Integrating AI-Based Natural Language Processing in Vocational Education: Usability, Learning Gains, and Student Engagement in Indonesia

Authors

DOI:

https://doi.org/10.62486/latia2025362

Keywords:

Artificial Intelligence, Natural Language Processing, 4D Development Model, Digital Assistant, Vocational Education

Abstract

Introduction: The advancement of Artificial Intelligence (AI) has brought substantial changes to education, particularly through AI-based digital assistants.
Objective: This study developed and evaluated an AI-powered digital assistant equipped with Natural Language Processing (NLP) capabilities, specifically designed for Indonesian vocational schools.
Methods: Adopting the 4D development model (Define, Design, Develop, Disseminate), the system was created using machine learning algorithms and NLP to enhance interactivity and personalization. The assistant enables natural language interaction, provides real-time feedback, and adapts learning material difficulty to students’ comprehension levels. The system was tested with 100 vocational school students, with usability assessed using the System Usability Scale (SUS) and learning gains measured through pre- and post-tests.
Results: Results showed a SUS score of 71.05, indicating good usability, and a significant improvement in post-test scores compared to pre-test scores (p < 0.001), reflecting enhanced conceptual understanding, engagement, and motivation.
Conclusions: These findings demonstrate the potential of AI-powered NLP assistants to enrich vocational education and prepare students for technology-driven industrial demands.

 

References

Ji H, Han I, Ko Y. A systematic review of conversational AI in language education: Focusing on the collaboration with human teachers. J Res Technol Educ. 2023;55(1):48–63. https://doi.org/10.1080/15391523.2022.2142873 DOI: https://doi.org/10.1080/15391523.2022.2142873

Holstein K, Aleven V. Designing for human–AI complementarity in K-12 education. AI Mag. 2022;43(2):239–48. https://doi.org/10.1002/aaai.12058 DOI: https://doi.org/10.1002/aaai.12058

Jeon J. Chatbot-assisted dynamic assessment (CA-DA) for L2 vocabulary learning and diagnosis. Comput Assist Lang Learn. 2021. https://doi.org/10.1080/09588221.2021.1987272 DOI: https://doi.org/10.1080/09588221.2021.1987272

Sajja R, Sermet Y, Cikmaz M, Cwiertny D, Demir I. Artificial intelligence-enabled intelligent assistant for personalized and adaptive learning in higher education. Information. 2024;15(10):596. https://doi.org/10.3390/info15100596 DOI: https://doi.org/10.3390/info15100596

Huang W, Hew KF, Fryer LK. Chatbots for language learning—Are they really useful? A systematic review of chatbot-supported language learning. J Comput Assist Learn. 2022;38:237–57. https://doi.org/10.1111/jcal.12610 DOI: https://doi.org/10.1111/jcal.12610

Jeon J, Lee S, Choe H. Enhancing EFL pre-service teachers’ affordance noticing and utilizing with the Synthesis of Qualitative Evidence strategies: An exploratory study of a customizable virtual environment platform. Comput Educ. 2022;190:104620. https://doi.org/10.1016/j.compedu.2022.104620 DOI: https://doi.org/10.1016/j.compedu.2022.104620

Alam A. Harnessing the power of AI to create intelligent tutoring systems for enhanced classroom experience and improved learning outcomes. In: Intelligent Communication Technologies and Virtual Mobile Networks. Singapore: Springer; 2023. p. 571–91. https://doi.org/10.1007/978-981-99-1767-9_42 DOI: https://doi.org/10.1007/978-981-99-1767-9_42

Ubah AE, Onakpojeruo EP, Ajamu J, Mangai TR, Isa AM, Ayansina NB, et al. A review of artificial intelligence in education. In: 2022 Int Conf Artificial Intelligence of Things and Crowdsensing (AIoTCs). IEEE; 2022. p. 38–45. https://doi.org/10.1109/AIoTCs58181.2022.00104 DOI: https://doi.org/10.1109/AIoTCs58181.2022.00104

Awad SO, Mohamed Y, Shaheen R. Applications of artificial intelligence in education. Al-Azkiyaa-Int J Lang Educ. 2022;1(1):71–81. https://doi.org/10.33102/alazkiyaa.v1i1.10 DOI: https://doi.org/10.33102/alazkiyaa.v1i1.10

Tan S. Harnessing Artificial Intelligence for innovation in education. In: Learning Intelligence: Innovative and Digital Transformative Learning Strategies. Singapore: Springer; 2023. p. 335–63. https://doi.org/10.1007/978-981-19-9201-8_8 DOI: https://doi.org/10.1007/978-981-19-9201-8_8

