ABSTRACT
To support people enjoying exercises or learning performances at home such as Yoga poses or traditional dances, we have developed Exercise and Performance Learning Assistant System (EPLAS). In EPLAS, the user can practice it by following the model performance of the instructor in the video. Then, the key poses of the user will be rated as the feedback by comparing the keypoints between the instructor and the user that are extracted by OpenPose. We have provided the platform using the web browser. However, OpenPose needs to run on OS directly. We developed the EPLAS platform in this paper using Node.js as the web application server. When a user requests it via the browser, the rating function is immediately executed on the server. Furthermore, we employ use Docker to simply distribute the platform. We invited 10 Okayama University students to do various Yoga positions using the EPLAS for assessments, and the results verified the success of the deployment. © 2022 IEEE.
ABSTRACT
To assist practicing exercises or learning performances by themselves at home under pandemic of COVID-19, we have studied the Exercise and Performance Learning Assistant System (EPLAS) and implemented the user interface using a web browser for practicing Yoga poses. EPLAS offers a video content of model actions by an instructor to be followed by the user, and automatically takes the photos of the critical poses. Then, it rates each critical pose by differences of body key points extracted by OpenPose between the user photo and the instructor one. In this paper, we implement the EPLAS platform using Node.js as the web application server to run the rating function automatically on the server when it is requested on the browser. For evaluations, we asked 10 students in Okayama University to practice 10 Yoga poses using the interface, and confirmed its correctness. © 2022 IEEE.
ABSTRACT
Learning Assistants (LAs) are undergraduate students that serve as course assistants in STEM courses to facilitate the learning of their near-peers. This paper explored the perspectives of LAs at four institutions with respect to mentoring and their personal outcomes. Interviews with program coordinators revealed different goals and implementation of the LA programs at each institution. Survey responses from the LAs revealed differences by school in the percentage who felt that they had been mentored as well as how the LA's perceived that they had mentored others. The most common outcomes from serving as an LA were teaching skills, communication skills, confidence, and satisfaction from giving back. Statistically significant correlations were found between some mentoring attributes and outcomes, such as perceiving that their mentoring included listening was correlated with the outcomes of satisfaction from giving back (phi 0.323) and communication skills (phi 0.134). The results may be impacted by COVID-related online instruction. This preliminary study is laying the groundwork for a larger study to examine the ties between different LA program characteristics and the outcomes for LAs. © American Society for Engineering Education, 2022.
ABSTRACT
BACKGROUND: The Learning Assistant (LA) model with its subsequent support and training has evidenced significant gains for undergraduate STEM learning and persistence, especially in high-stakes courses like Calculus. Yet, when a swift and unexpected transition occurs from face-to-face to online, remote learning of the LA environment, it is unknown how LAs are able to maintain their motivation (competence, autonomy, and relatedness), adapt to these new challenges, and sustain their student-centered efforts. This study used Self-Determination Theory (SDT) to model theoretical aspects of LAs' motivations (persistence and performance) both before and after changes were made in delivery of a Calculus II course at Texas Tech University due to COVID-19 interruptions. RESULTS: Analysis of weekly written reflections, a focus group session, and a post-course questionnaire of 13 Calculus II LAs throughout Spring semester of 2020 showed that LAs' reports of competence proportionally decreased when they transitioned online, which was followed by a moderate proportional increase in reports of autonomy (actions they took to adapt to distance instruction) and a dramatic proportional increase in reports of relatedness (to build structures for maintaining communication and building community with undergraduate students). CONCLUSIONS: Relatedness emerged as the most salient factor from SDT to maintain LA self-determination due to the COVID-19 facilitated interruption to course delivery in a high-stakes undergraduate STEM course. Given that online learning continues during the pandemic and is likely to continue after, this research provides an understanding to how LAs responded to this event and the mounting importance of relatedness when LAs are working with undergraduate STEM learners. Programmatic recommendations are given for enhancing LA preparation including selecting LAs for autonomy and relatedness factors (in addition to competence), modeling mentoring for remote learners, and coaching in best practices for online instruction.