{"CACHEDAT":"2026-11-11 17:07:17","HOWSUBJECTMAP":{},"SLUG":"argumentation-obhxMtos82","MARKDOWN":"# Argumentation\n\nArgumentation is the process of supporting a position with arguments. \n\n→ a position is the claim at the highest level: the answer to a polarising question (e.g. \"No.\").\n\n# Argument {{arguments}}\n\nan argument is used to justify (rather than explain) a claim or to persuade others of it\n\n| Part | What it does | Guiding question |\n|------|--------------|------------------|\n| **Claim** | states what is asserted | *What is asserted?* |\n| **Reason** | says why the claim holds | *Why? (\"because …\")* |\n| **Evidence** | backs the reason | *What shows this?* |\n| **Warrant** | connects the reason to the claim | *What must one accept for the reason to count?* |\n\n### Claim {{claims}}\n\na statement presented as true or right that others can question\n\n* A claim **without** supporting evidence is **unsupported**.\n* A claim **with** supporting evidence is **supported**, but not necessarily adequately backed, i.e. justified.\n\n→ **Empirical claims** can be checked against data and the scientific knowledge base.\n\n\n:::warning\n**\"Claim\" can mean different things in different contexts.** \n\n* In a **scientific explanation (CER, McNeill & Krajcik 2012)**, the claim is a conclusion about a phenomenon (e.g. *\"Plants grow faster in more light.\"*). Osborne & Patterson (2011) criticise this term: strictly, an explanation has no claim, only a phenomenon to be explained, which is empirical and not in dispute.\n* In an **argument**, the claim is a statement presented as true or right that others can question. It may be empirical (e.g. *\"Wind farms lower the value of houses with a view of them.\"*) or normative (e.g. *\"Wind farms in protected areas break a promise to future generations.\"*).\n\n→ Make explicit which kind of claim learners are dealing with.\n\n:::\n\n### Evidence\n\nwhat backs the reason of an argument\n\n| Category | Type | What it is | How it can be judged | Example | |\n|----------|------|------------|----------------------|---------|-----|\n| **Empirical** | **Data** | measurements, studies, statistics | can be verified; can be checked against the scientific knowledge base | *\"A regional study found lower sale prices for houses with a view of turbines.\"* | |\n| | **Expert statements** | statements by people with relevant expertise | can be judged for the expert’s credibility; can be traced back to the data they rest on | *“A planning expert says that property prices recover within a few years.”* | |\n| **Non-empirical** | **Personal experience** | the speaker's own observations | can be judged for credibility; not generalisable | *\"Where I used to have an open view of the hills, all I see now are turbines.\"* | |\n| **Values** | shared principles, often laid down in norms or laws | can be judged for legitimacy | *The German Federal Nature Conservation Act (§ 1) requires nature and landscape to be protected \"also in responsibility for future generations\".* | |\n| **Interests** | what the speaker or their group gains or loses | can be judged for legitimacy | *\"As homeowners, we would lose a large part of our savings.\"* | |\n| **Emotions** | feelings the speaker reports | can be taken seriously, not verified | *\"Every time I look out of my window now, I feel like a stranger in my own village.\"* | |\n\nOnly empirical evidence can be checked against the scientific knowledge base. Arguments based on values, interests, emotions, or personal experience are still relevant to socio-scientific issues: their legitimacy has to be discussed and considered, not verified.\n\n\n:::warning\n**An expert statement is mediated evidence**: what it’s worth depends on what it rests on.\n\n* Based on data, e.g. “Studies show prices recover within a few years.”: that’s indirect empirical evidence, and it can be traced back to the data. \n* Based on judgement, e.g. a forecast or a recommendation: not empirical. Only the expert’s credibility counts.\n\n:::\n\n\n:::warning\n**Reported vs. evoked emotions:** An argument that *reports* the speaker's own feelings is legitimate. An argument that *evokes* emotions in the audience to bypass critical thinking is a manipulation strategy (e.g. *\"Imagine your children growing up between grinding turbines!\"*).\n\n:::\n\n### Example\n\n**Polarising question:** *Should wind farms be built in protected landscapes to help the shift to clean energy?*\\n**Stakeholder:** local resident · **Position:** *No* (binary)\n\nTogether, the three arguments and the position form the resident's viewpoint.\n\n#### Argument 1 – personal experience <- individual perspective\n\n* Claim: *Wind farms spoil this landscape*\n* Reason: *because they replace open views with technical structures.*\n* Evidence (personal experience): *\"Where I used to have an open view of the hills, all I see now are turbines.\"*\n* Warrant: *A landscape is valued for its open, natural views.*\n\n#### Argument 2 – empirical <- economic perspective\n\n* Claim: *Wind farms lower the value of houses with a view of them*\n* Reason: *because buyers avoid homes with turbines in view.*\n* Evidence (empirical): *\"A regional study found that houses with a view of turbines sold for less, and took longer to sell, than comparable houses without such a view.\"*\n* Warrant: *A house is worth what buyers are willing to pay for it.*\n\n#### Argument 3 – values <- social perspective\n\n* Claim: *Wind farms in protected areas break a promise to future generations*\n* Reason: *because protected status is a promise to protect these areas for those who come after us.*\n* Evidence (values): *The German Federal Nature Conservation Act (§ 1) requires nature and landscape to be protected \"also in responsibility for future generations\".