Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 17th May 2024, 05:44:09am GMT

 
 
Session Overview
Session
27 SES 16 C: Teaching Methods in Mathematics and Business
Time:
Friday, 25/Aug/2023:
1:30pm - 3:00pm

Session Chair: Francine Athias
Location: James McCune Smith, TEAL 607 [Floor 6]

Capacity: 102 persons

Paper Session

Show help for 'Increase or decrease the abstract text size'
Presentations
27. Didactics - Learning and Teaching
Paper

How Students Learn from Instructional Explanations – A Think-aloud Study on the Impact of General Rules and Concrete Examples

Christiane Schopf

WU Vienna, Austria

Presenting Author: Schopf, Christiane

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.


Methodology, Methods, Research Instruments or Sources Used
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.

Conclusions, Expected Outcomes or Findings
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


27. Didactics - Learning and Teaching
Paper

Multiplicative Problem Posing

Francine Athias1, Olivier Lerbour2, Anne Henry2, Gérard Sensevy3

1ELLIADD, université de Franche-Comte, France; 2LINE; 3CREAD

Presenting Author: Athias, Francine

Problem solving is reported as an essential criterion for the appropriation of mathematical skills. According to mathematicians, psychologists, and mathematics educators, it allows in particular to access the meaning of mathematical notions (e.g. Schoenfeld, 1985).

With this respect, Problem Posing has been recognized as a valuable activity in mathematics education (e.g. Ellerton, 1986; Singer, Ellerton & Cai., 2013 ; Cai et al., 2015). However, researchers (e.g. Zhang & Cai, 2021) have shown the complex nature of teaching mathematics through problem posing. This paper would like to contribute to this research trend.

In this paper, we will focus on multiplicative problem posing. Our purpose is to provide a first understanding of a practice of using problem posing to teach mathematics over a long duration. Our research is part of a larger one, namely the ACE research (Arithmetic and Comprehension in Elementary School). This research proposes a mathematical program in first, second and third grade.

In ACE, a prominent emphasis is put on public representations of mathematical relations seen as “any configuration of characters, images, or concrete objects that symbolizes an abstract idea” (Goldin & Kaput, 1996) and may include manipulative materials, pictures or diagrams, spoken language, or written symbols.

Our early studies concerning one-step additive problems focused on semantic features (Riley, Greeno & Heller, 1983). An extension of our study focus on multiplicative word problems in grades 2 et 3. Our research is organized in a Cooperative Engineering (Sensevy & Bloor, 2020), where teachers and researchers have progressively built a curriculum, in the way of lesson studies (Miyakawa & Winsløw, 2009) with some representational tools. These representations have been worked out at the same time as means for exploring numbers and as problem-posing tools. In this research, the teachers belong to the research team, and are considered as teachers-researchers.

We focus on the fundamental fact, in the teaching-learning process, that students learn by relying on a previous set of meanings, that we may call an already-there (CDpE, 2019). In order to teach, a teacher has to gain a deep understanding of this already-there. For doing that, we argue that a promising avenue consists of organizing the teaching-learning process on the basis of specific examples of the way problems are posed and solved. These emblematic examples of the practice can be seen progressively as exemplar, in Kuhn's sense (Kuhn, 1977). In that way, we will see how a system of exemplars is designed to help students to pose multiplicative problems on their own. In this paper, we thus investigate the following research question: How can a teacher organize problem posing tasks by giving habits of representations of mathematical relationships?


Methodology, Methods, Research Instruments or Sources Used
To do this, we rely on concrete work in a classroom, whose teacher is part of a cooperative engineering (Sensevy et al., 2013; Jofffredo Le Brun et al., 2018), a collective of teachers and researchers gathered in a AeP network (AeP, Associated educational Places), hereafter referred to as the DEEC-ACE Collective1. This collective is carrying out a research project centered on Problem Posing, granted by the French Research National Agency  (ANR), the DECO project (Determining Efficiency of Controlled Experiments). The choice of the collective is to go from a non-problematized situation (for example, a sweet costs 2€, the children buy 4 sweets. The children pay a total of 8€) to three problematized situations (for example, a sweet costs 2€, the children buy 4 sweets. How much will they pay? ). DEEC-ACE teachers-researchers made classroom videos of the creation of multiplicative problems. Within the cooperative work,  meetings were also filmed which enabled the researchers or the teachers to review certain moments. These data were subject to editing on different scales (synopses, transcripts etc.) and enabled a better sharing of the issues raised within the engineering cooperative. Analysis focused on both the classroom sessions and the engineering dialogue using the same joint action theoretical framework (Sensevy, 2014; CDpE, 2019).
For the purpose of this presentation, a particular teacher’s class and the collective’s exchanges will be presented.

