Website-Based STEM Learning Using Encyclopedias for Students with Special Needs
DOI:
https://doi.org/10.32528/justindo.v11i1.5029Keywords:
Information Technology, STEM, Encyclopedia Website, Students with special needAbstract
In the world of education, we continue to create and innovate to improve the learning process and achieve desired learning outcomes. One of them is using digital-based learning (Digital Learning) which can be accessed with information technology. This research aims to determine the response to implementing a video blog-based learning system with a STEM (Science, Technology, Engineering, and Mathematics) approach. Apart from that, students will be given assignments using the Encyclopedia Website tool which contains formulas and logical flows related to Algorithms and Complexity courses. This will produce meaningful, quality learning that can be used by the wider community, especially to make it easier for students with special needs to learn to compile a simple algorithm. The method applied in implementing a website for students with special needs is a usability test with Nielsen' Attributes of Usability (NAU). Researchers carry out website evaluations with the aim of measuring and knowing the level of success of the website, how easy it is for users to understand. The research results showed that (1) the usability test with Nielsen' Attributes of Usability (NAU) can be used to measure the quality of website usability; (2) testing success rate of 100% because there were no failures in testing the search feature. Testing found a test pattern, namely that the more search keywords there are, the greater the number of document links produced, and the time required, however, it can significantly increase the highest similarity value of 0.21; (3) the respondents' conclusions show that the learnability, memorability, efficiency, errors attributes have an average helpful conclusion of 11, while the Satisfaction attribute has a very helpful average conclusion of 7.
References
Alenezi, M. (2023). Digital Learning and Digital Institution in Higher Education. Education Sciences, 13(1). https://doi.org/10.3390/educsci13010088
Camilleri, M. A., & Camilleri, A. C. (2017). Digital Learning Resources and Ubiquitous Technologies in Education. Technology, Knowledge and Learning, 22(1), 65–82. https://doi.org/10.1007/s10758-016-9287-7
Çiftçi, A., & Topçu, M. S. (2023). Improving early childhood pre-service teachers’ computational thinking skills through the unplugged computational thinking integrated STEM approach. Thinking Skills and Creativity, 49, 101337. https://doi.org/https://doi.org/10.1016/j.tsc.2023.101337
Evans, J., & Lunt, I. (2002). Inclusive education: are there limits? European Journal of Special Needs Education, 17(1), 1–14. https://doi.org/10.1080/08856250110098980
Fajrin, R., & Hasairin, A. (2024). Proceeding of The 11 th Annual International Seminar on Trends in Science and Science Education (AISTSSE). https://doi.org/10.2478/9788368412017-009
Gurunath, R., & Samanta, D. (2022). A Novel Approach for Semantic Web Application in Online Education Based on Steganography. International Journal of Web-Based Learning and Teaching Technologies, 17(4). https://doi.org/10.4018/IJWLTT.285569
Hund, A., Wagner, H. T., Beimborn, D., & Weitzel, T. (2021). Digital innovation: Review and novel perspective. In Journal of Strategic Information Systems (Vol. 30, Number 4). Elsevier B.V. https://doi.org/10.1016/j.jsis.2021.101695
Kızılcan, D. Ş., Güzel, Y., & Türkmenoğlu, B. (2024). Clustering of atoms relative to vector space in the Z-matrix coordinate system and ‘graphical fingerprint’ analysis of 3D pharmacophore structure. Molecular Diversity, 28(6), 4087–4104. https://doi.org/10.1007/s11030-023-10798-1
Nylén, D., & Holmström, J. (2015). Digital innovation strategy: A framework for diagnosing and improving digital product and service innovation. Business Horizons, 58(1), 57–67. https://doi.org/10.1016/j.bushor.2014.09.001
Pinchuk, O. P., & Luparenko, L. A. (2023). Web-oriented encyclopedic edition as a tool for dissemination of verified knowledge in the field of education. Educational Technology Quarterly, 2023(2), 141–156. https://doi.org/10.55056/etq.582
Raffi, M., & Halim, E. (2023). Recycling Application Usability Testing Using the Nielsen Attributes of Usability (NAU). 2023 International Conference of Computer Science and Information Technology (ICOSNIKOM), 1–6. https://doi.org/10.1109/ICoSNIKOM60230.2023.10364344
Saifudin, I., & Widiyaningtyas, T. (2024). Systematic Literature Review on Recommender System: Approach, Problem, Evaluation Techniques, Datasets. IEEE Access, 12, 19827–19847. https://doi.org/10.1109/ACCESS.2024.3359274
Saifudin, I., Widiyaningtyas, T., Zaeni, I. A. E., & Aminuddin, A. (2025). SVD-GoRank: Recommender System Algorithm using SVD and Gower’s Ranking. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3533558
Sailer, M., Murböck, J., & Fischer, F. (2021). Digital learning in schools: What does it take beyond digital technology? Teaching and Teacher Education, 103. https://doi.org/10.1016/j.tate.2021.103346
Selviana, M., Syahputra, I. R., Mawaddah, A., Fachri, M. R., & Ramadhan, S. (2024). Tanggung Jawab Negara Dalam Pemenuhan Hak Atas Pendidikan Menurut Undang-Undang 1945. In Mediation : Journal of Law (Vol. 3, Number 2). https://pusdikra-publishing.com/index.php/jhkm/index
Sumarni, W., Sudarmin, S., Sumarti, S. S., & Kadarwati, S. (2022). Indigenous knowledge of Indonesian traditional medicines in science teaching and learning using a science–technology–engineering–mathematics (STEM) approach. Cultural Studies of Science Education, 17(2), 467–510. https://doi.org/10.1007/s11422-021-10067-3
Xu, D., & Miller, T. (2022). A simple neural vector space model for medical concept normalization using concept embeddings. Journal of Biomedical Informatics, 130. https://doi.org/10.1016/j.jbi.2022.104080
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Ilham Saifudin, Wiwik Suharso, Syahrul Mubaroq
This work is licensed under a Creative Commons Attribution 4.0 International License.
