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Klein, Carrie; Lester, Jaime; Rangwala, Huzefa; Johri, Aditya – Review of Higher Education, 2019
An instrumental case study was conducted at a large, public research university to understand the organizational barriers, incentives, and opportunities related to adoption of learning analytics tools by faculty members and professional advising staff. Data was culled from focus groups with six faculty and twenty-one advisors and from interview…
Descriptors: Higher Education, Decision Making, Leadership, Academic Advising
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Lester, Jaime; Klein, Carrie; Rangwala, Huzefa; Johri, Aditya – ASHE Higher Education Report, 2017
The purpose of this monograph is to give readers a practical and theoretical foundation in learning analytics in higher education, including an understanding of the challenges and incentives that are present in the institution, in the individual, and in the technologies themselves. Among questions that are explored and answered are: (1) What are…
Descriptors: Educational Research, Data Collection, Data Analysis, Higher Education
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Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya – International Educational Data Mining Society, 2016
The past few years has seen the rapid growth of data mining approaches for the analysis of data obtained from Massive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a student may achieve on a given grade-related assessment based on information, considered as prior performance or prior…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
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Johri, Aditya; Yang, Seungwon; Vorvoreanu, Mihaela; Madhavan, Krishna – Advances in Engineering Education, 2016
As part of our NSF funded collaborative project on Data Sharing within Engineering Education Community, we conducted an empirical study to better understand the current climate of data sharing and participants' future expectations of the field. We present findings of this mixed method study and discuss implications. Overall, we found strong…
Descriptors: Engineering Education, Data, Knowledge Management, Educational Practices