The Optentia Research Unit, North-West University, in collaboration with the Research Support Department, North-West University, and the Norwegian Institute of Technology, invite you to a two-day workshop titled Teaching with Research, exploring ways to strengthen teaching through research-informed practices.
This two-day workshop brings together university lecturers to examine how research is taught—and how teaching practice in this area can be strengthened. While grounded in research content, the focus is on pedagogy: how to design learning experiences that help students engage critically and practically with research. Hosted at Monate Game Lodge, the event offers space to share teaching approaches, test new ideas, and connect with colleagues working toward better methods education.
The workshop will produce practical outputs, including teaching resources and ideas for integrating new approaches into curricula, which can be shared across institutions. By centering pedagogy in the teaching of research, the event aims to improve student learning outcomes and, ultimately, the quality of research emerging from South African higher education.
Why Join
Who Should Attend
Workshop Details
Dates: 24–25 November 2025
Venue: Monate Game Lodge
Duration: Two days (in-person)
Facilitators: Optentia Research Unit, North-West University, the Research Support Department, North-West University, and the Norwegian Institute of Technology
Registration: https://forms.cloud.microsoft/r/MsRg4Wp33t?origin=lprLink
Contact
RSVP by: 30 October 2025, 12:00
Enquiries:
Ms Lynn Booysen
NWU Optentia Research Unit
email: lynn.booysen@nwu.ac.za
website: www.optentia.co.za
Workshop Programme
09:00 – Opening and Welcome (Prof. Ian Rothmann)
09:15 – Session 1: AI as a Research and Teaching Tool (Prof. Leon De Beer)
This session examines how AI can support both research and pedagogy. Participants will explore how to guide students in using AI tools for literature synthesis, conceptual framework development, data visualisation, and scenario simulation—while maintaining critical awareness of bias, overreliance, and plagiarism. The focus is on the responsible use of AI in research, teaching, and supervision; learning strategies to help students use AI thoughtfully in research; evaluating AI outputs critically; and maintaining transparency in AI-assisted work. Educators will also experiment with AI for teaching tasks such as generating case studies, designing rubrics, and creating adaptive feedback systems.
11:15 – Refreshments
11:45 – Session 2: Building Hyper-Personalised AI Learning Systems (Prof. Llewellyn van Zyl)
Research methods can be complex for students, and personal feedback is often hard to scale. This hands-on session introduces OpenAI’s Agentic Prompt Framework—a structured approach to prompting that helps educators generate pedagogically sound outputs using AI tools like ChatGPT.
You will learn how to craft prompts that reflect your teaching philosophy, guide AI reasoning for clarity, accuracy, and context, and demonstrate how AI can explain complex research concepts such as qualitative coding or data interpretation. A live demonstration will show how vague queries can become precise, reasoning-rich teaching prompts.
13:00 – Lunch
14:00 – Session 3: Building Hyper-Personalised AI Learning Systems (Prof. Llewellyn van Zyl)
Move from prompting to creation. Using Google’s NotebookLM, participants will build a virtual research methods assistant that reflects their expertise, course materials, and feedback philosophy. Students can then adapt these assistants to support their own projects, datasets, and reflections—creating personalised learning companions that evolve over time. The focus is on scaling teaching impact and tailoring learning to each student’s research journey.
15:15 – Refreshments
15:30 – Practice and Reflection
16:15 – Relaxation / Pre-booked game drive
19:00 – Dinner
Day 2 – Teaching Research Thinking
08:00 – Recap
08:15 – Session 4: The Triple Loop – Linking Research, Practice, and Teaching in Norway (Prof. Marit Christensen and Prof. Siw Tone Innstrand)
This session examines how research, teaching, and professional practice can reinforce one another. Drawing on Norwegian higher education innovations, participants will discuss how reflective cycles between research and pedagogy can strengthen research capacity and relevance. The focus is on building reflective, interconnected models of research-led teaching.
09:15 – Session 4: Teaching for Critical Inquiry (Prof. Leoni van der Vaart)
This session explores how to integrate reasoning and evidence-based thinking across disciplines. The focus is on moving beyond skills training to embedding these habits of thought within supervision, classroom dialogue, and feedback.
10:15 – Refreshments
10:45 – Session 5: Teaching and Supervision for Critical Inquiry (Prof. Ian Rothmann)
This session continues to explore how to integrate reasoning and evidence-based thinking across disciplines. The focus is on moving beyond skills training to embedding these habits of thought within supervision, classroom dialogue, and feedback.
11:45 – Session 6: The Future of Supervision (Prof. Leon de Beer)
A conversation about how AI and digital tools are changing the supervisory role. Discuss expectations for AI-assisted work, feedback on AI-generated content, and maintaining academic integrity. Participants will consider how to balance innovation, ethics, and mentorship in guiding responsible inquiry. The focus is on cultivating critical, ethical, and inquiry-driven research practices through integrated teaching, assessment, and supervision.
12:45 – Lunch
13:30 – Session 6: Curriculum Design for the 2025+ Research Classroom
Facilitators: Prof. Ian Rothmann, Prof. Leon de Beer, Prof. Leoni van der Vaart, Prof. Llewellyn van Zyl
Work collaboratively to design future-oriented research methodology curricula that prepare students for an AI-augmented academic environment. Discussions will centre on how to integrate AI literacy, ethics, and responsible supervision into departmental or institutional practice. Topics include a) Embedding AI literacy and ethics; b) Designing fair assessment for AI-augmented work; c) Supervising responsibly in digital environments; d) Promoting replication, transparency, and methodological diversity.