
SFU-002 - Module 5 (Learning Outcomes)
Springpod Team
Created on September 6, 2024
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Transcript
Learning Outcomes
Here are six learning outcomes tailored for the work simulation you've just completed. These learning outcomes are designed to provide a broad range of competencies that are critical for a career in sports analytics, helping to build a strong foundation in this field.
Data Collection and Research Skills
Data Cleaning and Organisation
Data Analysis
Predictive Analysis
Data Visualisation
Report Writing and Presentation
Detailed breakdown
Here's a breakdown of what's to come in the course.
Learning objectives
Remembering: Identify sources and steps for data collection. Understanding: Define the business question or objective.
Preparation Task
(10 minutes)
Preparation Task
(10 minutes)
Remembering: Identify sources and steps for data collection. Understanding: Define the business question or objective.
Preparation Task
(10 minutes)
Applying: Collect data from various sources.Analysing: Organise and compile the collected data.
Research Task
(30 minutes)
Remembering: Identify sources and steps for data collection. Understanding: Define the business question or objective.
Preparation Task
(10 minutes)
Applying: Clean and format the data, and identify key metrics.Analysing: Use visual tools to analyse trends and perform SWOT analysis.
Analysis Task
(30 minutes)
BACK
NEXT
Remembering: Identify sources and steps for data collection. Understanding: Define the business question or objective.
Preparation Task
(10 minutes)
Creating: Develop insights and actionable recommendations based on data analysis.Evaluating: Assess the findings and provide recommendations.
Create Task
(20 minutes)
Remembering: Identify sources and steps for data collection. Understanding: Define the business question or objective.
Preparation Task
(10 minutes)
Creating: Compile a detailed report and prepare a presentation.Evaluating: Share and get feedback to improve the final output.
Document & Present
(15 minutes)
Remembering: Identify sources and steps for data collection. Understanding: Define the business question or objective.
Preparation Task
(10 minutes)
Evaluating: Reflect on the learning experience and its application.Understanding: Consider how the exercise enhanced skills and identify areas for further improvement.
Reflection Task
(10 minutes)
Detailed breakdown
Here's a breakdown of what's to come in the course.
Learning objectives
BACK
NEXT
Conclusion
By the end of this activity, you will have gained practical experience in collecting and analysing marketing intelligence data, understanding how to make data-driven business decisions, and improving your analytical skills. This activity leverages accessible tools and methods, ensuring it is practical and feasible within the given timeframe.Now that you're all prepped, mark this section as complete and let's make a start on the simulation module!
Learning objectives
BACK
Reporting and Presentation
Improve abilities in compiling comprehensive analytics reports and presentations that clearly communicate data analysis, visualisations, and predictive analysis to stakeholders.
Data Visualisation
Gain skills in using data visualisation tools and techniques to create easy-to-understand visual representations of complex sports data and analytics findings.
Data Analysis
Learn how to analyse sports data effectively to identify key performance indicators, trends, patterns, and correlations that impact a sports team's performance.
Data Cleaning and Organisation
Gain proficiency in using spreadsheet tools (Excel, Google Sheets) to clean, format, and organise collected sports data in preparation for analysis.
Predictive Analysis
Develop the skills to use analysed data and identified trends to make informed predictions about future performance outcomes for a sports team.
Data Collection and Research Skills
Develop the ability to identify, source, and gather relevant market intelligence data from various online resources and databases.