The Effectiveness of Varying the Design Pattern of an Interactive Chatbot Based on (Artificial Intelligence / Database) within an E-Learning Environment in Developing Digital Software and Application Usage Skills and Reducing Mind-Wandering Levels among Students with Autism Spectrum Disorders

Al-Mansi, Sami Abdel-Latif Abbas

doi:10.21608/jsrep.2025.440487

The Effectiveness of Varying the Design Pattern of an Interactive Chatbot Based on (Artificial Intelligence / Database) within an E-Learning Environment in Developing Digital Software and Application Usage Skills and Reducing Mind-Wandering Levels among Students with Autism Spectrum Disorders

Document Type : Original Article

Author

Sami Abdel-Latif Abbas Al-Mansi

Lecturer, Department of Educational Technology, Faculty of Education, Al-Azhar University – Cairo

10.21608/jsrep.2025.440487

Abstract

The current research aimed to address the shortcomings and weaknesses in the level of achievement and skill performance in digital programs and applications, and to reduce the level of mind-wandering among students with autism spectrum disorder (ASD). This was achieved by designing two types of interactive chatbot models based on (Artificial Intelligence / Database) within an e-learning environment and evaluating their effectiveness. To achieve this goal, the study employed the (Developmental Research Method), which includes the descriptive analytical method, systems development method, and quasi-experimental method. The research sample consisted of 24 first-year preparatory students with ASD during the first semester of the 2024/2025 academic year. They were divided into two experimental groups: the first group studied using an AI-based chatbot, while the second group used a database-based chatbot. The research tools included a knowledge achievement test, a performance observation checklist for digital program and application skills, and a mind-wandering scale. The experiment was conducted, results were recorded and analyzed. The study reached several key findings, most notably: the effectiveness of interactive chatbots in improving academic achievement, enhancing skill performance in digital applications, and reducing mind-wandering among students with ASD. There was a statistically significant difference at the level of (α ≤ 0.05) between the mean ranks of the two experimental groups in the post-application of the knowledge achievement test, the performance observation checklist, and the mind-wandering scale — in favor of the first group that used the AI-based chatbot. The study recommended the integration of AI applications in teaching students with ASD, leveraging the results to develop e-learning environments based on interactive chatbots for various categories of students with special needs, and conducting further research on different chatbot variables and their integration into diverse e-learning systems and environments.

