Effects of worked examples, example-problem, and problem-example pairs on novices’ learning

Research has demonstrated that instruction that relies more heavily on example study is more effective for novices’ learning than instruction consisting of problem solving. However, ‘a heavier reliance on example study’ has been implemented in different ways. For example, worked examples only (WE), example-problem pairs (WE-PS), or problem-example pairs (PS-WE) have been used. This study investigated the effectiveness of all three strategies compared to problem solving only (PS), using electrical circuits troubleshooting tasks; participants were secondary education students who were novices concerning those tasks. Based on prior research, it was hypothesized and confirmed that WE and WE-PS would lead to lower cognitive load during learning and higher learning outcomes than PS. In addition, the open questions of whether there would be any differences between WE and WE-PS, and whether there would be any differences between PS-WE and PS were explored. Results showed no differences between WE and WE-PS or between PS-WE and PS. This study can inform instructional designers on which example-based learning strategies to implement: it does not seem necessary to alternate example study and problem solving, but when doing so, example-problem pairs should be used rather than problem-example pairs.     

Example-based learning: The benefits of prompting organization before providing examples

Example-based learning often follows a design in which learners first receive instructional explanations that communicate new principles and concepts and second examples thereof. In this setting, using the knowledge components of the instructional explanations to explain the examples (i.e., generating principle-based self-explanations) is considered to be a highly important learning process. However, a potential suboptimality of this learning process is that it scarcely requires learners to organize the content of the instructional explanations into coherent mental representations. Thus, in two experiments we investigated whether prompting learners to organize the content of the instructional explanations before providing them with the examples (and self-explanation prompts) enhances the effectiveness of example-based learning. We consistently found that organization prompts fostered learning regardless of whether the learners also received self-explanation prompts. Hence, in example-based learning, learners should be prompted to not only generate principle-based self-explanations but also to organize the content of the instructional explanations.     

Example-based learning: Effects of different types of examples on student performance,cognitive load and self-efficacy in a statistical learning task

Previous research has indicated the disconnect between example-based research focusing on worked examples (WEs) and that focusing on modeling examples. The purpose of this study was to examine and compare the effect of four different types of examples from the two separate lines of research, including standard WEs, erroneous WEs, expert (masterly) modeling examples, and peer (coping) modeling examples, on student performance (knowledge retention, near transfer, and far transfer), cognitive load, and self-efficacy. One hundred and sixteen students participated in the study by undergoing computer-based instruction in one of the four versions differing in how examples were provided. The results showed that, overall, expert modeling examples were most effective in promoting knowledge retention, near transfer, and far transfer, while peer modeling examples were shown to be superior in fostering self-efficacy among the four different types of examples.     

Completion of partially worked-out examples as a generation strategy for improving monitoring accuracy

Students’ Judgments of Learning (JOLs) are often inaccurate: students often overestimate their future test performance. Because of the consequences that JOL inaccuracy can have for regulating study activities, an important question is how JOL accuracy can be improved. When learning texts, JOL accuracy has been shown to improve through ‘generation strategies’, such as generating keywords, summaries, or concept maps. This study investigated whether JOL accuracy can also be improved by means of a generation strategy (i.e., completing blank steps in the examples) when learning to solve problems through worked example study. Secondary education students of 14–15 years old (cf. USA 9th grade) either studied worked examples or completed partially worked examples and gave JOLs. It was found that completion of worked examples resulted in underestimation of future test performance. It seems that completing partially worked-out examples made students less confident about future performance than studying fully worked examples. However, this did not lead to better regulation of study.     

Incorporating motivation into multimedia learning

What is the role of motivation in multimedia learning? Cognitive theories of multimedia learning tend to focus on instructional methods aimed at reducing extraneous processing (such as highlighting the essential material) or managing essential processing (such as breaking a lesson into parts), whereas motivational theories tend to focus on instructional methods aimed at fostering generative processing (such as adding appealing graphics or challenging scenarios). Moreno's (2005) cognitive affective theory of learning from media is intended to better incorporate motivation and metacognition into theories of multimedia learning, helping to extend or clarify Mayer's (2009) cognitive theory of multimedia learning and Sweller's (Sweller, Ayres, & Kaluga, 2011) cognitive load theory. The research presented in this special section examines motivating instructional features intended to promote generative processing—such as adding appealing graphics (Magner, Schwonke, Aleven, Popescu, & Renkl, 2013; Plass, Heidig, Hayward, Homer, & Um, 2013) or challenging scenarios (D'Mello, Lehman, Pekrun, & Graesser, 2013). Overall, motivational features can improve student learning by fostering generative processing as long as the learner is not continually overloaded with extraneous processing or overly distracted from essential processing.     

