Course Title: Applied Research Analytics
Part A: Course Overview
Course Title: Applied Research Analytics
Credit Points: 12.00
Important Information:
Note: This course is taught fully online for this teaching period, and not face-to-face.
Course Coordinator: Andrew Timming
Course Coordinator Phone: +61 3 99255320
Course Coordinator Email: andrew.timming@rmit.edu.au
Course Coordinator Location: B080-9-085
Course Coordinator Availability: By Appointment
Pre-requisite Courses and Assumed Knowledge and Capabilities
Candidates will be expected to have achieved the candidature of confirmation milestone.
Course Description
This course aims to provide candidates who have acquired data or are in the process of acquiring data through their research projects with appropriate quantitative and/or qualitative data analysis skills, techniques, and use of software tools.
The focus is on equipping candidates on the practical applications of advanced techniques and tools to effectively analyse, present and interpret research data.
Candidates will also be exposed to the underlying assumptions, integrity principles and practices of quantitative and/or qualitative data analysis techniques and their impact.
The course will be modular in structure allowing candidates to complete the components they need to prepare for their research project and to enable more granular recognition of prior learning.
This course:
- Optional for HDR candidates post CoC
- Runs every two years
Objectives/Learning Outcomes/Capability Development
To complete this course, candidates would be expected to demonstrate:
a. Critical thinking through analysis of their research data in the context of more advanced analytical or interpretive approaches.
b. High-level communication skills through oral and written presentations outlining their approach to analysis or interpretation of their datasets, in the context of their research questions.
c. Creativity and problem-solving skills in the application of advanced analytical/ interpretative technique to their data set and research questions.
On successful completion of the course, candidates will be able to:
CLO1 Research and apply advanced scientific qualitative and/or quantitative methods when analysing, presenting and interpreting research data. CLO2 Develop advanced skills in the use of qualitative and/or quantitative data analysis software and their limitations relevant to their research area.CLO3 Apply principles and frameworks of responsible conduct of research in data management, analysis, interpretation and research communication. CLO4 justify and communicate the analysis of research data in high quality written reports/manuscripts/chapters.
Overview of Learning Activities
The course will be conducted in seminar style and activities will be based on the needs of the candidates in terms of their data sets and research questions. Candidates will be expected to identify approaches relevant to their study and explore analysis tools and techniques under the guidance of experienced staff. Seminar discussion will focus on particular datasets and research questions each week. Candidates will be expected to present at the various stages of their further investigation of appropriate analysis of their data.
Overview of Learning Resources
Candidates will require access to quantitative and qualitative data analysis tools.
Overview of Assessment
The assessment tasks, their weighting and the course learning outcomes to which they are aligned are as follows.
Assessment Task 1: 20%
Linked CLOs: 1, 2, 3
Assessment Task 2: 30%
Linked CLOs: 2, 3, 4, 5
Assessment Task 3: 50%
Linked CLOs: 2, 3, 4, 5