Embedded Files
⭐ Connecting Data Literacy to Essential Key Concepts ⭐️
Exploring Data Literacy offers authentic opportunities to revisit the Essential Key Concept of Decimal Reasoning and Proportional Reasoning:
B1.4 → Read, represent, compare, and order decimal numbers up to thousandths
Students apply this skill when plotting precise continuous data - such as daily temperatures or time records - on broken-line graphs and histograms to ensure accurate and meaningful visual comparisons.
B1.6 → Equivalences among fractions and decimal numbers up to thousandths
This skill supports students in converting data values (e.g., 0.25 = 1/4 of respondents) to ensure accurate fractional and decimal representations in infographics.
B2.11 → Divide decimal numbers by whole numbers up to 10
Students calculate averages or per-unit measures and then determine whether a histogram or broken-line graph more clearly conveys their findings.
B2.12 → Solve problems involving ratios, including percents and rates
In creating infographics, students calculate pecentages or rates (such as 60% preference for Option A) and decide how to visually represent those comparisons - such as with ratio bars or labelled graphs.
Expectation Cluster
Expectation Cluster
D1.1 describe the difference between discrete and continuous data, and provide examples of each
D1.2 collect qualitative data and discrete and continuous quantitative data to answer questions of interest about a population, and organize the sets of data as appropriate, including using intervals
D1.3 select from among a variety of graphs, including histograms and broken-line graphs, the type of graph best suited to represent various sets of data; display the data in the graphs with proper sources, titles, and labels, and appropriate scales; and justify their choice of graphs
D1.4 create an infographic about a data set, representing the data in appropriate ways, including in tables, histograms, and broken-line graphs, and incorporating any other relevant information that helps to tell a story about the data
Mathematical Modelling is a key process expectation that connects across multiple strands. Opportunities to engage students in modelling may arise naturally within rich, real-world contexts — for example, in financial literacy (e.g., creating a budget), measurement (e.g., designing a garden space), or data (e.g., interpreting results from a student survey).
We recommend using open-ended tasks where students define problems, make decisions, and justify their thinking — even in informal ways — as early steps toward developing modelling skills.
See our Mathematical Modelling page for more information.
Process Expectation Focus: Communicating, Selecting Tools and Strategies
Organize your observations of student learning related to the key concepts and skills for this topic:
Explore a menu of possible MathUP lessons, Building Fluency lessons, problems, explorations and games.
During this topic, pay attention to the students' ability to develop self-awareness and sense of identity.
Do students perceive themselves as capable math learners?
Can students describe some of their mathematical strengths?
Do students demonstrate ownership of their learning? (e.g. using the resources and tools in the classroom, asking questions, using feedback to set a personal learning goal, taking risks in their learning)
Models and Tools
Models and Tools
Concrete Learning Resources Tools:
grid paper
snap cubes
tiles
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