*\n* Warrant: *Promises made to future generations must be kept.*\n\n## Argumentation structures\n\nhow the arguments of an information item are arranged\n\n* **Linear:** presents only arguments for one position.\n* **Dual-perspective:** presents arguments for and against the position, then weighs them to reach a conclusion.\n* **Rebuttal-based:** raises counter-arguments and refutes them.\n\n## ☑ Logical Fallacies {{logical fallacy}}\n\n\n:::success\n- [ ] Check for hasty generalisations - Conclusion from too little evidence.\n- [ ] Check for false dilemmas - Limiting options to two when more exist.\n- [ ] Check for straw man arguments - Misrepresenting a position to refute it easily.\n- [ ] Check for appeals to ignorance - Claiming truth due to lack of disproof.\n- [ ] Check for appeals to authority - Assuming truth based on authority alone.\n- [ ] Check for red herrings - Distracting from the main issue.\n- [ ] Check for false causes - Confusing correlation with causation.\n- [ ] Check for ad hominem - Attacking the person, not the argument.\n- [ ] Check for ad populum - Arguing truth from popularity.\n- [ ] Check for slippery slopes - Asserting one step leads to extremes.\n- [ ] Check for circular reasoning - Using the conclusion as a premise.\n\n:::\n\n\n:::tip\n* \n* \n* \n\n:::\n\n# Explanation {{explanations}}\n\nan explanation is used to make sense of a phenomenon based on other scientific facts to generate understanding\n\n→ essential to creating new knowledge (nature of science)\n\nCER (Claim – Evidence – Reasoning; McNeill & Krajcik 2012) is widely used in school science to help students construct scientific explanations.\n\n| Part | What it does | Guiding question |\n|------|--------------|------------------|\n| **Claim** | conclusion about a phenomenon | *What happens?* |\n| **Empirical Evidence** | provides data that support the claim – appropriate and sufficient | *Which data show this?* |\n| **Reasoning** | explains why the data count as evidence for the claim, using a scientific principle | *Which principle explains it?* |\n\n\n:::tip\n## The Conflation of Argumentation and Explanation in Science Education\n\n**Explanations** and **arguments** serve different purposes (Osborne & Patterson 2011).\n\nCER was developed for **scientific explanations**. An explanation accounts for a phenomenon that is not in dispute: it links data to a scientific principle to show *why* something happens (e.g. *Plants grow faster in more light – light provides the energy for photosynthesis.*) → nature of science.\n\nAn **argument** justifies a claim that is contested and could be answered differently, e.g. a position on a polarising question. \n\n→ Use **Claim – Evidence – Reasoning** to explain empirical findings.\n\n→ Use **Claim – Reason – Evidence – Warrant** to argue for a position.\n\n* **Different logic of inquiry.** CER comes from science education and models the path of an investigation: data → claim → explanation through theory. The claim is what can be read from the data (“Plants grow faster in more light.”). The reason (mechanism) only comes in the reasoning, as an application of a scientific principle (“… because light provides energy for photosynthesis.”). In debate, by contrast, the position comes first and the reasons are often named straight away (claim → because → evidence). Those are two different genres: **explaining** vs **arguing**.\n* **Separating observation from theory.** If the claim carried the “because” (reason), students would mix what the data show with how they interpret them. The bare claim forces them to stay with the evidence first. The “because” asserts a mechanism, often a causal one, that the data alone don’t prove. Data often show only correlations. The mechanism comes from theory, so it belongs in the reasoning, where it can be checked.\n\n→ In socio-scientific issues, the line between explanation and argument can blur. The debate is then not about the explanation itself, but about which of several competing explanations is valid (e.g. human activity vs. natural variation as the cause of rising global temperatures). Sometimes the debate goes further and disputes the phenomenon itself (e.g. that global temperatures are rising at all).\n\n:::\n\n\n\n---\n\n**References**\n\n* Berland, Leema K. & McNeill, Katherine L. 2012. For whom is argument and explanation a necessary distinction? A response to Osborne and Patterson. In: *Science Education* 96 (5). 808–813. https://doi.org/10.1002/sce.21000\n* Booth, Wayne C. & Colomb, Gregory G. & Williams, Joseph M. & Bizup, Joseph & FitzGerald, William T. ⁴2016. *The Craft of Research*. Chicago: University of Chicago Press.\n* Christenson, Nina & Chang Rundgren, Shu-Nu & Höglund, Hans-Olof. 2012. Using the SEE-SEP model to analyze upper secondary students' use of supporting reasons in arguing socioscientific issues. In: *Journal of Science Education and Technology* 21 (3). 342–352. https://doi.org/10.1007/s10956-011-9328-x\n* McNeill, Katherine L. & Krajcik, Joseph S. 2012. *Supporting Grade 5–8 Students in Constructing Explanations in Science: The Claim, Evidence, and Reasoning Framework for Talk and Writing*. Boston: Pearson.\n* McNeill, Katherine L. & Lizotte, David J. & Krajcik, Joseph S. & Marx, Ronald W. 2006. Supporting students' construction of scientific explanations by fading scaffolds in instructional materials. In: *Journal of the Learning Sciences* 15 (2). 153–191. https://doi.org/10.1207/s15327809jls1502_1\n* Osborne, Jonathan F. & Patterson, Alexis. 2011. Scientific argument and explanation: A necessary distinction? In: *Science Education* 95 (4). 627–638. https://doi.org/10.1002/sce.20438\n* Toulmin, Stephen E. ²2003 [1958]. *The Uses of Argument*. Cambridge: Cambridge University Press.","RENDERMODE":"markdown","HTML":"

