Background Similar to other domains, engineering education lacks a framework to classify active learning methods used in classrooms, which makes it difficult to evaluate when and why they are effective for learning.Purpose/Hypothesis This study evaluated the effectiveness and applicability of the Differentiated Overt Learning Activities (DOLA) framework, which classifies learning activities as interactive, constructive, or active, for engineering classes. We tested the ICAP hypothesis that student learning is more effective in interactive than constructive activities, which are more effective than active activities, which are more effective than passive activities.Design/Method We conducted two studies to determine how and to what degree differentiated activities affected student learning outcomes; we measured student knowledge and understanding of materials science and engineering concepts.Results Study 1 showed that students scored higher on all postclass quiz questions after participating in interactive and constructive activities than after the active activities. Student scores on more difficult, inference questions suggested that interactive activities provided significantly deeper learning than constructive or active activities. Study 2 showed that student learning, in terms of gain scores, increased systematically from passive to active to constructive to interactive, as predicted by the ICAP hypothesis. All the increases, from condition to condition, were significant.Conclusions Our analyses of classroom activities in the engineering domain showed that they fit within the taxonomy of the DOLA framework. The results of the two studies provided evidence to support the predictions of the ICAP hypothesis.

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Engineering educators often experiment with various teaching methods to figure out which methods most effectively improve learning. A common research design uses a pairwise comparison -pitting one pedagogical method against another method and comparing the results. Often the two methods compared are traditional lecture versus active learning. These pairwise comparison studies are commonly framed as investigating the question, Does active learning work? This question has been uppermost in the mind of many in the engineering education community (Streveler & Smith, 2006). In this guest editorial we argue that the broad research question, Does active learning work? has been sufficiently answered for most types of students (Freeman et al., 2014;Prince, 2004;Springer et al., 1999) and contend that it is now appropriate and helpful to take a more nuanced view of active learning. Drawbacks of the Current ApproachWhat's wrong with asking, Does active learning work? We put forward two concerns.First, we argue that this broad question has been sufficiently answered. A recent metaanalysis by Freeman et al. (2014) found that, on average, students who were active learned more than students who were passive. The shift was significant -learning improved by about 0.5 standard deviations, a result that agrees with an earlier meta-analysis of small-group activities (Springer, Stanne, & Donovan, 1999). Prince (2004) conducted a literature review to compare active and passive learning in engineering education and found a generally positive trend -although he did not quantify the effect. These consistent results allow us to be confident that, on average, engaging students through active strategies enhances learning.A second concern lies in the fact that the phrase "active learning" encompasses a wide spectrum of learning activities -all contrasted with passively sitting and listening to a lecture. An example offers an illustration of the limitations of this approach. Suppose instead of investigating learning gains, we wanted to investigate health gains, and we asked the question, Is it better to be physically active rather than sedentary? To answer that question, we could group together people who did any kind of exercise and compare them to people who did not exercise at all. Not surprisingly, we would find that on average people who do some exercise are healthier than people who do not exercise at all. However, there are other important questions about the effectiveness of exercise that we could not answer with this approach:What kind of exercise works best?What is the relative effectiveness of exercise A compared with exercise B?How much exercise is optimum?What kinds of exercise are best for people with certain physical conditions? Journal of Engineering EducationV C 2017 ASEE.

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Background Working effectively in teams is an important 21st century skill as well as a fundamental component of the ABET professional competencies. However, successful teamwork is challenging, and empirical studies with adolescents concerning how the collaboration quality of team members is related to team performance are limited. Purpose/Hypothesis This study investigated the relationship between team collaboration quality and team performance in a robotics competition using multiple measures of team performance, including both objective task performance and expert judge evaluations, on a diverse set of supporting performance dimensions. Design/Method Data included Table Score, Robot Design, Research Project, Core Values, and Collaboration Quality scores for 366 youths on 61 K‐8 robotics teams that participated in a FIRST LEGO League Championship. Regression and mediation analyses were conducted to explore the relation between effective team collaboration and team performance. Furthermore, analysis of variance was conducted to explore the relationship between Collaboration Quality and team experience. Results Collaboration Quality was a good predictor of robotics team performance across all measures (with R2 = .50 and p < .001). Mediation analysis revealed that the Robot Design acted as a full mediator for the predictive effect of Collaboration Quality on the Table Score. In addition, the cumulative amount of team experience was significantly related to Collaboration Quality. Conclusions Overall, this study using collaboration performance assessments and actual competition data with a large number of teams confirms the importance of high‐quality teamwork in producing superior products with students engaged in authentic engineering tasks.

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