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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
Schatz, Sae; Feemster, Val; Tompkins, Juli – Advanced Distributed Learning Initiative, 2021
In May of 2020, the Advanced Distributed Learning Initiative (ADL) and the Defense Acquisition University (DAU) partnered with USALearning/PowerTrain to create a practical application of ADL's 2019 TLA Reference Implementation. The purpose of this project was to recreate key components of the Reference Implementation with commercially-available,…
Descriptors: Distance Education, Competency Based Education, Electronic Learning, Computer Uses in Education
Franck Salles; Aurélie Lacroix – International Association for the Evaluation of Educational Achievement, 2024
Digital technologies have the potential to revolutionize education by enhancing quality, fairness, and efficiency. However, equitable access to these technologies remains a challenge. ILSAs (international large-scale assessments) have shown that the relationship between digital use and performance varies across countries and over time. To fully…
Descriptors: Achievement Tests, Elementary Secondary Education, Foreign Countries, Mathematics Tests
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Gupta, Shivangi; Sabitha, A. Sai – Education and Information Technologies, 2019
Aimed at a massive outreach and open access education, Massive Open Online Courses (MOOC) has evolved incredibly engaging millions of learners' over the years. These courses provide an opportunity for learning analytics with respect to the diversity in learning activity. Inspite of its growth, high dropout rate of the learners', it is examined to…
Descriptors: Retention (Psychology), Online Courses, Learner Engagement, Electronic Learning
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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ElAtia, Samira; Ipperciel, Donald; Zaiane, Osmar; Bakhshinategh, Behdad; Thibaudeau, Patrick – International Journal of Information and Learning Technology, 2021
Purpose: In this paper, the challenging and thorny issue of assessing graduate attributes (GAs) is addressed. An interdisciplinary team at The University of Alberta -- developed a formative model of assessment centered on students and instructor interaction with course content. Design/methodology/approach: The paper starts by laying the…
Descriptors: Foreign Countries, College Graduates, Student Characteristics, Formative Evaluation
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Joseph G. Donelan; Yu Liu – Advances in Accounting Education: Teaching and Curriculum Innovations, 2021
This chapter advocates a teaching approach for the statement of cash flows (SCF) that includes introduction of the SCF early in the curriculum using the accounting equation format, which helps students visualize the cash and accrual activities. We then adapt this accounting equation format to a worksheet model that can be used later in the…
Descriptors: Accounting, Business Education, Teaching Methods, Curriculum Design
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Sarwar, Sohail; García-Castro, Raul; Qayyum, Zia Ul; Safyan, Muhammad; Munir, Rana Faisal – International Association for Development of the Information Society, 2017
Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…
Descriptors: Student Characteristics, Profiles, Courseware, Electronic Learning
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Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay – Education and Information Technologies, 2017
Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the…
Descriptors: Electronic Learning, Metadata, Computer System Design, Design Preferences