Analisis Kelayakan Penggunaan Artificial Intelligence dalam Pembelajaran Menggambar Bangunan Sipil di Teknik Sipil UNSIKA
DOI:
https://doi.org/10.59188/jurnalsostech.v5i8.32378Keywords:
artificial intelligence, CIPP evaluation, technical drawing, technology education, vocational learningAbstract
The rapid development of technology in higher education encourages the integration of Artificial Intelligence (AI) into the learning process, including in the Civil Building Drawing course. Students of the Civil Engineering Study Program at UNSIKA often face difficulties in understanding technical drawings due to their educational background and the conventional methods used in teaching. This study aims to evaluate the feasibility and readiness of implementing AI technology in the drawing course using the CIPP (Context, Input, Process, Product) evaluation model. This is a descriptive-evaluative research involving 46 students who have completed the subject. Data were collected through a Likert-scale questionnaire and analyzed descriptively. The results indicate that all four evaluation components are in the “Good” category, with the highest score in the process component and the lowest in the product component. These findings suggest that while students generally accept AI-assisted learning processes, there is still uncertainty about its tangible impact on learning outcomes. It is concluded that AI holds strong potential to enhance the quality of technical drawing education, provided there are improvements in planning, student engagement, and structured learning outcome evaluation.
References
Azwar, S. (2022). Reliabilitas dan validitas. Pustaka Pelajar.
Dhafet, N. A. M., Haryono, H., & Handayani, S. S. D. (2022). Evaluasi Program Pembelajaran Model Belajar dari Rumah Pada Taman Kanak-Kanak di Masa Pandemi. Jurnal Smart Paud, 5(2). https://doi.org/10.36709/jspaud.v5i2.19
Dong, H. (2024). Study on evaluation of execution capability based on artificial intelligence CIPP model: A case study from Henan Agricultural. EAI Endorsed Transactions on Scalable Information Systems, 11(4). https://doi.org/10.4108/eetsis.5234
Fitriyanto, M. N., & Idjar, Y. (2021). Efektivitas pembelajaran gambar teknik mesin dengan AutoCAD 2020 di SMK Negeri 1 Palangka Raya. STEAM Engineering (Journal of Science, Technology, Education and Mechanical Engineering), 2(2), 73–78. https://doi.org/10.37304/jptm.v2i2.1695
Hallmark, T. F. (2025). Integrating artificial intelligence in engineering education: A work in progress systematic review of applications and challenges. Proceedings of ASEE Gulf-Southwest Section Conference. https://doi.org/10.18260/1-2--55058
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Kamil, N., Sope, Y. A., Dewi, U. K., Hadijah, & Zahrah, F. (2023). Evaluasi pembelajaran CIPP pada pembelajaran STEAM di PAUD. Anakta: Jurnal Pendidikan Islam Anak Usia Dini, 2(2), 98–104. https://doi.org/10.35905/anakta.v2i2.7152
Luo, D., Kim, M., Qian, H., & Liang, Z. (2024). Evaluation and optimization of blended teaching mode in higher vocational colleges: A comparative study of CIPP model and artificial neural network evaluation model. International Journal of Information and Education Technology, 14(12), 1734–1742. https://doi.org/10.18178/ijiet.2024.14.12.2204
Oktavia, C., & Nurkholis, A. (2022). Artificial intelligence untuk keberlangsungan bidang konstruksi. JUMATISI, 3(2), 244–249. https://doi.org/10.24127/jumatisi.v3i2.4114
Rathore, M., & Gadge, L. (2024). Study of the difficulties and challenges faced by engineering students in engineering drawing. International Journal of Research in Applied Science and Engineering Technology (IJRASET), 12. https://doi.org/10.22214/ijraset.2024.65934
Ratnaya, N., Pramudibyanto, R. C., & Widodo, A. (2022). CIPP evaluation model for vocational education: A critical review. International Journal of Education and Vocational Studies, 4(2), 116–122. https://doi.org/10.31014/aior.1993.05.03.519
Rienties, B., Simonsen, H. K., & Herodotou, C. (2020). Defining the boundaries between artificial intelligence in education, computer-supported collaborative learning, educational data mining, and learning analytics: A need for coherence. Frontiers in Education, 5, 1–5. https://doi.org/10.3389/feduc.2020.00128
Sagala, S. (2010). Konsep dan makna pembelajaran: Untuk membantu memecahkan problem belajar dan mengajar. Alfabeta.
Sankaran, S., & Saad, N. (2022). Evaluating the Bachelor of Education Program based on the context, input, process, and product model. Frontiers in Education, 7, Article 924374. https://doi.org/10.3389/feduc.2022.924374
Setyanto, R. W., Sukatiman, S., & Nurhidayati, A. N. (2022). Evaluasi program praktik industri mahasiswa pendidikan teknik bangunan menggunakan model CIPP. Indonesian Journal of Civil Engineering Education, 7(2), Article 61095. https://doi.org/10.20961/ijcee.v7i2.61095
Stufflebeam, D. L., & Zhang, G. (2017). The CIPP evaluation model: How to evaluate for improvement and accountability. Guilford Press.
Tiwari, A. S., Bhagat, K. K., & Lampropoulos, G. (2024). Designing and evaluating an augmented reality system for an engineering drawing course. Smart Learning Environments, 11(1), 1–19. https://doi.org/10.1186/s40561-023-00289-z
Yamin, M. (2010). Strategi pembelajaran berbasis kompetensi. Gaung Persada Press.
Zhang, N., Leong, W. Y., Zhang, T., & Wei, C. (2024). Artificial Intelligence in Engineering Education: A Review of Pedagogical Innovations. INTI Journal, 2024. Retrieved from https://iuojs.intimal.edu.my/index.php/intijournal/article/view/624
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