Work

Evaluating a Guided Personalised Learning Model in Undergraduate Engineering Education: A Data-Driven Approach to Student-Centred Pedagogy

Year: 2025

Type: article

Abstract: This study investigates the implementation and impact of the Guided Personalised Learning (GPL) model, a structured pedagogical framework designed to operationalise personalised and student-centred learning in STEM higher education. The GPL model integrates three interconnected components: a three-dimensional knowledge and skill grid, Interactive Learning Progress Assessments (ILPA), and an adaptive learning resource pool. These components were embedded into two undergraduate engineering modules, Network Engineering and Software Engineering, at a UK university. A mixed-method evaluation, centred on student attainment data across two academic years, revealed statistically significant improvements among students who engaged with GPL, particularly those who completed ILPA activities. Participation was associated with higher mean grades, increased proportions of high achievers, and reduced failure rates. These findings demonstrate the GPL model’s effectiveness in supporting learner autonomy, formative assessment, and targeted feedback, while offering a scalable strategy for integrating personalised learning into mainstream STEM curricula.

Source: Education Sciences

DOI: 10.3390/educsci15070925

Authors: Yue Chen, Ling Ma, Pireh Pirzada, Kok Keong Chai

Institution: Queen Mary University of London

Language: English

Topic: Engineering Education and Curriculum Development

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,172