Browsing by Author "Asher, Andrew"

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    A Comprehensive Primer to Library Learning Analytics Practices, Initiatives, and Privacy Issues
    (American Library Association, 2020-04) Jones, Kyle M. L.; Briney, Kristin A.; Goben, Abigail; Salo, Dorothea; Asher, Andrew; Perry, Michael R.; Library and Information Science, School of Informatics and Computing
    Universities are pursuing learning analytics practices to improve returns from their investments, develop behavioral and academic interventions to improve student success, and address political and financial pressures. Academic libraries are additionally undertaking learning analytics to demonstrate value to stakeholders, assess learning gains from instruction, and analyze student-library usage, et cetera. The adoption of these techniques leads to many professional ethics issues and practical concerns related to privacy. In this narrative literature review, we provide a foundational background in the field of learning analytics, library adoption of these practices, and identify ethical and practical privacy issues.
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    “We're being tracked at all times”: Student perspectives of their privacy in relation to learning analytics in higher education
    (Wiley, 2020) Jones, Kyle M. L.; Asher, Andrew; Goben, Abigail; Perry, Michael R.; Salo, Dorothea; Briney, Kristin A.; Robertshaw, M. Brooke; Library and Information Science, School of Informatics and Computing
    Higher education institutions are continuing to develop their capacity for learning analytics (LA), which is a sociotechnical data‐mining and analytic practice. Institutions rarely inform their students about LA practices, and there exist significant privacy concerns. Without a clear student voice in the design of LA, institutions put themselves in an ethical gray area. To help fill this gap in practice and add to the growing literature on students' privacy perspectives, this study reports findings from over 100 interviews with undergraduate students at eight U.S. higher education institutions. Findings demonstrate that students lacked awareness of educational data‐mining and analytic practices, as well as the data on which they rely. Students see potential in LA, but they presented nuanced arguments about when and with whom data should be shared; they also expressed why informed consent was valuable and necessary. The study uncovered perspectives on institutional trust that were heretofore unknown, as well as what actions might violate that trust. Institutions must balance their desire to implement LA with their obligation to educate students about their analytic practices and treat them as partners in the design of analytic strategies reliant on student data in order to protect their intellectual privacy.