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Fuentes, Pablo; Camarero, Cristobal; Herreros, David; Mateev, Vladimir; Vallejo, Fernando; Martinez, Carmen – IEEE Transactions on Learning Technologies, 2022
Understanding the architecture of a processor can be uninteresting and deterring for computer science students, since low-level details of computer architecture are often perceived to lack real-world impact. These courses typically have a strong practical component where students learn the fundamentals of the computer architecture and the handling…
Descriptors: Computer Science Education, Computer System Design, Programming Languages, Fatigue (Biology)
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Larraza-Mendiluze, Edurne; Garay-Vitoria, Nestor; Soraluze, Iratxe; Martín, José; Muguerza, Javier; Ruiz-Vazquez, Txelo – ACM Transactions on Computing Education, 2016
The computer input/output (I/O) subsystem and its functioning are very abstract concepts that are difficult for undergraduate freshmen to understand. However, it is important that freshmen assimilate these low-level concepts if they are going to be taught about the operating systems (OS) working over that architecture layer, or working directly…
Descriptors: Active Learning, Student Projects, Computer Science Education, College Freshmen
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Verdú, Elena; Regueras, Luisa M.; Gal, Eran; de Castro, Juan P.; Verdú, María J.; Kohen-Vacs, Dan – Educational Technology Research and Development, 2017
INTUITEL is a research project aiming to offer a personalized learning environment. The INTUITEL approach includes an Intelligent Tutoring System that gives students recommendations and feedback about what the best learning path is for them according to their profile, learning progress, context and environmental influences. INTUITEL combines…
Descriptors: Technology Integration, Intelligent Tutoring Systems, Computer Networks, Computer System Design
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Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
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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