Adaptive

Learn Philosophy of Science

Read the notes, then try the practice. It adapts as you go.When you're ready.

Session Length

~17 min

Adaptive Checks

15 questions

Transfer Probes

Lesson Notes Key Concepts Concept Map Worked Example Start Adaptive Practice

Lesson Notes

Philosophy of science is the branch of philosophy that examines the foundations, methods, and implications of science. It investigates questions about what counts as science, how scientific theories are constructed and validated, and what relationship scientific claims have to truth and reality. Central concerns include the nature of scientific explanation, the structure of scientific theories, and the criteria that distinguish genuine science from pseudoscience. Philosophers of science analyze how observation, experimentation, and reasoning work together to produce knowledge, and whether the methods scientists use are genuinely capable of revealing objective truths about the natural world.

The field has a rich intellectual history stretching from ancient Greek thinkers like Aristotle, who developed early frameworks for empirical inquiry, through the Scientific Revolution of the 16th and 17th centuries, which prompted new reflections on method by figures such as Francis Bacon and Rene Descartes. In the 20th century, philosophy of science became a distinct academic discipline, shaped by the logical positivists of the Vienna Circle, who emphasized verification and formal logic, and later transformed by Karl Popper's falsificationism, Thomas Kuhn's paradigm theory, Imre Lakatos's research programmes, and Paul Feyerabend's methodological anarchism. These thinkers raised profound questions about whether science progresses cumulatively or through revolutionary upheavals, and whether any single method can account for scientific success.

Today, philosophy of science intersects with virtually every scientific discipline and has practical relevance for public policy, education, and the public understanding of science. Debates continue over scientific realism versus anti-realism, the role of values in science, the nature of causation, the unity or disunity of scientific methods across disciplines, and how to interpret probabilistic and statistical reasoning. The field also engages with contemporary issues such as the replication crisis, the demarcation of science from misinformation, and the ethical dimensions of emerging technologies like artificial intelligence and genetic engineering.

You'll be able to:

Analyze the demarcation problem and evaluate criteria for distinguishing scientific theories from pseudoscience and metaphysics
Compare inductivist, falsificationist, and Kuhnian paradigm models of scientific methodology and theory change over time
Evaluate the realism versus anti-realism debate regarding whether scientific theories describe mind-independent reality accurately
Apply philosophical analysis to examine the roles of models, explanation, and causation in scientific reasoning and practice

One step at a time.

Key Concepts

Falsifiability

Karl Popper's criterion that for a theory to be considered scientific, it must make predictions that could, in principle, be shown to be false by observation or experiment. Falsifiability distinguishes science from pseudoscience, not by proving theories true, but by requiring that they be testable and potentially refutable.

Example: Einstein's general relativity predicted that starlight would bend around the sun by a specific amount. Arthur Eddington's 1919 solar eclipse observation could have falsified this prediction, but instead confirmed it, lending strong support to the theory.

Paradigm Shift

Thomas Kuhn's concept describing a fundamental change in the basic assumptions, methods, and accepted results within a scientific discipline. During a paradigm shift, the dominant framework (paradigm) is replaced by a new one that better accounts for anomalies the old paradigm could not explain.

Example: The transition from Newtonian mechanics to Einsteinian relativity constituted a paradigm shift: the very concepts of space, time, and gravity were redefined, and phenomena like Mercury's orbital precession, unexplainable under Newton, were resolved.

Demarcation Problem

The philosophical challenge of defining clear criteria that distinguish science from non-science and pseudoscience. Various proposals have been offered, including verifiability (logical positivists), falsifiability (Popper), and puzzle-solving within paradigms (Kuhn), but no single criterion has gained universal acceptance.

Example: Astrology makes predictions about human behavior based on celestial positions, but its claims are typically vague and unfalsifiable, leading most philosophers to classify it as pseudoscience rather than science.

Scientific Realism

The philosophical position that successful scientific theories describe the world approximately as it really is, and that the entities they posit (such as electrons, genes, and quarks) genuinely exist, even when they cannot be directly observed. Realists argue that the success of science would be miraculous if theories did not at least approximately correspond to reality.

Example: A scientific realist would argue that electrons are real entities, not just useful fictions, because theories positing electrons have led to the successful development of transistors, semiconductors, and modern electronics.

Induction and the Problem of Induction

Induction is the reasoning process of drawing general conclusions from specific observations. The problem of induction, identified by David Hume, is that no finite number of observations can logically guarantee a universal conclusion. We cannot prove that the future will resemble the past, yet science relies heavily on inductive reasoning.

Example: Observing that the sun has risen every morning throughout recorded history does not logically guarantee it will rise tomorrow. Yet science proceeds by assuming regularities observed in the past will continue, which Hume argued lacks ultimate logical justification.

Underdetermination of Theory by Evidence

The thesis that the available empirical evidence is always compatible with more than one theory. Since multiple theories can account for the same observations, evidence alone cannot conclusively determine which theory is correct, raising questions about how scientists choose among competing theories.

Example: Before the Michelson-Morley experiment, both the luminiferous ether theory (with a contraction hypothesis) and the early form of special relativity could account for the same optical observations, illustrating how evidence can underdetermine theory choice.

Logical Positivism

A philosophical movement originating with the Vienna Circle in the 1920s-1930s that held that meaningful statements are either analytically true (true by definition) or empirically verifiable through observation. Statements that are neither were considered meaningless, which effectively excluded much of metaphysics and theology from meaningful discourse.

Example: A logical positivist would argue that the statement 'the absolute is perfect' is meaningless because it cannot be verified by any empirical observation, whereas 'water boils at 100 degrees Celsius at sea level' is meaningful because it can be tested.

Theory-Ladenness of Observation

The idea, advanced by philosophers including N.R. Hanson and Thomas Kuhn, that all observation is influenced by the observer's prior theoretical commitments, expectations, and conceptual frameworks. There is no purely neutral observation; what scientists see is shaped by what they already believe.

Example: When Tycho Brahe and Johannes Kepler both observed the sunrise, Brahe 'saw' the sun moving around a stationary Earth (geocentric framework), while Kepler 'saw' the Earth rotating toward a stationary sun (heliocentric framework). The same visual experience was interpreted through different theoretical lenses.

More terms are available in the glossary.

Explore your way

Choose a different way to engage with this topic — no grading, just richer thinking.

Explore your way — choose one:

Explore with AI →

Concept Map

See how the key ideas connect. Nodes color in as you practice.

Worked Example

Walk through a solved problem step-by-step. Try predicting each step before revealing it.

Adaptive Practice

This is guided practice, not just a quiz. Hints and pacing adjust in real time.

Small steps add up.

What you get while practicing:

Math Lens cues for what to look for and what to ignore.
Progressive hints (direction, rule, then apply).
Targeted feedback when a common misconception appears.

Teach It Back

The best way to know if you understand something: explain it in your own words.

Keep Practicing

More ways to strengthen what you just learned.

Flashcards Mixed Practice Mistake Journal