Argumentation

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Argumentation is the process of supporting a position with arguments.

\n

→ a position is the claim at the highest level: the answer to a polarising question (e.g. "No.").

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Argument

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an argument is used to justify (rather than explain) a claim or to persuade others of it

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
PartWhat it doesGuiding question
Claimstates what is assertedWhat is asserted?
Reasonsays why the claim holdsWhy? ("because …")
Evidencebacks the reasonWhat shows this?
Warrantconnects the reason to the claimWhat must one accept for the reason to count?
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Claim

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a statement presented as true or right that others can question

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    \n
  • A claim without supporting evidence is unsupported.\n
    • \n
  • A claim with supporting evidence is supported, but not necessarily adequately backed, i.e. justified.\n
    • \n
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→ Empirical claims can be checked against data and the scientific knowledge base.

\n
\n
\n\n

"Claim" can mean different things in different contexts.

\n
    \n
  • In a scientific explanation (CER, McNeill & Krajcik 2012), the claim is a conclusion about a phenomenon (e.g. "Plants grow faster in more light."). Osborne & Patterson (2011) criticise this term: strictly, an explanation has no claim, only a phenomenon to be explained, which is empirical and not in dispute.\n
    • \n
  • In an argument, the claim is a statement presented as true or right that others can question. It may be empirical (e.g. "Wind farms lower the value of houses with a view of them.") or normative (e.g. "Wind farms in protected areas break a promise to future generations.").\n

    → Make explicit which kind of claim learners are dealing with.

