An Aid for Speechless, Visually and Hearing Impaired Students in Classroom

Kalist, V.; Joe, A. Anne Frank; Veeramuthu, A.

doi:10.1109/icces48766.2020.9137961

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…In particular, small portions of these studies focused on students with special needs. Wearable technology bridges the communication gap between special students and normal students, and also helps them to integrate into society and participate in various activities in life and learning, providing them with a more inclusive educational environment (Díaz et al, 2016; Mehmood & Lee, 2017; Kalist et al, 2020; Nuguri et al, 2021). Instructional staff, including instructors, course designers, or teaching assistants, came in the second (35%) place to assist them in gaining insights about course design and instructional practices (Edwards et al, 2017; Khakurel et al, 2019; Dong & Li, 2021; Acevedo et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Learning Analytics Based on Wearable Devices: A Systematic Literature Review From 2011 to 2021

Liu

Ren

Kong

et al. 2022

Journal of Educational Computing Research

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Wearable devices are an emerging technological tool in the field of learning analytics. With the help of wearable technologies, an increasing number of scholars have a strong interest in studying the associations between student data and learning outcomes in different learning environments. This systematic review examines 120 articles published between 2011 and 2021, exploring current research on learning analytics based on wearable devices in detail from both descriptive and content analysis. The descriptive analysis reviewed the included literature in five dimensions: publication times of the reviewed literature, wearable devices and data types used in studies, stakeholders, objectives, and methods involved in the analysis procedure. The content analysis aims to examine the literature covered in terms of three categorical domains of educational objectives: cognitive, affective, and behavioral, to investigate the practical applications and potential issues of learning analytics based on wearable devices. After that, based on the overall research content of the reviewed literature, a framework for learning analytics based on wearable devices is present, and its application process is summarized and analyzed for the reference of related researchers. At last, we summarize the limitations of existing studies and present several recommendations to further promote research and development in this field.

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