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Men, Qiwei; Gimbert, Belinda; Cristol, Dean – International Journal of Mobile and Blended Learning, 2023
With the rapid expansion of mobile, blended, and seamless learning, researchers claim two factors, lack of self-discipline and poor time management, adversely impact learning performance. In online educational environments, reduced social interactions and low engagement levels generate high dropout rates. Self-regulated learning (SRL), the…
Descriptors: Metacognition, Independent Study, Dropout Rate, Time Management
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Jin, Yuxi; Li, Ping; Wang, Wenxiao; Zhang, Suiyun; Lin, Di; Yin, Chengjiu – Interactive Learning Environments, 2023
We design a generative adversarial network (GAN)-based pencil drawing learning system for art education on large image datasets to help students study how to draw pencil drawings for images and scenes. The system generates a pencil drawing result for a natural image based on GAN. The GAN network is trained on pencil drawing big datasets containing…
Descriptors: Art Education, Learning Analytics, Learning Management Systems, Homework
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Hilpert, Jonathan C.; Greene, Jeffrey A.; Bernacki, Matthew – British Journal of Educational Technology, 2023
Capturing evidence for dynamic changes in self-regulated learning (SRL) behaviours resulting from interventions is challenging for researchers. In the current study, we identified students who were likely to do poorly in a biology course and those who were likely to do well. Then, we randomly assigned a portion of the students predicted to perform…
Descriptors: Learning Theories, Independent Study, Artificial Intelligence, Biology
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Hillman, Velislava – Learning, Media and Technology, 2023
The need for a comprehensive education data governance -- the regulation of who collects what data, how it is used and why -- continues to grow. Technologically, data can be collected by third parties, rendering schools unable to control their use. Legal frameworks partially achieve data governance as businesses continue to exploit existing…
Descriptors: Data Collection, Governance, Data Use, Laws
Raffaghelli, Juliana E., Ed.; Sangrà, Albert, Ed. – Higher Education Dynamics, 2023
This collection focuses on the role of higher education institutions concerning datafication as a complex phenomenon. It explores how the universities can develop data literac(ies) shaping tomorrow skills and "formae mentis" to face the most deleterious effects of datafication, but also to engage in creative and constructive ways with…
Descriptors: Data Use, Higher Education, Educational Change, Data Analysis
Maddox, Bryan – OECD Publishing, 2023
The digital transition in educational testing has introduced many new opportunities for technology to enhance large-scale assessments. These include the potential to collect and use log data on test-taker response processes routinely, and on a large scale. Process data has long been recognised as a valuable source of validation evidence in…
Descriptors: Measurement, Inferences, Test Reliability, Computer Assisted Testing
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Vázquez-Cano, Esteban; Quicios-García, María-Pilar; Fombona, Javier; Rodríguez-Arce, Jorge – Education and Information Technologies, 2023
The main objective of this research is to determine the perception of teachers about the elements that increases the educational effectiveness of gamified apps in primary education. A methodology based on an importance-performance analysis was developed, using a structural equations model to calculate the degree of importance of each variable. The…
Descriptors: Instructional Design, Computer Oriented Programs, Gamification, Elementary Education
Matthew Carroll – Cambridge University Press & Assessment, 2023
Each year, when GCSE and A level results are published, a common talking point in media coverage is how results of male and female students differ. This reflects a popular fascination with such differences, but there is also a deeper, longstanding research interest in sex differences in education, not just in England, but around the world.…
Descriptors: Gender Differences, Foreign Countries, Educational Change, Academic Achievement
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Sarah Blanchard Kyte; Celeste Atkins; Elizabeth Collins; Regina Deil-Amen – Journal of Postsecondary Student Success, 2023
Universities are increasingly turning toward data-driven technologies like data dashboards to support advisors' work in student success, yet little empirical work has explored whether these tools help or hinder best practices in advising, which is in many ways a relationship-based enterprise. This mixed-methods study analyzed whether and why the…
Descriptors: Learning Analytics, Computer Software, School Holding Power, Academic Persistence
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Gagliardi, Jonathan S.; Johnson, Gina – New Directions for Institutional Research, 2019
Institutional Research (IR) has historically been tasked with fulfilling reporting requirements and information requests that are often transactional. This has changed more recently in light of the ongoing analytics revolution, which has highlighted the need for a more intentional approach to producing and using rigorous evidence to support…
Descriptors: Institutional Research, Learning Analytics, Global Approach, Educational Change
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Kitto, Kirsty; Knight, Simon – British Journal of Educational Technology, 2019
Artificial intelligence and data analysis (AIDA) are increasingly entering the field of education. Within this context, the subfield of learning analytics (LA) has, since its inception, had a strong emphasis upon ethics, with numerous checklists and frameworks proposed to ensure that student privacy is respected and potential harms avoided. Here,…
Descriptors: Ethics, Learning Analytics, Artificial Intelligence, Data Analysis
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Cook, Jessica; Chen, Cuixian; Reid-Griffin, Angelia – Journal of Effective Teaching in Higher Education, 2019
In a society where first hand work experience is greatly valued many universities or institutions of higher education have designed their Quality enhancement plan (QEP) to address student applied learning. This paper is the results of a university's QEP plan, called Experiencing Transformative Education Through Applied Learning or ETEAL. This…
Descriptors: Experiential Learning, Learning Analytics, College Students, Statistical Analysis
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Huang, Karina; Bryant, Tonya; Schneider, Bertrand – International Educational Data Mining Society, 2019
With the advent of new data collection techniques, there has been a growing interest in studying co-located groups of students using Multimodal Learning Analytics to automatically identify collaborative learning states. In this paper, we analyze a multimodal dataset (N=84) made of eye-tracking, physiological and motion sensing data. We leverage…
Descriptors: Cooperative Learning, Artificial Intelligence, Eye Movements, Learning Analytics
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Karaoglan Yilmaz, Fatma Gizem; Yilmaz, Ramazan – Technology, Knowledge and Learning, 2022
One of the main problems encountered in the online learning process is the low or absence of students' engagement. They may face problems with behavioral engagement, cognitive engagement, emotional engagement in online learning environments. It is thought that the problems related to students' engagements can be overcome with personalized…
Descriptors: Learning Analytics, Intervention, Learner Engagement, Electronic Learning
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Vong, Wai Keen; Lake, Brenden M. – Cognitive Science, 2022
In order to learn the mappings from words to referents, children must integrate co-occurrence information across individually ambiguous pairs of scenes and utterances, a challenge known as cross-situational word learning. In machine learning, recent multimodal neural networks have been shown to learn meaningful visual-linguistic mappings from…
Descriptors: Vocabulary Development, Cognitive Mapping, Problem Solving, Visual Aids
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