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Classifying living things (age 9+)

PROCEDURAL
Science›Scientific Inquiry|Ages 9—11|ID: mt_rDjtmDogJr

Record data and results of increasing complexity using scientific diagrams, classification keys, tables, scatter graphs, bar and line graphs

Mastery Evidence

  • Choose and create an appropriate graph type for the data (bar chart, line graph, scatter graph)
  • Draw graphs with correctly labelled axes, appropriate scales, and accurate plotting
  • Use classification keys and scientific diagrams to present complex findings

Assessment Prompt

“Can [child] choose the right type of graph for their data — a bar chart for categories or a line graph for continuous data — and draw it accurately?”

Curriculum Standards1 alignment

KS2U.Sci.WS.3The national curriculum in England
Recording data and results

recording data and results of increasing complexity using scientific diagrams and labels, classification keys, tables, scatter graphs, bar and line graphs

Science · Upper Key Stage 2

Prerequisites2

Show full prerequisite tree
  • Classifying living things hard

    Must present data in basic formats before using complex graphs and scientific diagrams

    • Pictograms and tally charts soft

      Science data presentation (tables, bar charts) builds on maths pictogram/table skills

      • Pictograms and tally charts (age 6+) hard

        Constructing pictograms, tally charts, and bar charts requires these display vocabulary terms

      • Sorting into categories hard

        Constructing pictograms and tally charts requires classifying and counting objects first

        • Comparing groups: more or fewer soft

          Sorting categories by count benefits from ability to compare quantities

          • Counting objects to 20 soft

            Counting a set helps when comparing groups, but younger children (GB age 4) can compare using matching without formal counting to 20

            • How Many in Total? hard

              Answering 'how many?' requires the cardinality principle

              • One-to-one counting hard

                Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

            • One-to-one counting hard

              Counting objects to answer 'how many?' requires one-to-one correspondence

        • Counting objects to 20 hard

          Counting objects in each category requires being able to count sets of objects

          • How Many in Total? hard

            Answering 'how many?' requires the cardinality principle

            • One-to-one counting hard

              Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

          • One-to-one counting hard

            Counting objects to answer 'how many?' requires one-to-one correspondence

      • Sorting Data into Categories soft

        Data representation formats (pictograms, tally charts) support organising data

        • How Many in Total? soft

          Counting data in categories requires understanding cardinality

          • One-to-one counting hard

            Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

        • Pictograms and tally charts (age 6+) hard

          Organising and representing data requires data, tally, frequency, and category vocabulary

        • Sorting into categories hard

          Organising data in categories builds on classifying and counting objects in categories

          • Comparing groups: more or fewer soft

            Sorting categories by count benefits from ability to compare quantities

            • Counting objects to 20 soft

              Counting a set helps when comparing groups, but younger children (GB age 4) can compare using matching without formal counting to 20

              • How Many in Total? hard

                Answering 'how many?' requires the cardinality principle

                • One-to-one counting hard

                  Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

              • One-to-one counting hard

                Counting objects to answer 'how many?' requires one-to-one correspondence

          • Counting objects to 20 hard

            Counting objects in each category requires being able to count sets of objects

            • How Many in Total? hard

              Answering 'how many?' requires the cardinality principle

              • One-to-one counting hard

                Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

            • One-to-one counting hard

              Counting objects to answer 'how many?' requires one-to-one correspondence

    • Measuring accurately hard

      Must take accurate measurements before presenting complex data

      • Measurable Attributes of Objects soft

        Systematic scientific measurement builds on understanding measurable attributes from maths

      • Observing with simple equipment hard

        Must observe closely before taking systematic measurements

        • Asking scientific questions hard

          Must ask questions before learning to observe closely

          • Asking Questions soft

            Formulating scientific questions builds on the general skill of asking relevant questions to extend understanding, developed in English speaking and listening

            • Question Words hard

              Generating effective questions requires knowledge of question words (who, what, where, when, why, how)

            • Listening and responding hard

              Listening and responding needed before asking questions

            • Exploring Ideas Through Talk soft

              Related speaking skill supports this topic

              • Feeling of not understanding soft

                Using talk to explore ideas and speculate requires noticing what you don't yet understand — the comprehension-monitoring habit in a spoken register

                • Asking for Help hard

                  Noticing confusion and acting on it requires already knowing that asking for help is a valid response to being stuck

          • Observation vs Interpretation soft

            Asking good scientific questions requires noticing the distinction between observation and interpretation — a question like 'why did this happen?' only makes sense once you've separated what you saw from what you inferred

            • Feeling of not understanding soft

              Noticing the observation/interpretation distinction requires monitoring your own thinking — the universal comprehension-monitoring habit applied to scientific reasoning

              • Asking for Help hard

                Noticing confusion and acting on it requires already knowing that asking for help is a valid response to being stuck

          • Feeling of not understanding soft

            Asking scientific questions is the science-domain expression of the universal comprehension-monitoring habit: noticing what you don't yet understand

            • Asking for Help hard

              Noticing confusion and acting on it requires already knowing that asking for help is a valid response to being stuck

          • Persisting When It's Hard soft

            Scientific enquiry requires persistence through uncertainty — the universal persistence habit underpins willingness to keep investigating

    • Recording Data hard

      Must gather data simply before presenting in charts and diagrams

      • Simple tests and experiments hard

        Must perform tests before learning to gather and record data

        • Observing with simple equipment hard

          Must observe closely before performing simple tests

          • Asking scientific questions hard

            Must ask questions before learning to observe closely

            • Asking Questions soft

              Formulating scientific questions builds on the general skill of asking relevant questions to extend understanding, developed in English speaking and listening

