NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 46 results Save | Export
Wesley Jeffrey – ProQuest LLC, 2024
Sociologists of education have a longstanding interest in studying the relationship between schooling and inequality in society. While we know education matters for who gets ahead, we still know relatively less about the processes and mechanisms behind this relationship. In my dissertation, I focus on higher education as a key site where…
Descriptors: Academic Rank (Professional), Higher Education, Social Networks, Correlation
Peer reviewed Peer reviewed
Direct linkDirect link
Sun, Geng; Lin, Jiayin; Shen, Jun; Cui, Tingru; Xu, Dongming; Kayastha, Mahesh – British Journal of Educational Technology, 2020
Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an…
Descriptors: Learning Activities, Data Analysis, Open Education, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
Kam Hong Shum; Samuel Kai Wah Chu; Cheuk Yu Yeung – Interactive Learning Environments, 2023
This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…
Descriptors: Student Behavior, Online Courses, Cooperative Learning, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
de Carvalho, Walisson Ferreira; Zárate, Luis Enrique – International Journal of Information and Learning Technology, 2021
Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…
Descriptors: Causal Models, Algorithms, Learning Analytics, Correlation
Peer reviewed Peer reviewed
Direct linkDirect link
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals
Chen, Li; Yoshimatsu, Nobuyuki; Goda, Yoshiko; Okubo, Fumiya; Taniguchi, Yuta; Oi, Misato; Konomi, Shin'ichi; Shimada, Atsushi; Ogata, Hiroaki; Yamada, Masanori – Research and Practice in Technology Enhanced Learning, 2019
The purpose of this study was to explore the factors that might affect learning performance and collaborative problem solving (CPS) awareness in science, technology, engineering, and mathematics (STEM) education. We collected and analyzed data on important factors in STEM education, including learning strategy and learning behaviors, and examined…
Descriptors: STEM Education, Cooperative Learning, Feedback (Response), Learning Strategies
Peer reviewed Peer reviewed
Direct linkDirect link
Chen, Weiyu; Brinton, Christopher G.; Cao, Da; Mason-Singh, Amanda; Lu, Charlton; Chiang, Mung – IEEE Transactions on Learning Technologies, 2019
We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…
Descriptors: Online Courses, Outcomes of Education, Prediction, Course Content
Peer reviewed Peer reviewed
Direct linkDirect link
Montgomery, Amanda P.; Mousavi, Amin; Carbonaro, Michael; Hayward, Denyse V.; Dunn, William – British Journal of Educational Technology, 2019
Blended learning (BL) is a popular e-Learning model in higher education that has the potential to take advantage of learning analytics (LA) to support student learning. This study utilized LA to investigate fourth-year undergraduates' (n = 157) use of self-regulated learning (SRL) within the online components of a previously unexamined BL…
Descriptors: Blended Learning, Educational Technology, Higher Education, Undergraduate Students
Peer reviewed Peer reviewed
Direct linkDirect link
Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel – Journal of Educational Computing Research, 2019
Several studies have focused on identifying the significant behavioral predictors of learning performances in web-based courses by examining the log data variables of learning management systems, including time spent on lectures, the number of assignments submitted, and so forth. However, such studies fail to quantify the impact of emotional,…
Descriptors: Predictor Variables, Correlation, Student Motivation, Metacognition
Peer reviewed Peer reviewed
Direct linkDirect link
Worsley, Marcelo; Blikstein, Paulo – International Journal of Artificial Intelligence in Education, 2018
This paper presents three multimodal learning analytic approaches from a hands-on learning activity. We use video, audio, gesture and bio-physiology data from a two-condition study (N = 20), to identify correlations between the multimodal data, experimental condition, and two learning outcomes: design quality and learning. The three approaches…
Descriptors: Multimedia Materials, Correlation, Outcomes of Education, Design
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Pytlarz, Ian; Pu, Shi; Patel, Monal; Prabhu, Rajini – International Educational Data Mining Society, 2018
Identifying at-risk students at an early stage is a challenging task for colleges and universities. In this paper, we use students' oncampus network traffic volume to construct several useful features in predicting their first semester GPA. In particular, we build proxies for their attendance, class engagement, and out-of-class study hours based…
Descriptors: College Freshmen, Grade Point Average, At Risk Students, Academic Achievement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Shen, Shitian; Mostafavi, Behrooz; Barnes, Tiffany; Chi, Min – Journal of Educational Data Mining, 2018
An important goal in the design and development of Intelligent Tutoring Systems (ITSs) is to have a system that adaptively reacts to students' behavior in the short term and effectively improves their learning performance in the long term. Inducing effective pedagogical strategies that accomplish this goal is an essential challenge. To address…
Descriptors: Teaching Methods, Markov Processes, Decision Making, Rewards
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Vieira, Camilo; Goldstein, Molly Hathaway; Purzer, Senay; Magana, Alejandra J. – Journal of Learning Analytics, 2016
Engineering design is a complex process both for students to participate in and for instructors to assess. Informed designers use the key strategy of conducting experiments as they test ideas to inform next steps. Conversely, beginning designers experiment less, often with confounding variables. These behaviours are not easy to assess in…
Descriptors: Engineering, Design, Experiments, Student Behavior
Peer reviewed Peer reviewed
PDF on ERIC Download full text
McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2016
Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate…
Descriptors: Data Collection, Student Behavior, Academic Achievement, Correlation
Hillman, Kylie – Australian Council for Educational Research, 2015
Surveys like the recent Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study (PIRLS) enable educators, policy makers and the wider community to compare Australian students with each other, as well as their counterparts across the world. An essential part of a positive school climate…
Descriptors: Foreign Countries, Bullying, Educational Research, Behavior Problems
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4