Janardhanan AK, Rajamohan K, Manu KS, Rangasamy S. Digital education for a resilient new normal using artificial intelligence—applications, challenges, and way forward. In: Digital Teaching, Learning and Assessment. Chandos Publishing; 2023. p. 21–44. https://doi.org/10.1016/b978-0-323-95500-3.00001-8 DOI: https://doi.org/10.1016/B978-0-323-95500-3.00001-8

Hamal O, El Faddouli NE, Harouni MHA, Lu J. Artificial intelligent in education. Sustainability. 2022;14(5):2862. https://doi.org/10.3390/su14052862 DOI: https://doi.org/10.3390/su14052862

Hijón-Neira R, Connolly C, Pizarro C, Pérez-Marín D. Prototype of a recommendation model with artificial intelligence for computational thinking improvement of secondary education students. Computers. 2023;12(6):113. https://doi.org/10.3390/computers12060113 DOI: https://doi.org/10.3390/computers12060113

Gligorea I, Cioca M, Oancea R, Gorski A-T, Gorski H, Tudorache P. Adaptive learning using artificial intelligence in e-learning: A literature review. Educ Sci. 2023;13(12):1216. https://doi.org/10.3390/educsci13121216 DOI: https://doi.org/10.3390/educsci13121216

Kandlhofer M, Steinbauer G, Hirschmugl-Gaisch S, Huber P. Artificial intelligence and computer science in education: From kindergarten to university. In: 2016 IEEE Frontiers in Education Conference (FIE). IEEE; 2016. p. 1–9. https://doi.org/10.1109/FIE.2016.7757570 DOI: https://doi.org/10.1109/FIE.2016.7757570

Gautam S, Akgun M, Mitra P. Exploring the challenges of AI experts to inform AI curriculum. In: Proc 54th ACM Tech Symp Comput Sci Educ V.2. 2022. p. 1338. https://doi.org/10.1145/3545947.3576284 DOI: https://doi.org/10.1145/3545947.3576284

Matias A, Zipitria I. Promoting ethical uses in artificial intelligence applied to education. In: Int Conf Intelligent Tutoring Systems. Cham: Springer; 2023. p. 604–15. https://doi.org/10.1007/978-3-031-32883-1_53 DOI: https://doi.org/10.1007/978-3-031-32883-1_53

Magistretti S, Legnani M, Pham CTA, Dell’Era C. The 4S model for AI adoption: Integrating design thinking and technology development. Res Technol Manag. 2024;67(3):54–63. https://doi.org/10.1080/08956308.2024.2325859 DOI: https://doi.org/10.1080/08956308.2024.2325859

Henne S, Mehlin V, Schmid E, Schacht S. Components of digital assistants in higher education environments. In: 2022 IEEE 28th Int Conf Eng Technol Innov (ICE/ITMC) & 31st Int Assoc Manage Technol (IAMOT) Joint Conf. IEEE; 2022. p. 1–8. https://doi.org/10.1109/ice/itmc-iamot55089.2022.10033236 DOI: https://doi.org/10.1109/ICE/ITMC-IAMOT55089.2022.10033236

Zawacki-Richter O, Bai JY, Lee K, Slagter van Tryon PJ, Prinsloo P. New advances in artificial intelligence applications in higher education? Int J Educ Technol High Educ. 2024;21(1):32. https://doi.org/10.1186/s41239-024-00464-3 DOI: https://doi.org/10.1186/s41239-024-00464-3

Viberg O, Engström L, Saqr M, Hrastinski S. Exploring students’ expectations of learning analytics: A person-centered approach. Educ Inf Technol. 2022;27(6):8561–81. https://doi.org/10.1007/s10639-022-10980-2 DOI: https://doi.org/10.1007/s10639-022-10980-2

Chan CKY, Hu W. Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. Int J Educ Technol High Educ. 2023;20(1):43. https://doi.org/10.1186/s41239-023-00411-8. DOI: https://doi.org/10.1186/s41239-023-00411-8

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Published

2025-08-28

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Original

How to Cite

1.
Farell G, Faiza D, Delianti VI, Wahyudi R, Samala AD, Taş N. Integrating AI-Based Natural Language Processing in Vocational Education: Usability, Learning Gains, and Student Engagement in Indonesia. LatIA [Internet]. 2025 Aug. 28 [cited 2025 Sep. 4];3:362. Available from: https://latia.ageditor.uy/index.php/latia/article/view/362