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Showing 1 to 15 of 21 results Save | Export
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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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Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
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Olga Ovtšarenko – Discover Education, 2024
Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…
Descriptors: Artificial Intelligence, Algorithms, Technology Uses in Education, Opportunities
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Verma, Anil; Singh, Aman; Lughofer, Edwin; Cheng, Xiaochun; Abualsaud, Khalid – Journal of Computing in Higher Education, 2021
Sustainable quality education is a big challenge even for the developed countries. In response to this, education 4.0 is gradually expanding as a new era of education. This work intends to unfold some hidden parameters that are affecting the quality education ecosystem (QEE). Academic loafing, unawareness, non-participation, dissatisfaction, and…
Descriptors: Educational Quality, Ecology, Sustainability, Higher Education
Varun Mandalapu – ProQuest LLC, 2021
Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…
Descriptors: Models, Student Behavior, Learning Management Systems, Data Use
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Jakab, Imrich; Ševcík, Michal; Grežo, Henrich – Electronic Journal of e-Learning, 2017
The methods of geospatial data processing are being continually innovated, and universities that are focused on educating experts in Environmental Science should reflect this reality with an elaborate and purpose-built modernization of the education process, education content, as well as learning conditions. Geographic Information Systems (GIS)…
Descriptors: Models, Higher Education, Geographic Information Systems, Environmental Education
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Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Whitney, Carol; Marton, Yuval – Online Submission, 2013
The SERIOL model of orthographic analysis proposed mechanisms for converting visual input into a serial encoding of letter order, which involved hemisphere-specific processing at the retinotopic level. As a test of SERIOL predictions, we conducted a consonant trigram-identification experiment, where the trigrams were briefly presented at various…
Descriptors: Visual Stimuli, Word Recognition, Models, Orthographic Symbols
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Hamblin, David J.; Phoenix, David A. – Journal of Higher Education Policy and Management, 2012
There are increasing demands for higher levels of data assurance in higher education. This paper explores some of the drivers for this trend, and then explains what stakeholders mean by the concept of data assurance, since this has not been well defined previously. The paper captures insights from existing literature, stakeholders, auditors, and…
Descriptors: Higher Education, Educational Technology, Stakeholders, Quality Assurance
Michalski, Greg V. – Association for Institutional Research (NJ1), 2011
Excessive college course withdrawals are costly to the student and the institution in terms of time to degree completion, available classroom space, and other resources. Although generally well quantified, detailed analysis of the reasons given by students for course withdrawal is less common. To address this, a text mining analysis was performed…
Descriptors: College Instruction, Courses, Withdrawal (Education), College Students
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Kovacevic, Aleksandar; Ivanovic, Dragan; Milosavljevic, Branko; Konjovic, Zora; Surla, Dusan – Program: Electronic Library and Information Systems, 2011
Purpose: The aim of this paper is to develop a system for automatic extraction of metadata from scientific papers in PDF format for the information system for monitoring the scientific research activity of the University of Novi Sad (CRIS UNS). Design/methodology/approach: The system is based on machine learning and performs automatic extraction…
Descriptors: Scientific Research, Library Administration, Classification, Information Science
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Barnes, Tiffany; Stamper, John – Educational Technology & Society, 2010
In building intelligent tutoring systems, it is critical to be able to understand and diagnose student responses in interactive problem solving. However, building this understanding into a computer-based intelligent tutor is a time-intensive process usually conducted by subject experts. Much of this time is spent in building production rules that…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Tutors, Probability
Raths, David – Campus Technology, 2010
In the tug-of-war between researchers and IT for supercomputing resources, a centralized approach can help both sides get more bang for their buck. As 2010 began, the University of Washington was preparing to launch its first shared high-performance computing cluster, a 1,500-node system called Hyak, dedicated to research activities. Like other…
Descriptors: Educational Finance, Researchers, Information Technology, Competition
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
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