Framework for Intervention and Assistance in University Students with Dyslexia

Corredor, Carolina Mejía; Gesa, Ramón Fabregat

doi:10.1109/icalt.2012.170

Cited by 6 publications

(2 citation statements)

References 4 publications

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“…Flipped classroom allows learners to communicate through visual, auditory, and voice channels to achieve personalized interaction with tools and improve students ' motivation and performance [47].…”

Section: Personalized Development Of Students In the Flipped Classroommentioning

confidence: 99%

The Influence of the Traditional Teaching Approach Transfer to Flipped Classroom Approach on Dyslexia

Chen¹

2021

Advances in Social Science, Education and Humanities Research

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Many studies have shown that the development of teaching methods and the influence factors of dyslexia have something in common for learners. However, the influence of the teaching approach on dyslexia remains unclear and still has details that need to be further studied. In this study, I attempt to review the influence of the traditional teaching approach transfer to flipped classroom approach on dyslexia through various literary theories. I expected to find out flipped classroom approach influences dyslexia, and flipped classroom approach can help learners with dyslexia. In practice, it can help learners with dyslexia or educators who treat dyslexia.

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Section: Personalized Development Of Students In the Flipped Classroommentioning

confidence: 99%

The Influence of the Traditional Teaching Approach Transfer to Flipped Classroom Approach on Dyslexia

Chen¹

2021

Advances in Social Science, Education and Humanities Research

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“…Learning analytics are being used within the field of teaching and learning for many purposes: identifying students at risk in their academic programming [4], early detection of ADHD [5] or providing personalized and adapted support to university students with dyslexia [6]. Also, learning curves have been used for some time to perform summative evaluations of educational systems, including comparing multiple versions of a system to evaluate whether new features are beneficial or detrimental to learning performance [7].…”

Section: Introductionmentioning

confidence: 99%

Managing E-Learning Metadata Within TOOLBOX.ACADEMY: Knowledge Acquisition With Big Data Algorithms at the Student and Group Levels

Vico¹,

M²,

Orden³

et al. 2019

EDULEARN Proceedings

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E-learning is not only providing new means to access knowledge, and changing the way teaching takes place at the school and at home, it is also paving the way to learn more and know better about the students' skills, competences, attitude or disorders. Statistics and AI-based big data are the methods to acquire this knowledge, that is of great value for educators and managing teams. Indeed, what looks like a simple interaction between the student and yet another application interface, actually generates a considerable amount of metadata which holds the clues of how the student's cognitive processes deal with the task in question. This metadata, when treated properly, reveals useful knowledge to improve education, as a recent experience with the ToolboX Academy environment has shown. While atypical slopes in learning curves might point toward ADHD or intellectual giftedness, recurrent typing errors might reveal dyslexia, or discalculia might be detected by numeric errors over the average. What is more, tasks in this environment are specially designed for detecting other disorders, like daltonism. These are but examples of what coding environments can reveal with basic big data analysis, but the fine-grain interaction does actually store even more data, and group-level processing can also disclose deficiencies in the teaching process, in general or particular subjects, mainly in the STEM area. In this paper, we describe the approach followed by ToolboX Academy to disclose this information.

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Educational Recommendation System Utilizing Learning Styles: A Systematic Literature Review

et al. 2023

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Learning styles, learners' preferred ways to learn, can be applied to design personalized learning courses for the individual learner. One of those applications is the recommender system. This study ran a systematic literature review on the recommender system utilizing learning styles from two dependable academic libraries, IEEE Xplore and ScienceDirect, which included six reviewed topics; research objective, research methodology, educational recommendation, learning styles theory, learning style identification, and recommendation algorithm. Finally, the obtained information was examined and summarized in order to develop a unique strategy for leveraging the utilization of learning style theory for a recommender system to improve learning efficiency.INDEX TERMS Educational recommender system, learning styles, systematic literature review.

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Framework for Intervention and Assistance in University Students with Dyslexia

Cited by 6 publications

References 4 publications

The Influence of the Traditional Teaching Approach Transfer to Flipped Classroom Approach on Dyslexia

The Influence of the Traditional Teaching Approach Transfer to Flipped Classroom Approach on Dyslexia

Managing E-Learning Metadata Within TOOLBOX.ACADEMY: Knowledge Acquisition With Big Data Algorithms at the Student and Group Levels

Educational Recommendation System Utilizing Learning Styles: A Systematic Literature Review

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