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1. Unequal Impacts of Augmented Reality on Learning and Collaboration During Robot Programming with Peers

   https://doi.org/10.1145/3432944  

   Radu, Iulian ; Hv, Vivek ; Schneider, Bertrand ( January 2021 , Proceedings of the ACM on Human-Computer Interaction)

   null (Ed.)

   Augmented reality (AR) applications are growing in popularity in educational settings. While the effects of AR experiences on learning have been widely studied, there is relatively less research on understanding the impact of AR on the dynamics of co-located collaborative learning, specifically in the context of novices programming robots. Educational robotics are a powerful learning context because they engage students with problem solving, critical thinking, STEM (Science, Technology, Engineering, Mathematics) concepts, and collaboration skills. However, such collaborations can suffer due to students having unequal access to resources or dominant peers. In this research we investigate how augmented reality impacts learning and collaboration while peers engage in robot programming activities. We use a mixed methods approach to measure how participants are learning, manipulating resources, and engaging in problem solving activities with peers. We investigate how these behaviors are impacted by the presence of augmented reality visualizations, and by participants? proximity to resources. We find that augmented reality improved overall group learning and collaboration. Detailed analysis shows that AR strongly helps one participant more than the other, by improving their ability to learn and contribute while remaining engaged with the robot. Furthermore, augmented reality helps both participants maintain a common ground and balance contributions during problem solving activities. We discuss the implications of these results for designing AR and non-AR collaborative interfaces. 

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2. Assessment of Metacognitive Skills in Design and Manufacturing

   https://doi.org/10.18260/1-2--34191  

   Elliott, L ; Aqlan, F. ; Zhao, R. ; Janney, M. ( June 2020 , ASEE Annual Conference proceedings)

   Metacognition is the understanding of your own knowledge including what knowledge you do not have and what knowledge you do have. This includes knowledge of strategies and regulation of one’s own cognition. Studying metacognition is important because higher-order thinking is commonly used, and problem-solving skills are positively correlated with metacognition. A positive previous disposition to metacognition can improve problem-solving skills. Metacognition is a key skill in design and manufacturing, as teams of engineers must solve complex problems. Moreover, metacognition increases individual and team performance and can lead to more original ideas. This study discusses the assessment of metacognitive skills in engineering students by having the students participate in hands-on and virtual reality activities related to design and manufacturing. The study is guided by two research questions: (1) do the proposed activities affect students’ metacognition in terms of monitoring, awareness, planning, self-checking, or strategy selection, and (2) are there other components of metacognition that are affected by the design and manufacturing activities? The hypothesis is that the participation in the proposed activities will improve problem-solving skills and metacognitive awareness of the engineering students. A total of 34 undergraduate students participated in the study. Of these, 32 were male and 2 were female students. All students stated that they were interested in pursuing a career in engineering. The students were divided into two groups with the first group being the initial pilot run of the data. In this first group there were 24 students, in the second group there were 10 students. The groups’ demographics were nearly identical to each other. Analysis of the collected data indicated that problem-solving skills contribute to metacognitive skills and may develop first in students before larger metacognitive constructs of awareness, monitoring, planning, self-checking, and strategy selection. Based on this, we recommend that the problem-solving skills and expertise in solving engineering problems should be developed in students before other skills emerge or can be measured. While we are sure that the students who participated in our study have awareness as well as the other metacognitive skills in reading, writing, science, and math, they are still developing in relation to engineering problems. 

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3. Implementing Collaborative Online Lab Experiences to Facilitate Active Learning

   Tcheslavski, GV ; Yoo, J ; Sayil, SS ( June 2024 , ASEE)

   Laboratory experience is among the key components in engineering education. It is highly instrumental and plays a significant role in students’ knowledge building, application, and distribution. Learning in laboratories is interactive and often collaborative. On the other hand, students, who learn engineering through online mechanisms, may face challenges with labs, which were frequently documented during the recent pandemic. To address such challenges, innovative online lab learning modules were developed, and learning strategies were implemented in five courses in electrical engineering, Circuits I, Electronics I, Electronics II, Signals and Systems, and Embedded System, through which students gain solid foundation before advancing to senior design projects. The two main incorporated strategies were Open-Ended lab design and Teamwork implementation. Open-Ended lab modules using a lab-in-a-box approach allow students solving lab problems with multiple approaches fostering problem solving both independently and collaboratively. This innovative lab design promotes problem solving at various cognitive levels. It is better suited for concept exploration and collaborative lab learning environments as opposed to the traditional lab works with a prescribed approach leading students to follow certain procedures that may lack the problem exploration stage. Additionally, course instructors formed online lab groups, so that students were sharing the problem-solving process – from ideas formation to solutions – with their peers. To evaluate the effectiveness of the implemented lab strategies, students in the participating courses were randomly divided into experimental and control groups. Both assignment grades and students' feedback via surveys were used to evaluate students' learning. Participants in the control group were learning in labs through the materials that were aligned with core concepts by following predetermined procedures. Students in the experimental group learned through inquiry-based lab materials that required them to work in teams by integrating core concepts together to find a solution and while following one of potentially many approaches. To maximize the online lab learning effect and to replicate the contemporary industry, commerce, and research practices, instructor-structured cooperative learning strategies were applied along with pre-lab simulations and instructional videos. This paper showcases the outcomes of our 2nd year implementation of active learning laboratory strategies on the mixed population of online and face-to-face students. We observed that students in the experimental group generally outperformed their counterparts in labs and showed significantly higher results in the assignments addressing more advanced concept understanding and applications (grand average of 88.3% vs. 66.3%). Surveys also indicated that students saw the benefits of collaboration with Open-Ended lab modules not only for learning concepts, but also for improving their communication skills. Students were able to collaborate on lab problems through various communication tools, such as course Learning Management System (LMS) and mobile apps forming online learning communities. We believe that that the implementation of open-ended collaborative laboratory strategies can assist students in cultivating a deeper comprehension, fostering self-confidence, and refining their critical thinking abilities, all while strengthening their sense of inclusion within the field of engineering. 

