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Drawing conclusions from evidence

META
ScienceScientific Inquiry|Ages 7—9|ID: mt_7VrR1GzhrN

Report on findings from enquiries using oral and written explanations, draw simple conclusions, make predictions, and suggest improvements

Mastery Evidence

  • Write or present a clear report of findings from an investigation
  • Draw a conclusion that answers the original question, supported by data
  • Make a prediction for a new situation based on the results, and suggest improvements to the method

Assessment Prompt

“After finishing an experiment, can [child] explain what they found out, what it means, what they'd predict for next time, and how they could improve the test?”

Curriculum Standards2 alignments

KS2L.Sci.WS.6The national curriculum in England
Reporting on findings from enquiries

reporting on findings from enquiries, including oral and written explanations, displays or presentations of results and conclusions

Science · Lower Key Stage 2
KS2L.Sci.WS.7The national curriculum in England
Drawing conclusions and making predictions

using results to draw simple conclusions, make predictions for new values, suggest improvements and raise further questions

Science · Lower Key Stage 2

Prerequisites4

Show full prerequisite tree
  • Teaching It Back soft

    Reporting scientific findings in your own words draws directly on the universal self-explanation habit

  • Classifying living things hard

    Must present data before reporting conclusions and making predictions

    • 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

  • Building Writing Stamina soft

    Reporting science findings orally and in writing draws on the non-fiction writing skills (recounts, explanations) established in English

  • Fair testing hard

    Must conduct fair tests before reporting on findings from enquiries

    • Simple tests and experiments hard

      Must do simple tests before setting up formal fair tests with controlled variables

      • 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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