Keywords

References

Bartl-Pokorny, K. D., Pykała, M., Uluer, P., Barkana, D. E., Baird, A., Kose, H., et al. (2021). Robot-based intervention for children with autism spectrum disorder: a systematic literature review. IEEE Access 9, 165433–165450. doi: 10.1109/ACCESS.2021.3132785
Barua, P. D., Vicnesh, J., Gururajan, R., Oh, S. L., Palmer, E., Azizan, M. M., et al. (2022). Artificial intelligence enabled personalised assistive tools to enhance education of children with neurodevelopmental disorders—a review. 19, 1192
Boroson, B. (2020). Decoding Autism and Leading the Way to Successful Inclusion. ASCD. USA.
Cha, I., Kim, S. I., Hong, H., Yoo, H., & Lim, Y. K. (2021). Exploring the use of a voicebased conversational agent to empower adolescents with autism spectrum disorder. In Proceedings of the 2021 CHI conference on human factors in computing systems. 1-15.
Charron, N., Lewis, L., & Craig, M. (2017). A robotic therapy case study: Developing joint attention skills with a student on the autism spectrum. Journal of Educational Technology Systems, 46(1), 137-148.
Chen, M., Xiao, W., Hu, L., Ma, Y., Zhang, Y., & Tao, G. (2021). Cognitive wearable robotics for autism perception Technology (TOIT), 21(4), 1-16.
Chen, T., Chen, Y., Yuan, M., Gerstein, M., Li, T., Liang, H., et al. (2020). The development of a practical artificial intelligence tool for diagnosing and evaluating autism spectrum disorder: multicenter study. JMIR Med. Informat/ 8, e15767. doi: 10.2196/15767
Chung, E. Y. H. (2021). Robot-mediated social skill intervention programme for children with autism spectrum disorder: an aba time-series study. Int. J. Soc. Robot. 13, 1095–1107.
Fachantidis, N., Syriopoulou-Delli, C. K., Vezyrtzis, I., & Zygopoulou, M. (2020). Beneficial effects of robot-mediated class activities on a child with ASD and his typical classmates. International Journal of Developmental Disabilities, 66(3), 245-253.
Fox KC, Spreng RN, Ellamil M, Andrews-Hanna JR, Christoff K. The wandering brain: 2015 meta-analysis of functional neuroimaging studies of mindwandering and related spontaneous thought processes. Neuroimage.
Frolli, A., Cavallaro, A., La Penna, I., Sica, S. L., & Bloisi, D. (2023). Artificial intelligence and autism spectrum disorders: a new perspective on learning.
Hadri, S. A., & Bouramoul, A. (2023). Towards a deep learning based contextual chat bot for preventing depression in young children with autistic spectrum disorder. Smart Health, 27, 100371.‏
Helfer B. Boxhoorn S. Songa J. Steel C. Maltezos.. & Asherson P.(2020). Emotion recognition and mind wandering in adults with attention deficit hyperactivity disorder or autism spectrum disorder. J Psychiatr Res. 2021;134: 89- 96.
Huijnen, C. A., Lexis, M. A., & de Witte, L. P. (b2016). Matching robot KASPAR to autism spectrum disorder (ASD) therapy and educational goals. International Journal of Social Robotics, 8(4), 445-455.
Lampos, V., Mintz, J., & Qu, X. (2021). An artificial intelligence approach for selecting effective teacher communication strategies in autism education. npj Science of Learning, 6(1), 25.
McVay, J. & Kane, M. (2010). Does Mind Wandering Reflect Executive Function or Executive Failure? Comment on Smallwood and Schooler
MOLHEM: An innovative android application with an interactive avatar-based chatbot for Arab children with ASD. Education and Information Technologies, 1-35.
Montserrat, M. et al. (2022). Chatbot, as Educational and Inclusive Tool for People with Intellectual Disabilities. Journal of Sustainabitiy, 14, 2-14.
Musa R., et al. (2021). Smart Autistika: Mobile Game Application with chatbot for the learning of Autistic children. Journal of Research& Design in Challenging Environment, 4(2), 978- 967.
Reichle, E. D., Reineberg, A. E., & Schooler, J. W. (2010). Eye movements during mindless reading. Psychological Science, 21, 1300 –1310.
Risko, E. F., Anderson, N., Sarwal, A., Engelhardt, M., & Kingstone, A. (2012). Everyday attention: Variation in mind wandering and memory in a lecture. Applied Cognitive Psychology, 26(2), 234– 242
Simhadri Apparao Polireddi, N., & Kavitha, J. (2023). Effectiveness of automated chatbots for operational support and self-service based on fuzzy classifier for ASD. Soft Computing, 1-8.‏
Singh, A., Raj, K., Kumar, T., Verma, S., & Roy, A. M. (2023). Deep learning-based cost-effective and responsive robot for autism treatment. Drones, 7(2), 81.
Smallwood, J., & Schooler, J. (2006). The restless mind. Psychological bulletin, 132(6), 946-958.
So, W. C., Cheng, C. H., Lam, W. Y., Huang, Y., Ng, K. C., Tung, H. C., & Wong, W. (2020). A Robot-Based Play-Drama Intervention May Improve the Joint Attention and Functional Play Behaviors of Chinese-Speaking Preschoolers with Autism Spectrum Disorder: A Pilot Study. Journal of Autism and Developmental Disorders, 50(2), 467-481
Soemer, A., & Schiefele, U. (2019). Text difficulty, topic interest, and mind wandering during reading. Learning and Instruction, 61, 12-22.
Sullivan, Y. (2016). Costs and Benefits of Mind Wandering in a Technological Setting: Findings and Implications. PhD Dissertation, University of North Texas
Sweidan, S. Z., Almawajdeh, S. K., Khawaldeh, A. M., & Darabkh. K. A. (2024).
MOLHEM: An innovative android application with an interactive avatar-based chatbot for Arab children with ASD. Education and Information Technologies, 1-35.
Sweidan, S. Z., Almawajdeh, S. K., Khawaldeh, A. M., & Darabkh. K. A. (2024).
Tang, Y., Chen, L., Chen, Z., Chen, W., Cai, Y., Du, Y., ... & Sun, L. (2024). EmoEden: Applying Generative Artificial Intelligence to Emotional Learning for Children with HighFunction Autism. In Proceedings of the CHI Conference on Human Factors in Computing Systems. 1-20
VamsidharEnireddy, C Karthikeyan, and Ramkumar Jb. )2022(. Automated Chatbots for Autism Spectrum Disorder Using AI Assistance. Artificial Intelligence and the Fourth Industrial Revolution, 153
Wammes, J. D., Seli, P., Cheyne, J. A., Boucher, P. O., & Smilek, D. (2016). Mind wandering during lectures II: Relation to academic performance. Scholarship of Teaching and Learning in Psychology, 2(1), 33–48.
Watkins (2008). Psychological bulletin, 136(2), 188-197.
Xue G, Mei L, Chen C, Lu ZL, Poldrack R, Dong Q (2011).enhances subsequent recognition memory by reducing neural repetition suppression. J Cogn Neurosci 23:1624–1633.
Zhao, Yue & Lofi, Christoph & Hauff, Claudia. (2017). Scalable MindWandering Detection for MOOCs: A Webcam-Based Approach. 330-344.
Malik, G., Tayal, D. K., & Vij, S. (2019). An analysis of the role of artificial intelligence in education and teaching. In Recent Findings in Intelligent Computing Techniques 407-417.
Nghi T, Phuc, T., & Thang, N. (2019). Al Applying Chatbot for Teaching a Foreign Language: An Empirical Research. International Journal of Scientific& Technology Research8, (12), 897-902
Bii, K, Too, K., & Mukwa, W. (2018). Teacher Attitude Towards Use of Chatbots in Routine Teaching. Universal Journal of Educational Research,6 (7),1586-1597.
Deveci Topal, A., Dilek Eren, C., & Kolburan Geçer, A. (2021). Chatbot application in a 5th grade science course. Education and Information Technologies, 26(5), 6241-6265.‏
Deveci, A, Eren, C., & Geçer, A. (2021). Chatbot Application in A th5 Grade Science Course. Education and Information Technologies,6 (2),1-21.
Fyer , L., Ainley, M., Thompson, A., Gibson, A., & Sherlock, Z (2017). Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners. Computers in Human Behavior, 75(1), 461-468.
Nghi T, Phuc, T., & Thang, N. (2019). Al Applying Chatbot for Teaching a Foreign Language: An Empirical Research. International Journal of Scientific& Technology Research8, (12), 897-902
Vanichvasin, P. (2021). Chatbot Development as a Digital Learning Tool to Increase Students' Research Knowledge. International Education Studies, 14(2), 44-53.‏
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education-where are the educators?. International. Journal of Educational Technology in Higher Education, 16(1), 39.