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1. The CLICK Approach and its Impact on Learning Introductory Probability Concepts in an Industrial Engineering Course

   Lopez, Christian ; Ashour, Omar ; Cunningham, James ; Tucker, Conrad ; Lynch, Paul ( June 2020 , ASEE Annual Conference proceedings)

   The objective of this work is to present an initial investigation of the impact the Connected Learning and Integrated Course Knowledge (CLICK) approach has had on students’ motivation, engineering identity, and learning outcomes. CLICK is an approach that leverages Virtual Reality (VR) technology to provide an integrative learning experience in the Industrial Engineering (IE) curriculum. To achieve this integration, the approach aims to leverage VR learning modules to simulate a variety of systems. The VR learning modules offer an immersive experience and provide the context for real-life applications. The virtual simulated system represents a theme to transfer the system concepts and knowledge across multiple IE courses as well as connect the experience with real-world applications. The CLICK approach has the combined effect of immersion and learning-by-doing benefits. In this work, VR learning modules are developed for a simulated manufacturing system. The modules teach the concepts of measures of location and dispersion, which are used in an introductory probability course within the IE curriculum. This work presents the initial results of comparing the motivation, engineering identity, and knowledge gain between a control and an intervention group (i.e., traditional vs. CLICK teaching groups). The CLICK approach group showed greater motivation compared tomore »a traditional teaching group. However, there were no effects on engineering identity and knowledge gain. Nevertheless, it is hypothesized that the VR learning modules will have a positive impact on the students’ motivation, engineering identity, and knowledge gain over the long run and when used across the curriculum. Moreover, IE instructors interested in providing an immersive and integrative learning experience to their students could leverage the VR learning modules developed for this project.« less
2. The concerns and perceived challenges students faced when traditional in-person engineering courses suddenly transitioned to remote learning

   Yu, Fan ; Milord, Johanna ; Orton, Sarah L. ; Flores, Lisa. Y. ; & Marra, Rose. M. ( June 2022 , 2022 ASEE Annual Conference)

   This research evaluates the impact of switching college engineering courses from in-person instruction to emergency remote learning among engineering students at a university in the Midwest. The study aimed to answer the question: What were the concerns and perceived challenges students faced when traditional in-person engineering courses suddenly transitioned to remote learning? The goal of this study is to uncover the challenges students were facing in engineering online courses and to understand students’ concerns. Our findings can help improve teaching instruction to provide students with previously unavailable educational assistance for online engineering courses. We collected online survey responses during weeks 8 and 9 of the academic semester, shortly after the COVID-19 shutdown and emergency transition to remote learning in Spring 2020. The survey included two open-ended questions which inquired about students’ feedback about moving the class online, and one two-item scale which assessed students’ confidence in online engineering learning. Data analysis for the open-ended questions was guided by the theoretical framework - Social Cognitive Career Theory [1] that explores how context, person factors and social cognitions contribute to career goals, interests and actions. A phenomenological approach [2] was conducted to understand the experience of these students. Open coding and axialmore »coding [2] methods were used to create initial categories then themes related to students' concerns and challenges. Data from the two-item scale was evaluated using descriptive statistics: means, standard deviations, and ranges. Four main themes with separate sub-categories emerged from the student responses: 1) Instructor’s ability to teach course online (Instructional limitations, Seeking help, Increased Workload), 2) Student’s ability to learn online (Time Management, Lower engagement and motivation, Harder to absorb material, Hard to focus, Worry about performance), 3) Difficulties outside of class (Technology issues), and 4) No concerns. Students seemed more concerned about their ability to learn the material (48% of responses) than the instructor’s ability to teach the material (36% of responses). The instructional limitations or lack of instructional support (22% of responses) and time management (12% of responses) were among the major concerns in the sub-categories. The results from two-item scale indicated participants' s confidence in their ability to master their classroom knowledge was at an intermediate level via online instruction (6/10), and participants' confidence in the instructor's ability to teach knowledge in online classes is moderate to high (7/10). The results align with the open-ended question response in which students were somewhat more concerned about their ability to learn than the instructor’s ability to teach. The themes and analysis will be a valuable tool to help institutions and instructors improve student learning experiences.« less
3. A comparison study of human examples vs. non-human examples in an evolution lesson leads to differential impacts on student learning experiences in an introductory biology course

   https://doi.org/10.1186/s12052-021-00148-w  

   Grunspan, Daniel Z. ; Dunk, Ryan D. ; Barnes, M. Elizabeth ; Wiles, Jason R. ; Brownell, Sara E. ( December 2021 , Evolution: Education and Outreach)