Effects of training self-assessment and using assessment standards on retrospective and prospective monitoring of problem solving

Both retrospective and prospective monitoring are considered important for self-regulated learning of problem-solving skills. Retrospective monitoring (or self-assessment; SA) refers to students' assessments of how well they performed on a problem just completed. Prospective monitoring (or Judgments of Learning; JOLs) refers to students' judgments about how well they will perform on a (similar) problem on a future test. We investigated whether secondary education students' SA accuracy could be improved by training (Experiment 1 and 2), or by providing assessment standards (Experiment 2), and whether this would also affect the accuracy of JOLs. Accurate assessment of past performance might provide a good cue for judging future performance. Both Experiment 1 and 2 showed no effect of training on SA or JOL accuracy, but SA and JOLs were positively correlated with each other and negatively with effort. Providing standards did improve SA and JOL accuracy on identical problems, and performance on all problems.     

Using heuristic worked examples to promote inquiry-based learning

Inquiry learning can be facilitated by having students investigate the domain through a computer simulation and express their acquired understanding in a runnable computer model. This study investigated whether heuristic worked examples can further enhance students' inquiry behaviour, the quality of the models they create, and their domain knowledge. High-school students were offered a simulation of an electrical circuit and a modelling tool. Students in the experimental condition (n = 46) could consult heuristic worked examples that explained what activities were needed and how they should be performed. Students in the control condition (n = 36) did not receive this support. Cross-condition comparisons confirmed that heuristic worked examples improved students' inquiry behaviour and enhanced the quality of their models. However, few students created a model that reflected full understanding of the electrical circuit, and the expected between-group difference in posttest scores failed to appear. Based on these findings, improvements to the design of heuristic worked examples are proposed.     

Effects of worked examples on step performance in solving complex problems

The instructional effect of worked examples has been investigated in many research studies. However, most of them evaluated the overall performance of the participants in solving post-intervention problems, rather than individual step performance in multi-step problems. The two experiments reported in this article investigated the relations between using worked examples and individual step performance in solving isomorphic problems. In Experiment 1, the effect of worked examples was found for overall performance for novice learners, whereas this effect was gradually reduced from Step 1 (the most difficult one) at which the effect was the strongest, to Step 3 (the easiest one) at which the effect was the weakest or even disappeared. In Experiment 2, relatively more knowledgeable participants learned the same sets of materials, and no effect of worked examples was found for either overall performance or individual step performance. Learner levels of expertise and levels of element interactivity were used to explain the results.     

Effects of creating video-based modeling examples on learning and transfer

Two experiments investigated whether acting as a peer model for a video-based modeling example, which entails studying a text with the intention to explain it to others and then actually explaining it on video, would foster learning and transfer. In both experiments, novices were instructed to study a text, either with the intention of being able to complete a test (condition A), or being able to explain the content to others (condition B and C). Moreover, students in condition C actually had to explain the text by creating a webcam-video. In Experiment 1 (N = 76 secondary education students) there was no effect of study intention on learning (A = B), but explaining during video creation significantly fostered transfer performance (C > B; C > A). In Experiment 2 (N = 95 university students), study intention did have an effect on learning (C > A; B > A), but only actual video creation significantly fostered transfer performance (C > A).     

The 9-step problem design process for problem-based learning: Application of the 3C3R model

The design of problems is crucial for the effectiveness of problem-based learning (PBL). Research has shown that PBL problems have not always been effective. Ineffective PBL problems could affect whether students acquire sufficient domain knowledge, activate appropriate prior knowledge, and properly direct their own learning. This paper builds on the 3C3R problem design model, which is a systematic conceptual framework for guiding the design of effective and reliable problems for PBL. To help practitioners apply the 3C3R model, this paper introduces a 9-step problem design process. The initial steps guide an instructional designer through analyses on learning goal, content, and context to help select problems. Later steps ensure that the problem appropriately affords the specifications identified in the analyses. The last two steps incorporate a reflection component, as well as ensure the integrity of the 3C3R components in the problem.     

