Research Article
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Year 2020, Volume: 8 Issue: 2, 905 - 917, 15.06.2020
https://doi.org/10.17478/jegys.698869

Abstract

References

  • Abowd, G. D. (1999). Classroom 2000: An experiment with the instrumentation of a living educational environment. IBM Systems Journal, 38(4), 508–530. https://doi.org/10.1147/sj.384.0508
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  • Aftab, H., Gilani, K., Lee, J., Nkenyereye, L., Jeong, S., & Song, J. (2019). Analysis of identifiers on IoT platforms. Digital Communications and Networks. https://doi.org/10.1016/j.dcan.2019.05.003
  • Akyol, Z., & Garrison, R. D. (2008). The Development of a Community of Inquiry Over Time in an Online Course: Understanding the Progression and Integration of Social, Cognitive and Teaching Presence. Journal of Asynchronous Learning Networks, 12(3–4), 3–22.
  • Al-Hitmi, M., & Sherif, K. (2018). Employee perceptions of fairness toward IoT monitoring. VINE Journal of Information and Knowledge Management Systems, 48(4), 504–516. https://doi.org/10.1108/vjikms-01-2018-0007
  • Al-Sharhan, S. (2016). Smart classrooms in the context of technology-enhanced learning (TEL) environment. In M. Ally & K. Alshahrani (Eds.), Transforming Education in the Gulf Region: Emerging Learning Technologies and Innovative Pedagogy for the 21st Century (Routledge Research in Education) (1st ed., pp. 188–214). London, United Kingdom: Routledge.
  • Altamimi, A. B., & Ramadan, R. A. (2016). Towards internet of things modeling: a gateway approach. Complex Adaptive Systems Modeling, 4(1). https://doi.org/10.1186/s40294-016-0038-3
  • Anastasiades, P. S. (2012). Design of a Blended Learning Environment for the Training of Greek Teachers: Results of the Survey on Educational Needs. In P. S. Anastasiades (Ed.), Blended Learning Environments for Adults: Evaluations and Frameworks (1st ed., pp. 230–256). Hershey, Pennsylvania: IGI Global.
  • Atzori, L., Iera, A., & Morabito, G. (2017). Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm. Ad Hoc Networks, 56, 122–140. https://doi.org/10.1016/j.adhoc.2016.12.004
  • Bonk, C. J., & Graham, C. R. (2007). The Handbook of Blended Learning: Global Perspectives, Local Designs (1st ed.). San Francisco: Pfeiffer.
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  • Brusilovsky, P., & Peylo, C. (2003). Adaptive and Intelligent Web-based Educational Systems. International Journal of Artificial Intelligence in Education, 13(2–4), 156–172.
  • Casola, V., De Benedictis, A., Rak, M., & Villano, U. (2019). Toward the automation of threat modeling and risk assessment in IoT systems. Internet of Things, 7, 100056. https://doi.org/10.1016/j.iot.2019.100056
  • Celesti, A., Lay-Ekuakille, A., Wan, J., Fazio, M., Celesti, F., Romano, A., Villari, M. (2019). Information management in IoT cloud-based tele-rehabilitation as a service for smart cities: Comparison of NoSQL approaches. Measurement, 151, 107218. https://doi.org/10.1016/j.measurement.2019.107218
  • Chen, W., & Looi , C.-K. (2007). Incorporating online discussion in face to face classroom learning: A new blended learning approach. Retrieved December 30, 2019, from https://www.learntechlib.org/p/44503/.
  • Chiu, C.-K., Tseng, J. C. R., & Hsu, T.-Y. (2016). Blended context-aware ubiquitous learning in museums: environment, navigation support and system development. Personal and Ubiquitous Computing, 21(2), 355–369. https://doi.org/10.1007/s00779-016-0986-9
  • Cockrum, T. (2017). Emerging Models of Practice in Flipped English Language Arts Classrooms. Applying the Flipped Classroom Model to English Language Arts Education, 160–176. https://doi.org/10.4018/978-1-5225-2242-3.ch009
  • Dong, X., Chang, Y., Wang, Y., & Yan, J. (2017). Understanding usage of Internet of Things (IOT) systems in China. Information Technology & People, 30(1), 117–138. https://doi.org/10.1108/itp-11-2015-0272
  • Dorri, A., Kanhere, S. S., & Jurdak, R. (2016). Blockchain in internet of things: Challenges and Solutions. Computing Research Repository, abs/1608.05187. Retrieved from https://arxiv.org/abs/1608.05187
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  • Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2018). Blended learning: the new normal and emerging technologies. International Journal of Educational Technology in Higher Education, 15(1). https://doi.org/10.1186/s41239-017-0087-5
  • Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018). A Review on the Use of Blockchain for the Internet of Things. IEEE Access, 6, 32979–33001. https://doi.org/10.1109/access.2018.2842685
  • Garrison, D.R., & Vaughan, N. D. (2011). Blended Learning in Higher Education: Framework, Principles, and Guidelines. Hoboken, NJ: Wiley.
  • Garrison, D.R., Anderson, T., & Archer, W. (1999). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/s1096-7516(00)00016-6
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  • Hara, H., & Kuwabara, H. (2015). Innovation in On-site Work Using Smart Devices and Augmented Reality Technology. Fujitzu Science Technology Journal, 51(2), 12–19.
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A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?

