Shermain completed her Bachelor of Science in Psychology at the University of Wollongong, Australia, and her Master of Science in Psychology: Learning Sciences at the Ludwig-Maximilians-Universität of Munich, Germany. As part of her Master thesis, Shermain compared between traditional statistical methods and machine learning methods to predict students' science performance using a large-scale educational assessment data. Currently, as a Research Associate with CRADLE@NTU, she is involved in a project investigating the use of microlearning with the workforce of Singapore.
Shermain is a strong advocate for Open Science; adopting openness and transparency in one’s research practices increases the informational value and impact of research, as the data can be reanalysed and synthesised in future studies. Furthermore, they increase the credibility of the results, as independent verification of the findings is possible. For this reason, she has signed the Commitment to Research Transparency.
Shermain’s research interests centre around student learning and development. She is interested in understanding how students can be equipped with 21st century skills to successfully navigate the modern world. Revolving around this goal, her main topics of interest include:
• Learning Sciences: Scientific reasoning and argumentation, critical thinking capacity, collaborative learning, and instructional design.
• Interdisciplinary Research: Use of machine learning methods to develop predictive models for use in education and learning.
• Research Methodologies: Meta-analytic approach and SEM.
Ongoing research projects in CRADLE@NTU
Orchestration of Microlearning to Support Singapore’s Workforce in their Lifelong Learning Journey: Learner, Design and Performance