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Chiu, Wang-Kin – Education Sciences, 2021
The technological advancement and rapid development of artificial intelligence have led to a growing number of studies investigating pedagogical innovations incorporated with emerging technologies in this digital era. An increasing amount of empirical evidence has suggested the potential benefits of incorporating digital technologies and…
Descriptors: Technological Advancement, Artificial Intelligence, Educational Innovation, Educational Technology
Houston, David M.; Henig, Jeffrey R. – Annenberg Institute for School Reform at Brown University, 2021
We examine the effects of disseminating academic performance data--either status, growth, or both--on parents' school choices and their implications for racial, ethnic, and economic segregation. We conduct an online survey experiment featuring a nationally representative sample of parents and caretakers of children age 0-12. Participants choose…
Descriptors: School Choice, School Segregation, Accountability, Academic Achievement
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Rajabalee, Yousra Banoor; Santally, Mohammad Issack; Rennie, Frank – International Journal of Distance Education Technologies, 2020
This paper reports the findings of a research using marks of students in learning activities of an online module to build a predictive model of performance for the final assessment of the module. The objectives were (1) to compare the performances of students of two cohorts in terms of continuous learning assessment marks and final learning…
Descriptors: Performance Factors, Electronic Learning, Learning Analytics, Learning Activities
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Georgakopoulos, Ioannis; Chalikias, Miltiadis; Zakopoulos, Vassilis; Kossieri, Evangelia – Education Sciences, 2020
Our modern era has brought about radical changes in the way courses are delivered and various teaching methods are being introduced to answer the purpose of meeting the modern learning challenges. On that account, the conventional way of teaching is giving place to a teaching method which combines conventional instructional strategies with…
Descriptors: Academic Failure, Blended Learning, Learner Engagement, Student Participation
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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
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Knoop-van Campen, Carolien; Molenaar, Inge – Frontline Learning Research, 2020
In technology empowered classrooms teachers receive real-time data about students' performance and progress on teacher dashboards. Dashboards have the potential to enhance teachers' feedback practices and complement human-prompted feedback that is initiated by teachers themselves or students asking questions. However, such enhancement requires…
Descriptors: Feedback (Response), Technology Integration, Teacher Student Relationship, Behavior Patterns
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Mozahem, Najib Ali – International Journal of Mobile and Blended Learning, 2020
Higher education institutes are increasingly turning their attention to web-based learning management systems. The purpose of this study is to investigate whether data collected from LMS can be used to predict student performance in classrooms that use LMS to supplement face-to-face teaching. Data was collected from eight courses spread across two…
Descriptors: Integrated Learning Systems, Data Use, Prediction, Academic Achievement
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Tärning, Betty; Lee, Yeon Joo; Andersson, Richard; Månsson, Kristian; Gulz, Agneta; Haake, Magnus – Journal of the Learning Sciences, 2020
Background: Previous research shows that critical constructive feedback, that scaffolds students to improve on tasks, often remains untapped. The paper's aim is to illuminate at what stages students provided with such feedback drop out of feedback processing. Methods: In our model, students can drop out at any of five stages of feedback…
Descriptors: Feedback (Response), Computer Games, Educational Games, Elementary School Students
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Varghese, Femina P.; Nolan, Jon; Ali, Saba Rasheed; Anderson, Evan; Southerland, Ryan – Journal of Career Development, 2020
Vocational psychologists have predicted the utilization of telepsychology in career interventions, yet vocational research have not capitalized on this modality. The purpose of this article is to describe how telepsychology could be used effectively in vocational psychology research to expand the reach and application of the field's scholarship to…
Descriptors: Industrial Psychology, Career Counseling, Computer Mediated Communication, Ethics
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Kent, Carmel; Cukurova, Mutlu – Journal of Learning Analytics, 2020
Although collaboration is considered a key 21st-century skill, oftentimes it is only assessed through the outcome measures of individual learners. In this paper, we draw upon collaborative cognitive load theory (CCLT) to explain the process of collaboration in learning from the point of view of the collective, rather than an individual learner.…
Descriptors: Cooperative Learning, Learning Analytics, Difficulty Level, Evaluation Methods
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Cookson, April; Kim, Daesang; Hartsell, Taralynn – International Journal of Information and Communication Technology Education, 2020
The purpose of this project was to increase student achievement, engagement, and satisfaction using animated instructional videos in an online general psychology course at a community college. This project not only considered the data collected from student activity tracking, but also examined students' perception of how the videos engaged and…
Descriptors: Academic Achievement, Learner Engagement, Student Satisfaction, Animation
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Chu, Wei; Pavlik, Philip I., Jr. – International Educational Data Mining Society, 2023
In adaptive learning systems, various models are employed to obtain the optimal learning schedule and review for a specific learner. Models of learning are used to estimate the learner's current recall probability by incorporating features or predictors proposed by psychological theory or empirically relevant to learners' performance. Logistic…
Descriptors: Reaction Time, Accuracy, Models, Predictor Variables
Dina Foster; Caitlin McLemore; Brandon Olszewski; Ali Chaudhry; Ekaterina Cooper; Laurie Forcier; Rose Luckin – UK Department for Education, 2023
A rapid, exploratory review to establish a shared understanding of what constitutes good quality EdTech and implementation. The review: (1) examined existing frameworks and standards; and (2) identified the characteristics, quality components, essential conditions and evaluation criteria for the design and implementation of EdTech. The report…
Descriptors: Standards, Educational Technology, Guidelines, Evidence Based Practice
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Shabnam Ara S. J.; Tanuja R. – Journal of Education and e-Learning Research, 2024
Understanding the factors that influence students' results in hybrid learning environments is becoming increasingly important in today's educational environment. The goal of this research is to examine factors that influence students' academic performance as well as their level of participation in blended learning environments. A comprehensive…
Descriptors: Academic Achievement, Blended Learning, Learning Analytics, Technology Education
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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
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