              • Question Words hard

                Generating effective questions requires knowledge of question words (who, what, where, when, why, how)

              • Listening and responding hard

                Listening and responding needed before asking questions

              • Exploring Ideas Through Talk soft

                Related speaking skill supports this topic

                • Feeling of not understanding soft

                  Using talk to explore ideas and speculate requires noticing what you don't yet understand — the comprehension-monitoring habit in a spoken register

                  • Asking for Help hard

                    Noticing confusion and acting on it requires already knowing that asking for help is a valid response to being stuck

            • Observation vs Interpretation soft

              Asking good scientific questions requires noticing the distinction between observation and interpretation — a question like 'why did this happen?' only makes sense once you've separated what you saw from what you inferred

              • Feeling of not understanding soft

                Noticing the observation/interpretation distinction requires monitoring your own thinking — the universal comprehension-monitoring habit applied to scientific reasoning

                • Asking for Help hard

                  Noticing confusion and acting on it requires already knowing that asking for help is a valid response to being stuck

            • Feeling of not understanding soft

              Asking scientific questions is the science-domain expression of the universal comprehension-monitoring habit: noticing what you don't yet understand

              • Asking for Help hard

                Noticing confusion and acting on it requires already knowing that asking for help is a valid response to being stuck

            • Persisting When It's Hard soft

              Scientific enquiry requires persistence through uncertainty — the universal persistence habit underpins willingness to keep investigating

  • Bar graphs soft

    Complex science graphs (scatter, line) build on maths discrete/continuous data graphing

    • Representing numbers with objects (age 8+) hard

      Scaled bar charts are prerequisite to continuous data and time graphs

      • Pictograms and tally charts hard

        Constructing simple pictograms/tables is prerequisite to scaled versions

        • Pictograms and tally charts (age 6+) hard

          Constructing pictograms, tally charts, and bar charts requires these display vocabulary terms

        • Sorting into categories hard

          Constructing pictograms and tally charts requires classifying and counting objects first

          • Comparing groups: more or fewer soft

            Sorting categories by count benefits from ability to compare quantities

            • Counting objects to 20 soft

              Counting a set helps when comparing groups, but younger children (GB age 4) can compare using matching without formal counting to 20

              • How Many in Total? hard

                Answering 'how many?' requires the cardinality principle

                • One-to-one counting hard

                  Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

              • One-to-one counting hard

                Counting objects to answer 'how many?' requires one-to-one correspondence

          • Counting objects to 20 hard

            Counting objects in each category requires being able to count sets of objects

            • How Many in Total? hard

              Answering 'how many?' requires the cardinality principle

              • One-to-one counting hard

                Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

            • One-to-one counting hard

              Counting objects to answer 'how many?' requires one-to-one correspondence

        • Sorting Data into Categories soft

          Data representation formats (pictograms, tally charts) support organising data

          • How Many in Total? soft

            Counting data in categories requires understanding cardinality

            • One-to-one counting hard

              Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

          • Pictograms and tally charts (age 6+) hard

            Organising and representing data requires data, tally, frequency, and category vocabulary

          • Sorting into categories hard

            Organising data in categories builds on classifying and counting objects in categories

            • Comparing groups: more or fewer soft

              Sorting categories by count benefits from ability to compare quantities

              • Counting objects to 20 soft

                Counting a set helps when comparing groups, but younger children (GB age 4) can compare using matching without formal counting to 20

                • How Many in Total? hard

                  Answering 'how many?' requires the cardinality principle

                  • One-to-one counting hard

                    Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

                • One-to-one counting hard

                  Counting objects to answer 'how many?' requires one-to-one correspondence

            • Counting objects to 20 hard

              Counting objects in each category requires being able to count sets of objects

              • How Many in Total? hard

                Answering 'how many?' requires the cardinality principle

                • One-to-one counting hard

                  Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

              • One-to-one counting hard

                Counting objects to answer 'how many?' requires one-to-one correspondence

      • Pictograms and tally charts (age 6+) hard

        Drawing scaled bar charts and pictograms requires axis, scale, label, and frequency vocabulary

      • Picture & Bar Graphs hard

        Single-unit bar graphs are prerequisite to scaled bar graphs

        • Sorting Data into Categories hard

          Drawing picture/bar graphs extends organising and representing data

          • How Many in Total? soft

            Counting data in categories requires understanding cardinality

            • One-to-one counting hard

              Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

          • Pictograms and tally charts (age 6+) hard

            Organising and representing data requires data, tally, frequency, and category vocabulary

          • Sorting into categories hard

            Organising data in categories builds on classifying and counting objects in categories

            • Comparing groups: more or fewer soft

              Sorting categories by count benefits from ability to compare quantities

              • Counting objects to 20 soft

                Counting a set helps when comparing groups, but younger children (GB age 4) can compare using matching without formal counting to 20

                • How Many in Total? hard

                  Answering 'how many?' requires the cardinality principle

                  • One-to-one counting hard

                    Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

                • One-to-one counting hard

                  Counting objects to answer 'how many?' requires one-to-one correspondence

            • Counting objects to 20 hard

              Counting objects in each category requires being able to count sets of objects

              • How Many in Total? hard

                Answering 'how many?' requires the cardinality principle

                • One-to-one counting hard

                  Cardinality principle builds on one-to-one correspondence — you must count correctly to know the last number tells 'how many'

              • One-to-one counting hard

                Counting objects to answer 'how many?' requires one-to-one correspondence

    • Pictograms and tally charts (age 6+) hard

      Distinguishing discrete from continuous data and choosing graphical methods requires these terms

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