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Jennifer Scianna; Rogers Kaliisa – Educational Technology Research and Development, 2024
Educational researchers have pointed to socioemotional dimensions of learning as important in gaining a more nuanced description of student engagement and learning. However, to date, research focused on the analysis of emotions has been narrow in its focus, centering on affect and sentiment analysis in isolation while neglecting how emotions…
Descriptors: Computer Mediated Communication, Discussion, Discourse Analysis, Asynchronous Communication
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Ni Li – International Journal of Web-Based Learning and Teaching Technologies, 2025
In depth exploration of how the pandemic has reshaped the education ecosystem over the past three years, especially in the context of the surge in demand for online education courses and learning platforms, this article focuses on the field of student ideological and political education, and innovatively constructs a moral and political education…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Algorithms
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Fan, Si; Chen, Lihua; Nair, Manoj; Garg, Saurabh; Yeom, Soonja; Kregor, Gerry; Yang, Yu; Wang, Yanjun – Education Sciences, 2021
This study aimed to identify factors influencing student engagement in online and blended courses at one Australian regional university. It applied a data science approach to learning and teaching data gathered from the learning management system used at this university. Data were collected and analysed from 23 subjects, spanning over 5500 student…
Descriptors: Learner Engagement, Learning Analytics, Integrated Learning Systems, Adoption (Ideas)
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Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content
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Li, Jiawei; Supraja, S.; Qiu, Wei; Khong, Andy W. H. – International Educational Data Mining Society, 2022
Academic grades in assessments are predicted to determine if a student is at risk of failing a course. Sequential models or graph neural networks that have been employed for grade prediction do not consider relationships between course descriptions. We propose the use of text mining to extract semantic, syntactic, and frequency-based features from…
Descriptors: Course Descriptions, Learning Analytics, Academic Achievement, Prediction
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Wan, Han; Zhong, Zihao; Tang, Lina; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2023
Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models…
Descriptors: Online Courses, Learning Management Systems, Higher Education, Student Behavior
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Maaliw, Renato R., III – Online Submission, 2020
Most virtual learning environment fails to recognize that students have different needs when it comes to learning. With the evolving characteristics and tendencies of students, these learning environments must provide adaptation and personalization features for adaptive learning materials, course content and navigational designs to support…
Descriptors: Virtual Classrooms, Electronic Learning, Integrated Learning Systems, Individualized Instruction
Amy Graham Goodman – ProQuest LLC, 2021
The goal of learning analytics is to optimize learning and the environments in which it occurs. Since 2011, when learning analytics was defined as a separate and distinct area of academic inquiry, the literature has identified a need for research that presents evidence of effective learning analytics, as well as, learning analytics research that…
Descriptors: Metacognition, Learning Analytics, Calculus, Mathematics Instruction
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Tatel, Corey E.; Lyndgaard, Sibley F.; Kanfer, Ruth; Melkers, Julia E. – Journal of Learning Analytics, 2022
As the demand for lifelong learning increases, many working adults have turned to online graduate education in order to update their skillsets and pursue advanced credentials. Simultaneously, the volume of data available to educators and scholars interested in online learning continues to rise. This study seeks to extend learning analytics…
Descriptors: Course Selection (Students), Enrollment Trends, Academic Achievement, Learning Analytics
Maaliw, Renato R., III – Online Submission, 2016
Virtual Learning Environment (VLE) such as Moodle, Blackboard, and WebCT are commonly and successfully used in E-education. While they focus on supporting educators in creating and holding online courses, they typically do not consider the individual differences of learners. However, learners have different needs and characteristics such as prior…
Descriptors: Virtual Classrooms, Electronic Learning, Integrated Learning Systems, Cognitive Style