The proposed paper deals with the design of instructional explanations in business teaching. In particular, it investigates the research question, whether (concrete) examples in teacher explanations do have an impact on students’ understanding and achievement.

The literature on quality criteria for instructional explanations attaches great significance to the use of examples (e.g., Findeisen 2017, Kulgemeyer 2018, Leinhardt 2001, Schopf/Zwischenbrugger 2015, Tharby 2018). It is assumed that examples facilitate understanding and support learning and transfer.

According to Tennyson and Cocchiarella's (1986) instructional design theory for teaching concepts general definitions are helpful in concept learning but examples play a predominant role for understanding. Similarly, according to Fortmüller’s (1997) theoretical considerations on 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 elaborate and illustrate the principle using a variety of examples in different contexts. Theories of analogical reasoning 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, empirical evidence that shows the actual effects of concrete examples in instructional explanations is scarce. Quantitative research on teacher effectiveness and teacher clarity (e.g., Armento 1977, Cruickshank/Kennedy 1986) as well as qualitative analysis of teacher explanations (e.g., Geelan 2003, Treagust/Harrison 2000) have, inter alia, identified examples as an important ingredient of effective explanations. But, these studies do not allow for the deduction of specific propositions on the impact of examples, nor of actual causal conclusions. Several experiments investigating the acquisition of psychological concepts substantiate the claim that giving definitions and examples leads to better learning than giving definitions only (e.g., Balch 2005, Rawson/Ruthann/Jacoby 2015). Also, 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 (e.g., Chen/Daehler 2000, Cheng/Holyoak/Nisbett/Oliver 1986, Fong/Krantz/Nisbett 1986). But, most of this work deals with learning from texts (self-study materials) and stems from the fields of psychology, natural sciences, and mathematics. There is hardly any research available that focuses on the role of examples in teacher explanations. What is more, in the field of business teaching there is generally a lack of research on instructional explanations. Thus, to the best of my knowledge the presented study is the first that directly investigates the effects of examples in oral teacher explanations of business contents on students’ understanding and achievement.

The aim of the study was to test the following hypotheses. Hypothesis (I): Teacher explanations which explicate a concept or principle by means of a (concrete or abstract) example and in general terms (a) are perceived as more understandable and (b) result in superior achievement, when compared to teacher explanations which explicate a concept or principle in general terms only. Hypothesis (II): Teacher explanations which explicate a concept or principle by means of a concrete example and in general terms (a) are perceived as more understandable and (b) result in superior achievement, when compared to teacher explanations which explicate a concept or principle by means of an abstract example and in general terms. Hypothesis (III): Teacher explanations which explicate a concept or principle by means of a concrete example and in general terms (a) are perceived as more understandable and (b) result in superior achievement, when compared to teacher explanations which explicate a concept or principle by means of a concrete example only.

To test these hypotheses an experiment with a between-subjects design was conducted. Six versions of a teacher explanation on the topic “break-even point” were video-recorded: (A) concrete example with concrete visualisation plus general rule with abstract visualisation, (B) abstract example with concrete visualisation plus general rule with abstract visualisation, (C) general rule and abstract visualisation only, (D) concrete example and concrete visualisation only, (E) concrete example with abstract visualisation plus general rule with abstract visualisation, (F) abstract example with abstract visualisation plus general rule with abstract visualisation. All explanation versions comprised the same basic information, followed the same structure and had about the same length. 68 second year classes from 26 business academies in Vienna and Lower Austria participated in the study. The adjusted sample comprised of 1,264 students. The experiment started with a pre-questionnaire. The main objective was to check the students’ prior knowledge about the concept to be explained. The second objective was to collect information about the sample regarding further variables that might influence students’ evaluation of and learning from the explanation, such as gender, age, first language, grades, and motivation to learn. The students were then asked to carefully watch the explanation (one of the six versions), to take notes and to try to understand the information given. The third part of the experiment was a post-questionnaire consisting of three sections. In section one students should evaluate the overall understandability of the explanation on a five-point rating scale and give spontaneous reasons for their rating (open-ended question). To evaluate the understandability of the explanation in more detail, section two comprised eleven statements, derived from Schopf and Zwischenbrugger's (2015) heuristic for the design of instructional explanations in business teaching. In section three students were asked to self-assess as to how far the explanation helped them to achieve the defined learning objectives. Finally, to measure students’ actual achievement, a post-test was administered, which contained a recall-task, two application tasks, and a transfer task. All materials were embedded in an online survey tool. The open-ended items including test items were coded by two independent coders (kappa values >.60 for all and >.75 for most items). To assess the effects of the different explanation versions Kruskal-Wallis tests, ANOVAs as well as ANCOVAs were conducted, and effect sizes were calculated. Post hoc power calculation based on the smallest significant effect found showed an achieved power of more than 99%.

Data analyses showed a similar pattern for all dependent variables. The concrete example explanation versions led to significantly or at least by trend better results than the abstract example explanation versions and the without example explanation version. Students rated the concrete example explanation versions as more understandable. Mean self-assessments of the concrete example explanation groups were better for all learning objectives. Consistently, students who had watched one of the concrete example explanation versions were also significantly or at least by trend more successful in the post-test. Effects were generally rather small, and only for perceived understandability was a moderate effect found. No relevant differences emerged between the explanation versions using abstract and concrete visualisations and the explanation versions using the abstract visualisation only. The findings clearly support research hypothesis (II), but yield only restricted support for research hypothesis (I). Statistically significant differences were found between the concrete example explanation versions and the without example explanation version, but no statistically significant differences were found between the abstract example explanation versions and the without example explanation version except for the application task scores. Research hypothesis (III) has to be dismissed in the present form. Students rated the explanation version with concrete example and without general rule by trend best. Contrary to expectations, the students who had watched this explanation version also performed comparatively well in the application and transfer tasks. Only in the recall task did they show a poorer performance than the other groups. Although several questions remain open for further research, it can be concluded, that in order to be highly understandable and to enhance achievement, (business) teachers should include concrete examples in their explanations.

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