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Block-Based Development of Mobile Learning Experiences for the Internet of Things
Iván Ruiz-Rube1, José Miguel Mota1, Tatiana Person1
1School of Engineering, University of Cádiz, Avenida de la Universidad de Cádiz, 10, 11519 Puerto Real, Cádiz, Spain.
Sensors (Basel, Switzerland)
|December 15, 2019
Summary
This study introduces easier block-based programming for the Internet of Things (IoT) and mobile app development. Novice users can now create smart learning experiences with data processing and visualization more simply.
Area of Science:
- Computer Science
- Human-Computer Interaction
- Educational Technology
Background:
- The Internet of Things (IoT) facilitates smart user experiences but requires advanced programming skills, posing a barrier for non-technical individuals.
- Developing interactive IoT applications for learning environments necessitates accessible tools for a wider audience.
Purpose of the Study:
- To simplify the creation of mobile applications for smart learning experiences by extending a block-based programming language.
- To enable non-technical users to develop IoT applications that process and visualize sensor data streams.
Main Methods:
- Extensions were developed for the App Inventor block-based programming language to support IoT app creation.
- A workshop was conducted with students lacking prior IoT and mobile app programming experience.
- An experimental study involved academics from various disciplines in a mobile app development course.
Main Results:
- Students successfully created simplified IoT apps for data ingestion, processing, and visual representation.
- The proposed stream processing blocks in App Inventor facilitated faster and easier development for novice programmers.
- The extensions made the creation of smart learning experiences more accessible compared to standard App Inventor features.
Conclusions:
- The enhanced App Inventor blocks significantly lower the barrier to entry for developing IoT-based smart learning applications.
- The study validates the effectiveness of simplified programming tools for empowering diverse users in IoT development.
- Future work can explore further enhancements for complex data stream processing and interactive learning environments.
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