This research portfolio is designed to authentically mimic the professional practice of a Health Data Scientist. It targets the pedagogies of 'assessment for learning', with particular emphasis on 'lifelong learning'. Students will be involved 'as partners' in the design. During the program induction, students will have been given the opportunity to learn the basics of reflection based on the SOLO taxonomy, and the use of rubrics in standards-based assessment.

Each student will have a project supervisor to help guide them through the course. Each student will have the option to devise a research question together with a supervisor, (subject to approval) or to select from approved projects developed by supervisors. This course may be undertaken in a 'workplace' environment with a workplace supervisor and also a UNSW supervisor.

Students can choose either a traditional research project including complex data analysis of health data OR development of an online tool in health data science with practical application (eg data visualisation, Shiny app, knitr report).

The student will be required to submit a portfolio consisting of:

Project protocol (20%), 1000 words

Consisting (as appropriate to the particular study) of a:

The project background including a literature review and knowledge gap
Aims/Research Questions/Hypotheses
Data source/study population description
Data Analysis Plan/Tool development plan
Project timeline

Feedback will be given by the supervisor and course convenor using a marking rubric designed specifically for this purpose.

Output (60%), 5000-10000 words.

The output will depend on the type of project chosen. For a traditional research project a thesis or manuscript draft is the expected output in the format of Introduction, Methods, Results, Discussion. For a tool development project a Technical report as well as the developed tool is the expected output.

A complete portfolio will be required to pass the course.

The output will be assessed using a standard-based marking rubric independently by two markers- the supervisor and a content-knowledge expert that is organised by the supervisor at the outset of the course. Marking discrepancy over 10 marks will be in the first instance attempt to be resolved by discussion. Where agreement cannot be reached, a third marker (at the course convenor’s discretion) will adjudicate.

Oral presentation (20%)

A 10 minute research presentation, with an additional 5 minutes for question and answers.

The presentation will be assessed in real-time using a standard-based rubric by the course convenor.