Translated by P. Colton, S. Bundy, and T. Dove, I. Van Eemeren and B. Garssen eds. Dunham, W. Epstein, S. Gasteren, A. Grosholz, E. Hairer, E. Hanson, N. Feigl and G. Maxwell eds. Heath, T. Hitchcock, D. Blair, C.
Forms of Reasoning in the Design Science Research Process | SpringerLink
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Leng, M. Leng, A. Paseau, and M. Potter eds. Macedo L. Wiggins ed. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and the merits and shortcomings of both activities. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society.
The textbook is designed to be adaptable to a wide variety of different kinds of courses.
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In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses. Causal Reasoning, Misc in Epistemology. Experimentation in Science in General Philosophy of Science. Explanation, Miscellaneous in General Philosophy of Science. Edit this record.
Mark as duplicate. Find it on Scholar. Request removal from index. Revision history. Configure custom resolver. Richard Kitchener - - Upa. Critical Reasoning: A Practical Introduction. The precise explanation for this discrepancy between tests is unknown; 27 however, the low psychometric quality of the CCTST may contribute.
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The CCTST exhibits low internal consistency and poor construct validity, 43 , 44 , 45 , 46 making it difficult to give scores a clear interpretation. Moreover, the two forms of the CCTST are not statistically equivalent, 44 , 47 and share identical or trivially modified items. Similar problems beset other common tests of critical thinking.
Our study had two distinctive pedagogical features.
First, students learned how to visualize arguments contained in real scholarly texts, as opposed to highly simplified arguments. Second, their work was met with detailed and timely instructor feedback. Argument visualization provided the medium in which students could engage these texts and discuss their interpretations with the instructors and each other, and this was critically supported through effective pedagogy. The present findings do not fully disentangle the contributions of the use of argument visualization from the intensive and interactive nature of the course, as well as its explicit focus on argument analysis.
While control students did participate in the standard Princeton University curriculum which places a high value on rigorous analytical reasoning , they did not receive intensive training in non-visual argument analysis. Disentangling these factors is a critical priority for future research, which will both advance our theoretical understanding of the underlying learning mechanisms and provide a clearer guide for curriculum development.
Indeed, in order to more directly evaluate the contribution of training in argument visualization, per se, we are currently conducting a series of controlled laboratory experiments. In these studies, naive participants are instructed in argument analysis using either prose-based or diagram-based examples.
All participants then read a series of brief argumentative texts, and answer multiple-choice questions assessing their ability to identify the logical structure latent in each. As they answer these questions, the diagram group inspects visualizations of the arguments, whereas the prose group views matched verbal descriptions. Insofar as the graphical elements of argument visualizations help students to analyze texts, we hypothesize that the visualization group will perform better and show greater improvement than the group who train on prose examples only.
On the other hand, if the graphical elements do not enhance student comprehension, then we expect both groups to perform equivalently.data.adtags.pro/topographic-surveying-including-geographic-exploratory.php
Abductive Reasoning: Logic, Visual Thinking, and Coherence
Taken together, our findings show that organizing good pedagogical practices e. We hope that future studies will investigate how students move beyond using argument visualizations to analyze existing prose and employ this technique to compose novel arguments. In the long run, findings from this line of inquiry will both deepen our understanding of how concrete visualizations support abstract reasoning and provide a model for improving analytical-reasoning pedagogy.
Due to institutional constraints, we could not randomize students into the seminar and control groups but had to use standard mechanisms for enrolling students; thus, our study was a quasi-experiment. Recruitment of control students focused on individuals who expressed interest in the seminar but were not enrolled due to limited space in the class. Thus, despite our use of a convenience sample, we were able to assemble a group of control students that did not differ significantly from the seminar group in their intended college majors at pretest, indicating that they took similar courses other than the seminar.
Moreover, pretest and self-reported SAT subject scores indicated that students in the two groups had comparable skills at pretest. Control students did not receive explicit training in argument analysis using either visual or non-visual techniques. Comparing paid and unpaid participants revealed no meaningful differences in test scores or outcome measures. We base our analysis on data from all control students and all students who enrolled in all iterations of the seminar.