New Associate Professor Explores How AI Is Changing Work and Student Learning

Samuel Kernan Freire joined the Learning Technology & Analytics research group as Associate Professor of Applied Research on 1 June. Through his new research line, AI Agility, he aims to help programmes better prepare students for the workplace. This is important because the use of AI during students' education influences their professional development, while AI is simultaneously transforming the nature of work itself. We spoke to Samuel about his background and his plans for the research line.

From Aerospace Engineering to Human-Centred AI

Halfway through his Aerospace Engineering degree, Samuel decided to switch to Industrial Design Engineering. He went on to complete a Master's in Integrated Product Design, followed by a PhD on human-centred AI in manufacturing environments.

"I think my background in both the technical and human-centred aspects of AI helps me better understand the social challenges that arise as AI becomes part of our daily work and lives."

A New Research Line: AI Agility

Samuel's new research line, AI Agility in Education, focuses on helping educational programmes respond more quickly to changes in professional practice. His plan is to gather feedback from employers about how students perform during internships and work placements, and translate those insights into practical recommendations for degree programmes.

Developments in AI are moving faster than ever. Updating a curriculum once every five years simply isn't enough anymore.

He continues: "We want to make better use of the signals students pick up during internships and practice-based projects. For example, they may discover that the way they learn software development in the classroom no longer matches professional practice, or that they need stronger critical skills when working with AI-generated output. I want to capture these kinds of experiences, both positive and negative, in a systematic way and feed them back to the programmes. That allows them to adapt their curricula, teaching methods and assessment much more quickly."

A University-Wide, Systematic Approach

For Samuel, the systematic nature of the approach is essential. Academic staff already maintain close relationships with industry partners, but valuable feedback often arrives in an ad hoc and fragmented way.

"At the moment, that information is collected informally and ends up scattered across different programmes."

A university-wide structure would also enable broader analysis.

"It would allow us to identify differences between programmes and disciplines, so that recommendations can be tailored to their specific contexts."

Design Thinking and Mixed Methods

Samuel prefers a design thinking approach and plans to use mixed research methods.

"I want to combine quantitative data with observations and in-depth interviews involving both students and workplace supervisors."

He is currently in discussions with several degree programmes and expects to pilot the methodology within the Faculty of Technology. The goal is to develop an approach that is practical and valuable for everyone involved. Existing contact moments between programmes and employers—such as graduation projects—offer ideal opportunities to gather feedback.

"My idea is to start with a preliminary study based on existing data and add a number of focused questions to the evaluation forms."

If I start now, my recommendations can still feed into the current curriculum review processes.

Samuel is eager to build something that programmes can immediately benefit from.

"The new educational vision of The Hague University of Applied Sciences places new demands on curricula. Most programmes are currently revising their curricula, so if I get started after the summer, my recommendations can still contribute to those developments."

Building on a Strong Network

Over the past two years, Samuel worked as part of The Hague University of Applied Sciences' AI & Data Science Expert Team, collaborating with colleagues from faculties, professional services and research groups. This broad experience, together with the network he has built across the university, makes him well suited for his new role.

He will continue to contribute to the Expert Team and remain involved in the RAISE-UP project within the Data Science research group, which also focuses on AI in education. He will spend two days a week working within the Learning Technology & Analytics research group.

Strengthening the Centre of Expertise

The Learning Technology & Analytics research group is part of the Centre of Expertise Global and Inclusive Learning, which focuses on educational transformation, among other themes. Samuel's research fits closely with these ambitions, including the Centre's focus on inclusion. "We may discover that not all students are equally able to work effectively with AI, or that AI amplifies existing differences in motivation. Those are important issues for us to understand."

Samuel is looking forward to working with Professor of Applied Research Theo Bakker and the rest of the team to increase the impact of their work—both within the university and in the wider academic community.

For now, his primary focus is on understanding the signals emerging from professional practice. Looking further ahead, he would also like to investigate how AI use in primary and secondary education affects students before they enter higher education. "If pupils are already using AI throughout their school years, we'll be welcoming a very different generation of first-year students."

Would you like to learn more about the research group? Visit the Learning Technology & Analytics research group webpage.

Do you have ideas or suggestions for Samuel's research line? He would love to hear from you. You can reach him at [email protected].