Session Information
27 SES 16 C, Teaching Methods in Mathematics and Business
Paper Session
Contribution
The proposed paper deals with the question how students learn from instructional explanations (in business teaching), in particular, to what extent they rely on the presented concrete example and/or on the explicated general rule when solving application and transfer tasks.
For concept learning, Tennyson and Cocchiarella (1986) state – referring to prototype learning research – that general definitions are helpful but that examples play a predominant role for understanding. Several experiments investigating the acquisition of psychological concepts substantiate the claim that giving definitions and examples leads to better learning than giving definitions only (Balch 2005; Rawson/Ruthann/Jacoby 2015), and suggest that students make more use of known examples than of general definitions when classifying new cases (Zamary/Rawson 2018).
Similarly, in teaching principles that enable students to deal with certain types of tasks/problems, the best strategy seems to be to explicate the general principle and to illustrate and elaborate it using a variety of examples (Fortmüller 1997). Several experimental studies document that abstract and concrete information complement each other in principle-learning and, thus, the combination of rule and example training fosters transfer (Chen/Daehler 2000; Cheng et al. 1986; Fong/Krantz/Nisbett 1986). Theories of analogical reasoning generally assume that concrete examples are easier to understand than abstract principles, and that generated understanding can be transferred to novel situations (Gentner/Loewenstein/Thompson 2003). However, the relation of abstract information and example details in mental representations as well as their role in problem solving is questionable (Reeves/Weisberg 1994). Based on structure-mapping theory (Gentner, 1983, 1989) and pragmatic schema theory (Gick/Holyoak 1983; Holyoak/Koh 1987) on the one hand and exemplar theories on the other hand, Ross (1987) formulates two contrasting hypotheses: According to the principle-cuing hypothesis, learners use examples to access the abstract principle, which is then – once understood – directly applied to solve a novel problem. According to the example-analogy hypothesis, a principle is only understood in terms of an example, such that learners need the example in order to be able to apply the principle to the problem at hand. Empirical findings mostly support the example-analogy view (Chen/Daehler 2000; Holyoak/Koh 1987; Ross 1987). Ross and Kilbane (1997) show that when an abstract principle is explained and afterwards illustrated by an example, students primarily rely on the example. They argue that it might be preferable to employ an embedded-principle method in order to tie the explanation to the example.
In order to investigate the impact of concrete examples and general rules in instructional explanations in business teaching on students’ understanding and achievement, Schopf (2021) compared several versions of a teacher explanation (example-rule, rule-only, example-only) on the topic “break-even point” in an experimental study with second year business academy students. The hypothesis that a teacher explanation with an example-rule pattern is perceived as more understandable and results in superior achievement, than a teacher explanation which only contains the general rule, was confirmed. The finding that in the application tasks mean performance of the example-rule and the example-only groups was significantly better than mean performance of the rule-only group, while mean performance in the transfer task was generally very poor and did not significantly differ between groups, may lead to the conclusion that students from the example-rule and the example-only groups were able to solve the application tasks by using the concrete example as an analogue without having fully understood the underlying general principle. However, students’ notes on the work sheets did not provide sufficient evidence to support this assumption.
Thus, in a follow-up project the author wants to dive deeper and analyse students’ thinking processes.
Method
For this purpose, a qualitative think-aloud study with first and/or second year business academy students who do not have any prior knowledge about the break-even point is planned. The idea is to reuse the recorded standardised teacher explanation versions from the experimental study. In an interview-like situation one of these versions will be shown to an individual student. The student will be asked to watch the explanation and take notes. Afterwards he/she will be handed a work sheet with a replication, an application and a transfer task. The student will be asked to verbalise as accurately as possible his/her thoughts while working on the tasks. If necessary, the interviewer will ask more detailed questions in order to elicit further explications. The interview will be recorded on video in order to allow for a simultaneous analysis of students’ verbalisations and notes taken on the work sheet. In a first step the explanation version which explicates the concept break-even point and the principle of its calculation by means of a concrete example and in general terms (example-rule explanation) will be used for about ten interviews. For comparative reasons, in a second step the explanation version which explicates the same concept and principle in general terms only (rule-only explanation) as well as the explanation version which explicates this concept and principle by means of a concrete example only (example-only explanation) will be used for about another ten interviews each. In order to enhance the representativeness of the sample, the author will try to find volunteers from different classes and schools and to achieve a balance between genders, students with and without a migration background as well as students with high, average and low grades in the subjects business administration and accounting. Data collection and analysis will be carried out iteratively until a certain level of theoretical saturation is reached. Thus, the exact number of interviews will depend on the quality of the interviews and the conclusions that can be drawn from the ongoing analysis.
