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Mthokozisi Masumbika Ncube; Patrick Ngulube – Discover Education, 2025
Despite the increasing interest in data analytics applications within postgraduate education research, there remains a significant gap in research dedicated to exploring mixed methods research for such investigations. This study undertook to bridge this gap by exploring the application and use of mixed methods research to examine data analytics…
Descriptors: Data Analysis, Graduate Students, Educational Research, Mixed Methods Research
Mark Nichols – Open Learning, 2024
Learning analytics promise significant benefit to online education providers through improved, better-targeted student services. Much has been written about the potential of analytics and how they might be technically implemented, and various ethical considerations are published highlighting the significant potential risk of gathering,…
Descriptors: Learning Analytics, Ethics, Guidelines, Policy Formation
Wong, Billy Tak-ming; Li, Kam Cheong; Cheung, Simon K. S. – Journal of Computing in Higher Education, 2023
This paper presents an analysis of learning analytics practices which aimed to achieve personalised learning. It addresses the need for a systematic analysis of the increasing amount of practices of learning analytics which are targeted at personalised learning. The paper summarises and highlights the characteristics and trends in relevant…
Descriptors: Learning Analytics, Individualized Instruction, Context Effect, Stakeholders
Ridwan Whitehead; Andy Nguyen; Sanna Järvelä – Journal of Learning Analytics, 2025
Incorporating non-verbal data streams is essential to understanding the dynamics of interaction within collaborative learning environments in which a variety of verbal and non-verbal modes of communication intersect. However, the complexity of non-verbal data -- especially gathered in the wild from collaborative learning contexts -- demands…
Descriptors: Case Studies, Nonverbal Communication, Video Technology, Data Analysis
Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
Caspari-Sadeghi, Sima – Cogent Education, 2023
Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…
Descriptors: Learning Analytics, Data Analysis, Higher Education, Feedback (Response)
Zhang, Yuyu; Chan, Kan Kan – Interactive Learning Environments, 2023
Visual analytics (VA) technology has become a significant tool for business decision-makers to explore novel insights. One of its key features is analytical reasoning through interactive visualization that users have direct sensemaking in problem-solving processes. Few studies have examined how VA can be applied in business education for improving…
Descriptors: Visual Aids, Visualization, Learning Analytics, Data Analysis
Ana Stojanov; Ben Kei Daniel – Education and Information Technologies, 2024
The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…
Descriptors: Higher Education, Learning Analytics, Well Being, Decision Making
Feldman-Maggor, Yael; Barhoom, Sagiv; Blonder, Ron; Tuvi-Arad, Inbal – Education and Information Technologies, 2021
Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…
Descriptors: Data Analysis, Educational Research, Data Processing, Learning Analytics
Zareen Alamgir; Habiba Akram; Saira Karim; Aamir Wali – Informatics in Education, 2024
Educational data mining is widely deployed to extract valuable information and patterns from academic data. This research explores new features that can help predict the future performance of undergraduate students and identify at-risk students early on. It answers some crucial and intuitive questions that are not addressed by previous studies.…
Descriptors: Data Analysis, Information Retrieval, Content Analysis, Information Technology
Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Paul Joseph-Richard; James Uhomoibhi – INFORMS Transactions on Education, 2024
Scholarly interests in developing personalized learning analytics dashboards (LADs) in universities have been increasing. LADs are data visualization tools for both teachers and learners that allow them to support student success and improve teaching and learning. In most LADs, however, a teacher-centric, institutional view drives their designs,…
Descriptors: Learning Analytics, Learning Management Systems, Independent Study, Undergraduate Students
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
Mouri, Kousuke; Suzuki, Fumiya; Shimada, Atsushi; Uosaki, Noriko; Yin, Chengjiu; Kaneko, Keiichi; Ogata, Hiroaki – Interactive Learning Environments, 2021
This paper describes a method to collect data of which section of pages learners were browsing in digital textbooks without eye-tracking technologies. In previous researches on digital textbook systems, it was difficult to collect such data without using eye-tackers. However, eye-trackers cost a massive budget. Our proposed system automatically…
Descriptors: Data Analysis, Textbooks, Electronic Publishing, Data Collection
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