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Kapelner, Adam; Soterwood, Jeanine; Nessaiver, Shalev; Adlof, Suzanne – IEEE Transactions on Learning Technologies, 2018
Vocabulary knowledge is essential to educational progress. High quality vocabulary instruction requires supportive contextual examples to teach word meaning and proper usage. Identifying such contexts by hand for a large number of words can be difficult. In this work, we take a statistical learning approach to engineer a system that predicts…
Descriptors: Vocabulary Development, Databases, Training, Models
Mangaroska, Katerina; Giannakos, Michail – IEEE Transactions on Learning Technologies, 2019
As the fields of learning analytics and learning design mature, the convergence and synergies between the two are becoming an important area for research. This paper intends to summarize the main outcomes of a systematic review of empirical evidence on learning analytics for learning design. Moreover, this paper presents an overview of what and…
Descriptors: Data Analysis, Instructional Design, Learning Activities, Databases
Usai, Francesco; O'Neil, Kiera G. R.; Newman, Aaron J. – IEEE Transactions on Learning Technologies, 2018
Computer and smartphone-based applications for second language (L2) learning have become popular tools, being integrated in many classroom-based courses and adopted by the public at large. Yet, despite a significant body of research that suggests that individuals differ in their ability to learn L2, it is still unclear what factors predict…
Descriptors: Second Language Instruction, Educational Technology, Technology Uses in Education, Educational Games
Schwendimann, Beat A.; Rodriguez-Triana, Maria Jesus; Vozniuk, Andrii; Prieto, Luis P.; Boroujeni, Mina Shirvani; Holzer, Adrian; Gillet, Denis; Dillenbourg, Pierre – IEEE Transactions on Learning Technologies, 2017
This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning…
Descriptors: Literature Reviews, Educational Research, Data Analysis, Data Processing
Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Mejia, Carolina; Florian, Beatriz; Vatrapu, Ravi; Bull, Susan; Gomez, Sergio; Fabregat, Ramon – IEEE Transactions on Learning Technologies, 2017
Existing tools aim to detect university students with early diagnosis of dyslexia or reading difficulties, but there are not developed tools that let those students better understand some aspects of their difficulties. In this paper, a dashboard for visualizing and inspecting early detected reading difficulties and their characteristics, called…
Descriptors: Clinical Diagnosis, Dyslexia, Visualization, Metacognition

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