Eye tracking, usability, and user experience: A systematic review
Usability and user experience (UX) are emerging concerns around not only application
development but everything designed to be used by people. Evaluation of the UX is, by …
development but everything designed to be used by people. Evaluation of the UX is, by …
Educational data mining: a review of the state of the art
Educational data mining (EDM) is an emerging interdisciplinary research area that deals
with the development of methods to explore data originating in an educational context. EDM …
with the development of methods to explore data originating in an educational context. EDM …
Combining unsupervised and supervised classification to build user models for exploratory learning environments
In this paper, we present a data-based user modeling framework that uses both
unsupervised and supervised classification to build student models for exploratory learning …
unsupervised and supervised classification to build student models for exploratory learning …
Clustering and profiling students according to their interactions with an intelligent tutoring system fostering self-regulated learning
In this paper, we present the results obtained using a clustering algorithm (Expectation-
Maximization) on data collected from 106 college students learning about the circulatory …
Maximization) on data collected from 106 college students learning about the circulatory …
Eye-tracking for user modeling in exploratory learning environments: An empirical evaluation
C Conati, C Merten - Knowledge-Based Systems, 2007 - Elsevier
In this paper, we describe research on using eye-tracking data for on-line assessment of
user meta-cognitive behavior during interaction with an environment for exploration-based …
user meta-cognitive behavior during interaction with an environment for exploration-based …
Applications of machine learning in improving learning environment
Abstract Machine learning are having a tremendous impact on the teaching industry.
Teaching industry is adopting new technologies to predict the future of education system. It …
Teaching industry is adopting new technologies to predict the future of education system. It …
Examining successful attributes for undergraduate students by applying machine learning techniques
CY Ko, FY Leu - IEEE Transactions on Education, 2020 - ieeexplore.ieee.org
Contribution: This study applies supervised and unsupervised machine learning (ML)
techniques to discover which significant attributes that a successful learner often …
techniques to discover which significant attributes that a successful learner often …
Extracting velocity-based user-tracking features to predict learning gains in a virtual reality training application
Virtual Reality (VR) for training and education of real-world tasks has been researched
extensively and has growing use in industry. The data generated by trainees in VR could be …
extensively and has growing use in industry. The data generated by trainees in VR could be …
Supporting teachers in adaptive educational systems through predictive models: A proof of concept
E Gaudioso, M Montero… - Expert Systems with …, 2012 - Elsevier
Adaptive educational systems (AESs) guide students through the course materials in order
to improve the effectiveness of the learning process. However, AES cannot replace the …
to improve the effectiveness of the learning process. However, AES cannot replace the …
[HTML][HTML] Машинное обучение в совершенствовании образовательной среды
КБ Мухамадиева - Образование и проблемы развития общества, 2020 - cyberleninka.ru
Машинное обучение оказывает огромное влияние на педагогическую индустрию.
Преподавательская отрасль внедряет новые технологии для прогнозирования …
Преподавательская отрасль внедряет новые технологии для прогнозирования …