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Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
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Feldman-Maggor, Yael; Barhoom, Sagiv; Blonder, Ron; Tuvi-Arad, Inbal – Education and Information Technologies, 2021
Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…
Descriptors: Data Analysis, Educational Research, Data Processing, Learning Analytics
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Liu, Min; Pan, Zilong; Li, Chenglu; Han, Songhee; Shi, Yi; Pan, Xin – International Journal on E-Learning, 2021
There has been an increasing interest in learning analytics (LA) research especially in higher education (HE) in recent years. In this study, we conducted a systematic focused review of research, from 2016 to present, on using analytics in HE (specifically system- or user-generated data) to understand in what way such analytics has been…
Descriptors: Learning Analytics, Educational Research, Higher Education, Data Collection
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Hemy Ramiel; Eran Fisher – Learning, Media and Technology, 2024
This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack…
Descriptors: Epistemology, Social Emotional Learning, Data, Higher Education
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Adejo, Olugbenga; Connolly, Thomas – Journal of Education and Practice, 2017
The increase in education data and advance in technology are bringing about enhanced teaching and learning methodology. The emerging field of Learning Analytics (LA) continues to seek ways to improve the different methods of gathering, analysing, managing and presenting learners' data with the sole aim of using it to improve the student learning…
Descriptors: Higher Education, Program Implementation, Information Utilization, Evidence Based Practice
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Mathies, Charles; Valimaa, Jussi – Tertiary Education and Management, 2013
Recent changes in European higher education have accompanied a strong desire and need by national ministries to have comparable data across institutions and a growing recognition from campus leaders that effective planning and decision-making requires reliable institutional data and analyses. This has induced changes and restructuring of duties…
Descriptors: Higher Education, Institutional Evaluation, Governance, Data Analysis
Niemi, David; Gitin, Elena – International Association for Development of the Information Society, 2012
An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…
Descriptors: Higher Education, Online Courses, Academic Persistence, Identification
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Burns, Shelley, Ed.; Wang, Xiaolei, Ed.; Henning, Alexandra, Ed. – National Center for Education Statistics, 2011
Since its inception, the National Center for Education Statistics (NCES) has been committed to the practice of documenting its statistical methods for its customers and of seeking to avoid misinterpretation of its published data. The reason for this policy is to assure customers that proper statistical standards and techniques have been observed,…
Descriptors: National Surveys, Data Processing, Statistical Data, Data Collection
Nandeshwar, Ashutosh R. – ProQuest LLC, 2010
In the modern world, higher education is transitioning from enrollment mode to recruitment mode. This shift paved the way for institutional research and policy making from historical data perspective. More and more universities in the U.S. are implementing and using enterprise resource planning (ERP) systems, which collect vast amounts of data.…
Descriptors: Higher Education, Institutional Research, Graduation Rate, Program Effectiveness
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Ewell, Peter; L'Orange, Hans – State Higher Education Executive Officers, 2009
A rapidly changing global economy, shifting demographics, and concerns about our ability to maintain a competitive workforce have focused national attention on the educational systems of America's states, highlighting their critical role in ensuring a productive and creative future for our country. As a result, Americas colleges and universities…
Descriptors: Higher Education, Elementary Secondary Education, Information Management, Design Requirements
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Toole, Patrick J.; Hoffner, Vernon R. – Journal of Higher Education, 1974
Based on a study conducted in Michigan, this article summarizes many of the problems involved in data collection and coordination. A number of specific recommendations are presented to alleviate these problems. (Editor)
Descriptors: Cooperative Programs, Coordination, Data Collection, Data Processing
Gose, Frank J. – 1989
The accuracy and reliability aspects of data integrity are discussed, with an emphasis on the need for consistency in responsibility and authority. A variety of ways in which data integrity can be compromised are discussed. The following sources of data corruption are described, and the ease or difficulty of identification and suggested actions…
Descriptors: Administrative Problems, Data, Data Collection, Data Processing
Petranek, Jan G. – Currents, 1984
Recent technological advances have put alumni-development computer systems within reach of most colleges and universities. Options, including the types of hardware available, the many ways to match an office's needs to your hardware, and the types of software available are discussed. (MLW)
Descriptors: Alumni, Computer Programs, Computers, Data Collection
Wirt, Edgar – Coll Univ, 1969
Adapted from presentation of Unit I of the MODS Seminar, the National pilot program of AACRAO, Fort Collins, Colorado, April 1967. (AD)
Descriptors: Data Collection, Data Processing, Higher Education, Information Retrieval
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