Aligning the Polytechnic Provision of CET with SkillsFuture: Meeting Learners' and Employers' Needs

Professor Stephen Billett (Griffith University) and Dr Anthony Leow, Republic Polytechnic

Against the backdrop of the SkillsFuture national movement to promote skills mastery and lifelong learning, the research seeks to identify and address gaps in existing educational provisions and capacities of teachers in the post-secondary education institutions (PSEIs) for employability-related continuing education and training (CET) across the Singaporean workforce. It also investigates CET educators’ viewpoints and their teaching practices by examining (i) their perspectives regarding the facilitators and barriers to CET teaching and learning, and (ii) how their professional development in the CET terrain can be realised. By investigating the CET experience from aspects of both students and CET educators in the teaching-learning partnership, the study can potentially illuminate the personal, professional and organisational dimensions of the CET experience.

Project Summary by PI here

A Blended Learning Course through Academic Practice Partnership to Enhance Workplace Clinical Teaching and Learning

Associate Professor Liaw Sok Ying, National University of Singapore

The research seeks to inform professional development of clinical nurses who are critical in facilitating nursing students’ learning at work in the clinical setting. The study will explore the experiences of clinical nurses and academic educators in supporting workplace clinical teaching and learning, and examine the effects of a blended learning course to enhance workplace clinical teaching and learning. The outcomes can therefore contribute to developing a successful partnership model of best practices between healthcare workplace and academic institutions.

Project Summary by PI here

Course Suggestion for Career Planning: Evaluating Strategies to Support Lifelong Learning. A Pilot on Using Analytics to Recommend SkillsFuture Credit Courses

Professor Robert Kamei, National University of Singapore

The aim of this study is to create a recommender system that can help Singaporeans find, select and complete CET programmes that are suited to both their personal strengths and the needs of the broader Singapore economy. It uses both recent artifical intelligence and data mining techniques as well as behavourial science to better understand how and why people pursue opportunities for lifelong learning. The pilot will test and evaluate the quality of its recommendations.

Project Summary by PI here