learning and assessment are highlighted.

2. SDG 9: Industry, Innovation and Infrastructure

   • The role of artificial intelligence (AI) and large language models (LLMs) in education is a key focus.
   • Concerns about the environmental impact of powering AI data centers are mentioned.

3. SDG 10: Reduced Inequalities

   • The article addresses disparities in education outcomes linked to socioeconomic background, such as the advantage of private schools and the burden of student debt on poorer students.

4. SDG 12: Responsible Consumption and Production

   • Reference to the large amounts of water and energy used to power AI data centers relates to sustainable resource use.

2. Specific Targets Under Those SDGs

1. SDG 4: Quality Education

   • Target 4.3: Ensure equal access for all women and men to affordable and quality technical, vocational and tertiary education, including university.
   • Target 4.7: Ensure that all learners acquire the knowledge and skills needed to promote sustainable development, including education for sustainable lifestyles and human rights.

2. SDG 9: Industry, Innovation and Infrastructure

   • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors, including promoting sustainable and environmentally sound technologies.

3. SDG 10: Reduced Inequalities

   • Target 10.2: Empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other status.

4. SDG 12: Responsible Consumption and Production

   • Target 12.2: Achieve the sustainable management and efficient use of natural resources.

3. Indicators Mentioned or Implied to Measure Progress

1. SDG 4 Indicators

   • Proportion of students achieving proficiency in assessments (implied by discussion of exam cancellations, grade inflation, and assessment formats).
   • Participation rate in tertiary education (implied by references to university attendance and assessment methods).
   • Equity indicators such as differences in outcomes between private and public school students.

2. SDG 9 Indicators

   • Energy consumption of data centers (implied by concerns about water and energy use for AI infrastructure).
   • Adoption rates of AI and digital technologies in education.

3. SDG 10 Indicators

   • Student debt levels by socioeconomic background (explicitly mentioned in the article).
   • Employment rates among students (68% with part-time jobs noted).

4. SDG 12 Indicators

   • Water and energy use efficiency in AI data centers (implied).

4. Table: SDGs, Targets and Indicators

Source: theguardian.com