The proliferation of learning analytics (LA) in higher education has relied on data from learning management systems (LMS) like Canvas and Blackboard. Despite widespread LMS usage, students often lack clarity on what specific data is collected and who has access to it. This study explores undergraduate students’ understanding of data collection practices within the Canvas LMS. We analyzed survey responses of nearly 600 students, examining students’ awareness of the various roles within Canvas and their corresponding data permissions. The results reveal that students exhibit a general awareness of data collection practices but are unsure about the extent of their data’s use and misinterpret the use of data analytics, highlighting a a greater need for critical data education in universities and other educational contexts. These findings suggest a critical need for universities to enhance transparency and educate students on data privacy and LMS functionalities.

Academics’ use of social media platforms is widely recognized and often understood as an extension of traditional academic practice. However, this understanding does not account for academics’ use of pseudonymous Twitter accounts. We used a combination of computational and human-driven methods to examine the activity of 59 anonymized, self-identified academics on Twitter. Our computational analysis identified five broad topics: discussing academic life, discussing British news and affairs, discussing everyday life, surviving lockdown, and engaging with academic Twitter. Within these broad topics, we identified 24 more specific codes, most of which were concentrated in individual topics, with some cross-cutting codes. These codes demonstrate how the pseudonymous accounts considered in this study can be considered ‘authentically academic’ even if they do not conform with widespread expectations of academic social media use.