Assessment 1 & 2 Criteria
This document outlines the assessment criteria for assessment one and two of B1701.
Assessment One
Introduction
The first assessment for the module is due during Module Week 13 (academic week 6). This assessment is worth 25% of your overall grade for the module.
For this assessment you will provide a 10-minute presentation to an (imaginary) overseas coaching team of a sport of your choice (you can choose any sport except football). Specifically, you should address the following key aspects:
- Describe to the coaching team why and how analytics can play a critical role in the recruitment and talent identification (30%)
- Identify relevant key performance indicators for your sport of choice (40%)
- Reflect on the future of recruitment analytics and talent identification in your sport of choice (20%).
In addition, the presentation will also be graded on the overall quality of your presentation (10%).
Assessment criteria
Criteria 1: Describe why and how analytics can play a critical role in the recruitment and talent identification (30%)
Characteristic 1: demonstrate a comprehensive understanding of why data analytics can be used to identify talent and key players in sport of your choice
Comment: The presentation should demonstrate a deep understanding of the role sport data analytics plays in enhancing talent identification or recruitment of key players in your sport.
For example, you could:
Describe specific data analytic tools, techniques, or methodologies currently used in your sport.
Give examples of key performance indicators linked to recruitment and talent identification in your sport and/or other sports.
Characteristic 2: demonstrate a comprehensive understanding of how data analytics can be used to identify talent and key players in sport of your choice
- Comment: The presentation should demonstrate a deep understanding of the steps required to implement the use of data analytics talent identification or recruitment of key players in your sport
- For example, you could:
- Highlight the process required to develop a recruitment analytics strategy
- Think about the different options based on the sport or organisation you present to
Criteria 2: Identify relevant key performance indicators for your sport of choice (40%)
Characteristic 1: identify and discuss the key performance indicators used in your sport of choice
Comment: Your presentation should show a deep understanding of the key performance indicators used in your sport.
For example, you could:
Use relevant literature to highlight key performance indicators and their effectiveness
Reflect on the relevance of the performance indicators depending on other factors
Evaluate the pro’s and con’s of the key performance indicators
Characteristic 2: demonstrates a clear and thorough understanding of how these KPIs are measured or monitored.
Comment: Your presentation should show an overview of how the before mentioned key performance indicators are measured and why we would use them
For example, you could:
Outline different measurement methods used
Evaluate the validity and reliability of measures
Provide pro’s and con’s for these measures
Criteria 3: Reflect on the future of recruitment analytics and talent identification in your sport of choice (20%)
Characteristic 1: highlight current gaps in the literature
Comment: Your presentation should show a deep understanding of the current state of data analytics for recruitment and talent identification purposes in your sport of choice.
For example, you could:
- Use relevant literature from your sport and/or other relevant sports to highlight any gaps.
Characteristic 2: reflect on the future of data analytics for recruitment.
Comment: Your presentation should reflect on how we can move the use of data analytics for recruitment and talent identification purposes in your sport of choice forward.
For example, you could:
Use previous identified gaps and explain how to overcome these
Reflect on how data analytics is used in other sports and what we can learn from that.
Criteria 4: Quality of Presentation (10%)
In addition to the three outcomes listed above, your presentation:
should be fluent, well-paced, and have a clear and logical structure
should contain slides that are uncluttered and easy to read
should demonstrate confidence and professionalism in presentation style and use clear and articulate language
should adhere to the time limit (10 minutes)
Grading
Grading will be in line with the University’s guidance on marking (Type B). Each of the four criteria are weighted as indicated above to make up the overall grade for the assessment.
Assessment Two
Introduction
The second assessment for the module is due at the end of week 19 (academic exam period). This assessment is worth 75% of your overall grade for the module.
For this assessment, you will be asked to submit a 2,500 word project report created via R Markdown. You will be given a data set and a case study you need to address. Specifically, you should address the following key aspects:
Formulate the steps required to identify the relevant key performance indicators (20%)
Manipulate and organise data and identify key talent based on the key performance indicators (25%)
Critique for and against the use of specific key performance indicators for the recruitment purpose (25%)
Create an analytical program for recruitment analytics in R (20%)
In addition, the report will also be graded on the overall quality of your report (10%).
Assessment criteria
Criteria 1: Formulate the steps required to identify the relevant key performance indicators (20%).
Characteristic 1: present a well-structured and appropriate methodological approach to address the research question(s).
Comment: your report should clearly specify the methods used to answer your research questions.
For example, you could:
Explain the dataset used.
Explain the key performance indicators used.
Characteristic 2: clearly explain the rationale behind your chosen methods and justify their suitability for the study using previous literature
Comment: In addition to explaining your methods used, your report should show a deep understanding of the rationale behind the methods you have chosen.
For example, you could:
Explain how the questions to the management informed your approach.
Provide evidence on the validity and reliability of your chosen methods.
Criteria 2: Manipulate and organise data and identify key talent based on the key performance indicators (25%)
Characteristic 1: clearly describe any data manipulation/ preparation taking place.
Comment: Your report should show a deep understanding of the importance of data preparation, cleaning, and manipulation.
For example, you could:
Explain data filtering methods.
Showcase how you adjusted KPIs for any cofounders impacting on the KPIs.
Characteristic 2: clearly describe your analytical approach.
Comment: Your report should show a deep understanding of the correct use of data analytical methods you used.
For example, you could:
- Explain why you used a certain method over another.
- Use multiple methods and compare their performance.
Characteristic 3: present your results in a clear and logical manner including visualisations where appropriate.
Comment: You should organise your results in a clear and logical manner so the coaching team can easily draw conclusions from your report.
For example, you could:
Provide an overview of the top N players.
Create visualisations comparing players.
Criteria 3: Critique for and against the use of specific key performance indicators for the recruitment purpose (25%)
Characteristic 1: discuss the strengths and weaknesses of your study/ use of KPIs.
Comment: Your report should show a critical reflection of the strengths and weaknesses of your study.
For example, you could:
- Highlight the sample used and discuss if there are limitations to using this sample.
Characteristic 2: make recommendations to the team for future analysis.
Comment: Your report should show a reflection on where to go next. What strategies could the team implement in the future to further improve their analytical approach?
For example, you could:
Highlight novel approaches which could be implemented in the future
Think about data collection methods which may improve future recruitment analytics.
Criteria 4: Create an analytical program for recruitment analytics in R (20%)
Characteristic 1: The complexity of your analysis.
Comment: Reports showing a higher complexity in analysis and data manipulation score better on this characteristic (if done correctly!).
For example, you could:
Include predictive analysis.
Use more advanced KPIs which require some data manipulation.
Characteristic 2: Execution and structure of your code.
Comment: R code which structured and labelled correctly will score higher on this element.
For example, you could:
Ensure your code is structured clearly.
Use section headers to separate different sections.
Criteria 5: Overall quality report (10%)
In addition to the four outcomes listed above, your report:
should be created as a R Markdown document.
meets the word limit (2,500 words).
is logically organized and flows coherently.
is written in a clear and professional writing style and adheres to academic standards.
properly references relevant sources to back up your statement using IEEE format.
Grading
Grading will be in line with the University’s guidance on marking (Type B). Each of the five criteria are weighted as indicated above to make up the overall grade for the assessment.