Skip to main content

SERVE as Instructional Design for Low-Connectivity Online Self-directed Modules

  • Conference paper
  • First Online:
Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022) (NiDS 2022)

Abstract

COVID-9 pandemic caused suspensions of face-to-face classes and moved the teaching of science from physical to online. However, some high school students experienced unconducive home learning environment, economic issues, and internet connectivity limitations, thus making real time synchronous classes unfavorable and frustrating. This study aimed to address this issue by using the SERVE model to create and implement a self-directed earth science module anchored upon 4 stages – present, supplement, inquire, engage. It was found that the module promoted self-directed learning, learning in low connectivity situations, and science inquiry and reflective skills. Public schools undergoing remote learning modality may benefit from the SERVE model, however, the model should also be tested in a more massive scale.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Budrikis, Z.: Physics in a time of COVID-19. Nat. Rev. Phys. 2, 177 (2020). https://doi.org/10.1038/s42254-020-0166-8

    Article  Google Scholar 

  2. UNESCO: 1.37 Billion Students Now Home as COVID-19 School Closures Expand, Ministers Scale up Multimedia Approaches to Ensure Learning Continuity. https://en.unesco.org/news/137-billion-students-now-home-covid-19-school-closures-expand-ministers-scale-multimedia

  3. Cynthia, B.: OVPAA Memorandum No. 2020-68 (2020). https://up.edu.ph/wp-content/uploads/2020/07/20200702-OVPAA-Final-cbb-June-22-Memorandum-2020-68-2.pdf

  4. Iglesias-Pradas, S., Hernández-García, Á., Chaparro-Peláez, J., Prieto, J.L.: Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: a case study. Comput. Hum. Behav. 119, 106713 (2021). https://doi.org/10.1016/j.chb.2021.106713

    Article  Google Scholar 

  5. Pham, H., Tran, Q.-N., La, G.-L., Doan, H.-M., Vu, T.-D.: Readiness for digital transformation of higher education in the Covid-19 context: the dataset of Vietnam’s students. Data Brief. 39, 107482 (2021). https://doi.org/10.1016/j.dib.2021.107482

    Article  Google Scholar 

  6. Munastiwi, E., Puryono, S.: Unprepared management decreases education performance in kindergartens during Covid-19 pandemic. Heliyon. 7, e07138 (2021). https://doi.org/10.1016/j.heliyon.2021.e07138

    Article  Google Scholar 

  7. Barrot, J.S., Llenares, I.I., del Rosario, L.S.: Students’ online learning challenges during the pandemic and how they cope with them: the case of the Philippines. Educ. Inf. Technol. 26(6), 7321–7338 (2021). https://doi.org/10.1007/s10639-021-10589-x

    Article  Google Scholar 

  8. Kornpitack, P., Sawmong, S.: Empirical analysis of factors influencing student satisfaction with online learning systems during the COVID-19 pandemic in Thailand. Heliyon. 8, e09183 (2022). https://doi.org/10.1016/j.heliyon.2022.e09183

    Article  Google Scholar 

  9. Agyeiwaah, E., Badu Baiden, F., Gamor, E., Hsu, F.-C.: Determining the attributes that influence students’ online learning satisfaction during COVID-19 pandemic. J. Hosp. Leis. Sport Tour. Educ. 100364 (2021). https://doi.org/10.1016/j.jhlste.2021.100364

  10. Mamun, M.A.A., Lawrie, G., Wright, T.: Instructional design of scaffolded online learning modules for self-directed and inquiry-based learning environments. Comput. Educ. 144, 103695 (2020). https://doi.org/10.1016/j.compedu.2019.103695

    Article  Google Scholar 

  11. Al Mamun, M.A., Lawrie, G., Wright, T.: Exploration of learner-content interactions and learning approaches: the role of guided inquiry in the self-directed online environments. Comput. Educ. 178, 104398 (2022). https://doi.org/10.1016/j.compedu.2021.104398

    Article  Google Scholar 

  12. Gumalal, J., Vilbar, A., Bernardez, F.: Exploring a flexible blended learning model in technology deficient classroom. In: Theory and Practice of Computation, pp. 77–85. CRC Press (2020)

    Google Scholar 

  13. Fisher, T., Denning, T., Higgins, C., Loveless, A.: Teachers’ knowing how to use technology: exploring a conceptual framework for purposeful learning activity. Curric. J. 23, 307–325 (2012). https://doi.org/10.1080/09585176.2012.703492

    Article  Google Scholar 

  14. Wang, Y., Cao, Y., Gong, S., Wang, Z., Li, N., Ai, L.: Interaction and learning engagement in online learning: the mediating roles of online learning self-efficacy and academic emotions. Learn. Individ. Differ. 94, 102128 (2022). https://doi.org/10.1016/j.lindif.2022.102128

    Article  Google Scholar 

  15. Kanetaki, Z., et al.: Grade prediction modeling in hybrid learning environments for sustainable engineering education. Sustainability. 14, 5205 (2022). https://doi.org/10.3390/su14095205

    Article  Google Scholar 

  16. Yaniawati, P., Kariadinata, R., Sari, N.M., Pramiarsih, E.E., Mariani, M.: Integration of e-learning for mathematics on resource- based learning: increasing mathematical creative thinking and self-confidence. Int. J. Emerg. Technol. Learn. IJET. 15, 60 (2020). https://doi.org/10.3991/ijet.v15i06.11915

    Article  Google Scholar 

  17. Zhu, M.: Enhancing MOOC learners’ skills for self-directed learning. Distance Educ. 42, 441–460 (2021). https://doi.org/10.1080/01587919.2021.1956302

    Article  Google Scholar 

  18. Brame, C.J.: Effective educational videos: principles and guidelines for maximizing student learning from video content. CBE—Life Sci. Educ. 15, es6 (2016). https://doi.org/10.1187/cbe.16-03-0125

  19. Yang, A.C.M., Chen, I.Y.L., Flanagan, B., Ogata, H.: How students’ self-assessment behavior affects their online learning performance. Comput. Educ. Artif. Intell. 3, 100058 (2022). https://doi.org/10.1016/j.caeai.2022.100058

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jeraline Gumalal .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gumalal, J., Vilbar, A. (2023). SERVE as Instructional Design for Low-Connectivity Online Self-directed Modules. In: Krouska, A., Troussas, C., Caro, J. (eds) Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022). NiDS 2022. Lecture Notes in Networks and Systems, vol 556. Springer, Cham. https://doi.org/10.1007/978-3-031-17601-2_5

Download citation

Publish with us

Policies and ethics