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Viet-Ngu Hoang; Will Connell; Radhika Lahiri; H. Nadeeka De Silva; Xuan-Hoan Pham – TechTrends: Linking Research and Practice to Improve Learning, 2025
Dashboards have become a crucial element of contemporary business operation and management; therefore, it is desirable for business students to acquire knowledge of them. This article investigates the effectiveness of designing learning activities around investment dashboards in the context of introductory business analytics (IBA) courses. We…
Descriptors: Introductory Courses, Business Education, Management Systems, Statistics Education
Bo Pei; Ying Cheng; Alex Ambrose; Eva Dziadula; Wanli Xing; Jie Lu – Smart Learning Environments, 2024
The availability of large-scale learning data presents unprecedented opportunities for investigating student learning processes. However, it is challenging for instructors to fully make sense of this data and effectively support their teaching practices. This study introduces LearningViz, an interactive learning analytics dashboard to help…
Descriptors: Learning Analytics, Learning Management Systems, Computer Uses in Education, Educational Technology
Khanal, Shristi Shakya; Prasad, P.W.C.; Alsadoon, Abeer; Maag, Angelika – Education and Information Technologies, 2020
The constantly growing offering of online learning materials to students is making it more difficult to locate specific information from data pools. Personalization systems attempt to reduce this complexity through adaptive e-learning and recommendation systems. The latter are, generally, based on machine learning techniques and algorithms and…
Descriptors: Electronic Learning, Barriers, Online Courses, Accuracy
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
Rafiepour, Abolfazl; Abdolahpour, Kazem; Farsani, Danyal – Mathematics Teaching Research Journal, 2022
The main purpose of this study is to develop a conceptual understanding of the irrational number of the square root of 2 ([square root]2 ). Participants in the study were 20 ninth-grade male students. Activity Theory was used as a framework to show the development of the conceptual understanding. Since this study was conducted during the COVID-19…
Descriptors: Concept Formation, Mathematical Concepts, Mathematics Instruction, COVID-19
Khosravi, Hassan; Kitto, Kirsty; Williams, Joseph Jay – Journal of Learning Analytics, 2019
This paper presents a platform called RiPPLE (Recommendation in Personalised Peer-Learning Environments) that recommends personalized learning activities to students based on their knowledge state from a pool of crowdsourced learning activities that are generated by educators and the students themselves. RiPPLE integrates insights from…
Descriptors: Data Analysis, Learning Activities, Management Systems, Foreign Countries
Kumar, Jeya Amantha; Bervell, Brandford; Osman, Sharifah – Education and Information Technologies, 2020
Google Classroom (GC) has provided affordances for blended learning in higher education. Given this, most institutions, including Malaysian higher educational institutions, are adopting this learning management system (LMS) technology for supporting out of classroom pedagogical. Even though quantitative evidence exists to confirm the usefulness of…
Descriptors: Blended Learning, Teaching Methods, Higher Education, Management Systems
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
Aydogdu, Seyhmus – Education and Information Technologies, 2020
Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made,…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
Smith, Brent; Milham, Laura – Advanced Distributed Learning Initiative, 2021
Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of…
Descriptors: Learning Analytics, Computer Software, Metadata, Learning Activities
DeMara, Ronald F.; Bacanli, Salih S.; Bidoki, Neda; Xu, Jun; Nassiff, Edwin; Donnelly, Julie; Turgut, Damla – Journal of Educational Technology Systems, 2020
This research developed an approach to integrate the complementary benefits of digitized assessments and peer learning. Its basic premise and associated hypotheses are that by using student assessments of correct and incorrect quiz answers using a fine-grained resolution to pair them into remediation peer-learning cohorts is an effective means of…
Descriptors: Undergraduate Students, Engineering Education, Computer Assisted Testing, Pilot Projects
Zarzour, Hafed; Sellami, Mokhtar – Interactive Learning Environments, 2018
In this study, a linked data-based annotation approach is proposed. A learning system has been developed based on the approach by providing an annotating function, a linked data enrichment function, a sharing function and faceted search function. To evaluate the effectiveness of this innovative approach, an experiment was carried out in which two…
Descriptors: Academic Achievement, Documentation, Cognitive Ability, Experimental Groups
Saito, Tomohiro; Watanobe, Yutaka – International Journal of Distance Education Technologies, 2020
Programming education has recently received increased attention due to growing demand for programming and information technology skills. However, a lack of teaching materials and human resources presents a major challenge to meeting this demand. One way to compensate for a shortage of trained teachers is to use machine learning techniques to…
Descriptors: Programming, Computer Science Education, Electronic Learning, Instructional Materials
Godwin-Jones, Robert – Language Learning & Technology, 2017
From its earliest days, practitioners of computer-assisted language learning (CALL) have collected data from computer-mediated learning environments. Indeed, that has been a central aspect of the field from the beginning. Usage logs provided valuable insights into how systems were used and how effective they were for language learning. That…
Descriptors: Second Language Learning, Second Language Instruction, Computer Assisted Instruction, Computer Software
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