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Abductive Logic·Advanced·5 lessons·~260 min
How to compare explanations without confusing them with proofs
What you'll learn
Lessons
Introduces inference to the best explanation and distinguishes abductive reasoning from deduction and induction. Establishes the 'observations, rivals, comparison, proportionate conclusion' routine used in later lessons.
Teaches students a repeatable structure for writing and evaluating best-explanation arguments, based on observations, hypotheses, comparison, and proportionate conclusions.
Explains how to compare candidate hypotheses using standards such as scope, fit, simplicity, and coherence, and warns against weighting only one virtue at the expense of the others.
Students diagnose flawed abductive arguments and revise them to make the reasoning more rigorous, with particular attention to missing rivals, overstated conclusions, and 'best of a bad lot' mistakes.
An integrative lesson that asks students to run the full best-explanation cycle on mixed cases: list candidate explanations, apply explanatory virtues, pick the best, and check whether the winning explanation is actually good enough or merely the best of a bad lot.
How to study
Each lesson opens with a guided walkthrough — read it before the activity.
Look at why each step follows, not just what the answer is.
Know which rule applies and what would make the response weak before you start.
Optional context for the unit. Each lesson surfaces the concepts and rules it uses — these are here when you want the bigger picture.
A fact or data point that calls for explanation.
A candidate explanation proposed to account for the observations.
A form of reasoning in which we infer that one hypothesis is currently the best explanation of the evidence when compared with rivals.
The range of evidence or observations a hypothesis successfully explains.
How closely a hypothesis matches the specific features of the observations, as opposed to merely being consistent with them.
A virtue of a hypothesis that explains the observations without introducing unnecessary assumptions or entities.
The degree to which a hypothesis fits with well-supported background knowledge and with other accepted claims.
A concern that the 'best explanation' might still be poor if the real explanation was never among the considered candidates.