ADPS - 有阅读障碍学生学习繁体中文的预检工具

IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS IEEE Transactions on Learning Technologies Pub Date : 2024-04-02 DOI:10.1109/TLT.2024.3384290
Ka-Yan Fung;Kit-Yi Tang;Tze Leung Rick Lui;Kuen-Fung Sin;Lik-Hang Lee;Huamin Qu;Shenghui Song
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引用次数: 0

摘要

对儿童进行特殊学习障碍(如阅读障碍)预检对有效干预至关重要。有了快速可靠的预检结果,特殊教育协调员就可以为学生提供早期干预,减轻他们的学习压力。遗憾的是,由于资源有限,香港很多学生在接受读写困难评估时已过了黄金期,即六岁以下。为此,信息技术可以建立自动预检工具来解决这一问题。然而,由于中文缺乏音标相关性,为学习中文的儿童进行读写障碍预检具有挑战性。本文开发了一种自动读写困难预选系统(ADPS),为识别高危儿童提供快速测试。通过两个阶段的方法,我们首先开发了基于语言特点的游戏化工具,然后通过对比研究对结果进行评估。对 30 名有读写困难的学生和 32 名没有读写困难的学生进行的试点测试结果表明,ADPS 能有效区分两类学生。此外,交互式设计元素还能激励学生独立进行预检。
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ADPS—A Prescreening Tool for Students With Dyslexia in Learning Traditional Chinese
Prescreening children for specific learning disabilities, e.g., dyslexia, is essential for effective intervention. With a quick and reliable prescreening result, special education coordinators (SENCOs) can provide students with early intervention and relieve their learning pressure. Unfortunately, due to the limited resources, many students in Hong Kong receive dyslexia assessments beyond the golden period, i.e., under the age of six. To this end, information technology could establish automatic prescreening tools to address this issue. However, dyslexia prescreening for children learning Chinese is challenging due to the lack of sound–script correlation in Chinese. In this article, an automatic dyslexia prescreening system (ADPS) is developed to provide a quick test to identify at-risk children. Through a two-stage approach, we first develop a gamified tool based on linguistic characteristics and then evaluate the result by a comparison study. Results from a pilot test on 30 students with dyslexia and 32 students without dyslexia indicate that the ADPS can effectively distinguish between two groups of students. Furthermore, the interactive design elements can motivate students to conduct the prescreening independently.
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来源期刊
IEEE Transactions on Learning Technologies
IEEE Transactions on Learning Technologies COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
7.50
自引率
5.40%
发文量
82
审稿时长
>12 weeks
期刊介绍: The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.
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