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An empirical test of a taxonomy of responses to anomalous data in science
343
Citations
28
References
1998
Year
Inquiry-based LearningScience EducationAnomaly DetectionEducational PsychologyScience TeachingEducationCausal InferenceSocial SciencesReproducible ResearchStem EducationMathematics EducationScience TeachersData ScienceBiasStatisticsCognitive ScienceEmpirical TestScientific LiteracyData-driven ScienceLearning SciencesOutlier DetectionKnowledge DiscoveryScientific RationalityPhysical SciencesReasoningTeachingNatural SciencesNovelty DetectionEpistemologyScience And Technology StudiesAnomalous DataDescriptive Research
The purpose of this study was to test a taxonomy of seven proposed responses to anomalous data. Our results generally supported the taxonomy but indicated that one additional type of response should be added to the taxonomy. We conclude that there are eight possible responses to anomalous data: (a) ignoring the data, (b) rejecting the data, (c) professing uncertainty about the validity of the data, (d) excluding the data from the domain of the current theory, (e) holding the data in abeyance, (f) reinterpreting the data, (g) accepting the data and making peripheral changes to the current theory, and (h) accepting the data and changing theories. We suggest that this taxonomy could help science teachers in two ways. First, science teachers could use the taxonomy to try to anticipate how students might react to anomalous data so as to make theory change more likely. Second, science teachers could use the taxonomy as a framework to guide classroom discussion about the nature of scientific rationality. In addition, the taxonomy suggests directions for future research. © 1998 John Wiley & Sons, Inc. J Res Sci Teach 35: 623–654, 1998.
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