A Tale of Many IoTs
A Modular Constructivist Course Design for Internet of Things Education
Bibliographic Data
| ID | 20296377 |
|---|---|
| Authors | Agustin Zuniga (0000-0002-6481-3559, University of Helsinki), Ngoc Thi Nguyen (0000-0003-1011-8937, University of Helsinki), Mika Tompuri (0009-0008-8015-3707, University of Helsinki), Henrik Nygren (0000-0001-7991-5796, University of Helsinki), Petteri Nurmi (0000-0001-8262-6434, University of Helsinki) |
| Year | 2025 |
| Volume | 68 |
| Issue | 6 |
| Pages | 516-527 |
| Publication date | 2025-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Education (JOURNAL) |
| Journal identifiers | ISSN: 0018-9359 • E-ISSN: 1557-9638 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/te.2025.3624281 |
| OpenAlex | W4415968821 |
| Language | EN |
| References cited | 34 |
Contribution: This study demonstrates that a modular constructivist approach to Internet of Things (IoT) education significantly enhances student engagement, knowledge retention, and practical application of concepts. The distinctive aspect of this approach lies in its adaptability to various teaching modalities, including traditional classrooms and massive open online courses (MOOCs), while effectively covering the comprehensive IoT ecosystem. Background: The rapid proliferation of IoT technologies across various sectors has created a pressing demand for a skilled workforce adept in IoT principles. However, existing educational models often provide a limited perspective on IoT, underscoring the necessity for a holistic educational framework that can be applied across diverse educational programs. Intended Outcomes: The primary outcomes of this approach include improved student knowledge and understanding of IoT concepts, increased engagement in the learning process, enhanced retention rates, and the ability to apply learned concepts in practical scenarios. Application Design: The course employs a modular constructivist instructional approach, which allows for the integration of modern learning theories and constructivist principles. This design facilitates adaptability to various teaching modalities and encourages active learning through hands-on experiences in each module, covering critical aspects of the IoT ecosystem. Findings: The findings show significant improvements in student knowledge, with self-assessment data showing increases between 41.5% and 89.6% across all topic areas. Performance metrics and qualitative feedback consistently indicate that the course effectively enhances understanding of IoT concepts, demonstrating its versatility and effectiveness in different learning environments
Active learning (machine learning) · Adaptability · Constructivist teaching methods · Educational technology · Instructional design · Internet of Things · Learning theory · Modalities · Modular design · IoT and Edge/Fog Computing · Mobile Learning in Education · Teaching and Learning Programming
| Highly cited | No |
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