Year 2020, Volume: 8 Issue: 2, 905 - 917, 15.06.2020
https://doi.org/10.17478/jegys.698869

Abstract

This qualitative research has the purpose to analyze and synthesize a model of Blended Learning (BL) with IoT-based technology. Data sources are related literature, textbooks, research, articles, and websites. The author used analysis and synthesis tables with the content analysis method. IoT-based technology was considered to refer to all heterogeneous objects and devices through any networks, and BL is the educational approach to combine F2F instruction with ICT instruction. Many devices and “things” in IoT-based technology were added in class to create and improve a smart learning environment for the learning goals. This study divided BL into 4 characteristics; F2F, Self-paced, Tele-D, and Ubiquitous, which were further categorized into 3 typical cases of learning environments, Digital, Embedded, and Side-by-side cases. A framework of this model has 2 roles of user interfaces (teacher and student) which link 6 modules and a set of databases and 2 types of contexts (classroom and personal).

References

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  • Aftab, H., Gilani, K., Lee, J., Nkenyereye, L., Jeong, S., & Song, J. (2019). Analysis of identifiers on IoT platforms. Digital Communications and Networks. https://doi.org/10.1016/j.dcan.2019.05.003
  • Akyol, Z., & Garrison, R. D. (2008). The Development of a Community of Inquiry Over Time in an Online Course: Understanding the Progression and Integration of Social, Cognitive and Teaching Presence. Journal of Asynchronous Learning Networks, 12(3–4), 3–22.
  • Al-Hitmi, M., & Sherif, K. (2018). Employee perceptions of fairness toward IoT monitoring. VINE Journal of Information and Knowledge Management Systems, 48(4), 504–516. https://doi.org/10.1108/vjikms-01-2018-0007
  • Al-Sharhan, S. (2016). Smart classrooms in the context of technology-enhanced learning (TEL) environment. In M. Ally & K. Alshahrani (Eds.), Transforming Education in the Gulf Region: Emerging Learning Technologies and Innovative Pedagogy for the 21st Century (Routledge Research in Education) (1st ed., pp. 188–214). London, United Kingdom: Routledge.
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  • Anastasiades, P. S. (2012). Design of a Blended Learning Environment for the Training of Greek Teachers: Results of the Survey on Educational Needs. In P. S. Anastasiades (Ed.), Blended Learning Environments for Adults: Evaluations and Frameworks (1st ed., pp. 230–256). Hershey, Pennsylvania: IGI Global.
  • Atzori, L., Iera, A., & Morabito, G. (2017). Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm. Ad Hoc Networks, 56, 122–140. https://doi.org/10.1016/j.adhoc.2016.12.004
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  • Casola, V., De Benedictis, A., Rak, M., & Villano, U. (2019). Toward the automation of threat modeling and risk assessment in IoT systems. Internet of Things, 7, 100056. https://doi.org/10.1016/j.iot.2019.100056
  • Celesti, A., Lay-Ekuakille, A., Wan, J., Fazio, M., Celesti, F., Romano, A., Villari, M. (2019). Information management in IoT cloud-based tele-rehabilitation as a service for smart cities: Comparison of NoSQL approaches. Measurement, 151, 107218. https://doi.org/10.1016/j.measurement.2019.107218
  • Chen, W., & Looi , C.-K. (2007). Incorporating online discussion in face to face classroom learning: A new blended learning approach. Retrieved December 30, 2019, from https://www.learntechlib.org/p/44503/.
  • Chiu, C.-K., Tseng, J. C. R., & Hsu, T.-Y. (2016). Blended context-aware ubiquitous learning in museums: environment, navigation support and system development. Personal and Ubiquitous Computing, 21(2), 355–369. https://doi.org/10.1007/s00779-016-0986-9
  • Cockrum, T. (2017). Emerging Models of Practice in Flipped English Language Arts Classrooms. Applying the Flipped Classroom Model to English Language Arts Education, 160–176. https://doi.org/10.4018/978-1-5225-2242-3.ch009