   Abstract Background Instructors can teach evolution using any number of species contexts. However, not all species contexts are equal, and taxa choice can alter both cognitive and affective elements of learning. This is particularly true when teaching evolution using human examples, a promising method for evolution instruction that nevertheless comes with unique challenges. In this study, we tested how an evolution lesson focused on a human example may impact students’ engagement, perceived content relevance, learning gains, and level of discomfort, when compared to the same lesson using a non-human mammal example. We use this isomorphic lesson and a pre-post study design administered in a split-section introductory biology classroom to isolate the importance of the species context. Results For two of the four measurements of interest, the effect of using human examples could not be understood without accounting for student background. For learning gains, students with greater pre-class content knowledge benefited more from the human examples, while those with low levels of knowledge benefited from the non-human example. For perceived relevance, students who were more accepting of human evolution indicated greater content relevance from the human example. Regardless of condition, students with lower evolution acceptance reported greater levels of discomfort withmore »the lesson. Conclusions Our results illustrate the complexities of using human examples to teach evolution. While these examples were beneficial for many students, they resulted in worse outcomes for students that were less accepting of evolution and those who entered the course with less content knowledge. These findings demonstrate the need to consider diverse student backgrounds when establishing best practices for using human examples to teach evolution.« less
4. Intelligence Augmentation for Collaborative Learning

   Roschelle, Jeremy ( January 2021 , HCI International)

   Today’s classrooms are remarkably different from those of yesteryear. In place of individual students responding to the teacher from neat rows of desks, one more typically finds students working in groups on projects, with a teacher circulating among groups. AI applications in learning have been slow to catch up, with most available technologies focusing on personalizing or adapting instruction to learners as isolated individuals. Meanwhile, an established science of Computer Supported Collaborative Learning has come to prominence, with clear implications for how collaborative learning could best be supported. In this contribution, I will consider how intelligence augmentation could evolve to support collaborative learning as well as three signature challenges of this work that could drive AI forward. In conceptualizing collaborative learning, Kirschner and Erkens (2013) provide a useful 3x3 framework in which there are three aspects of learning (cognitive, social and motivational), three levels (community, group/team, and individual) and three kinds of pedagogical supports (discourse-oriented, representation-oriented, and process-oriented). As they engage in this multiply complex space, teachers and learners are both learning to collaborate and collaborating to learn. Further, questions of equity arise as we consider who is able to participate and in which ways. Overall, this analysis helps usmore »see the complexity of today’s classrooms and within this complexity, the opportunities for augmentation or “assistance to become important and even essential. An overarching design concept has emerged in the past 5 years in response to this complexity, the idea of intelligent augmentation for “orchestrating” classrooms (Dillenbourg, et al, 2013). As a metaphor, orchestration can suggest the need for a coordinated performance among many agents who are each playing different roles or voicing different ideas. Practically speaking, orchestration suggests that “intelligence augmentation” could help many smaller things go well, and in doing so, could enable the overall intention of the learning experience to succeed. Those smaller things could include helping the teacher stay aware of students or groups who need attention, supporting formation of groups or transitions from one activity to the next, facilitating productive social interactions in groups, suggesting learning resources that would support teamwork, and more. A recent panel of AI experts identified orchestration as an overarching concept that is an important focus for near-term research and development for intelligence augmentation (Roschelle, Lester & Fusco, 2020). Tackling this challenging area of collaborative learning could also be beneficial for advancing AI technologies overall. Building AI agents that better understand the social context of human activities has broad importance, as does designing AI agents that can appropriately interact within teamwork. Collaborative learning has trajectory over time, and designing AI systems that support teams not just with a short term recommendation or suggestion but in long-term developmental processes is important. Further, classrooms that are engaged in collaborative learning could become very interesting hybrid environments, with multiple human and AI agents present at once and addressing dual outcome goals of learning to collaborate and collaborating to learn; addressing a hybrid environment like this could lead to developing AI systems that more robustly help many types of realistic human activity. In conclusion, the opportunity to make a societal impact by attending to collaborative learning, the availability of growing science of computer-supported collaborative learning and the need to push new boundaries in AI together suggest collaborative learning as a challenge worth tackling in coming years.« less
5. Learning in a community of practice: Factors impacting english‐learning students' engagement in scientific argumentation

   https://doi.org/10.1002/tea.21310  

   González‐Howard, María ; McNeill, Katherine L. ( January 2016 , Journal of Research in Science Teaching)

   Recent education reform efforts have included an increasing push for school science to better mirror authentic scientific endeavor, including a focus on science practices. However, despite expectations that all students engage in these language‐rich practices, little prior research has focused on how such opportunities will be created for English‐learning students. This case study uses the conceptual framework of communities of practice to investigate the relationship between English‐learning students' argumentation and their middle school sheltered English immersion (SEI) science classroom community. Considering various aspects of this conceptual framework—including the role of legitimate peripheral participation, as well as the degree to which community members' goals and expectations around the practice of interest align—allowed us to identify classroom characteristics that both hindered and facilitated students' opportunities to engage in argumentation. First, the classroom community, and consequently the presence and quality of argumentative discourse, was influenced by student movement in and out of this classroom, as their English proficiencies improved. The constantly changing class roster made it difficult for newer members to watch, learn, and engage in argumentation with more knowledgeable peers. Furthermore, certain elements of the SEI approach, namely its deductive nature, conflicted with the type of instruction necessary to encourage languagemore »use for sensemaking. However, this instructional context also offered English‐learning students with affordances they may not find in other educational settings. Specifically, we found that when students worked in smaller group structures, such as pairs, and they utilized both their native and second language as a linguistic resource for engaging in science discourse, their engagement in argumentation was promoted. © 2016 Wiley Periodicals, Inc. J Res Sci Teach 53: 527–553, 2016

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