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 :
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