Training activity information
Details
Using a scripted data processing language create a script to demonstrate:
- Variables
- Data structures
- Pattern matching
- Loops
- Conditionals
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
- Variables (global and local), functions, expressions, and loops
- Variable types for example: string, float, and integer
- Data structures for example: arrays, dictionaries, lists, and tuples
- Pattern matching
- Errors and exceptions
- Input and output
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
- Which scripted data processing language will you be using (e.g., Python, R, MATLAB)?
- What is your current level of proficiency with this language?
- What specific tasks or examples will your script demonstrate to showcase the use of variables, data structures, pattern matching, loops, and conditionals?
- How will you structure your script to be clear, well-documented, and easy to understand?
- How will you test your script to ensure it functions correctly and demonstrates the required concepts?
- What challenges might you encounter in writing the script, especially with aspects like pattern matching or complex control flow (loops and conditionals)?
In action
- As you write the script, are you testing each part incrementally to ensure it functions as intended (e.g., variable assignment, data structure creation, pattern matching, loop execution, conditional logic)?
- Are you debugging as you go?
- Are you considering the efficiency and readability of your code as you write it?
- Are there alternative ways to achieve the same result that might be better?
- When demonstrating pattern matching, are you testing with different patterns and data to ensure it works correctly in various scenarios?
- As you implement loops and conditionals, are you thinking about the flow of execution and potential edge cases?
- Are you testing these scenarios?
- Are you commenting on your code to explain its functionality as you write it, making it easier to understand your thought process later?
On action
- Summarise the script you created, the data processing language you used, and how your script demonstrated the requested programming concepts.
- What did you learn about using a scripted data processing language to manipulate data?
- Did you improve your understanding of fundamental programming concepts such as variables, data structures, pattern matching, loops, and conditionals?
- How effective was your script in demonstrating these concepts?
- How does the ability to write scripts for data processing contribute to your analytical capabilities?
- Were there any challenges in implementing specific programming concepts or debugging your script?
- What did you learn from these challenges?
- Were there any more efficient or elegant ways you could have written the script that you realised after completion?
- What further features or capabilities of the data processing language do you want to learn?
- How can you improve your programming skills and write more efficient and readable code?
- What are your next steps in developing your scripting abilities for data analysis?
- What resources (e.g., online coding tutorials, language documentation) might be beneficial?
Beyond action
- Have you used scripting languages for data processing or encountered different scripting techniques since this DTA?
- How has your understanding of programming concepts and their application to data manipulation evolved?
- Have you shared your scripts or sought feedback on your coding practices?
- How has this experience influenced your ability to automate data processing tasks or analyse large datasets?
- Have you applied scripting skills in your work to improve efficiency or extract insights from data?
- Has your appreciation for the role of programming in healthcare analytics increased?
- What technical skills in data processing and programming did you develop that will be valuable in research, data analysis, or developing analytical tools?
- How has this experience informed your understanding of computational approaches in healthcare?
- What clear actions for continued development in specific scripting languages or data processing techniques have been identified?
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 1 |
Outcome
Explore and explain relationships between elements in a system. |