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Nina Bergdahl; Melissa Bond; Jeanette Sjöberg; Mark Dougherty; Emily Oxley – International Journal of Educational Technology in Higher Education, 2024
Educational outcomes are heavily reliant on student engagement, yet this concept is complex and subject to diverse interpretations. The intricacy of the issue arises from the broad spectrum of interpretations, each contributing to the understanding of student engagement as both complex and multifaceted. Given the emergence and increasing use of…
Descriptors: Learner Engagement, College Students, Student Behavior, Educational Technology
Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
Qi Zhou; Wannapon Suraworachet; Mutlu Cukurova – Education and Information Technologies, 2024
Collaboration is argued to be an important skill, not only in schools and higher education contexts but also in the workspace and other aspects of life. However, simply asking students to work together as a group on a task does not guarantee success in collaboration. Effective collaborative learning requires meaningful interactions among…
Descriptors: Learning Analytics, Cooperative Learning, Nonverbal Communication, Speech Communication
Prat, Alain; Code, Warren J. – International Journal of Mathematical Education in Science and Technology, 2021
The online homework system WeBWorK has been successfully used at several hundred colleges and universities. Despite its popularity, the WeBWorK system does not provide detailed metrics of student performance to instructors. In this article, we illustrate how an analysis of the log files of the WeBWorK system can provide information such as the…
Descriptors: Data Analysis, Homework, Student Behavior, Educational Technology
Ameloot, Elise; Rotsaert, Tijs; Schellens, Tammy – Journal of Computer Assisted Learning, 2022
Background: Although blended learning (BL) has multiple educational prospects, it also poses challenges such as keeping students motivated. Objectives: This study investigates students' perceptions of how learning analytics (LA) can be used to support the design of a BL environment in order to promote students' basic need for relatedness, which is…
Descriptors: Learning Analytics, Blended Learning, Student Attitudes, Need Gratification
Chen, Fu; Cui, Ying – Journal of Learning Analytics, 2020
Predictive analytics in higher education has become increasingly popular in recent years with the growing availability of educational big data. Particularly, a wealth of student activity data is available from learning management systems (LMSs) in most academic institutions. However, previous investigations into predictive analytics in higher…
Descriptors: Time on Task, Student Behavior, Integrated Learning Systems, Grade Prediction
Aziman Abdullah – International Society for Technology, Education, and Science, 2023
This study explores the potential of using screen time data in learning management systems (LMS) to estimate student learning time (SLT) and validate the credit value of courses. Gathering comprehensive data on actual student learning time is difficult, so this study uses LMS Moodle logs from a computer programming course with 490 students over 16…
Descriptors: Time Factors (Learning), Handheld Devices, Computer Use, Television Viewing
Thai, Thuan; Hartup, Kate; Colbourn, Adelle; Yeung, Amanda – Australian Journal of Teacher Education, 2021
In Australia, teacher education students must pass the Literacy and Numeracy Test for Initial Teacher Education (LANTITE) to meet accreditation requirements. Although this has been mandated since 2016, there are currently few resources available for students to use in preparation for the test. To help students prepare for the numeracy component of…
Descriptors: Foreign Countries, Computer Assisted Testing, Mathematics Tests, Numeracy
Nepal, Kedar; Paneru, Khyam; Basyal, Deepak – College Student Journal, 2020
This paper presents the results of a study on Calculus students' use of web-based homework. We collected data from students' web-based homework usage, such as their grades, time spent, number of attempts used to solve problems, and problem solutions. We also collected grades on in-class quizzes, which were given the day after homework had been…
Descriptors: Calculus, Undergraduate Students, Web Based Instruction, Mathematics Instruction
Sharma, Bibhya; Nand, Ravneil; Naseem, Mohammed; Reddy, Emmenual V. – Studies in Higher Education, 2020
The widespread use of technology has facilitated many changes in the education sector including higher education. Academic institutes are concentrating their efforts on measuring the level of student engagement and participation in online learning environments for student success. This paper analyses student log data to quantify the effectiveness…
Descriptors: Blended Learning, Learning Analytics, Electronic Learning, Grades (Scholastic)
Xu, Cuiqin; Xia, Jun – Computer Assisted Language Learning, 2021
The last two decades have witnessed a quick shift from pen-and-paper writing to computer keyboard writing. Corresponding to this shift in the writing medium are vigorous research efforts to understand new features of writing in computer keyboard settings. Using Inputlog7.0, this study investigated the writing process of 60 Chinese English as a…
Descriptors: Scaffolding (Teaching Technique), Writing Processes, Writing Skills, English (Second Language)
Chen, Zhongzhou; Xu, Mengyu; Garrido, Geoffrey; Gunthrie, Matthew W. – Physical Review Physics Education Research, 2020
This study examines whether including more contextual information in data analysis could improve our ability to identify the relation between students' online learning behavior and overall performance in an introductory physics course. We created four linear regression models correlating students' pass-fail events in a sequence of online learning…
Descriptors: Correlation, Electronic Learning, Performance Factors, Learning Analytics
Ifenthaler, Dirk; Gibson, David; Zheng, Longwei – International Association for Development of the Information Society, 2018
This study is part of a research programme investigating the dynamics and impacts of learning engagement in a challenge-based digital learning environment. Learning engagement is a multidimensional concept which includes an individual's ability to behaviourally, cognitively, emotionally, and motivationally engage in an on-going learning process.…
Descriptors: Learner Engagement, Electronic Learning, Learning Analytics, College Students
Nguyen, Quan; Rienties, Bart; Richardson, John T. E. – Assessment & Evaluation in Higher Education, 2020
Although the attainment gap between black and minority ethnic (BME) students and white students has persisted for decades, the potential causes of these disparities are highly debated. The emergence of learning analytics allows researchers to understand how students engage in learning activities based on their digital traces in a naturalistic…
Descriptors: Learning Analytics, Academic Achievement, Achievement Gap, Racial Differences