    \n
    • \n
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\n
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Evidence

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what backs the reason of an argument

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
CategoryTypeWhat it isHow it can be judgedExample
EmpiricalDatameasurements, studies, statisticscan be verified; can be checked against the scientific knowledge base"A regional study found lower sale prices for houses with a view of turbines."
Expert statementsstatements by people with relevant expertisecan be judged for the expert’s credibility; can be traced back to the data they rest on“A planning expert says that property prices recover within a few years.”
Non-empiricalPersonal experiencethe speaker's own observationscan be judged for credibility; not generalisable"Where I used to have an open view of the hills, all I see now are turbines."
Valuesshared principles, often laid down in norms or lawscan be judged for legitimacyThe German Federal Nature Conservation Act (§ 1) requires nature and landscape to be protected "also in responsibility for future generations".
Interestswhat the speaker or their group gains or losescan be judged for legitimacy"As homeowners, we would lose a large part of our savings."
Emotionsfeelings the speaker reportscan be taken seriously, not verified"Every time I look out of my window now, I feel like a stranger in my own village."
\n

Only empirical evidence can be checked against the scientific knowledge base. Arguments based on values, interests, emotions, or personal experience are still relevant to socio-scientific issues: their legitimacy has to be discussed and considered, not verified.

\n
\n
\n\n

An expert statement is mediated evidence: what it’s worth depends on what it rests on.

\n
    \n
  • Based on data, e.g. “Studies show prices recover within a few years.”: that’s indirect empirical evidence, and it can be traced back to the data.\n
    • \n
  • Based on judgement, e.g. a forecast or a recommendation: not empirical. Only the expert’s credibility counts.\n
    • \n
\n
\n
\n
\n
\n\n

Reported vs. evoked emotions: An argument that reports the speaker's own feelings is legitimate. An argument that evokes emotions in the audience to bypass critical thinking is a manipulation strategy (e.g. "Imagine your children growing up between grinding turbines!").

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Example

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Polarising question: Should wind farms be built in protected landscapes to help the shift to clean energy?
Stakeholder: local resident · Position: No (binary)

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Together, the three arguments and the position form the resident's viewpoint.

\n

Argument 1 – personal experience <- individual perspective

\n
    \n
  • Claim: Wind farms spoil this landscape\n
    • \n
  • Reason: because they replace open views with technical structures.\n
    • \n
  • Evidence (personal experience): "Where I used to have an open view of the hills, all I see now are turbines."\n
    • \n
  • Warrant: A landscape is valued for its open, natural views.\n
    • \n
\n

Argument 2 – empirical <- economic perspective

\n
    \n
  • Claim: Wind farms lower the value of houses with a view of them\n
    • \n
  • Reason: because buyers avoid homes with turbines in view.\n
    • \n
  • Evidence (empirical): "A regional study found that houses with a view of turbines sold for less, and took longer to sell, than comparable houses without such a view."\n
    • \n
  • Warrant: A house is worth what buyers are willing to pay for it.\n
    • \n
\n

Argument 3 – values <- social perspective

\n
    \n
  • Claim: Wind farms in protected areas break a promise to future generations\n
    • \n
  • Reason: because protected status is a promise to protect these areas for those who come after us.\n
    • \n
  • Evidence (values): The German Federal Nature Conservation Act (§ 1) requires nature and landscape to be protected "also in responsibility for future generations".\n
    • \n
  • Warrant: Promises made to future generations must be kept.\n
    • \n
\n

Argumentation structures

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how the arguments of an information item are arranged

\n
    \n
  • Linear: presents only arguments for one position.\n
    • \n
  • Dual-perspective: presents arguments for and against the position, then weighs them to reach a conclusion.\n
    • \n
  • Rebuttal-based: raises counter-arguments and refutes them.\n
    • \n
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☑ Logical Fallacies

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\n
\n\n
    \n
  • Check for hasty generalisations - Conclusion from too little evidence.\n
    • \n
  • Check for false dilemmas - Limiting options to two when more exist.\n
    • \n
  • Check for straw man arguments - Misrepresenting a position to refute it easily.\n
    • \n
  • Check for appeals to ignorance - Claiming truth due to lack of disproof.\n
    • \n
  • Check for appeals to authority - Assuming truth based on authority alone.\n
    • \n
  • Check for red herrings - Distracting from the main issue.\n
    • \n
  • Check for false causes - Confusing correlation with causation.\n
    • \n
  • Check for ad hominem - Attacking the person, not the argument.\n
    • \n
  • Check for ad populum - Arguing truth from popularity.\n
    • \n
  • Check for slippery slopes - Asserting one step leads to extremes.\n
    • \n
  • Check for circular reasoning - Using the conclusion as a premise.\n
    • \n
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\n\n
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Explanation