Tracing worked examples: effects on learning in geometry

Previous research has verified the benefits obtained when learners trace out worked examples with the index finger. Our study conducted two experiments to explore the reasons for this phenomenon and its generalizability. Experiment 1 compared the learning effects among tracing, non-tracing, and cueing methods. The cueing method was included to isolate the variable of drawing attention. Students employing the tracing method obtained higher transfer test scores compared to those employing the cueing and non-tracing methods, rating the far transfer test as easier. The tracing effect was verified to have a greater impact on learning than solely focusing learners’ attention. Experiment 2 compared the learning effects among three methods – tracing with the index finger, tracing with a computer mouse, and observing others tracing. Students who merely observed tracing obtained lower far transfer scores than those who traced either with their finger or with the mouse, rating the tests as more difficult. There was no significant difference between the other two groups. Tracing promotes learning more than merely observing tracing. The learning benefits of tracing partly stem from the fact that it is action-based and can be generalized to mouse tracing.     

Finding and fixing errors in worked examples: Can this foster learning outcomes?

Learning from worked examples is an effective learning method in well-structured domains. Can its effectiveness be further enhanced when errors are included? This was tested by determining whether a combination of correct and incorrect solutions in worked examples enhances learning outcomes in comparison to correct solutions only, and whether a mixture of correct and incorrect solutions is more effective when the errors are highlighted. In addition, the effectiveness of fostering self-explanations was assessed. In Experiment 1, the participants learned to solve probability problems under six conditions that constituted a 2 × 3-factorial design (Factor 1: correct and incorrect solutions with highlighting the errors vs. correct and incorrect solutions without highlighting the errors vs. correct solutions only; Factor 2: prompting written self-explanations vs. no prompts). An aptitude-treatment interaction was found: providing correct and incorrect solutions fostered far transfer performance if learners had favourable prior knowledge; if learners had poor prior knowledge correct solutions only were more favourable. Experiment 2 replicated this interaction effect. Thus, a mixture of correct and incorrect solutions in worked examples enhanced learning outcomes only for “good” learners. In addition, Experiment 2 showed that confronting learners with incorrect solutions changed the quality of their self-explanations: on the one hand, new types of effective self-explanations could be observed, but on the other hand the amount of the very important principle-based self-explanations was substantially reduced. A possible measure to prevent this negative side effect of incorrect solutions is discussed.     

Effects of performance feedback valence on perceptions of invested mental effort

We investigated whether the valence of performance feedback provided after a task, would affect participants’ perceptions of how much mental effort they invested in that same task. In three experiments, we presented participants with problem-solving tasks and manipulated the presence and valence of feedback between conditions (no, positive, or negative feedback valence), prior to asking them to rate how much mental effort they invested in solving that problem. Across the three experiments–with different problem-solving tasks and participant populations–we found that subjective ratings of effort investment were significantly higher after negative than after positive feedback; ratings given without feedback fell in between. These findings show that feedback valence alters perceived effort investment (possibly via task perceptions or affect), which can be problematic when effort is measured as an indicator of cognitive load. Therefore, it seems advisable to measure mental effort directly after each task, before giving feedback on performance.     

Case-based learning with worked examples in complex domains: Two experimental studies in undergraduate medical education

To investigate the effects of example format (erroneous examples vs. correct examples) and feedback format (elaborated feedback vs. knowledge of results feedback) on medical students' diagnostic competence in the context of a web-based learning environment containing case-based worked examples, two studies with a 2 × 2 design were conducted in the laboratory. In the first study (domain: arterial hypertension; N = 153) erroneous examples were effective in combination with elaborated feedback with respect to strategic and conditional knowledge. In the second study (domain: hyperthyroidism, N = 124), elaborated feedback supported all aspects of diagnostic competence, especially conditional knowledge.     

Improving problem solving with subgoal labels in expository text and worked examples

In highly procedural problem solving, procedures are typically taught with context-independent expository text that conceptually describes a procedure and context-dependent worked examples that concretely demonstrate a procedure. Subgoal labels have been used in worked examples to improve problem solving performance. The effect of subgoal labels in expository text, however, has not been explored. The present study examined the efficacy of subgoal labeled expository text and worked examples for programming education. The results show that learners who received subgoal labels in both the text and example are able to solve novel problems better than those who did not. In addition, subgoal labels in the text appear to have a different, rather than an additive, effect on learners compared to subgoal labels in the example. Specifically, subgoal labels in the text appear to help the learner articulate the procedure, and subgoal labels in the example appear to help the learner apply the procedure.     

