Agentic AI for Research, University Studies, and Professional Profile Development

Timetable

Weekly, online 

Module aim (aims)

The aim of this module is to introduce students to the practical, critical, and responsible use of AI in academic and professional contexts. The course focuses on how students can use agentic and automated AI systems to support university study, research, academic communication, and the development of their personal professional profiles.

 The module is designed to move beyond simple prompting and help students understand AI as a structured cognitive and organizational partner. Students will learn how to use AI to generate research questions, organize and evaluate sources, support reading and note-taking, improve academic writing, manage study workflows, prepare presentations, and develop professional materials such as biographies, CVs, and motivation statements.

 The module also aims to strengthen students’ awareness of academic integrity, human judgment, and ethical responsibility in increasingly automated academic environments. By the end of the course, students should be able to use AI in a strategic, reflective, and disciplined way that strengthens rather than weakens their intellectual independence.

 

Pre-requisites in terms of knowledge, skills and social competences (where relevant)

Students should have:

• a sufficient level of English to participate in class discussion, read academic and semi-academic texts, and complete written assignments in English
• basic digital literacy, including the ability to use online platforms, word processing tools, and standard university learning technologies
• a general familiarity with university study practices such as reading, note-taking, discussion, short writing tasks, and presentations

No advanced technical background is required. Students are not expected to have specialist knowledge of AI, coding, or automation before the course begins.

Syllabus

Week 1. Introduction to Agentic AI in University Life

Overview of the course. Introduction to agentic AI, automation, and AI-supported academic workflows. Difference between basic prompting and more structured AI-supported systems. Discussion of how AI may support studying, research, and professional growth.

 

Week 2. AI Literacy, Reliability, and Academic Integrity 

Strengths and weaknesses of AI systems. Hallucination, bias, verification, transparency, authorship, and ethical use. Discussion of acceptable and unacceptable uses of AI in academic settings.

 

Week 3. AI and Research Question Development

Using AI to move from a broad topic to a focused research question. Generating angles, narrowing scope, identifying promising lines of inquiry, and refining academic purpose.

 

Week 4. Source Discovery and Literature Mapping

Using AI to identify relevant types of sources, organize themes, distinguish between source discovery and source evaluation, and begin constructing a literature map.

 

Week 5. AI for Reading, Summarizing, and Note-Taking

 AI-supported approaches to reading academic texts. Comparing shallow and strong summaries. Building effective notes and using AI to support comprehension without replacing active reading.

 

Week 6. From Information to Argument

Using AI to support the transition from gathered information to clear argument. Building claims, support, structure, and basic counterargument awareness.

 

Week 7. AI for Academic Writing and Revision

Using AI to improve clarity, coherence, paragraph structure, tone, and revision strategy. Maintaining personal voice while benefiting from AI-supported feedback and redrafting.

 

Week 8. Mid-Course Integration: Designing a Research Workflow

Students integrate the first half of the course into a structured personal workflow for academic research, from question formation through reading, organization, and writing support.

 

Week 9. Automation for Study Management and Academic Productivity

AI-supported planning, scheduling, prioritization, reminders, and workflow design. Identifying repetitive academic tasks suitable for automation and distinguishing between productive and unproductive automation.

 

Week 10. Agentic AI for Collaboration and Group Projects

Using AI to support teamwork, project planning, meeting preparation, note organization, and follow-up communication. Maintaining accountability, leadership, and clarity in group contexts.

 

Week 11. AI for Presentation and Knowledge Communication

Using AI to prepare presentations, explain complex ideas more clearly, adapt information for different audiences, and create effective structures for oral and visual communication.

 

Week 12. Professional Identity and Academic Self-Presentation 

Using AI to identify strengths, clarify interests, and improve academic and professional self-presentation. Drafting short bios, profile summaries, and academic self-descriptions.

 

Week 13. CVs, Motivation Statements, and Professional Positioning

Using AI to improve CVs, application materials, scholarship statements, and motivation letters. Focus on specificity, credibility, and professional self-articulation.

 

Week 14. Building a Personal AI System for Academic and Career Development

Students design a coherent personal system that connects research, study management, writing, communication, and professional development into one structured approach.

 

Week 15. Final Presentations and Reflective Evaluation

Student presentations of final projects. Reflection on effective, ethical, and sustainable AI use in university life and beyond.

 

Reading list

Core readings

• Bearman, M., Ryan, J., and Ajjawi, R. (2023). Discourses of artificial intelligence in higher education: A critical literature review.
• Mollick, E. (2024). Co-Intelligence: Living and Working with AI. New York: Portfolio.
• Kasneci, E. et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences.
• Cotton, D. R. E., Cotton, P. A., and Shipway, J. R. (2024). Chatting and cheating? Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International.
• Luckin, R. (2018). Machine Learning and Human Intelligence: The Future of Education for the 21st Century. London: UCL Institute of Education Press.

 

Research, writing, and study skills

• Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., and FitzGerald, W. T. (2016). The Craft of Research. 4th ed. Chicago: University of Chicago Press.
• Graff, G., and Birkenstein, C. (2021). They Say / I Say: The Moves That Matter in Academic Writing. 5th ed. New York: W. W. Norton.
• Murray, R. (2017). Writing in Social Spaces: A Social Processes Approach to Academic Writing. London: Routledge.

 

Professional development and profile building

• Ibarra, H. (2015). Act Like a Leader, Think Like a Leader. Boston: Harvard Business Review Press.
• Cottrell, S. (2019). The Study Skills Handbook. 5th ed. London: Red Globe Press.