Development of Logic Gate Trainer Kit Media: Validity Study
DOI:
https://doi.org/10.58740/juwara.v5i1.497Keywords:
idi model, instructional media, logic gate, trainer kitAbstract
This study aims to develop a Logic Gate Trainer Kit as an effective instructional medium and to evaluate its validity through expert assessment. The development process adopts the Instructional Development Institute (IDI) model, which consists of three stages: define, develop, and evaluate. During the define phase, instructional needs and media specifications were identified. In the develop phase, a prototype of the trainer kit was created based on the instructional objectives and technical requirements. The evaluate phase involved expert validation to assess the media’s quality and relevance. A total of four media experts and four subject matter experts participated in the validation process. The results of the media expert validation yielded an average score of 0.78 %, exceeding the minimum validity threshold of 0.667 %, indicating that the media is valid. Similarly, the validation by subject matter experts produced an average score of 0.82%, confirming the content validity of the trainer kit. These findings demonstrate that the Logic Gate Trainer Kit is a valid learning medium and suitable for use in digital electronics instruction.
References
Fuada, S. (2022). Development of Educational Kit for Practical Course in the Topic of Phase-Shift RC Oscillator. International Journal of Online & Biomedical Engineering, 18(5). https://doi.org/10.3991/10.3991/ijoe.v18i05.29131
Gao, K., Sun, B., Cao, Z., Duan, X., Yan, W., Tong, G., ... & Shao, J. (2024). Biomaterial/organic heterojunction based memristor for logic gate circuit design, data encryption, and image reconstruction. Advanced Functional Materials, 34(36), 2401132. https://doi.org/10.1002/adfm.202401132
Ilyas, Q., Waseem, M. T., Junaid, H. M., Khan, Z. A., Munir, F., Shaikh, A. J., & Shahzad, S. A. (2022). Fluorescein based fluorescent and colorimetric sensors for sensitive detection of TNP explosive in aqueous medium: Application of logic gate. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 272, 120994. https://doi.org/10.1016/j.saa.2022.120994
Kholis, N., Zuhrie, M. S., & Burhanuddin, D. H. (2025). Development of Digital Electronics and Information Literacy Training Kit to Improve the Performance of Students Electrical Engineering Education. IJORER: International Journal of Recent Educational Research, 6(2), 347-361. https://doi.org/10.46245/ijorer.v6i2.784
Kohpeisansukwattana, N., Siriwattananon, N., & Charoenwanit, E. (2024). Developing a Mobile Game Application to Enhance Learning Experience in Programmable Logic Controller (PLC) Wiring beyond the Laboratory. International Journal of Interactive Mobile Technologies, 18(4). https://doi.org/10.3991/ijim.v18i04.42629
Lee, E. (2025). Development and implementation of an arduino-based digital logic circuit practice board module. Education and Information Technologies, 1-34. https://doi.org/10.1007/s10639-025-13604-7
Li, L., Yao, J. Y., Xu, J. X., Zeng, X., Wang, X., Shi, J., ... & Li, K. (2025). Bioinspired Molecular Logic Gate for Sequential Monitoring of ROS and Tyrosine Hydroxylase Activity in Hypertension. Sensors and Actuators B: Chemical, 138361. https://doi.org/10.1016/j.snb.2025.138361
Li, Y., Xiao, T. P., Bennett, C. H., Isele, E., Melianas, A., Tao, H., ... & Talin, A. A. (2021). In situ parallel training of analog neural network using electrochemical random-access memory. Frontiers in Neuroscience, 15, 636127. https://doi.org/10.3389/fnins.2021.636127
Mustakim, W., Effendi, H., Giatman, M., & Wulandari, D. P. (2024). Development of Internet of Things Trainer Kit as a Learning Media for Digital Circuit Subjects in Higher Education. International Journal of Online & Biomedical Engineering, 20(9). https://doi.org/10.3991/ijoe.v20i09.48349
Owolabi, A. O., Oke, A. O., Obalalu, A. M., Khan, U., Prasad, B., & Bajaj, M. (2024). Development of an Energy-Efficient Digital Trainer for Logic Design Education Using ATmega328P Microcontroller. In E3S Web of Conferences (Vol. 591, p. 08001). EDP Sciences.
Petersen, F., Kuehne, H., Borgelt, C., Welzel, J., & Ermon, S. (2024). Convolutional differentiable logic gate networks. Advances in Neural Information Processing Systems, 37, 121185-121203. https://doi.org/10.1051/e3sconf/202459108001
Qi, S., Li, X., Zhao, C., Tang, Y., Chen, W., Zou, H., & Huang, S. (2025). Application of explainable machine learning to eXtreme Gradient Boosting models of all-optical logic gates. Optical Engineering, 64(4), 048103-048103. https://doi.org/10.1117/1.oe.64.4.048103
Widinata, F., & Wirawan, I. M. (2025). Development of Programmable Logic Controller (PLC) Trainer Learning Media for Industrial Automation. Edunesia: Jurnal Ilmiah Pendidikan, 6(2), 766-783. https://doi.org/10.51276/edu.v6i2.1229
Yanie, A. (2024). The Effect of the Application of Logic Gate Learning Media It-Based to Improve Motivation and Learning Outcomes Students. JMRI Journal of Multidisciplinary Research and Innovation, 2(1), 15-23. https://doi.org/10.61240/jmri.v2i1.60
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 M. Syaiful
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
JUWARA: Jurnal Wawasan dan Aksara provides open access to anyone so that the information and findings in these articles are useful for everyone. This journal's article content can be accessed and downloaded for free, following the creative commons license used.
