
Research Fellow
3 days ago
For more details, please view Interdisciplinary Collaborative Core (ICC) | NTU Singapore
We are looking for a Research Fellow. The main responsibilities of this role involve the management of large datasets (in the excess of 21,000 data points) and advanced data analyses, including Hierarchical Linear Modelling and Growth Modelling. Additional responsibilities include providing drafts of the progress reports for MOE and maintaining a website with updates on our findings. The Research Fellow will be working with the MOE TRF Research Team, reporting directly to Dr. Evelyn Au.
Key Responsibilities:
- Management of large datasets across multiple courses and academic years.
- Conduct the required data analyses to test the hypotheses outlined by the research team, including Hierarchical Linear Modelling and Growth Modelling.
- Propose improvements to existing research/survey designs, materials and reports that lead to significant additional actionable insights for improving current pedagogical practices.
- Develop additional research hypotheses based on existing data to supplement existing projects that measure interdisciplinary and collaborative learning and its impact on students.
- Completion of progress reports based on MOE timeline.
- Update the project webpage for knowledge dissemination to the general public.
- Assist with the writing manuscripts for academic journals.
- Assist with preparation of slide decks for presentation of research to relevant stakeholders
- PhD from an internationally recognised university in Psychology or Education or related fields; specialisations in Quantitative Psychology and Educational Psychology preferred.
- A track record of internationally peer-reviewed publications in psychology, educational research, the learning sciences or science of learning or cognitive science, or related field preferred.
- At least 5 years of relevant experience working in a psychological or education related laboratory or teaching research methods and statistics to Psychology students at the undergraduate and graduate levels.
- Extensive knowledge and experience in psychological or education research methodologies, able to manage and analyse large data sets.
- Proficiency in data analyses software, including SPSS and R, and proficient in graphical-user interfaced software (e.g. Qualtrics, Verint, Google forms, Microsoft Office suite)
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