Course coordinator
Associate Professor Carl Woods
Course overview
- Study period
- Semester 2, 2025 (28/07/2025 - 22/11/2025)
- Study level
- Postgraduate Coursework
- Location
- External
- Attendance mode
- Online
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Human Movement & Nutrition Sci
This course offers coaches with a detailed insight to the theory underpinning skill learning in sport, emphasising its practical importance in developing, analysing and periodising effective learning environments.
SPCG6001 Movement and Performance Analysis aims to support student knowledge with regards to theory underpinning skill learning and performance analysis in sport. This theoretical basis is critical, as it opens significant practical value with regards to practice task design, notational analysis to support coach decision making, and the periodisation of skill development. These practical components will be of considerable value for coaches and sport scientists working across the high performance sport landscape. This course is divided into four Modules:
Module 1: Theory
This Module lays the grounding theoretical framework for the entire course. First, it explores the concept of meta-theory, touching on four dominant meta-theories that have shaped our understanding of human movement and skill learning. From here, we then explore a specific theory that considers human behaviour as occurring at an ecological scale of analysis, addressing what this means for the study of skilled behaviour in sport. By the end of this Module, you will be cognisant with dominant meta-theories across the human movement sciences, in addition to being well equipped to discuss an ecological theory of human behaviour and how this implicates the way we develop skill in high performance sport.
Module 2: Practice
This Module explores the practical utility of theory, drawing on an ecological approach to skill development in sport, which was detailed in Module 1. This will see us cover the key tenets of nonlinear pedagogy, and how this pedagogical approach shapes our role as coaches. Extending this, you will explore how to operationalise nonlinear pedagogy in your contexts by drawing upon the Environmental Designs Principles framework, considering principles such as Representative Learning Design, Repetition without Repetition and Constraints Manipulation. Through Case Report 1, you will gain the opportunity to apply the Environmental Design Principles framework to your coaching context.
Module 3: Performance analysis and skill periodisation
Building from Module's 1 and 2, this Module will explore how to analyse sports performance using a variety of different techniques. Specifically, it will cover how the use of notational analysis has been leveraged to build decision support systems in coaching, while concurrently touching on some critical limitations to these respective techniques. This will pave the way for a theoretically informed approach to performance analysis, which enables coaches to extract augmented information from competition to support decisions related to the coaching process. The second part of this Module will explore how this augmented information could be used to periodise skill development. To guide this process, two skill periodisation frameworks will be introduced, highlighting the principles and phases of each. Through Case Report 2, students will gain the opportunity to apply one of these periodisation frameworks to their context with the intent of supporting both the short- and long-term development of skill.
Module 4: Case examples from the field
As this course intends to show, theory can be an important ally for coaches, offering a competitive advantage that transcends a variety of advents, such as sports technology. Thus, the intent of Module 4 is to bring the ideas from Module's 1, 2, and 3 together, exemplifying how they have been brought to life in real-world examples from the field. The purpose of this is to show and inspire students, highlighting how highly theoretical ideas can yield real, concrete effects in the field. Students, thus, will be encouraged to emulate these case examples, thereby taking the lessons learned from this course and integrating them into their practice contexts.
Course requirements
Incompatible
You can't enrol in this course if you've already completed the following:
SPCG7002, EDUC2000, HMST2220, HMST2530, HMST3533, HMST7256, NEUR2530
Course contact
Course staff
Lecturer
Associate Professor Carl Woods
Aims and outcomes
2.1 Course Aims
- Demonstrate the ability to argue in support of meaningful performance measures to support athletes and coachesﾠ
- Demonstrate the ability to analyse movement skills based on foundational sport analysis methods and deterministic models
- Design training and testing programs through evidence-based decision-making.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Quiz |
Multiple Choice Quiz
|
30% (3 x MCQ each worth 10%) |
MCQ 1 11/08/2025 - 15/08/2025 MCQ 2 1/09/2025 - 5/09/2025 MCQ 3 22/09/2025 - 26/09/2025 |
| Paper/ Report/ Annotation | Case Report 1 | 40% |
19/09/2025 5:00 pm |
| Paper/ Report/ Annotation | Case Report 2 | 30% |
24/10/2025 5:00 pm |
Assessment details
Multiple Choice Quiz
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 30% (3 x MCQ each worth 10%)
- Due date
MCQ 1 11/08/2025 - 15/08/2025
MCQ 2 1/09/2025 - 5/09/2025
MCQ 3 22/09/2025 - 26/09/2025
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
At the end of Module’s 1, 2 and 3 there will be a 10 question MCQ. All questions will originate from lecture and some reading material.
