Training activity information
Details
Construct a computational model and interpret the output
Type
Developmental training activity (DTA)
Evidence requirements
Evidence the activity has been undertaken by the trainee.
Reflection on the activity at one or more time points after the event including learning from the activity and/or areas of the trainees practice for development.
An action plan to implement learning and/or to address skills or knowledge gaps identified.
Considerations
- Validating outputs
- Real world context and implications
- Uses and limitations
- Software techniques
- Outputs of the modelling system
- Quality assurance
- Local standards and guidelines
- Good programming practice including version control system, appropriate software tools etc.
Reflective practice guidance
The guidance below is provided to support reflection at different time points, providing you with questions to aid you to reflect for this training activity. They are provided for guidance and should not be considered as a mandatory checklist. Trainees should not be expected to provide answers to each of the guidance questions listed.
Before action
- What is the purpose and intended application of the computational model you will construct? What type of output is expected from the model, and how should it be interpreted in a physical science or clinical system context?
- What are the fundamental principles or algorithms underlying the type of computational model you will be working with? How will you approach the process of constructing the model, and what strategies will you use to interpret the resulting output effectively? What potential limitations or assumptions of this type of model do you need to be aware of?
- What are the specifications or requirements for the computational model (e.g., input data, parameters, desired outputs)? What software or tools will you be using to construct and run the model? Do you have any prior knowledge or resources related to the specific type of computational modelling involved?
In action
- Pay attention to your actions.
- How are you approaching the construction of the model?
- What assumptions are you making?
- What tools or programming languages are you using? Why?
- What decisions are you making regarding the model’s parameters, variables, and the algorithms used?
- When interpreting the output, what are you focusing on? How are you relating the output back to the model’s design and the real-world system it represents?2 What aspects feel intuitive, and what requires more conscious effort, such as debugging the model or understanding the significance of specific output values?
- How effectively are your actions resulting in a functional computational model and interpretable output?
- What challenges are you facing in building the model, running simulations, or understanding the results?
- What can you learn from this process as it unfolds about the process of computational modelling and output interpretation?
- How does this activity connect to your understanding of computational modelling principles and the specific domain of the model?
- Are there alternative approaches you could be considering for the model’s design or the interpretation of its output?
- What support or guidance might you need in this moment if you are struggling with the model construction or the meaning of the results?
- Are you validating the model’s assumptions and the reasonableness of its output?
On action
- Briefly describe the computational model you constructed and summarise the key outputs you obtained.
- What did you learn about constructing computational models and interpreting their results?
- Were there any unexpected findings or challenges?
- How does this experience relate to the application of computational models in a clinical setting?
- How did your understanding evolve as you analysed the model’s output?
- What areas of computational modelling and output interpretation do you need to develop further? How will you apply this learning in future projects?
- What are your next steps for improving your skills in this area, and what support or resources might be beneficial?
Beyond action
- Have you worked with other computational models or interpreted different types of output since this DTA? Did you compare your approach or findings with others?
- How has this activity influenced your ability to understand and critique computational models used in a clinical environment? Has it enhanced your analytical skills in general?
- What transferable skills, such as analytical skills and critical thinking, did you develop? What further actions can you take to improve your skills in computational modelling and output interpretation, perhaps by exploring different modelling techniques?
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 4 |
Outcome
Develop a computational model for physical sciences or clinical systems. |
| # 6 |
Outcome
Apply good software design and programming practice. |
| # 9 |
Outcome
Practice in accordance with legislation, ethics and best practice. |