Doctoral Supervision in the Age of AI: 1-Day Hands-On Training for Supervisors – Malta 2026

Maintaining academic judgement, research quality, and integrity in AI-mediated research environments

Hands-On Training: Doctoral Supervision in the Age of AI

Maintain academic judgement, research quality, and integrity in an AI-mediated research environment.

How does AI affect doctoral supervision?

“Doctoral education remains shaped by an intergenerational inheritance of academic practices that has evolved only marginally over recent decades. The rise of AI has made the need for change more urgent, more visible, and increasingly costly to ignore.”

Dr. Jim Wagstaff, Strategic Briefing Document: GSBM Malta Residency (May 2026). Advance copy; publication forthcoming.

Dr Jim Wagstaff, an AI entrepreneur who completed his doctorate in 2021, is now preparing to supervise doctoral candidates.

Aware of the “I supervise as I was supervised” bias embedded in doctoral education, he challenges us to rethink how supervision is approached.

What makes this training different is precisely that starting point.

Rather than asking how do we stop candidates using AI?, this workshop asks the harder question:

What is supervision actually for, and what does it require of us that no tool can replace?

Offered in Two Ways:
• As an individual stand-alone one-day training on 8 May 2026

• As part of the in-person Doctoral Faculty Residency in Malta (May 8–11, 2026)

Overview

This 1-day hands-on training for doctoral supervisors takes place on 8 May 2026 in Malta. Led by Dr. Jim Wagstaff, it covers AI integration in doctoral research, supervision integrity, and academic quality. Standard fee: €490 (Early Bird €290 until 15th April 2026). No technical AI expertise required.

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The training addresses one of the most significant transformations currently shaping doctoral education: the integration of Artificial Intelligence into doctoral research and supervision.

AI tools are already embedded in how doctoral candidates explore literature, collect and analyse data, and develop written work.

The key question is not whether AI will be used, but how supervisors maintain academic judgement, research quality, and integrity in an AI-mediated research environment.

This training is practical, applied, and supervisor-centred. It focuses on what supervisors must actually do when AI becomes part of the doctoral research process.

This intensive training is designed with flexibility in mind. You can join us for:

The Standalone 1-Day Training (8 May), or
The Full Residency (8–11 May)

Who is this training for?

This training is ideal for:

Doctoral supervisors and faculty involved in doctoral education
Experienced doctoral practitioners transitioning into academia or supervision
Doctoral candidates that want to better understand how AI is transforming doctoral research practice

This 1-Day training on 8 May is ideal for individuals seeking a targeted update on AI.

Those looking for a comprehensive professional development experience are encouraged to consider attending the Full Residency from 8 to 11 May.

No advanced technical AI expertise is required.

Learning Outcomes

Participants will:

Understand how AI is transforming doctoral research practice
Strengthen their ability to supervise AI-supported research responsibly
Develop practical strategies to safeguard research quality and integrity
Gain confidence addressing authorship, data, and methodological risks
Translate AI from uncertainty into a supervised research tool

Why this AI training matters?

AI creates significant challenges for doctoral supervision, particularly around academic integrity, as widespread student use (often exceeding 70%) blurs the line between support and over-reliance. Supervisors must also address research quality risks, since AI can generate plausible but inaccurate or fabricated content. In addition, policy gaps persist: although many institutions are developing guidance, consistency is lacking, requiring supervisors to interpret evolving frameworks such as those from UNESCO and the Quality Assurance Agency for Higher Education. Ultimately, AI complicates the supervisory relationship by challenging how independence, originality, and critical thinking are developed in doctoral research.

Training Agenda

Training Agenda	Friday, 8 May 2026
09:00–09:15	Calibration: Where Are We Starting From?
09:15-9:30	Applied Lab I AI Across the Research Lifecycle
10:45–11:00	Break
11:00–12:00	Applied Lab II: AI, Mixed Methods, and the Integration Problem
12:00–12:30	Supervisor Reflection \| When to Say: “Read the F***ing Papers”
12:30–13:30	Lunch
13:30–14:15	Data Clinic \| Ethics, Integrity, and Real-World Data Problems
14:15–15:00	Writing & Integrity Lab \| AI-Supported Writing Without Academic Fraud
15:00–15:15	Break
15:15–16:30	Synthesis Workshop \| What Supervision Must Now Enforce
16:30–17:30	Presentation of Findings \| From Working Groups to Shared Perspective
17:30–18:00	Closing \| Commitments: What Will You Do Differently?

The host - Dr. Jim Wagstaff

Dr. Jim Wagstaff

Dr. James (Jim) Wagstaff is a DoctorateHub GSBM Faculty member who began his career in the technology sector 35 years ago. Jim has been an educator and entrepreneur in Singapore for the last 14 years of his career. He co-founded Noodle Factory, an AI-powered teaching and learning platform, and Jam Factory, a management consulting and education services business. His career spans various executive roles in technology companies like Dell Technologies, Brocade Communications, and Hewlett Packard Enterprise. Jim's expertise lies in digital pedagogy, focusing on the application of AI in teaching and learning. He is dedicated to advancing educational technology and improving learning outcomes through his research and practical applications.
Jim teaches a continuing professional development course at Singapore Management University designed for educators who wish to apply innovative technologies in teaching and learning.
Dr. Wagstaff holds a doctorate and master’s degree from the University of Liverpool in the UK, a post-doctoral Diploma in Academic Practice, and several other certifications from other institutions. He is the author of the Generative AI Field Guide for Educators, which explores AI's transformative potential in education.

Training Highlights

DURATION

1 Day

Mode of participation: Standalone or Residency Integrated.

DATE

Friday 8 May 2026

The full Doctoral Faculty Residency is running from Friday 8 to Monday 11 May 2026

Learn more about the full residency

FEES

Standard fee: 490€ | Early Bird rate: 290€ (until 30 April 2026)

The following discounts apply: ● 70% discount for Young Doctoral Researcher. ● 40% discount for Doctoral Faculty Development Programme members ● Free for DoctorateHub GSBM Faculty as part of the Continuous Professional Development allowance.

STRUCTURE

The training combines Masterclass sessions, Applied supervisory labs, Case-based discussion, and Structured reflection.

All sessions are practice-oriented and grounded in real doctoral supervision contexts.

LOCATION

Malta - in person

Malta Life Sciences Park San Gwann, SGN 3000 Malta

MINIMUM REQUIREMENTS

The training is designed for individuals engaged in doctoral-level research and doctoral education.

No advanced technical AI expertise is required.

FAQs About the Doctoral Supervision and AI training

What are the admission requirements

The training is designed for individuals engaged in doctoral-level research and doctoral education.

What are the training fees?

The standard fees for the training are 490€. The Early Bird rate is 290€ (until 30 April 2026).

Do I need to be a member of the Doctoral Faculty Development programme to attend this training?

No. However, members of the Doctoral Development Programme will be admitted first.

Are there any discounts available?

Yes. The following discounts apply:

● 70% discount for Young Doctoral Researcher.
● 40% discount for Doctoral Faculty Development Programme members.
● Free for DoctorateHub GSBM Faculty as part of the Continuous Professional Development allowance.

Note: Discounts can not be combined with the Early Bird rate.

Want to get Ready for Doctoral Supervision in the Age of AI?