Expected Outcomes
The goal of the study is to find out more about students’ thinking processes when trying to recall, apply and transfer what they have learned from an instructional explanation containing a concrete example and/or the general rule. The following questions will be investigated in the analysis: How do students – after having watched an example-rule, an example-only or a rule-only instructional explanation – approach an application task, how do they approach a transfer task and which fallacies typically occur in the solution process? Which role do concrete example and general rule play in students’ thinking and reasoning? To what extent are students able to autonomously apply a general rule to solve a concrete task? To what extent are students able to autonomously derive a general rule from a concrete example? To what extent are students able to connect concrete example and general rule if both are presented in an explanation? To what extent are students able to fully understand a concept/principle from an instructional explanation following an example-rule pattern? Ideally, the findings will allow for the deduction of more detailed design guidelines for instructional explanations in business teaching with regard to the use of general rules and examples.
References
Balch, W. R. (2005): Elaborations of introductory psychology terms: Effects on test performance and subjective ratings. In: Teaching of Psychology, 32/1/29–34 Chen, Z. / Daehler, M. W. (2000): External and internal instantiation of abstract information facilitates transfer in insight problem solving. In: Contemporary Educational Psychology, 25/4/423–449 Cheng, P. W. / Holyoak, K. J. / Nisbett, R. E. / Oliver, L. M. (1986): Pragmatic versus syntactic approaches to training deductive reasoning. In: Cognitive Psychology, 18/293–328 Fong, G. T. / Krantz, D. H. / Nisbett, R. E. (1986): The effects of statistical training on thinking about everyday problems. In: Cognitive Psychology, 18/253–292 Fortmüller, R. (1997): Wissen und Problemlösen. Wien: Manz Gentner, D. (1983): Structure-mapping: A theoretical framework for analogy. In: Cognitive Science, 7/2/155–170 Gentner, D. (1989): The mechanisms of analogical reasoning. In: Vosniadou, S. / Ortony, A. (Eds.): Similarity and analogical reasoning. Cambridge: Cambridge University Press, 199–241 Gentner, D. / Loewenstein, J. / Thompson, L. (2003): Learning and transfer: A general role for analogical encoding. In: Journal of Educational Psychology, 95/2/393–408 Gick, M. L. / Holyoak, K. J. (1983): Schema induction and analogical transfer. In: Cognitive Psychology, 15/1–38 Holyoak, K. J. / Koh, K. (1987): Surface and structural similarity in analgogical transfer. In: Memory & Cognition, 15/4/332–340 Rawson, K. A. / Ruthann, T. C. / Jacoby, L. L. (2015): The power of examples: Illustrative examples enhance conceptual learning of declarative concepts. In: Educational Psychology Review, 27/3/483–504 Reeves, L. M. / Weisberg, R. W. (1994): The role of content and abstract information in analogical transfer. In: Psychological Bulletin, 115/3/381–400 Ross, B. H. (1987): This is like that: The use of earlier problems and the separation of similarity effects. In: Journal of Experimental Psychology, 13/4/629–639 Ross, B. H. / Kilbane, M. C. (1997): Effects of principle explanation and superficial similarity on analogical mapping in problem solving. In: Journal of Experimental Psychology, 23/2/427–440 Schopf, C. (2021): Verständlich und motivierend erklären im Wirtschaftsunterricht. Habilitation thesis, WU Vienna Tennyson, R. D. / Cocchiarella, M. J. (1986): An empirically based instructional design theory for teaching concepts. In: Review of Educational Research, 56/1/40–71 Zamary, A. / Rawson, K. A. (2018): Which technique is most effective for learning declarative concepts - Provided examples, generated examples, or both? In: Educational Psychology Review, 30/1/275–301
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