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De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
Mahzoon, Mohammad Javad; Maher, Mary Lou; Eltayeby, Omar; Dou, Wenwen; Grace, Kazjon – Journal of Learning Analytics, 2018
Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a model based on temporal relationships of heterogeneous data as the basis for building predictive models. We show how within- and between-semester temporal patterns can provide insight into the…
Descriptors: Data Analysis, Learning, Models, Time
Mangaroska, Katerina; Sharma, Kshitij; Giannakos, Michail; Træteberga, Hallvard; Dillenbourg, Pierre – Journal of Learning Analytics, 2018
This study investigates how multimodal user-generated data can be used to reinforce learner reflection, improve teaching practices, and close the learning analytics loop. In particular, the aim of the study is to utilize user gaze and action-based data to examine the role of a mirroring tool (i.e., Exercise View in Eclipse) in orchestrating basic…
Descriptors: Eye Movements, Student Behavior, Computer Science Education, Programming
Waddington, R. Joseph; Nam, SungJin; Lonn, Steven; Teasley, Stephanie D. – Journal of Learning Analytics, 2016
Early Warning Systems (EWSs) aggregate multiple sources of data to provide timely information to stakeholders about students in need of academic support. There is an increasing need to incorporate relevant data about student behaviors into the algorithms underlying EWSs to improve predictors of students' success or failure. Many EWSs currently…
Descriptors: Dropout Prevention, Data Analysis, STEM Education, Core Curriculum
Shum, Simon Buckingham; Sándor, Ágnes; Goldsmith, Rosalie; Bass, Randall; McWilliams, Mindy – Journal of Learning Analytics, 2017
When used effectively, reflective writing tasks can deepen learners' understanding of key concepts, help them critically appraise their developing professional identity, and build qualities for lifelong learning. As such, reflective writing is attracting substantial interest from universities concerned with experiential learning, reflective…
Descriptors: Reflection, Writing Assignments, Educational Research, Data Collection
Nguyen, Quan; Huptych, Michal; Rienties, Bart – Journal of Learning Analytics, 2018
Extensive research in learning science has established the importance of time management in online learning. Recently, learning analytics (LA) has shed further lights on the temporal characteristics of learning by allowing researchers to capture authentic digital footprints of student learning behaviours. Nonetheless, students' timing of…
Descriptors: Time Management, Online Courses, Educational Technology, Technology Uses in Education
Herodotou, Christothea; Rienties, Bart; Verdin, Barry; Boroowa, Avinash – Journal of Learning Analytics, 2019
Predictive Learning Analytics (PLA) aim to improve learning by identifying students at risk of failing their studies. Yet, little is known about how best to integrate and scaffold PLA initiatives into higher education institutions. Towards this end, it becomes essential to capture and analyze the perceptions of relevant educational stakeholders…
Descriptors: Prediction, Data Analysis, Higher Education, Distance Education
Atapattu, Thushari; Falkner, Katrina – Journal of Learning Analytics, 2018
Lecture videos are amongst the most widely used instructional methods within present Massive Open Online Courses (MOOCs) and other digital educational platforms. As the main form of instruction, student engagement behaviour, including interaction with videos, directly impacts the student success or failure and accordingly, in-video dropouts…
Descriptors: Lecture Method, Video Technology, Online Courses, Mass Instruction
Caprotti, Olga – Journal of Learning Analytics, 2017
This paper describes investigations in visualizing logpaths of students in an online calculus course held at Florida State University in 2014. The clickstreams making up the logpaths can be used to visualize student progress in the information space of a course as a graph. We consider the graded activities as nodes of the graph, while information…
Descriptors: Online Courses, Calculus, Markov Processes, Graphs
Dvorak, Tomas; Jia, Miaoqing – Journal of Learning Analytics, 2016
This study analyzes the relationship between students' online work habits and academic performance. We utilize data from logs recorded by a course management system (CMS) in two courses at a small liberal arts college in the U.S. Both courses required the completion of a large number of online assignments. We measure three aspects of students'…
Descriptors: Online Courses, Educational Technology, Study Habits, Academic Achievement
Ivancevic, Vladimir – Journal of Learning Analytics, 2014
Tests targeting the upper limits of student ability could aid students in their learning. This article gives an overview of an approach to the construction of such tests in programming, together with ideas on how to implement and refine them within a learning management system.
Descriptors: Item Banks, Educational Research, Data Collection, Data Analysis
Ye, Cheng; Biswas, Gautam – Journal of Learning Analytics, 2014
Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
Crick, Ruth Deakin; Knight, Simon; Barr, Steven – Journal of Learning Analytics, 2017
Central to the mission of most educational institutions is the task of preparing the next generation of citizens to contribute to society. Schools, colleges, and universities value a range of outcomes--e.g., problem solving, creativity, collaboration, citizenship, service to community--as well as academic outcomes in traditional subjects. Often…
Descriptors: Educational Improvement, Holistic Approach, Data Collection, Data Analysis
Miyamoto, Yohsuke R.; Coleman, Cody A.; Williams, Joseph Jay; Whitehill, Jacob; Nesterko, Sergiy; Reich, Justin – Journal of Learning Analytics, 2015
A long history of laboratory and field experiments have demonstrated that dividing study time into many sessions is often superior to massing study time into few sessions, a phenomenon known as the "spacing effect." We use this well-established finding from the psychology literature as inspiration for investigating how students…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
Pardos, Zachary A. – Journal of Learning Analytics, 2015
In Miyamoto et al. (2015, this issue) the authors looked to substantiate the presence of the spacing effect, referenced from the psychology literature, in several MOOCs. Their secondary analyses constituted a robust, empirical finding on the correspondence between session distribution and certification but with only a coarse, analogous…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
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