Submission guidelines
To be completed as an online quiz via the course Blackboard site
Deferral or extension
You may be able to apply for an extension.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Case Report 1
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 40%
- Due date
19/09/2025 5:00 pm
- Learning outcomes
- L02, L03, L04, L06, L07
Task description
Students will be required to theoretically overview and systematically outline the design of a practice session by drawing upon the Environmental Design Principles framework. This case report is to consist of three main sections.
Submission guidelines
To be submitted via the relevant Turnitin submission portal on the course Blackboard site.
Deferral or extension
You may be able to apply for an extension.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Case Report 2
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 30%
- Due date
24/10/2025 5:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05, L06
Task description
Students will be required to overview and integrate the SAP framework within their coaching context, exemplifying three of its principles. Students are encouraged to use hypothetical examples and corresponding notations specific to their sport, as there is no expectation that they collect data for this case report. We are interested in understanding how students would measure, monitor and evaluate skill training in their context.
Submission guidelines
To be submitted via the relevant Turnitin submission portal on the course Blackboard site.
Deferral or extension
You may be able to apply for an extension.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 24 |
Absence of evidence of achievement of course learning outcomes. Course grade description: Fails to satisfy most or all of the basic requirements of the course: |
| 2 (Fail) | 25 - 44 |
Minimal evidence of achievement of course learning outcomes. Course grade description: Fails to satisfy some of the basic requirements of the course. Clear deficiencies in performance, but evidence that some basic requirements have been met |
| 3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Fails to satisfy all basic requirement for pass but is close to satisfactory overall and has compensating strengths in some aspects: |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Satisfies all of the basic learning requirements for the course, such as knowledge of fundamental concepts and performance of basic skills; demonstrates sufficient quality of performance to be considered satisfactory or adequate or competent or capable in the course |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Demonstrates ability to use and apply fundamental concepts and skills of the course, going beyond mere replication of content knowledge or skill to show understanding of key ideas, awareness of their relevance, some use of analytical skills, and some originality or insight |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Demonstrates awareness and understanding of deeper and subtler aspects of the course, such as ability to identify and debate critical issues or problems, ability to solve non-routine problems, ability to adapt and apply ideas to new situations, and ability to invent and evaluate new ideas |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Demonstrates imagination, originality or flair, based on proficiency in all the learning objectives for the course; work is interesting, surprising, exciting, challenging or erudite |
Additional course grading information
A final percentage mark will be rounded to the nearest whole number (e.g. 64.50 and above will be rounded to 65 and 64.49 and below will be rounded down to 64.)
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Use of generative Artificial Intelligence (AI) or Machine Translation (MT)
The assessment tasks in this course have been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment tasks in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass these assessment tasks, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Additional learning resources information
A number of selected readings and learning resources will be made available through the course Blackboard site as hyperlinks. These readings should be incorporated in assessment submission and are assessable during the completion of assessment items.ﾠ
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 3 |
Not Timetabled |
Theory This Module will cover:
Learning outcomes: L06 |
Multiple weeks From Week 4 To Week 6 |
Not Timetabled |
Practice This Module will cover:
Learning outcomes: L04, L06, L07 |
Multiple weeks From Week 7 To Week 9 |
Not Timetabled |
Performance analysis and skill periodisation This Module will cover:
Learning outcomes: L01, L02, L03, L04, L05, L06, L07 |
Multiple weeks From Week 10 To Week 12 |
Not Timetabled |
Case examples This Module will cover:
Learning outcomes: L06 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: