LibGuides: Learning Analytics in Higher Education: Dissertations

Dissertation Databases

ProQuest Dissertations & Theses @ National University This link opens in a new window
Content: National University & NCU student dissertations and literature reviews.
Purpose: Use for foundational research, to locate test instruments and data, and more.
Special Features: Search by advisor (chair), degree, degree level, or department. Includes a read-aloud feature.
ProQuest Dissertations and Theses Global - Full Text This link opens in a new window
Content: Global student dissertations and literature reviews.
Purpose: Use for foundational research, to locate test instruments and data, and more.
Special Features: Search by advisor (chair), degree, degree level, or department. Includes a read-aloud feature
The ProQuest Dissertations & Theses database (PQDT) is the world's most comprehensive collection of dissertations and theses. It is the database of record for graduate research, with over 2.3 million dissertations and theses included from around the world.

Selected Dissertations

Learn how to find dissertations in the Library. See the FAQ: How can I find completed dissertations in the Library?

All the Data We Can Get: A Contextual Study of Learning Analytics and Student Privacy
Explores student privacy perspectives of higher education actors building capacity for learning analytics through an interpretive case study. Author: Kyle M. L. Jones, The University of Wisconsin – Madison.
Blended Learning and Bottlenecks in the California State University System: An Empirical Look at the Importance of Demographic and Performance Analytics
In an effort to investigate the extent to which student demographics and performance analytics explain student success outcomes in a popular blended learning psychology course, an explanatory sequential design was used to study 18,254 students enrolled in the course between 2006 and 2014. Author: Maureen Augusta Guarcello, University of San Diego.
The Construction and Validation of an Instructor Learning Analytics Implementation Model to Support At-Risk Students
The goal was to develop and validate a model to guide instructors in the implementation of learning analytics tools to support academically at-risk students with the purpose of improving learning outcomes. Author: Holly McKee, Nova Southeastern University.
The Implementation of Learning Analytics in Assessing Course Redesigns for College Level Statistics Courses
Studies two learning analytics problems: 1) comparing an online and standard face-to-face offerings of an upper division applied statistics course that is a curriculum bottleneck at San Diego State University; 2) evaluating a new supplementary instruction component to a large enrollment introductory statistics course recognized as presenting an undesirably high repeatable grade rate. Author: Joshua R. Beemer, San Diego State University.
Learning Analytics in Post-Secondary Education: The Utilization of Big Data to Support Part-Time Adjunct Faculty Members in the Academic Advisement of Nontraditional Students
This study examined the new analytical tools implemented by the college to discern the challenges faced by the adjunct faculty members in leading, managing, and being held accountable and responsible for the academic advising of non-traditional students. Author: Nathaniel B. Walker IV, Capella University.
Student Experience of Learning Analytics as a Factor in Motivation in Online Courses
The purpose of this qualitative case study was to examine the student experience with learning analytics in an online course. Author: Kerrie Specker, Northcentral University.
Understanding Ethical Concerns in the Design, Application, and Documentation of Learning Analytics in Post-secondary Education
Five-stage study using a cross-disciplinary perspective based on existing frameworks in rhetoric and scientific and technical communication, united by their ethical lens, from genre, persuasion, human-computer interaction, social power, semiotics, visual design, new media literacy, and pedagogy to create a matrix for understanding ethical concerns in learning analytics in post-secondary education. Author: Jenni Swenson, University of Minnesota.
Use of Temporal Access Data to Predict Academic Performance of the Self-Paced Online Student
The purpose of the current study was to investigate the possibility of using temporal access data, such as access timings (the first access time of postings, the first access time of lecture videos, upload time of the first homework) and access frequencies (view discussion frequency, add discussion frequency, view resource frequency) to predict the academic performance so that intervention can be done before the end of the course. Author: Yuk Lan Wong, Northcentral University.
Using Analytics to Encourage Student Responsibility for Learning and Identify Course Designs That Help
Shows how learning analytics could be implemented to encourage student responsibility for learning and identify effective faculty course designs that help. Author: John Lance Fritz, University of Maryland.
What Do the Numbers Really Mean? An Examination of Learning Analytics Related To Online Courses and University Student Retention and Success
The purpose of this study was to examine factors that affect university student retention and success, with particular consideration for students who have taken online courses during their undergraduate career. Author: Austin T. Winger, The University of North Dakota.