Year Level

Year 5-6

Duration

60 minutes

Class Size

110 students

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Unit Context: Entrepreneurship in Action (Lesson 11 of 12)

Lesson Title: Data-Driven Decision Making
Lesson Description:
Students will explore how data collection, analysis, and interpretation inform business decisions. They will practice evaluating consumer preferences and market trends using real-world data.

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Australian Curriculum Alignment

Learning Area: Humanities and Social Sciences (HASS) - Economics and Business

Year 5 Content Descriptions:

• AC9HS5S02: Locate, collect and organise information and data from primary and secondary sources in a range of formats
• AC9HS5S03: Evaluate information and data in a range of formats to identify and describe patterns and trends, or to infer relationships
• AC9HS6S03 (Year 6 extension): Evaluate information and data in a range of formats to identify and describe patterns and trends, or to infer relationships

Mathematics (Year 6)

• AC9M6ST03: Plan and conduct statistical investigations by posing and refining questions or identifying problems and collecting relevant data; analyse and interpret the data and communicate findings within the context of the investigation

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Learning Objectives

By the end of this lesson, students will be able to:

1. Collect primary data effectively using surveys and observations relevant to consumer preferences (Aligned to AC9HS5S02).
2. Organise collected data using tables and graphic organisers (AC9HS5S02, AC9M6ST03).
3. Analyse and interpret data to identify patterns and trends related to market preferences and consumer behaviour (AC9HS5S03, AC9M6ST03).
4. Make informed decisions based on data to evaluate business opportunities or product preferences (AC9HS5S03).
5. Communicate findings clearly using graphs and verbal explanations (AC9M6ST03).

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Resources Required

• Pre-prepared simple survey forms (paper/digital) about consumer preferences (e.g., favourite snacks, colours, logo design options)
• Graph paper or digital graphing tool (e.g., spreadsheet software)
• Whiteboard and markers
• Projector/screen for demonstration
• Worksheets for recording and organising data
• Printed or digital examples of bar graphs, pie charts, and tables
• Timer/clock for activity management

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Lesson Flow

1. Introduction and Context Setting (10 minutes)

• Hook: Present a real-life business scenario. For example, a student-run healthy snack stall wants to decide which snack to sell based on what other students prefer.
• Brief Discussion: Explain the importance of data collection and interpretation in business decision-making.
• Learning Intentions: Share the objectives for today’s lesson.
• Curriculum Link: Explain briefly how this lesson connects to Maths and HASS content.

2. Mini Lesson: What is Data-Driven Decision Making? (10 minutes)

• Explain key terms: data, consumer preferences, patterns, trends, decision-making.
• Show examples of data presented as tables, bar graphs, and pie charts (use student-friendly examples).
• Model how to read simple graphs and infer what the data tells us about preferences.
• Discuss how businesses use data to decide what products to sell.

3. Group Activity Part 1: Data Collection (15 minutes)

• Split the class into 10 groups of 11 students. Each group conducts a short survey within their group or a neighbouring group on a simple question about preferences (e.g., favourite fruit snack or preferred logo colour).
• Use paper or digital survey forms. Each student completes the survey quickly.
• Guide students to assist each other in organising response sheets for clarity.

4. Group Activity Part 2: Data Organisation & Analysis (15 minutes)

• Each group organises their collected data into tables on their worksheet.
• Using graph paper or spreadsheet tools, groups create a bar graph or pie chart representing their survey results.
• Teacher circulates and supports with graph construction, checking for accurate data representation.

5. Group Presentations and Interpretation (7 minutes)

• Each group briefly shares their graph and describes the patterns they observed. For example, “Most students preferred strawberry flavour” or “Blue was the most popular logo colour.”
• Discuss as a class what decisions could be made using this data (e.g., what snack to sell, what branding to choose).

6. Lesson Closure and Reflection (3 minutes)

• Recap the importance of using data to make business decisions.
• Ask students questions such as:
  • Why is it important to collect data before making a decision?
  • How did your group decide what graph to use?
• Outline that the next (final) lesson will focus on developing a business pitch using data insights.

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Assessment

Formative Assessment during lesson:

• Observation of student participation in data collection and group tasks.
• Accuracy in data organisation and graph creation assessed via worksheets.
• Quality of group presentations interpreting their data patterns.

Success criteria:

• Students can collect data using surveys.
• Students organise data into tables and graphs with teacher support.
• Students identify at least one clear pattern or trend from their data.
• Students articulate how data could influence business decisions.

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Differentiation and Inclusion

• Provide sentence starters and labelled templates for students requiring additional literacy support.
• Allow use of assistive technology (tablets, calculators) for graphing.
• Challenge faster learners to analyse multiple variables or suggest what other data could be collected for better decision-making.

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Cross-Curriculum Priorities and General Capabilities

• Critical and Creative Thinking: Students analyse data critically and consider implications for decision-making.
• Numeracy: Students engage with statistics and data displays, interpreting and creating graphs.
• Ethical Understanding: Discuss how data collection is respectful of individuals’ opinions (e.g., privacy, consent).
• Personal and Social Capability: Work collaboratively during group tasks.

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Teacher Notes/Wow Factor

• Use digital polling tools (if available) to collect live data and instantly generate class charts, impressing students with technology integration.
• Include a mini-challenge: predict peak preferences before surveying and test the hypothesis with real data—engage scientific inquiry skills.
• Highlight examples of Australian entrepreneurs who used data effectively to meet market needs.
• Incorporate First Nations perspectives by briefly discussing decision-making in Indigenous businesses, applying data to respect community needs.

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Summary Table of Timing

Activity	Time (minutes)
Introduction and Context	10
Mini Lesson on Data Concepts	10
Group Data Collection	15
Data Organisation & Analysis	15
Group Presentations & Discussion	7
Closure and Reflection	3

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References to Australian Curriculum (v9)

• AC9HS5S02 — Locate, collect and organise information and data
• AC9HS5S03 — Evaluate information and data to identify and describe patterns and trends
• AC9M6ST03 — Plan and conduct statistical investigations, analyse and interpret data
• AC9HS6S03 — Evaluate information and data to identify patterns and relationships (Year 6 extension)

This detailed lesson plan aligns closely with the Australian Curriculum v9 requirements for Year 5-6 Business/HASS and Mathematics, specifically focusing on data-driven decision making in the context of entrepreneurship.