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Beasley, Zachariah J.; Piegl, Les A.; Rosen, Paul – IEEE Transactions on Learning Technologies, 2021
Accurately grading open-ended assignments in large or massive open online courses is nontrivial. Peer review is a promising solution but can be unreliable due to few reviewers and an unevaluated review form. To date, no work has leveraged sentiment analysis in the peer-review process to inform or validate grades or utilized aspect extraction to…
Descriptors: Case Studies, Online Courses, Assignments, Peer Evaluation
Fan, Si; Chen, Lihua; Nair, Manoj; Garg, Saurabh; Yeom, Soonja; Kregor, Gerry; Yang, Yu; Wang, Yanjun – Education Sciences, 2021
This study aimed to identify factors influencing student engagement in online and blended courses at one Australian regional university. It applied a data science approach to learning and teaching data gathered from the learning management system used at this university. Data were collected and analysed from 23 subjects, spanning over 5500 student…
Descriptors: Learner Engagement, Learning Analytics, Integrated Learning Systems, Adoption (Ideas)
Scanlon, Eileen – Journal of Interactive Media in Education, 2021
This paper explores the development of educational technology research over the last 50 years. This is done by considering what has influenced this development and what are current trends. The issue is further explored by considering what influence these trends have had on the development of distance learning pedagogy, especially for the education…
Descriptors: Educational Technology, Educational Research, Educational History, Educational Trends
Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Pardo, Abelardo; Fudge, Anthea; Gentili, Sheridan – Assessment & Evaluation in Higher Education, 2021
Research and development in learning analytics has established viable solutions for scaling personalised feedback to all students. However, questions remain regarding how such feedback is perceived, interpreted and acted upon by stakeholders. The present study reports on the analysis of focus group data from four courses to understand students'…
Descriptors: Student Attitudes, College Students, Emotional Response, Individualized Instruction
Yang, Albert C. M.; Chen, Irene Y. L.; Flanagan, Brendan; Ogata, Hiroaki – Educational Technology & Society, 2021
Precision education is a new challenge in leveraging artificial intelligence, machine learning, and learning analytics to enhance teaching quality and learning performance. To facilitate precision education, text marking skills can be used to determine students' learning process. Text marking is an essential learning skill in reading. In this…
Descriptors: Grading, Computer Assisted Testing, Automation, Artificial Intelligence
Hunt, Pihel; Leijen, Äli; van der Schaaf, Marieke – Education Sciences, 2021
While there is now extensive research on feedback in the context of higher education, including pre-service teacher education, little has been reported regarding the use of feedback from teachers to other teachers. Moreover, literature on the potential advantages that the use of technology, for example electronic portfolios and learning analytics,…
Descriptors: Teacher Attitudes, Teacher Evaluation, Peer Evaluation, Feedback (Response)
Lim, Soo Mang; Ghavifekr, Simin; Kenayathulla, Husaina Banu – Malaysian Online Journal of Educational Sciences, 2021
Dramatic shifts brought about by globalization, technological innovation, and data-driven decision-making practices are immensely reflected in the landscape of 21st century higher education. Learning Analytics or LA is an emerging multidisciplinary, technological practice with the ultimate goal of producing effective learning to improve students'…
Descriptors: Learning Analytics, Strategic Planning, Leadership Styles, Administrative Policy
Ninasivincha-Apfata, Jhon Edwar; Quispe-Figueroa, Ricardo Carlos; Valderrama-Solis, Manuel Alejandro; Maraza-Quispe, Benjamin – World Journal on Educational Technology: Current Issues, 2021
The objective of the research is to develop a methodology to analyse a set of data extracted from a learning management system, in order to implement a dashboard, which can be used by teachers to make timely and relevant decisions to improve the teaching-learning processes. The methodology used consisted of analysing 9,257 records extracted…
Descriptors: Learning Analytics, Integrated Learning Systems, Visual Aids, Technology Uses in Education
Joseph-Richard, Paul; Uhomoibhi, James; Jaffrey, Andrew – International Journal of Information and Learning Technology, 2021
Purpose: The aims of this study are to examine affective responses of university students when viewing their own predictive learning analytics (PLA) dashboards, and to analyse how those responses are perceived to affect their self-regulated learning behaviour. Design/methodology/approach: A total of 42 Northern Irish students were shown their own…
Descriptors: Prediction, Learning Analytics, Student Behavior, Affective Behavior
Dickler, Rachel; Gobert, Janice; Sao Pedro, Michael – Grantee Submission, 2021
Educational technologies, such as teacher dashboards, are being developed to support teachers' instruction and students learning. Specifically, dashboards support teachers in providing the just-in-time instruction needed by students in complex contexts such as science inquiry. In this study, we used the Inq-Blotterteacher-alerting dashboard to…
Descriptors: Educational Technology, Science Education, Science Process Skills, Intelligent Tutoring Systems
McAleavy, Tony; Riggall, Anna; Naylor, Ruth – Education Development Trust, 2021
Efficient use of resources depends upon many factors, but one key variable is the extent to which we design and implement activities which require funding in a way that is informed by relevant evidence. The application of insights about 'what works', derived from robust research, combined with evidence about context and real-time system data have,…
Descriptors: Evidence, Evidence Based Practice, Educational Improvement, Educational Research
Zualkernan, Imran – International Association for Development of the Information Society, 2021
A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…
Descriptors: Prediction, Engineering Education, Academic Achievement, Dropouts
Li, Xiaoyu; Xia, Jianping – Science Insights Education Frontiers, 2020
The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…
Descriptors: Foreign Countries, Middle School Students, Data Analysis, Data Collection
Chen, Fu; Cui, Ying; Chu, Man-Wai – International Journal of Artificial Intelligence in Education, 2020
The purpose of this case study is to demonstrate how to utilize machine learning approaches to analyze student process data for validating and informing digital game-based assessments (DGBAs) with an evidence-centered game design (ECgD). The first analysis was conducted to examine whether students' mastery of the overall skill required by the game…
Descriptors: Game Based Learning, Learning Analytics, Design, Evidence Based Practice
Ibañez, Patricia; Villalonga, Cristina; Nuere, Leire – Technology, Knowledge and Learning, 2020
The main objective of educational institutions is to achieve the integral development of their students in their learning and knowledge construction process. One way to achieve these objectives is the accompaniment and continuous monitoring of students in this process, adapting the methods to their training needs. In online and mixed teaching…
Descriptors: Learning Analytics, Foreign Countries, Educational Environment, Electronic Learning

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