Conclusions, Expected Outcomes or Findings
Some studies (Moyer-Packenham, Ulmer & Anderson, 2012) associate improvement in students’mathematical achievement with the use of visual models and schematic drawing in the process of teaching and learning. Based on visual explicitness of relationships, other researchers (Polotskaia & Savard, 2021) argue that it is the visual explicitness of relationships which facilitates problem solving. Our results show that primary school students are able to model, to pose and to solve new multiplicative problem on their own, based on exemplars (Kuhn, 1977). At the same time we argue that some teaching actions are the key of these results. These key actions are reachable thanks to the collective work of analyzing practice. Our results relate to a better understanding of the issues involved in such a problem modeling approach.
References
Cai, J., Hwang, S., Jiang, C., & Silber, S. (2015). Problem-posing research in mathematics education: Some answered and unanswered questions. In Mathematical problem posing (p. 3-34). Springer, New York, NY.
Collectif Didactique pour Enseigner (CDpE). (2019). Didactique pour enseigner. Presses Universitaires Rennaises.
Ellerton, N. F. (1986). Children’s made-up mathematics problems—A new perspective on talented mathematicians. Educational Studies in Mathematics, 17(3), 261‑271.
Goldin G. A., Kaput J. J. (1996). A joint perspective on the idea of representation in learning and doing mathematics. In Steffe L., Nesher P., Cobb P., Goldin G., Greer B. (Eds.), Theories of mathematical learning (p. 397–430). Hillsdale, NJ: Lawrence Erlbaum.
Joffredo-Le Brun, S., Morelatto, M., Sensevy, G. & Quilio, S. (2018). Cooperative Engineering in a Joint Action Paradigm.European Educational Research Journal, vol. 17(1), 187-208.
Kuhn, T. S. (1977). Second Thoughts on Paradigm. In The Essential Tension : Selected Studies in Scientific Tradition and Change (p. 293‑319). University of Chicago Press.
Miyakawa, T. et Winsløw, C.(2009). Didactical designs for student's proportional reasoning: an ''open'' approach lesson and a ''fundamental situation''. Educational studies in Mathematics, 72-2, pp. 199-218
Moyer-Packenham, P. S., Ulmer, L. A., & Anderson, K. L. (2012). Examining Pictorial Models and Virtual Manipulatives for Third-Grade Fraction Instruction. Journal of Interactive Online Learning, 11(3).
Polotskaia, E., & Savard, A. (2021). Some multiplicative structures in elementary education : A view from relational paradigm. Educational Studies in Mathematics, 106(3), 447‑469.
Riley, M. S., Greeno, J. G., & Heller, J. 1.(1983). Development of children's problem-solving ability in arithmetic. In H.P Ginsburg (Eds). The development of mathematical thinking (p. 153-196) New-York: Academic Press.
Schoenfeld, A. H. (1985). Mathematical problem solving. Orlando, Florida: Academic Press Inc.
Sensevy, G., Forest, D., Quilio, S. & Morales, G. (2013). Cooperative engineering as a specific design-based research. ZDM, The International Journal on Mathematics Education, 45(7), 1031-1043.
Sensevy, G., & Bloor, T. (2020). Cooperative Didactic Engineering. In S. Lerman (Éd.), Encyclopedia of Mathematics Education (p. 141‑145). Springer.
Sensevy, G. (2014). Characterizing teaching effectiveness in the Joint Action Theory in Didactics: an exploratory study in primary school. Journal of Curriculum studies, 46 (5), 577-610.
Singer, F. M., Ellerton, N., & Cai, J. (2013). Problem-posing research in mathematics education : New questions and directions. Educational Studies in Mathematics, 83(1), 1‑7.
Zhang, H., & Cai, J. (2021). Teaching mathematics through problem posing : Insights from an analysis of teaching cases. ZDM – Mathematics Education, 53(4), 961‑973.


 
Contact and Legal Notice · Contact Address:
Privacy Statement · Conference: ECER 2023
Conference Software: ConfTool Pro 2.6.149+TC
© 2001–2024 by Dr. H. Weinreich, Hamburg, Germany