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  • Dorri, A., Kanhere, S. S., & Jurdak, R. (2016). Blockchain in internet of things: Challenges and Solutions. Computing Research Repository, abs/1608.05187. Retrieved from https://arxiv.org/abs/1608.05187
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  • Driscoll, M. (2010). Web-Based Training: Creating e-Learning Experiences. Hoboken, NJ: Wiley.
  • Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2018). Blended learning: the new normal and emerging technologies. International Journal of Educational Technology in Higher Education, 15(1). https://doi.org/10.1186/s41239-017-0087-5
  • Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018). A Review on the Use of Blockchain for the Internet of Things. IEEE Access, 6, 32979–33001. https://doi.org/10.1109/access.2018.2842685
  • Garrison, D.R., & Vaughan, N. D. (2011). Blended Learning in Higher Education: Framework, Principles, and Guidelines. Hoboken, NJ: Wiley.
  • Garrison, D.R., Anderson, T., & Archer, W. (1999). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/s1096-7516(00)00016-6
  • Graham, C. R. (2006). Blended Learning system: definition, current trends and future directions. In C. J. Bonk & C. R. Graham (Eds.), The Handbook of Blended Learning: Global Perspectives, Local Designs (1st ed., pp. 1–21). San Francisco, USA: Wiley, John & Sons, Incorporated.
  • Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010
  • Hara, H., & Kuwabara, H. (2015). Innovation in On-site Work Using Smart Devices and Augmented Reality Technology. Fujitzu Science Technology Journal, 51(2), 12–19.
  • Haverinen-Shaughnessy, U., Shaughnessy, R. J., Cole, E. C., Toyinbo, O., & Moschandreas, D. J. (2015). An assessment of indoor environmental quality in schools and its association with health and performance. Building and Environment, 93, 35–40. https://doi.org/10.1016/j.buildenv.2015.03.006
  • Hwang, G.-J. (2014). Definition, framework and research issues of smart learning environments - a context-aware ubiquitous learning perspective. Smart Learning Environments, 1(1). https://doi.org/10.1186/s40561-014-0004-5
  • Hwang, G.-J., Tsai, C.-C., & Yang , S. J. H. (2008). Criteria, strategies and research issues of context-aware ubiquitous learning. Education Technology Society, 11(2), 81–91.
  • International Telecommunication Union-Telecommunication standardization sector. (2012). Overview of the internet of things, Recommendation ITU-T Y.2060. Retrieved November 10, 2019, from http://handle.itu.int/11.1002/1000/11559
  • Jeon, Y., Cho, C., Seo, J., Kwon, K., Park, H., Oh, S., & Chung, I.-J. (2018). IoT-based occupancy detection system in indoor residential environments. Building and Environment, 132, 181–204. https://doi.org/10.1016/j.buildenv.2018.01.043
  • Jin, M., Bekiaris-Liberis, N., Weekly, K., Spanos, C. J., & Bayen, A. M. (2018). Occupancy Detection via Environmental Sensing. IEEE Transactions on Automation Science and Engineering, 15(2), 443–455. https://doi.org/10.1109/tase.2016.2619720
  • Johanson, B., Fox, A., & Winograd, T. (2002). The Interactive Workspaces project: experiences with ubiquitous computing rooms. IEEE Pervasive Computing, 1(2), 67–74. https://doi.org/10.1109/mprv.2002.1012339
  • Koper, R. (2014). Conditions for effective smart learning environments. Smart Learning Environments, 1(1), 1–17. https://doi.org/10.1186/s40561-014-0005-4
  • Koucheryavy, A., Makolkina, M., & Paramonov, A. (2016). Applications of Augmented Reality Traffic and Quality Requirements Study and Modeling. Communications in Computer and Information Science, 241–252. https://doi.org/10.1007/978-3-319-51917-3_22
  • Lewis, L., & Parsad, B. (2008). Distance education at degree-granting postsecondary institutions : 2006–07 (NCES 2009–044). Retrieved from https://nces.ed.gov/pubs2009/2009044.pdf
  • Li, S., Xu, L. D., & Zhao, S. (2015). The internet of things: a survey. Information Systems Frontiers, 17(2), 243–259. https://doi.org/10.1007/s10796-014-9492-7
  • Liang, X., & Chen, Y. (2018). Libraries in Internet of Things (IoT) era. Library Hi Tech. https://doi.org/10.1108/lht-11-2017-0233
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There are 69 citations in total.