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an explanation is used to make sense of a phenomenon based on other scientific facts to generate understanding

\n

→ essential to creating new knowledge (nature of science)

\n

CER (Claim – Evidence – Reasoning; McNeill & Krajcik 2012) is widely used in school science to help students construct scientific explanations.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
PartWhat it doesGuiding question
Claimconclusion about a phenomenonWhat happens?
Empirical Evidenceprovides data that support the claim – appropriate and sufficientWhich data show this?
Reasoningexplains why the data count as evidence for the claim, using a scientific principleWhich principle explains it?
\n
\n
\n\n

The Conflation of Argumentation and Explanation in Science Education

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Explanations and arguments serve different purposes (Osborne & Patterson 2011). CER was developed for scientific explanations. An explanation accounts for a phenomenon that is not in dispute: it links data to a scientific principle to show why something happens (e.g. Plants grow faster in more light – light provides the energy for photosynthesis.) → nature of science. An argument justifies a claim that is contested and could be answered differently, e.g. a position on a polarising question. → Use Claim – Evidence – Reasoning to explain empirical findings. → Use Claim – Reason – Evidence – Warrant to argue for a position.

\n
    \n
  • Different logic of inquiry. CER comes from science education and models the path of an investigation: data → claim → explanation through theory. The claim is what can be read from the data (“Plants grow faster in more light.”). The reason (mechanism) only comes in the reasoning, as an application of a scientific principle (“… because light provides energy for photosynthesis.”). In debate, by contrast, the position comes first and the reasons are often named straight away (claim → because → evidence). Those are two different genres: explaining vs arguing.\n
    • \n
  • Separating observation from theory. If the claim carried the “because” (reason), students would mix what the data show with how they interpret them. The bare claim forces them to stay with the evidence first. The “because” asserts a mechanism, often a causal one, that the data alone don’t prove. Data often show only correlations. The mechanism comes from theory, so it belongs in the reasoning, where it can be checked.\n

    → In socio-scientific issues, the line between explanation and argument can blur. The debate is then not about the explanation itself, but about which of several competing explanations is valid (e.g. human activity vs. natural variation as the cause of rising global temperatures). Sometimes the debate goes further and disputes the phenomenon itself (e.g. that global temperatures are rising at all).

    \n
    • \n
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References

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    \n
  • Berland, Leema K. & McNeill, Katherine L. 2012. For whom is argument and explanation a necessary distinction? A response to Osborne and Patterson. In: Science Education 96 (5). 808–813. https://doi.org/10.1002/sce.21000\n
    • \n
  • Booth, Wayne C. & Colomb, Gregory G. & Williams, Joseph M. & Bizup, Joseph & FitzGerald, William T. ⁴2016. The Craft of Research. Chicago: University of Chicago Press.\n
    • \n
  • Christenson, Nina & Chang Rundgren, Shu-Nu & Höglund, Hans-Olof. 2012. Using the SEE-SEP model to analyze upper secondary students' use of supporting reasons in arguing socioscientific issues. In: Journal of Science Education and Technology 21 (3). 342–352. https://doi.org/10.1007/s10956-011-9328-x\n
    • \n
  • McNeill, Katherine L. & Krajcik, Joseph S. 2012. Supporting Grade 5–8 Students in Constructing Explanations in Science: The Claim, Evidence, and Reasoning Framework for Talk and Writing. Boston: Pearson.\n
    • \n
  • McNeill, Katherine L. & Lizotte, David J. & Krajcik, Joseph S. & Marx, Ronald W. 2006. Supporting students' construction of scientific explanations by fading scaffolds in instructional materials. In: Journal of the Learning Sciences 15 (2). 153–191. https://doi.org/10.1207/s15327809jls1502_1\n
    • \n
  • Osborne, Jonathan F. & Patterson, Alexis. 2011. Scientific argument and explanation: A necessary distinction? In: Science Education 95 (4). 627–638. https://doi.org/10.1002/sce.20438\n
    • \n
  • Toulmin, Stephen E. ²2003 [1958]. The Uses of Argument. Cambridge: Cambridge University Press.\n
    • \n
","UPDATEDAT":"2026-10-26T22:41:13.352Z","ID":"dca2a8ae-a661-4f21-bd5f-2b40d5d4fe3a","TITLE":"Argumentation"}