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Matthew Mauntel; Michelle Zandieh – International Journal of Research in Undergraduate Mathematics Education, 2024
In this article we analyze how students reason about linear combinations across multiple digital environments. We present the work of three groups of undergraduate students in the Southeast United States (US) who were considered ready to take linear algebra. The students played the game "Vector Unknown," reflected upon aspects of their…
Descriptors: Video Games, Algebra, Mathematics Instruction, Teaching Methods
Dominguez, Federico; Ochoa, Xavier; Zambrano, Dick; Camacho, Katherine; Castells, Jaime – IEEE Transactions on Learning Technologies, 2021
Multimodal learning analytics, which is collection, analysis, and report of diverse learning traces to better understand and improve the learning process, has been producing a series of interesting prototypes to analyze learning activities that were previously hard to objectively evaluate. However, none of these prototypes have been taken out of…
Descriptors: Learning Modalities, Learning Analytics, Automation, Oral Language
Witzenberger, Kevin; Gulson, Kalervo N. – Learning, Media and Technology, 2021
Pre-emption describes a system of automated knowledge creation and intervention that steers the present towards a desirable future, by building on knowledge derived from the past. Folding together temporalities makes it impossible to disprove pre-emption. It is increasingly featured within EdTech, introducing new forms of automated governance into…
Descriptors: Educational Technology, Technology Uses in Education, Governance, Learning Analytics
Prinsloo, Paul; Slade, Sharon; Khalil, Mohammad – British Journal of Educational Technology, 2022
Evidence shows that appropriate use of technology in education has the potential to increase the effectiveness of, eg, teaching, learning and student support. There is also evidence that technology can introduce new problems and ethical issues, e.g., student privacy. This article maps some limitations of technological approaches that ensure…
Descriptors: Student Records, Data, Privacy, Learning Analytics
Taylor, Kevin – Education and Culture, 2022
For Dewey, growth in the educative process means education that enriches and expands one's experience as it prepares students for not only a vocation but also entry into and transaction with the world. In few places can we see growth, generally understood, to be occurring as fast as in big data technology. This essay begins with an overview of…
Descriptors: Educational Philosophy, Educational Development, Technology Uses in Education, Learning Analytics
Doleck, Tenzin; Lemay, David John; Basnet, Ram B.; Bazelais, Paul – Education and Information Technologies, 2020
Large swaths of data are readily available in various fields, and education is no exception. In tandem, the impetus to derive meaningful insights from data gains urgency. Recent advances in deep learning, particularly in the area of voice and image recognition and so-called complete knowledge games like chess, go, and StarCraft, have resulted in a…
Descriptors: Learning Analytics, Prediction, Information Retrieval, Accuracy
Gongchang, Yueban; Wang, Yibing – AERA Online Paper Repository, 2020
Location tracking devices are becoming increasingly popular in practice to study movement of customers or track inventory. However, using location tracking devices in education contexts is quite novel. In this paper, we present a robust Bayesian nonparametric mixture model that clusters location data. We successfully apply this model on location…
Descriptors: Bayesian Statistics, Nonparametric Statistics, Multivariate Analysis, Interaction
Chen, Wenli; Tan, Jesmine S. H.; Zhang, Si; Pi, Zhongling; Lyu, Qianru – Educational Technology Research and Development, 2023
Nurturing twenty-first-century competency is one important agenda in this era, especially in developing collaborative learning and critical thinking skills. Yet, facilitating such a computer-supported collaborative learning (CSCL) environment is challenging. Although several technological platforms from past research studies were developed to…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Learning Analytics, Educational Technology
Jenay Robert – EDUCAUSE, 2024
Increasingly, data collection and analysis are core functions of higher education institutions. However, an EDUCAUSE QuickPoll revealed that just one in four (25%) of respondents believed the structure of data functions at their institution was ideal for their analytics needs, and only 16% of respondents indicated that their institutional data…
Descriptors: Higher Education, Learning Analytics, Data Collection, Privacy
Prasoon Patidar; Tricia J. Ngoon; Neeharika Vogety; Nikhil Behari; Chris Harrison; John Zimmerman; Amy Ogan; Yuvraj Agarwal – Journal of Learning Analytics, 2024
Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…
Descriptors: Learning Analytics, Classroom Observation Techniques, Data Analysis, Student Behavior
Tlili, Ahmed; Essalmi, Fathi; Jemni, Mohamed; Kinshuk, P.; Chen, Nian-Shing – International Journal of Information and Communication Technology Education, 2019
Advances in technology have given the learning analytics (LA) area further potential to enhance the learning process by using methods and techniques that harness educational data. However, the lack of guidelines on what should be taken into considerations during application of LA hinders its full adoption. Therefore, this article investigates the…
Descriptors: Learning Analytics, Data Use, Design Requirements, Validity
Han, Areum; Krieger, Florian; Greiff, Samuel – Journal of Learning Analytics, 2021
As technology advances, learning analytics is expanding to include students' collaboration settings. Despite their increasing application in practice, some types of analytics might not fully capture the comprehensive educational contexts in which students' collaboration takes place (e.g., when data is collected and processed without predefined…
Descriptors: Learning Analytics, Cooperative Learning, Classroom Environment, Time Factors (Learning)
Khulbe, Manisha; Tammets, Kairit – Technology, Knowledge and Learning, 2023
Insights derived from classroom data can help teachers improve their practice and students' learning. However, a number of obstacles stand in the way of widespread adoption of data use. Teachers are often sceptical about the usefulness of data. Even when willing to work with data, they often do not have the relevant skills. Tools for analysis of…
Descriptors: Faculty Development, Learning Analytics, Intervention, Teacher Attitudes
Laura Froehlich; Sebastian Weydner-Volkmann – Journal of Learning Analytics, 2024
Educational disparities between traditional and non-traditional student groups in higher distance education can potentially be reduced by alleviating social identity threat and strengthening students' sense of belonging in the academic context. We present a use case of how Learning Analytics and Machine Learning can be applied to develop and…
Descriptors: Learning Analytics, Electronic Learning, Distance Education, Equal Education
Omid Noroozi – International Journal of Technology in Education, 2025
The world currently grapples with ambiguity and uncertainty, facing ongoing challenges that span various aspects of life, from economic fluctuations and political instability to environmental crises and technological advancements. Confronting such ambiguity and uncertainty highlights the critical importance of equipping learners with…
Descriptors: Transformative Learning, Technology Uses in Education, Scaffolding (Teaching Technique), Computer Games

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