Details

Primary Language English
Subjects Other Fields of Education
Journal Section Differentiated Instruction
Authors

Kobchai Siripongdee 0000-0001-7745-8309

Paitoon Pımdee 0000-0002-3724-2885

Somkiat Tuntıwongwanıch This is me 0000-0003-4829-2543

Publication Date June 15, 2020
Published in Issue Year 2020 Volume: 8 Issue: 2

Cite

APA Siripongdee, K., Pımdee, P., & Tuntıwongwanıch, S. (2020). A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?. Journal for the Education of Gifted Young Scientists, 8(2), 905-917. https://doi.org/10.17478/jegys.698869
AMA Siripongdee K, Pımdee P, Tuntıwongwanıch S. A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?. JEGYS. June 2020;8(2):905-917. doi:10.17478/jegys.698869
Chicago Siripongdee, Kobchai, Paitoon Pımdee, and Somkiat Tuntıwongwanıch. “A Blended Learning Model With IoT-Based Technology: Effectively Used When the COVID-19 Pandemic?”. Journal for the Education of Gifted Young Scientists 8, no. 2 (June 2020): 905-17. https://doi.org/10.17478/jegys.698869.
EndNote Siripongdee K, Pımdee P, Tuntıwongwanıch S (June 1, 2020) A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?. Journal for the Education of Gifted Young Scientists 8 2 905–917.
IEEE K. Siripongdee, P. Pımdee, and S. Tuntıwongwanıch, “A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?”, JEGYS, vol. 8, no. 2, pp. 905–917, 2020, doi: 10.17478/jegys.698869.
ISNAD Siripongdee, Kobchai et al. “A Blended Learning Model With IoT-Based Technology: Effectively Used When the COVID-19 Pandemic?”. Journal for the Education of Gifted Young Scientists 8/2 (June 2020), 905-917. https://doi.org/10.17478/jegys.698869.
JAMA Siripongdee K, Pımdee P, Tuntıwongwanıch S. A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?. JEGYS. 2020;8:905–917.
MLA Siripongdee, Kobchai et al. “A Blended Learning Model With IoT-Based Technology: Effectively Used When the COVID-19 Pandemic?”. Journal for the Education of Gifted Young Scientists, vol. 8, no. 2, 2020, pp. 905-17, doi:10.17478/jegys.698869.
Vancouver Siripongdee K, Pımdee P, Tuntıwongwanıch S. A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?. JEGYS. 2020;8(2):905-17.

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