Abstract:

Enquiry based learning (EBL) offers a powerful pedagogical approach for fostering curiosity, independence, and creative problem solving in postgraduate engineering education. This paper presents the design and delivery of a Masters level robotics unit that integrates EBL to support a highly diverse student cohort engaging with machine learning methods central to modern robotics.

Students entering the programme bring varying disciplinary foundations: while some have strong mathematical and computational backgrounds, others transition from science domains such as biology, where exposure to formal modelling or algorithmic thinking may be limited. The unit replaces more traditional prescriptive assessment guidelines with an open enquiry assessment structure. Students are provided with two datasets and a reinforcement learning environment, but the challenge itself is deliberately underspecified. Learners must use these provided materials to independently define tasks of interest, design and implement suitable methods to achieve these tasks, and discuss and evaluate their findings. Student attainment is then assessed based on the quality of their enquiry-led approach as opposed to purely technical ability. Shifting the emphasis this way enables all learners, regardless of prior experiences, to demonstrate creativity, independent problem-solving and the ability to make critical judgements.

Early reflections suggest that this approach encourages deeper engagement with machine learning concepts, supports inclusive learning trajectories, and better mirrors the exploratory and open-ended nature of robotics research required in their capstone dissertation projects. However, the lack of clear structure in the assessment can cause student, leading to frustration and disengagement.

Keywords:

Enquiry based learning, curriculum design, Robotics.