Block-Based Development of Mobile Learning Experiences for the Internet of Things

The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 19; no. 24; p. 5467
Main Authors: Ruiz-Rube, Iván, Mota, José Miguel, Person, Tatiana, Corral, José María Rodríguez, Dodero, Juan Manuel
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 11.12.2019
MDPI
Subjects:
Communication
Computer engineering
Computer programming
Computer science
Computers
Embedded systems
End users
Internet of Things
Programming languages
Sensors
Software engineering
Students
Teaching
map-reduce
mobile apps
Internet of Things (IoT)
end-user development
App Inventor
block-based languages
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions to the block-based programming language used in App Inventor to make the creation of mobile apps for smart learning experiences less challenging. Such apps are used to process and graphically represent data streams from sensors by applying map-reduce operations. A workshop with students without previous experience with Internet of Things (IoT) and mobile app programming was conducted to evaluate the propositions. As a result, students were able to create small IoT apps that ingest, process and visually represent data in a simpler form as using App Inventor’s standard features. Besides, an experimental study was carried out in a mobile app development course with academics of diverse disciplines. Results showed it was faster and easier for novice programmers to develop the proposed app using new stream processing blocks.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s19245467