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4. The Affordance of Computer-Supportive Collaborative Learning in a Dynamics Course

   Lee, Y. ( July 2021 , Zone 1 Conference of the American Society for Engineering Education)

   null (Ed.)

   Over the past two decades, educators have used computer-supported collaborative learning (CSCL) to integrate technology with pedagogy to improve student engagement and learning outcomes. Researchers have also explored the diverse affordances of CSCL, its contributions to engineering instruction, and its effectiveness in K-12 STEM education. However, the question of how students use CSCL resources in undergraduate engineering classrooms remains largely unexplored. This study examines the affordances of a CSCL environment utilized in a sophomore dynamics course with particular attention given to the undergraduate engineering students’ use of various CSCL resources. The resources include a course lecturebook, instructor office hours, a teaching assistant help room, online discussion board, peer collaboration, and demonstration videos. This qualitative study uses semi-structured interview data collected from nine mechanical engineering students (four women and five men) who were enrolled in a dynamics course at a large public research university in Eastern Canada. The interviews focused on the individual student’s perceptions of the school, faculty, students, engineering courses, and implemented CSCL learning environment. The thematic analysis was conducted to analyze the transcribed interviews using a qualitative data analysis software (Nvivo). The analysis followed a six step process: (1) reading interview transcripts multiple times and preliminary in vivo codes; (2) conducting open coding by coding interesting or salient features of the data; (3) collecting codes and searching for themes; (4) reviewing themes and creating a thematic map; (5) finalizing themes and their definitions; and (6) compiling findings. This study found that the students’ use of CSCL resources varied depending on the students’ personal preferences, as well as their perceptions of the given resource’s value and its potential to enhance their learning. For example, the dynamics lecturebook, which had been redesigned to encourage problem solving and note-taking, fostered student collaborative problem solving with their peers. In contrast, the professor’s example video solutions had much more of an influence on students’ independent problem-solving processes. The least frequently used resource was the course’s online discussion forum, which could be used as a means of communication. The findings reveal how computer-supported collaborative learning (CSCL) environments enable engineering students to engage in multiple learning opportunities with diverse and flexible resources to both address and to clarify their personal learning needs. This study strongly recommends engineering instructors adapt a CSCL environment for implementation in their own unique classroom context. 

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5. Case study on engineering design intervention in physics laboratories

   Kaufman-Ortiz, K. ; Morphew, J. W. ; Rebello, N. S. ; & Rebello, C. M. ( January 2022 , 2022 ASEE Annual Conference & Exposition Proceedings)

   Problem-solving is a critical skill in the workplace, but recent college graduates are often deficient in problem-solving skills. Introductory STEM courses present engineering students with well-structured problems with single-path solutions that do not prepare students with the problem-solving skills they will need to solve complex problems within authentic engineering contexts. When presented with complex problems in authentic contexts, engineering students find it difficult to transfer the scientific knowledge learned in their STEM courses to solve these integrated and ill structured problems. By integrating physics laboratories with engineering design problems, students are taught to apply physics principles to solve ill-structured and complex engineering problems. The integration of engineering design processes to physics labs is meant to help students transfer physics learning to engineering problems, as well as to transfer the design skills learned in their engineering courses to the physics lab. We hypothesize this integration will help students become better problem solvers when they go out to industry after graduation. The purpose of this study is to examine how students transfer their understanding of physics concepts to solve ill-structured engineering problems by means of an engineering design project in a physics laboratory. We use a case-study methodology to examine two cases and analyze the cases using a lens of co-regulated learning and transfer between physics and engineering contexts. Observations were conducted using transfer lenses. That is, we observed groups during the physics labs for evidence of transfer. The research question for this study was, to what extent do students relate physics concepts with concepts from other materials (classes) through an engineering design project incorporated in a physics laboratory? Teams were observed over the course of 6 weeks as they completed the second design challenge. The cases presented in this study were selected using observations from the lab instructors of the team’s work in the first design project. Two teams, one who performed well, and one that performed poorly, were selected to be observed to provide insight on how students use physics concepts to engage in the design process. The second design challenge asked students to design an eco-friendly way of delivering packages of food to an island located in the middle of the river, which is home to critically endangered species. They are given constraints that the solution cannot disrupt the habitat in any way, nor can the animals come into contact directly with humans or loud noises. Preliminary results indicate that both teams successfully demonstrated transfer between physics and engineering contexts, and integrated physics concepts from multiple labs to complete the design project. Teams that struggle seem to be less connected with the design process at the beginning of the project and are less organized. In contrast, teams that are successful demonstrate greater co-regulated learning (communication, reflection, etc.) and focus on making connections between the physics concepts and principles of engineering design from their engineering course work. 

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