IoT text analytics in smart education and beyond

Autor: Hrag-Harout Jebamikyous, Dina Nawara, Abdul Hanan Khan Mohammed, Rasha Kashef
Rok vydání: 2021
Předmět:
Zdroj: Journal of Computing in Higher Education. 33:779-806
ISSN: 1867-1233
1042-1726
Popis: Data Analytics has become an essential part of the Internet of Things (IoT), mainly text analytics-related applications, since they can be utilized to benefit educational institutions, consumers, and enterprises. Text Analytics is excessively used in Smart Education after the emerging technologies such as personal computers, tablets, and even smartphones transformed the education system and improved the teaching methods by helping the teachers to evaluate the students' performance or determine the degree of similarity between a lecturer’s and the students’ posts in the discussion forum, and by collecting the students’ feedback on the teaching method, in order to categorize each feedback into positive or negative, which will help the lecturers in optimizing their way of teaching. In this paper, we highlight the main components of IoT analytics, along with a comprehensive background of text analytics used techniques and applications. This paper provides a comprehensive survey and comparison of the leveraged IoT Text Analytics models and methods in Smart Education and many other applications.
Databáze: OpenAIRE
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