Unit rationale, description and aim

The rapid growth of technology in high performance sport has reshaped how training and competition data are collected, analysed, and applied. This unit introduces students to the evolving technologies that influence sport, fitness, and athlete care, providing hands-on experience with industry-relevant tools while fostering critical evaluation of their application. 

Students will explore how to assess the validity, reliability, and ethical implications of technologies using contemporary frameworks. Through authentic, problem-based and project-based learning, students will gain experience with data collection, signal processing, and visualisation tools, while developing skills to interpret and communicate findings effectively to diverse stakeholders. The unit culminates in a technology-driven capstone project, preparing students for responsible innovation in sport and performance settings.  

The aim of this unit is to provide students with ethically grounded, applied, and critical skills to collect, analyse, interpret, and communicate performance data, using both emerging and established sports technologies providing career and industry ready skills for future employment.

2027 10

Campus offering

No unit offerings are currently available for this unit.

Prerequisites

EXSC120 Mechanical Bases of Exercise Science OR EXSC224 Mechanical Bases of Exercise

Incompatible

EXSC317 Data Analytics in Sport AND EXSC319 Performance Analysis in Sport

Learning outcomes

To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.

Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.

Explore the graduate capabilities.

Describe technologies used for the measurement and...

Learning Outcome 01

Describe technologies used for the measurement and monitoring of sport performance
Relevant Graduate Capabilities: GC1, GC2, GC10

Apply methods for collecting, managing, and proces...

Learning Outcome 02

Apply methods for collecting, managing, and processing data using sport-relevant tools
Relevant Graduate Capabilities: GC2, GC7, GC8, GC10

Interpret data to produce insights in athletic or ...

Learning Outcome 03

Interpret data to produce insights in athletic or sport contexts
Relevant Graduate Capabilities: GC1, GC2, GC9, GC10, GC11

Communicate solutions to performance-related chall...

Learning Outcome 04

Communicate solutions to performance-related challenges using sports technology
Relevant Graduate Capabilities: GC2, GC9, GC11, GC12

Create justifiable solutions for common problems i...

Learning Outcome 05

Create justifiable solutions for common problems in high performance sport using sports technologies
Relevant Graduate Capabilities: GC3, GC7, GC10, GC12

Content

Topics will include: 

  • Evolution and role of technology in high performance sport 
  • Contemporary methods of data collection in sport 
  • Principles of data management and workflow design 
  • Fundamentals of signal processing and smoothing 
  • Visualising performance data for interpretation 
  • Stakeholder-focused reporting and communication 
  • Ethics in data analysis and reporting 
  • Sport Technology Framework for evaluating technology 
  • Emerging technologies and future trends in sport 
  • Integrating multiple data streams for contextual decision-making 

Assessment strategy and rationale

This unit uses a developmental assessment structure designed to promote progressive learning and integration of theoretical knowledge, technical skills, and applied judgement. The first assessment introduces students to a real-world scenario where they must critically evaluate a chosen technology using the Sports Technology Framework. The second assessment extends this understanding into a practical application, requiring students to design a presentation that outlines how the evaluated technology could solve a real problem at a sport organisation or club. The final capstone task requires students to complete a technology-based project that applies their knowledge and skills to address a real-world performance problem using sport technology to analyse performance. 

Overview of assessments

To successfully pass the unit, students must demonstrate achievement of all learning outcomes and achieve a minimum overall mark of 50% from all assessment tasks.

Assessment Task 1: Written Task Critically asses...

Assessment Task 1: Written Task

Critically assess the use of a selected technology in a simulated sport performance scenario. 

Weighting

30%

Learning Outcomes LO1, LO2, LO4, LO5
Graduate Capabilities GC1, GC2, GC3, GC7, GC9, GC10, GC11

Assessment Task 2: Oral Presentation A presentat...

Assessment Task 2: Oral Presentation

A presentation that proposes a practical use case for technology to solve a problem in a sport organisation or club. 

Weighting

30%

Learning Outcomes LO1, LO2, LO4, LO5
Graduate Capabilities GC2, GC3, GC8, GC10, GC11, GC12

Assessment Task 3: Capstone Written Project Comp...

Assessment Task 3: Capstone Written Project

Complete a technology-based project that applies a selected sport technology to address a real-world performance problem through analysis and data-driven insights. 

Weighting

40%

Learning Outcomes LO2, LO3, LO4, LO5
Graduate Capabilities GC1, GC2, GC3, GC9, GC10, GC11, GC12

Learning and teaching strategy and rationale

This unit adopts a blended learning strategy to promote deep engagement through project-based and experiential learning. Students will engage in a flipped classroom model with pre-class materials, guided workshop experiences, and scaffolded group work. The curriculum supports students to progress from guided practicals to autonomous application in complex, industry-relevant contexts. 

Students will actively construct knowledge through hands-on technology exposure and critical reflection. These approaches reflect adult learning principles and experiential learning theory, supporting students in building applied knowledge through iterative practice and contextual problem-solving. 

Representative texts and references

Representative texts and references

Biggs, J., & Tang, C. (2011). Teaching for quality learning at university (4th ed.). Open University Press. 

Catapult Sports. (2020). User guides and implementation resources

Hopkins, W. G. (2016). A new view of statistics. http://www.sportsci.org/resource/stats/index.html 

Hughes, M., & Franks, I. (2004). Notational analysis of sport (2nd ed.). Routledge. 

Knowles, M. S., Holton, E. F., & Swanson, R. A. (2015). The adult learner: The definitive classic in adult education and human resource development (8th ed.). Routledge. 

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall. 

McGarry, T., O’Donoghue, P., & Sampaio, J. (2013). Routledge handbook of sports performance analysis. Routledge. 

O’Donoghue, P. (2010). Research methods for sports performance analysis. Routledge. 

Robertson, S., Zendler, J., De Mey, K., Haycraft, J., Ash, G. I., Brockett, C., … Rogowski, J. (2023). Development of a sports technology quality framework. Journal of Sports Sciences, 41(22), 1983–1993. https://doi.org/10.1080/02640414.2024.2308435 

VALD Performance. (2021). ForceDecks User Manual

van Dyk, N., et al. (2021). Data visualisation best practices in sports science. British Journal of Sports Medicine

Vincent, W. J., & Weir, J. P. (2012). Statistics in kinesiology (4th ed.). Human Kinetics. 

Wickham, H., & Grolemund, G. (2017). R for data science. O’Reilly Media 

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