Student Perceptions About Ethics, Privacy, and System Features in Learning Analytics at a Community College

Learning analytics systems are software designed to aggregate student data to be analyzed for the purpose of delivering information to students, with the goal of increasing student success, academic goal completion, and retention. Despite being identified as stakeholders and beneficiaries of learning analytics, student perceptions make up a small portion of present learning analytics research. Additionally, the majority of research focuses on four year institutions. The present study examined student perceptions of the extent to which Johnson County Community College considered ethics and privacy and presence and use of system features in its implementation of AccuCampus. The study found students had a moderately high agreement that JCCC considered ethics and privacy in its implementation of AccuCampus. Students also agreed about the presence and use of system features designed to enhance student success. There was a small, significant difference in levels of agreement that JCCC had considered ethics and privacy in their implementation of AccuCampus based on gender, with women having higher agreement. Further, the strongest predictor of intent to use advice from AccuCampus was a student’s perception of the presence and use of system features designed for promoting student success. Finally, first generation students had higher levels of agreement regarding both ethics and privacy considerations in AccuCampus as compared to students whose parents went to college. Similarly, first generation students had higher levels of agreement with the statement that system features designed to promote student success were present and used than non-first generation students.

Grantor dc:publisher

University of Kansas

Year dc:date.issued

2021

Author dc:creator

• Bailey, Barry J

Advisor dc:contributor.advisor

• Twombly, Susan

• Higher education administration

Statement dc:rights

• Copyright held by the author.

Language dc:language.iso

en

Dc Identifier Other

http://dissertations.umi.com/ku:17985

OAI identifier oai:identifier

oai:kuscholarworks.ku.edu:1808/39097