Assessment of Learners' Attention to E-Learning by Monitoring Facial Expressions for Computer Network Courses

Autor/in	Chen, Hong-Ren
Titel	Assessment of Learners' Attention to E-Learning by Monitoring Facial Expressions for Computer Network Courses
Quelle	In: Journal of Educational Computing Research, 47 (2012) 4, S.371-385 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0735-6331
Schlagwörter	Foreign Countries; Interactive Video; Computer Software Evaluation; Distance Education; Online Courses; Computer Uses in Education; Educational Technology; Teaching Methods; Learning Strategies; Electronic Learning; Feedback (Response); Attention Span; Instructional Design; Computer System Design; Computer Science Education; College Instruction; Program Effectiveness; Statistical Analysis; Comparative Analysis; Pretests Posttests; Nonverbal Communication; Taiwan + Suchen Sie Ihr Suchwort? Ausland; Interaktives Video; Softwareanalyse; Distance study; Distance learning; Fernunterricht; Online course; Online-Kurs; Computernutzung; Unterrichtsmedien; Teaching method; Lehrmethode; Unterrichtsmethode; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Lesson concept; Lessonplan; Unterrichtsentwurf; Computer science lessons; Informatikunterricht; Hochschullehre; Statistische Analyse; Non-verbal communication; Nonverbale Kommunikation
Abstract	Recognition of students' facial expressions can be used to understand their level of attention. In a traditional classroom setting, teachers guide the classes and continuously monitor and engage the students to evaluate their understanding and progress. Given the current popularity of e-learning environments, it has become important to assess the degree of attention during the online learning process. In this study, we used interactive video-capture facial-recognition technology to automatically detect the facial expressions of students as a means of analyzing their attention state during the e-learning process. Participants were divided into three different learning-strategy groups for a course on computer networks. An attention-detection feedback module evaluated participants' attention span during the learning sessions and initiated a response to redirect the participants' attention when they became distracted. The three groups of participants showed significant differences in their course achievement; this was attributed to the different learning strategies used for content presentation. A positive correlation was found between learning improvement and attention, indicating that video-capture facial-recognition technology can be used to provide timely learning assistance and appropriate stimulation to enhance the educational benefits of e-learning. (Contains 5 tables and 3 figures.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10