Accuracy of primary school children’s immediate and delayed judgments of learning about problem-solving tasks

Accuracy of students’ judgments of learning (JOLs) plays an important role in self-regulated learning. Most studies on JOL accuracy have focused on learning word pairs and text but problems-solving tasks are also very important in education. This study investigated whether children in grade 3 could differentiate in their JOLs between problem-solving tasks that varied in complexity. Participants (N = 76, 8–10 years old) engaged in solving four arithmetic problems, rated mental effort invested in each problem, gave either immediate or delayed JOLs, and completed a test containing isomorphic problems. The negative correlation that was found between invested mental effort and JOLs suggested that children's JOLs are sensitive to differences in complexity of the problem-solving tasks. Results on the relative and absolute accuracy of JOLs showed that immediate JOLs were numerically higher than delayed JOLs, and relative accuracy of immediate JOLs was moderately accurate, whereas delayed JOLs were not.     

Effects of pairs of problems and examples on task performance and different types of cognitive load

In two studies, we investigated whether a recently developed psychometric instrument can differentiate intrinsic, extraneous, and germane cognitive load. Study I revealed a similar three-factor solution for language learning (n = 108) and a statistics lecture (n = 174), and statistics exam scores correlated negatively with the factors assumed to represent intrinsic and extraneous cognitive load during the lecture. In Study II, university freshmen who studied applications of Bayes' theorem in example–example (n = 18) or example–problem (n = 18) condition demonstrated better posttest performance than their peers who studied the applications in problem–example (n = 18) or problem–problem (n = 20) condition, and a slightly modified version of the aforementioned psychometric instrument could help researchers to differentiate intrinsic and extraneous cognitive load. The findings provide support for a recent reconceptualization of germane cognitive load as referring to the actual working memory resources devoted to dealing with intrinsic cognitive load.     

论问题解决与教学促进

大多数教育工作者都认为问题解决很重要,但是他们对什么是问题解决持有不同观点,在怎样教给学生问题解决的本领上也没有达成一致意见。各种不同观点主要集中于将问题解决视为教育目标、教育方法以及技能训练之间的差异问题上。其一,目标型问题解决不应只限于良构问题解决,而应该延伸到现实问题解决;其二,对初学者来说,方法型问题解决有其明显的局限性,给予这些学习者足够帮助,对于培养他们的问题解决能力具有重要作用;其三,技能型问题解决不应被看作是只在培养专长过程的初期才会出现,而应被视为在系统1模式与系统2模式中平行发展的一个过程。总结以上观点,综合学习设计模式完全可以用来促进此三种类型的问题解决,并其本回答了问题解决最好应该怎样教的问题。     

Information comparisons in example-based hypermedia environments: supporting learners with processing prompts and an interactive comparison tool

Global comparisons of learning from hypertext/hypermedia and traditional presentation formats like text have yet failed to show major advantages concerning the effectiveness of hypermedia learning. Thus, it is proposed in the current paper to evaluate hypermedia environments more specifically with regard to their potential to implement and support well-defined learning approaches. According to this view, an effective hypermedia design needs to be based on thorough cognitive task analyses with regard to structures, processes, and resources that are required to benefit from a specific learning approach. This claim is illustrated by two experiments in which we explored the instructional potential of hypermedia environments for improving schema acquisition from worked-out examples. A cognitive task analysis was used to identify specific types of information comparisons that are crucial for successful schema induction and that might be effectively supported by suitably designed hypermedia environments. The experiments investigated two methods for enhancing comparison processes in hypermedia-assisted learning from worked-out examples, namely, elaboration prompts and an interactive comparison tool. Both methods improved performance for near-transfer problems. Ways of extending this task-analytical approach to facilitating far transfer are also discussed.

优化学习环境对"共同体"学习动力和学习能力的影响

运用建构主义教学观，优化学习环境、结果表明：激发了大学生的学习动机，提高了他们的学习能力；教师与学生实现了角色转变，形成师生互动的良好教学情景。