EPM5032 · Applied health data analytics group case study

Overview

In this unit you will work in a small team of three to four students to gain practical experience in health data analytics arising in an academic health research environment or industry. Your team will be provided with a set of research questions from which one question will be allocated per team member. You will work on answering your research question by applying the health data analytics process (visualisation, analysis, algorithms, etc.). You will work closely together as a team using the project health research data to produce a team research report and infographic for each research question. You will be asked to reflect on your own learning as the team work progresses. There are no lectures in this unit, although you will be expected to attend regular meetings with your team and tutor.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment in this unit includes hurdle assessment tasks. Failure of any hurdle assessment task may result in failure of the unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Elucidate strategies for answering research questions and associated health data analytical issues from a health or medical research dataset.
2. Search, access and analyse research literature as part of the process of developing solutions to health data analytics problems.
3. Evaluate and select research methods and techniques of data preparation and analysis appropriate to a given project, and practice these ethically and professionally.
4. Collaborate effectively with peers in devising a strategy for analysis of the health research data, implementing the strategy and producing a report.
5. Reflect on your learning, how it changes at each stage, and how it might relate to future learning experiences.
6. Harmonise team analysis findings into a scientific written report, and a presentation appropriate to a general audience
7. Critically assess and effectively use artificial intelligence (AI) tools responsibly, with transparency and specific to health data analytics

Workload

Twelve hours per week, consisting of (on average) • 3 hours per week for reading relevant material • 8 hours per week working on the health data analytics (i.e. data wrangling, analysis, report writing) • 1-hour face-to-face meeting with team and tutor No residential component is required.

Student experience, not official rules. Nothing here changes what the Handbook says.