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G. Biswas et al. (Eds.): AIED 2011, LNAI 6738, pp. 222–229, 2011. © Springer-Verlag Berlin Heidelberg 2011 When Is It Best to Learn with All Worked Examples? Bruce M. McLaren and Seiji Isotani Carnegie Mellon University, Human Computer Interaction Institute, 5000 Forbes Avenue, Pittsburgh, Pennsylvania {bmclaren,sisotani}@cs.cmu.edu Abstract. Worked examples have repeatedly demonstrated learning benefits in a range of studies, particularly with low prior knowledge students and when the examples are presented in alternating fashion with problems to solve. Recently, worked examples alternating with intelligently-tutored problems have been shown to provide at least as much learning benefit to students as all tutored problems, with the advantage of taking significantly less learning time (i.e., more efficiency) than all tutored problems. Given prior findings, together with the prevailing belief that students should be prompted to actively solve problems after studying examples, rarely have all worked examples been tried as a learning intervention. To test the conventional wisdom, as well as to explore an understudied approach, a study was conducted with 145 high school students in the domain of chemistry to compare alternating worked examples / tutored problems, all tutored problems, and all worked examples. It was hypothesized that the alternating condition would lead to better results (i.e., better learning and/or learning efficiency) than either all examples or all tutored problems. However, the hypothesis was not confirmed: While all three conditions learned roughly the same amount, the all worked examples condition took significantly less time and was a more efficient learning treatment than either alternating examples/tutored problems or all tutored problems. This paper posits an explanation for why this (seemingly) surprising result was found. Keywords: worked examples, intelligent tutors. 1 Introduction The learning benefits of worked examples have been thoroughly researched and well documented [1]. A key theoretical reason often cited for the benefits of worked examples is cognitive load theory [2]. In particular, compared to problem solving, worked examples are believed to lessen extraneous load, which refers to the use of cognitive resources for mental processes, such as search. While search methods such as means-ends analysis are often critical to solving problems, such approaches exhaust the cognitive resources of students that could be used for learning. By providing learners with a worked-out solution to study, which worked examples do, the need for search is avoided and students can concentrate on building cognitive schemas, so they can more readily solve similar problems in the future. Many studies have demonstrated the learning advantages of alternating worked examples with problems to solve (e.g., [3, 4, 5]). The learning benefits observed inWhen Is It Best to Learn with All Worked Examples? 223 these studies appear to leverage a two-step learning process in line with cognitive load theory. First, it is helpful for a student, particularly one with low prior knowledge in the domain of interest, to review an example to lessen cognitive load and maximize initial learning. The cognitive schema created by the student while studying the example can then be used to, second, tackle an isomorphic problem to solve, i.e., one with similar structure and/or elements to the example. Instead of grappling with many new and unfamiliar details in solving the new problem, as well as searching through memory, the student can easily recall the similar, just-reviewed example while, at the same time, engage in active cognitive processing to (hopefully) strengthen their understanding of this type of problem and thus achieve deep learning [5]. More recent studies have investigated the benefits of alternating worked examples with intelligently tutored problems [6]. These empirical investigations differ from more traditional worked examples research by the inclusion of tutored problems to solve, which provide step-by-step guidance in the form of hints and error feedback and thus offer more scaffolding than ordinary problems. Tutored problems are a middle ground between worked examples and problem solving: they allow students, if they wish, to create worked examples from the problems (by e.g. drilling down to bottom-out hints) but, at the same time, students can actively attempt to solve problems. These recent studies also differ from earlier research in that they have mostly been conducted in the classroom, a decidedly more difficult environment to test learning interventions than the laboratory setting of most prior studies. All of these recent studies have tested the hypothesis that replacing some tutored problems with worked examples will enhance student learning by reducing instructional time and/or increasing student learning, in terms of retention and transfer. For instance, Schwonke and colleagues [7], in two studies in the domain of geometry, found that a fading worked examples condition, one in which some tutored problems were replaced with examples that were, in turn, gradually replaced first by partially completed examples and, later, by fully-tutored problems, led to as much learning and transfer as a control condition of all tutored problems, yet in significantly less time. McLaren et al’s findings [8] in three studies in the domain of chemistry corroborated the efficiency findings of Schwonke et al – more specifically, an alternating example-tutored problem condition yielded the same learning as a tutored-problems-only control, but with significantly better learning efficiency. In summary, it appears that adding worked examples to tutored problem solving helps learning, but the benefits are mostly in improving learning efficiency. Learning outcomes are generally not as significant as those reported in untutored problem solving research (e.g., [3, 4]), which may be explained, at least in part, by the tougher control condition all tutored problems presents. Given these past findings, both in untutored and tutored problem solving research, together with the generally accepted two-step learning process discussed above and the cognitive load theory underlying it, it is not surprising that researchers have infrequently tested the benefits of presenting students with all worked examples. Why would we expect superior learning benefits with all worked examples when the


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