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Krasodomska, Joanna; Godawska, Justyna – Accounting Education, 2021
In this study, we examined the relationship between university students' engagement in a blended learning course and their performance. We also explored the roles which gender and nationality may play in the learning process. Our sample consisted of 335 students of International Accounting course. We used 23,796 student access computer logs as a…
Descriptors: Accounting, Electronic Learning, Correlation, Blended Learning
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
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
Lodzikowski, Kacper – Language Learning & Technology, 2021
This is the first paper that provides correlational evidence about how interacting with an online allophonic transcription tool helps learners of English as a Second Language (ESL) to improve their phonological awareness. The study investigates 55 advanced ESL learners at a Polish university enrolled in a course in English phonetics and phonology.…
Descriptors: Correlation, Phonological Awareness, Scores, Second Language Learning
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
Gaševic, Dragan; Jovanovic, Jelena; Pardo, Abelardo; Dawson, Shane – Journal of Learning Analytics, 2017
The use of analytic methods for extracting learning strategies from trace data has attracted considerable attention in the literature. However, there is a paucity of research examining any association between learning strategies extracted from trace data and responses to well-established self-report instruments and performance scores. This paper…
Descriptors: Foreign Countries, Undergraduate Students, Engineering Education, Educational Research
Rubio, Fernando; Thomas, Jonathan M.; Li, Qin – Computer Assisted Language Learning, 2018
This chapter describes a study of a blended language course that combines face-to-face (F2F) instructional time with an online component. The purpose of the study is to understand how teachers and students exploit the complementarity of the two delivery formats to improve the learning experience. The study first examines how the presence of an…
Descriptors: Student Participation, Blended Learning, Second Language Learning, Second Language Instruction
Pardo, Abelardo; Han, Feifei; Ellis, Robert A. – IEEE Transactions on Learning Technologies, 2017
Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…
Descriptors: Student Centered Learning, Learning Theories, College Students, Academic Achievement
Andergassen, Monika; Mödritscher, Felix; Neumann, Gustaf – Journal of Learning Analytics, 2014
Learner-centric research on factors influencing learning results has focused, among other things, on student characteristics, demographic data, and usage patterns in learning management systems (LMSs). This paper complements the existing research by investigating potential correlations between learning results and LMS usage during exam…
Descriptors: Drills (Practice), Repetition, Blended Learning, Correlation
McNaught, Carmel; Lam, Paul; Cheng, Kin Fai – Educational Technology Research and Development, 2012
This article reports a study of eLearning in 21 courses in Hong Kong universities that had a blended design of face-to-face classes combined with online learning. The main focus of the study was to examine possible relationships between features of online learning designs and student learning outcomes. Data-collection strategies included expert…
Descriptors: Foreign Countries, Electronic Learning, Blended Learning, Internet
Sampson, Demetrios G., Ed.; Spector, J. Michael, Ed.; Ifenthaler, Dirk, Ed.; Isaias, Pedro, Ed. – International Association for Development of the Information Society, 2016
These proceedings contain the papers of the 13th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2016), October 28-30, 2016, which has been organized by the International Association for Development of the Information Society (IADIS), co-organized by the University of Mannheim, Germany, and endorsed by the…
Descriptors: Conferences (Gatherings), Foreign Countries, Constructivism (Learning), Technological Advancement
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection