Application of Programming Algorithms to Support Computational Thinking in Children with Autism Spectrum Disorder

Zsalzsa Puspa Alivia; Jaja Kustija; Lala Septem Riza; Anne Hafina; Munir Munir; Wahyudin Wahyudin

doi:10.35445/alishlah.v17i4.8489

Application of Programming Algorithms to Support Computational Thinking in Children with Autism Spectrum Disorder

Zsalzsa Puspa Alivia, Jaja Kustija, Lala Septem Riza, Anne Hafina, Munir Munir, Wahyudin Wahyudin

Abstract

Children with Autism Spectrum Disorder (ASD) often experience challenges in logical reasoning and problem-solving, which can hinder their computational thinking (CT) development. This study aimed to examine the effectiveness of programming algorithm-based learning media in enhancing CT skills among children with ASD during Phase C informatics learning. A mixed-method approach combining Design-Based Research (DBR) and Single Subject Research (SSR) was employed. The study involved three children with ASD enrolled at SD BPI Bandung. The DBR process consisted of four stages: needs analysis, media design, development, and implementation. The intervention was conducted through an SSR design with three phases—Baseline 1 (A1), Intervention (B), and Baseline 2 (A2)—to assess changes in CT performance. All participants demonstrated notable improvements in CT skills following the intervention. For example, Participant KA’s score increased from 20% to 60%, KZ’s from 30% to 60%, and SB’s from 20% to 45%. The results indicated consistent upward trends and stable retention during the post-intervention baseline phase, suggesting that the programming algorithm learning media effectively enhanced computational thinking abilities. The findings support the use of structured, technology-assisted learning to promote CT in children with ASD. However, the small sample size limits generalizability, and future studies should include larger, more diverse participants. The study underscores the importance of developing adaptive, inclusive learning media that accommodate individual cognitive and sensory needs.

Keywords

autism spectrum disorder; computational thinking; learning media; programming algorithms

References

Alsaade, F. W., & Alzahrani, M. S. (2022). [Retracted] Classification and detection of autism spectrum disorder based on deep learning algorithms. Computational Intelligence and Neuroscience, 2022(1), 8709145. https://onlinelibrary.wiley.com/doi/abs/10.1155/2022/8709145

Apandi, A. R, Munir, M., & Riza, L. S. (2024). Implementation of multimedia interactive learning through a STEM approach based on computational thinking to improve student learning outcomes. Cendekia: Media Jurnal Ilmiah Pendidikan, 14(4), 437–447. https://doi.org/10.31004/cendekia.v14i4.12345

Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K–12. ACM Inroads, 2(1), 48–54. https://doi.org/10.1145/1929887.1929905

Bouck, E. C., Sands, P., Long, H., & Yadav, A. (2021). Preparing special education preservice teachers to teach computational thinking and computer science in mathematics. Teacher Education and Special Education, 44(3), 221–238. https://doi.org/10.1177/0888406420968056

Deng, W., Pi, Z., Lei, W., Zhou, Q., & Zhang, W. (2020). Pencil Code improves learners’ computational thinking and computer learning attitude. Computer Applications in Engineering Education, 28(1), 90–104. https://doi.org/10.1002/cae.22188

Djurdjevic-Pahl, A., Pahl, C., Fronza, I., & El Ioini, N. (2017). A pathway into computational thinking in primary schools. In 2017 International Conference on Computer Supported Education (pp. 165–175). https://doi.org/10.5220/0006379001650175

Elshahawy, M., Bakhaty, M., & Sharaf, N. (2020). Developing computational thinking for children with autism using a serious game. In 2020 24th International Conference Information Visualisation (IV) (pp. 761–766). IEEE. https://doi.org/10.1109/IV51561.2020.00138

Fauziyah, N., Budayasa, I. K., & Juniati, D. (2022). Cognition processes of ASD students: Recommendations for mathematics teaching and learning process. International Journal of Instruction, 15(3), 805–830. https://doi.org/10.29333/iji.2022.15344a

Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43. https://doi.org/10.3102/0013189X12463051

Hsu, T. C., Chang, S. C., & Hung, Y. T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296–310. https://doi.org/10.1016/j.compedu.2018.07.004

Hsu, T. C., & Chen, M. S. (2022). The engagement of students when learning to use a personal audio classifier to control robot cars in a computational thinking board game. Research and Practice in Technology Enhanced Learning, 17(1), 1–15. https://doi.org/10.1186/s41039-022-00195-y

Israel, M., Chung, M. Y., Wherfel, Q. M., & Shehab, S. (2020). A descriptive analysis of academic engagement and collaboration of students with autism during elementary computer science. Computer Science Education, 30(4), 444–468. https://doi.org/10.1080/08993408.2020.1759760

Kim, M., Kim, J. K., & Lee, W. (2024). Enhancing computational thinking in students with autism spectrum disorder and intellectual disabilities: A robot programming approach. International Journal of Developmental Disabilities, 0(0), 1–16. https://doi.org/10.1080/20473869.2024.2394735

Khoirunnisa, A. N., Munir, M., & Dewi, L. (2023). Design and prototype development of augmented reality in reading learning for autism. Computers, 12(3), 65. https://doi.org/10.3390/computers12030065

Khoirunnisa, A. N., Munir, M., Shahbodin, F., & Dewi, L. (2024). Augmented reality-based personalized learning in autism spectrum disorder reading skills. Journal of Special Education Technology. Advance online publication. https://doi.org/10.1177/01626434241234567

Knight, V. F., Wright, J., & DeFreese, A. (2019). Teaching robotics coding to a student with ASD and severe problem behavior. Journal of Autism and Developmental Disorders, 49(6), 2632–2636. https://doi.org/10.1007/s10803-019-03954-5

Lodi, M., & Martini, S. (2021). Computational thinking, between Papert and Wing. Science & Education, 30(4), 883–908. https://doi.org/10.1007/s11191-021-00201-4

Munir, M., Setiawan, W., Nugroho, E. P., Kusnendar, J., & Wibawa, A. P. (2018). The effectiveness of Multimedia in Education for Special Education (MESE) to improve reading ability and memorizing for children with intellectual disability. International Journal of Emerging Technologies in Learning, 13(8), 254–263. https://doi.org/10.3991/ijet.v13i08.8291

Muñoz, R., Morales, C., Villarroel, R., Quezada, A., & De Albuquerque, V. H. C. (2019). Developing a software that supports the improvement of the theory of mind in children with autism spectrum disorder. IEEE Access, 7, 7948–7956. https://doi.org/10.1109/ACCESS.2018.2889431

Muñoz, R., Villarroel, R., Barcelos, T. S., Riquelme, F., Quezada, A., & Bustos-Valenzuela, P. (2018). Developing computational thinking skills in adolescents with autism spectrum disorder through digital game programming. IEEE Access, 6, 63880–63889. https://doi.org/10.1109/ACCESS.2018.2876425

Rodríguez del Rey, Y. A., Cawanga Cambinda, I. N., Deco, C., Bender, C., Avello-Martínez, R., & Villalba-Condori, K. O. (2021). Developing computational thinking with a module of solved problems. Computer Applications in Engineering Education, 29(3), 506–516. https://doi.org/10.1002/cae.22389

Vella, L., Ring, H. A., Aitken, M. R., Watson, P. C., Presland, A., & Clare, I. C. H. (2018). Understanding self-reported difficulties in decision-making by people with autism spectrum disorders. Autism, 22(5), 549–559. https://doi.org/10.1177/1362361316687988

Vidal-Hall, C., Flewitt, R., & Wyse, D. (2020). Early childhood practitioner beliefs about digital media: Integrating technology into a child-centred classroom environment. European Early Childhood Education Research Journal, 28(2), 167–181. https://doi.org/10.1080/1350293X.2020.1724937

Wang, H. (2022). The application of interactive artificial intelligence in the intelligent integration of infants playing teaching aids. In 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC) (pp. 30–33). IEEE. https://doi.org/10.1109/ICAAIC53929.2022.9792789

Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717–3725. https://doi.org/10.1098/rsta.2008.0118

DOI: https://doi.org/10.35445/alishlah.v17i4.8489