ABSTRACT
This study reviews the literature to gain an in-depth understanding of the pedagogical role of social media in higher education institutions (HEI's) during the COVID-19 pandemic. A systematic search in the Web of Science, Scopus, and EBSCO databases yielded 34 relevant empirical studies published between January 2020 and April 2021. The findings reveal that: a) the innovative possibilities furnished through social media facilitated the transition to a complete online learning setting, b) the majority of studies are oriented towards the perspectives of students, c) the lack of well-defined policy hinders the effective utilization of social media in the pedagogical process, and d) questionnaires were the mostly used data collection method overlooking the significance of digital tracing as a rich source of data. This article provides a research agenda to advance the knowledge of the pedagogical possibilities of social media, especially that these platforms were not used to their full potential for teaching and learning during the pandemic. This study also has practical implications for HEI's and policymakers to recognize the significance of social media in maintaining educational sustainability. © 2022,International Journal of Emerging Technologies in Learning. All Rights Reserved.
ABSTRACT
Achieving high performance for GPU codes requires developers to have significant knowledge in parallel programming and GPU architectures, and in-depth understanding of the application. This combination makes it challenging to find performance optimizations for GPU-based applications, especially in scientific computing. This paper shows that significant speedups can be achieved on two quite different scientific workloads using the tool, GEVO, to improve performance over human-optimized GPU code. GEVO uses evolutionary computation to find code edits that improve the runtime of a multiple sequence alignment kernel and a SARS-CoV-2 simulation by 28.9% and 29% respectively. Further, when GEVO begins with an early, unoptimized version of the sequence alignment program, it finds an impressive 30 times speedup-a performance improvement similar to that of the hand-tuned version. This work presents an in-depth analysis of the discovered optimizations, revealing that the primary sources of improvement vary across applications;that most of the optimizations generalize across GPU architectures;and that several of the most important optimizations involve significant code interdependencies. The results showcase the potential of automated program optimization tools to help reduce the optimization burden for scientific computing developers and enhance performance portability for domain-specific accelerators. © 2022 IEEE.
ABSTRACT
This research paper addresses the adaptations that instructors at colleges and universities around the world made following the abrupt March 2020 transition from in-person teaching to remote teaching. An in-depth understanding about how teaching instructors chose to adapt their courses when under duress to do so provides insight into how to support future change efforts. The purpose of this case study is to examine how one engineering faculty member responded to the change in teaching format through a lens of adaptability. Data was collected from engineering instructors at an R1 institution via online surveys and interviews across the Spring 2020, Fall 2020, and Spring 2021 semesters. The interview data was coded deductively for behavioral, cognitive, and emotional adaptability to experiences, as per Martin's et al. [1] adaptability theory. Behavioral adaptability was displayed via narrative maps for interpretative purposes. Narrative maps were built to display the challenges, behaviors, and successes that one engineering faculty faced while teaching during the pandemic. Tables with descriptive quotes from the interview data are used to elaborate on what is depicted in the maps. It was found that when the faculty member tried to adapt a behavior to better address a challenge, they frequently found success. Understanding the ways instructors adapted their courses during the pandemic can provide insight into how changes are best implemented. This case study helps to lay the groundwork for understanding the future of engineering education in periods of new, changing, or uncertain circumstances. This research is best suited for presentation in a traditional lecture. © American Society for Engineering Education, 2022