4.7 Article

A comprehensive study of parameters in physical environment that impact students' focus during lecture using Internet of Things

期刊

COMPUTERS IN HUMAN BEHAVIOR
卷 53, 期 -, 页码 427-434

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2015.07.023

关键词

Smart classroom; Internet of Things; Classification; Machine learning; Pattern recognition; Student's focus

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We describe and analyze the impact of several parameters of the physical environment in a classroom on students' focus, where the term focus refers to the students' subjective feeling of their ability to concentrate on a lecture at a given moment. The primary goal is to identify those parameters that significantly affect students' focus during the lectures. We had measured several parameters in a real classroom environment using different low-cost smart devices. The research is based on the dataset collected from 14 recorded lectures attended by 197 students. We had measured five parameters of the physical environment and extracted 22 features from the lecturer's voice. After analyzing collected measurements, we had identified eight parameters that have shown to have statistically different values for focused and not focused segments. We used obtained dataset to test different classifiers and their ability to correctly classify focused against not focused segments of the lectures. We found out that AdaBoost M1 classifier had the best overall recognition accuracy (86.78%). After performing additional series of trials we identified three parameters that could be removed from the original dataset without changing classifier's accuracy, which left us five uncorrelated parameters that have shown to have significant impact on students' focus. (C) 2015 Elsevier Ltd. All rights reserved.

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