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Lynnette Brice; Alison Harrison; Alan Cadwallader – Journal of Open, Flexible and Distance Learning, 2023
The purpose of this paper is to share insights gained from the discovery, design, and delivery phases of creating a three-tiered model of non-academic learning support in open, distance, and flexible learning (ODFL): "Learner Engagement and Success Services (LESS)", at Open Polytechnic | Te Pukenga, New Zealand. Presented as a case…
Descriptors: Ethics, Learning Analytics, Intervention, Foreign Countries
Castillo-Zúñiga, Iván; Luna-Rosas, Francisco-Javier; López-Veyna, Jaime-Iván – Comunicar: Media Education Research Journal, 2022
This article presents an Internet data analysis model based on Web Mining with the aim to find knowledge about large amounts of data in cyberspace. To test the proposed method, suicide web pages were analyzed as a study case to identify and detect traits in students with suicidal tendencies. The procedure considers a Web Scraper to locate and…
Descriptors: Psychological Patterns, Suicide, Web Sites, Student Characteristics
Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
Almatrafi, Omaima – ProQuest LLC, 2018
A Massive Open Online Course (MOOC) is a course that is offered fully online and is usually open for enrollment by any individual, with no limit on the number of participants. MOOCs are a popular resource for learning worldwide with over 23 million new learners registering for MOOCs in 2017 alone. Coursera, the most popular MOOC platform, has…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
Sha, Lele; Rakovic, Mladen; Li, Yuheng; Whitelock-Wainwright, Alexander; Carroll, David; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2021
Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…
Descriptors: Classification, Computer Mediated Communication, Learning Analytics, Data Analysis
Zeng, Ziheng; Chaturvedi, Snigdha; Bhat, Suma – International Educational Data Mining Society, 2017
Characterizing the nature of students' affective and emotional states and detecting them is of fundamental importance in online course platforms. In this paper, we study this problem by using discussion forum posts derived from large open online courses. We find that posts identified as encoding confusion are actually manifestations of different…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
Crossley, Scott; Barnes, Tiffany; Lynch, Collin; McNamara, Danielle S. – International Educational Data Mining Society, 2017
This study takes a novel approach toward understanding success in a math course by examining the linguistic features and affect of students' language production within a blended (with both on-line and traditional face to face instruction) undergraduate course (n=158) on discrete mathematics. Three linear effects models were compared: (a) a…
Descriptors: Success, Mathematics Instruction, Language Usage, Blended Learning
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
Bendjebar, Safia; Lafifi, Yacine; Seridi, Hamid – International Journal of Web-Based Learning and Teaching Technologies, 2016
In e-learning systems, the tutors play many roles and carry out several tasks that differ from one system to another. The activity of tutoring is influenced by many factors. One factor among them is the assignment of the appropriate profile to the tutor. For this reason, the authors propose a new approach for modeling and evaluating the function…
Descriptors: Electronic Learning, Teaching Methods, Classification, Student Needs
Karimi, Hamid; Derr, Tyler; Huang, Jiangtao; Tang, Jiliang – International Educational Data Mining Society, 2020
Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…
Descriptors: Online Courses, Academic Achievement, Prediction, Teaching Methods
Seedhouse, Paul; Knight, Dawn – Applied Linguistics, 2016
There is currently an explosion in the number and range of new devices coming onto the technology market that use digital sensor technology to track aspects of human behaviour. In this article, we present and exemplify a three-stage model for the application of digital sensor technology in applied linguistics that we have developed, namely,…
Descriptors: Foreign Countries, Applied Linguistics, Man Machine Systems, Measurement Equipment
Teplovs, Chris – Journal of Learning Analytics, 2015
This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new, automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on…
Descriptors: Data Analysis, Data Collection, Theory Practice Relationship, Instructional Design
Pardos, Zachary A.; Horodyskyj, Lev – Journal of Learning Analytics, 2019
We introduce a novel approach to visualizing temporal clickstream behaviour in the context of a degree-satisfying online course, "Habitable Worlds," offered through Arizona State University. The current practice for visualizing behaviour within a digital learning environment is to generate plots based on hand-engineered or coded features…
Descriptors: Visualization, Online Courses, Course Descriptions, Data Analysis
Chung, Kon Shing Kenneth; Paredes, Walter Christian – Educational Technology & Society, 2015
In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…
Descriptors: Social Networks, Online Courses, Educational Technology, Electronic Learning
Gissel, Stig T. – Journal of Information Technology Education: Research, 2015
This study was undertaken to design, evaluate and refine an eBook-feature that supports students' decoding of unfamiliar text. The feature supports students' independent reading of eBooks with text-to-speech, graded support in the form of syllabification and rhyme analogy, and by dividing the word material into different categories based on the…
Descriptors: Foreign Countries, Books, Electronic Publishing, Scaffolding (Teaching Technique)