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Classifying living things

PROCEDURAL
Science›Scientific Inquiry|Ages 7—9|ID: mt_7IFpDVNsmt

Gather, record, classify, and present data in a variety of ways including tables, bar charts, labelled diagrams, and keys

Mastery Evidence

  • Organise data into a clear table with appropriate headings
  • Create a bar chart or pictogram from collected data
  • Use labelled diagrams and classification keys to present findings

Assessment Prompt

“After doing an experiment, can [child] put their results into a neat table, draw a bar chart, and add labels to a diagram to show what they found?”

Curriculum Standards2 alignments

KS2L.Sci.WS.4The national curriculum in England
Gathering, recording, classifying and presenting data

gathering, recording, classifying and presenting data in a variety of ways to help in answering questions

Science · Lower Key Stage 2
KS2L.Sci.WS.5The national curriculum in England
Recording findings using scientific language and diagrams

recording findings using simple scientific language, drawings, labelled diagrams, keys, bar charts, and tables

Science · Lower Key Stage 2

Prerequisites3

Show full prerequisite tree
  • 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

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