Abstract:

In early 2020, there was a drastic shift in the teaching modality across institutions of higher education as colleges and universities adapted to governmental guidelines in the face of COVID-19 lockdown restrictions. The shift to remote instruction and campus restrictions not only had the potential for limiting learning opportunities but also placed significant tolls on students’ well-being. While most, if not all institutions already had mature learning management systems (LMS) in place to facilitate online instruction, we argue that these same LMS platforms can fall short in replicating the social interactions students enjoy within physical learning spaces, a problem only exacerbated by governmental restrictions that all but eliminated any opportunities for students to interact in-person (e.g. restaurant closures, park closures, and concert cancellations). As a viable alternative to LMS-based systems, this research presents on the adoption of online social networking (OSN) software and its implementation across fully online undergraduate courses taken during COVID-19 lockdown restrictions. More specifically, this research implements customized OSN software, catered towards learning and enhanced with a dynamic sentiment analyzer. The dynamic sentiment analyzer was integrated into the course asynchronous online discussion board (AOD) and provided students with real-time assessment of the sentiment of discussion posts with the aim of fostering more positive interactions among participants and enhancing social capital. This research adopts experimental research methods to compare the sentiment of discussion board posts made by students using both a traditional LMS platform and the enhanced OSN platform. Through system analytics, social network analyses, and pre- and post-test surveys, our findings support the use of enhanced OSN software versus traditional LMS-based approaches. More specifically, overall findings identified that students participating during the pandemic and utilizing the enhanced OSN software (outfitted with the dynamic sentiment analyzer), yielded higher levels of social presence throughout the course and resulted in and more positive discussion board posts by students.

Keywords:

Social Learning, Online Social Networking, Sentiment Analysis, COVID-19.