Investigation of Technology-based Student Interaction for Social Learning in Online Courses
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abstract
In March 2020, the college of engineering in a large university in the southwest was required to teach the STEM courses in technology-enhanced formats with no face-to-face class meetings. As a response, all the courses were forced to rapidly migrate to an online or remote teaching/learning environment in order to mitigate the effects of the COVID-19 pandemic. This rapid change in teaching and learning modalities caused disruptions in the learning cycles, which lead to the development and adoption of mitigation strategies. The student interactions in online and remote courses have been shown to have an impact on their learning, similar to the student interaction in face-to-face courses which affects their learning. In addition to traditional learning in courses, social learning while informal in nature, has been shown to have significant effects on student learning. The goal of this study is to investigate: (i) the different technology/platforms and methods for interaction used by the instructors for the online STEM courses (ii) the tools that students adopted to manage their interactions with other students and with faculty outside the online STEM courses, and (iii) how the student interaction for asynchronous online courses compares to synchronous courses (remote courses) taken by the student. Preliminary results of the data collected through a survey indicate that students tended to use tools with robust mobile apps such as GroupMe & Slack to increase their interaction with other students outside of the online class time irrespective of the modality of instruction. Also, students interacted less with each other outside the online session in synchronous courses (1.24 hours per week on average) and more during the asynchronous courses (2.95 hours per week on average). However, when asked to rate the satisfaction with the interaction, the students rated their interactions in synchronous courses higher (median, mode = 4) than asynchronous courses (median, mode = 3) . Further analysis of the data will be carried out to understand the relationship between time spent and satisfaction when interacting in synchronous and asynchronous course.
