DocumentCode
1486838
Title
Sending Learning Pills to Mobile Devices in Class to Enhance Student Performance and Motivation in Network Services Configuration Courses
Author
Muñoz-Organero, Mario ; Munoz-Merino, P.J. ; Kloos, Carlos Delgado
Author_Institution
Carlos III of Madrid Univ., Leganes, Spain
Volume
55
Issue
1
fYear
2012
Firstpage
83
Lastpage
87
Abstract
Teaching electrical and computer software engineers how to configure network services normally requires the detailed presentation of many configuration commands and their numerous parameters. Students tend to find it difficult to maintain acceptable levels of motivation. In many cases, this results in their not attending classes and not dedicating enough time to acquire the required competencies. This paper describes a successful experiment that was able to improve student class attendance, performance, and motivational patterns by using mobile devices in class to provide students with contextualized learning pills. A learning pill is a simple exercise that summarizes some of the key concepts explained in class and promotes reflection and self-study. Each student attending a particular lecture or laboratory session automatically receives a learning pill on his or her mobile phone just after the related concept has been presented. This paper details the scenario used in the experiment and analyzes the performance and motivational patterns of 170 students at the Higher Polytechnic School, Carlos III University of Madrid, Leganes, Spain.
Keywords
computer aided instruction; educational aids; electrical engineering education; further education; mobile handsets; student experiments; Higher Polytechnic School; computer software engineers; configuration commands; contextualized learning pills; electrical engineers; mobile devices; mobile phone; motivational patterns; network services configuration courses; student class attendance; student performance; Conferences; Electronic learning; Mobile communication; Mobile handsets; Performance evaluation; Telematics; Educational technology; higher education; learning systems; pattern recognition; prediction methods; student experiments;
fLanguage
English
Journal_Title
Education, IEEE Transactions on
Publisher
ieee
ISSN
0018-9359
Type
jour
DOI
10.1109/TE.2011.2131652
Filename
5741748
Link To Document