← Home

Reading Cladograms

REPRESENTATIONAL
Science›Dinosaurs & Paleontology|Ages 9—11|ID: mt_cSPtyLF3q1

Read and create simple cladograms (branching diagrams) that show how groups of dinosaurs are related based on shared features, understanding that species sharing more features are more closely related

Mastery Evidence

  • Explain that a cladogram shows evolutionary relationships based on shared features
  • Read a simple cladogram to identify which two dinosaurs share the most recent common ancestor
  • Add a new species to a partially completed cladogram based on its listed features

Assessment Prompt

“If [child] saw a branching tree diagram showing dinosaur relationships, could they explain which dinosaurs are most closely related by looking at where the branches split?”

Prerequisites2

Show full prerequisite tree
  • Using evidence to answer questions soft

    Identifying differences/similarities (curriculum inquiry skill) supports reading cladograms based on shared features

    • Drawing conclusions from evidence hard

      Must draw conclusions before identifying patterns and using evidence to support findings

      • 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

    • Reading between the lines soft

      Using evidence to answer scientific questions mirrors the skill of asking and answering questions about key details in informational texts in English

    • Could there be another explanation? soft

      Identifying similarities and differences in evidence opens up space for alternative explanations — patterns that differ from expectations prompt the habit of seeking alternatives

      • Changing Your Mind with Evidence hard

        Actively seeking alternative explanations requires first having the habit of not defending your original interpretation against the evidence

        • Observation vs Interpretation hard

          Being willing to revise a hypothesis requires first distinguishing observation from interpretation — you can only update your interpretation if you recognise it as separate from the data

          • 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

        • Learning from Mistakes soft

          Changing your mind when evidence contradicts your prediction is the science form of the universal error-analysis habit — treating surprises as information rather than failures

          • Checking Your Own Work soft

            Investigating why something was wrong grows from the earlier habit of checking whether an answer seems right

          • Trying a New Approach hard

            Error analysis requires the habit of trying different approaches — you need to have tried something before you can analyse what went wrong

            • Feeling of not understanding hard

              Strategy switching is triggered by noticing the current approach isn't working — requires comprehension monitoring

              • Asking for Help hard

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

            • Planning a Task hard

              Switching strategy requires first having made a plan — you can only switch away from something you chose deliberately

              • Checking Your Own Work hard

                Planning before a task grows from the habit of checking back after finishing — both are self-regulatory bookends

      • Understanding Why soft

        Asking 'is there another explanation?' is the scientific form of the universal elaborative-interrogation habit

        • Teaching It Back hard

          Asking 'why does this work?' requires first being able to explain what you know — interrogation builds on explanation

    • Spotting Patterns soft

      Identifying similarities, differences, and changes in scientific data is the science form of the universal pattern-and-structure recognition habit

      • Connecting New & Old Ideas soft

        Spotting patterns across domains is an extension of the habit of connecting new ideas to existing ones

        • Thinking Before Starting hard

          Making connections between new and old ideas requires the habit of activating prior knowledge first

          • Persisting When It's Hard hard

            Activating prior knowledge requires the foundational habit of persistent engagement with new material

  • Dinosaur Hip Groups hard

    Must understand dinosaur classification before creating cladograms showing relationships

Unlocks1