Wiwin Suwarningsih; Nuryani; Endang Suryawati

Integrating Question Answering Technology into E-Health Education: A Computer-Supported Learning Approach

PDF (674KB), PP.182-200

Views: 0 Downloads: 0

Author(s)

Wiwin Suwarningsih ^1,* Nuryani ¹ Endang Suryawati ²

1. Research Center for Data and Information Sciences, National Research and Innovation Agency, Bandung, Indonesia

2. Research Center for Artificial Intelligence and Cyber Security, National Research and Innovation Agency, Bandung, Indonesia

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2026.04.11

Received: 18 Nov. 2025 / Revised: 10 Jan. 2026 / Accepted: 24 Feb. 2026 / Published: 8 Aug. 2026

Index Terms

E-Health, Nutrition Education, QA System, Stunting

Abstract

This study examines the integration of Question Answering (QA) technology into e-health education using scaffold method to address stunting prevention and understanding of early childhood nutrition in Indonesia. The research developed a computer-supported learning platform that combines adaptive QA systems with structured scaffolding techniques to support maternal knowledge development and informed nutrition practices. Data was collected from Indonesian stunting education programs and nutrition improvement initiatives targeting children under five years old. The platform implemented progressive learning modules that provided real-time responses to user queries while offering contextual support through scaffolded feedback mechanisms. Knowledge improvement was evaluated using a pre-test and post-test design administered before and after system interaction, with a follow-up assessment conducted four weeks later to measure retention. Results demonstrated improvements in knowledge retention scores (mean increase of 42%) and understanding of nutrition guidelines among participating mothers. The QA system helped clarify common misconceptions about complementary feeding practices while maintaining engagement through personalized learning paths. These findings indicate that scaffolded QA technology has potential as a supportive tool for e-health education in resource-limited settings, although broader implementation and long-term impact require further investigation.

Cite This Paper

Wiwin Suwarningsih, Nuryani, Endang Suryawati, "Integrating Question Answering Technology into E-Health Education: A Computer-Supported Learning Approach", International Journal of Modern Education and Computer Science(IJMECS), Vol.18, No.4, pp. 182-200, 2026. DOI:10.5815/ijmecs.2026.04.11

Reference

[1]J. Dol, B. Richardson, T. Boates, and M. Campbell-Yeo, “Learning to parent from Google? Evaluation of available online health evidence for parents of preterm infants requiring neonatal intensive care,” Health Informatics J., vol. 25, no. 4, pp. 1265–1277, Dec. 2019, doi: 10.1177/1460458217752564.
[2]J. Parga-Belinkie, B. Courchia, and D. Y. Barbeau, “Using media to transform education and public health messaging in the neonatal intensive care unit,” Semin. Perinatol., vol. 49, no. 7, p. 152150, Nov. 2025, doi: 10.1016/J.SEMPERI.2025.152150.
[3]Ministry of Health Republic of Indonesia, “Ministry of Health Republic of Indonesia, Indonesian Nutritional Status Survey (SSGI) 2022.” Accessed: Feb. 12, 2026. [Online]. Available: https://layanandata.kemkes.go.id/katalog-data/ssgi/ketersediaan-data/ssgi-2022
[4]Y. Abimulyani, Y. Y. Kainde, and M. T. Minggele, “Factors causing stunting in pregnant women and its prevention efforts: Public Health Perspectives,” Oshada, vol. 1, no. 6, pp. 68–81, Dec. 2024, doi: 10.62872/AC0HF695.
[5]G. Prayitno et al., “Community-powered environmental pathways to reduce stunting: Food security, social capital, and open innovation in semi-urban Indonesia,” Environmental Challenges, vol. 21, p. 101350, Dec. 2025, doi: 10.1016/J.ENVC.2025.101350.
[6]J. P. McNulty et al., “Professional challenges faced by student radiographers during COVID-19,” Radiography, vol. 31, no. 4, p. 103000, Jul. 2025, doi: 10.1016/J.RADI.2025.103000.
[7]S. Beaini, Y. Gharib, B. Kandil, C. Asmar, and N. Ziade, “ABS1178-HPR BUILDING RESILIENT HEALTHCARE SYSTEMS: INTEGRATING PLANETARY HEALTH EDUCATION IN THE FACE OF CLIMATE CHALLENGES – PERSPECTIVES FROM LEBANON,” Ann. Rheum. Dis., vol. 84, p. 1623, Jun. 2025, doi: 10.1016/J.ARD.2025.06.1031.
[8]L. J. Morrison, S. Otis-Green, J. Bruno, P. N. Fordham, and E. C. Carey, “A Decade of Interactive Educational Exchange: Impacting Interprofessional Palliative Care Education,” J. Pain Symptom Manage., vol. 70, no. 6, pp. e351–e365, Dec. 2025, doi: 10.1016/J.JPAINSYMMAN.2025.08.001.
[9]L. J. Morrison et al., “Launching the Next Steps to Improve Hospice and Palliative Medicine Fellow Performance Assessment: A Look Back to the Initial Toolkit of Assessment Methods,” J. Pain Symptom Manage., vol. 61, no. 3, pp. 613–627, Mar. 2021, doi: 10.1016/j.jpainsymman.2020.10.014.
[10]J. A. Greene, N. K. Choudhry, E. Kilabuk, and W. H. Shrank, “Online social networking by patients with diabetes: A qualitative evaluation of communication with Facebook,” J. Gen. Intern. Med., vol. 26, no. 3, pp. 287–292, Mar. 2011, doi: 10.1007/S11606-010-1526-3.
[11]Y. Shang and X. (Robert) Luo, “An empirical investigation of users’ engagement in online health communities for chronic diseases,” Information & Management, vol. 62, no. 8, p. 104213, Dec. 2025, doi: 10.1016/J.IM.2025.104213.
[12]L. Huang et al., “Second Victim Experiences of Health Care Learners and the Influence of the Training Environment on Postevent Adaptation,” Mayo Clin. Proc. Innov. Qual. Outcomes, vol. 8, no. 3, pp. 232–240, Jun. 2024, doi: 10.1016/J.MAYOCPIQO.2024.03.004.
[13]V. Young, Y. Yan, P. J. Mason, L. El-Assad, and M. Mulvaney, “Preparing health care learners using an interprofessional virtual simulation: A team-based community intervention,” J. Interprof. Educ. Pract., vol. 37, p. 100729, Dec. 2024, doi: 10.1016/J.XJEP.2024.100729.
[14]A. W. Kushniruk, M. M. Triola, E. M. Borycki, B. Stein, and J. L. Kannry, “Technology induced error and usability: The relationship between usability problems and prescription errors when using a handheld application,” Int. J. Med. Inform., vol. 74, no. 7–8, pp. 519–526, Aug. 2005, doi: 10.1016/J.IJMEDINF.2005.01.003.
[15]X. Chen, H. Du, P. Zheng, and J. Mou, “Understanding information sensitivity in the digital era: A literature analysis and future research agenda,” Electron. Commer. Res. Appl., vol. 74, p. 101550, Nov. 2025, doi: 10.1016/J.ELERAP.2025.101550.
[16]A. Osonuga, A. A. Osonuga, S. C. Fidelis, G. C. Osonuga, J. Juckes, and D. B. Olawade, “Bridging the digital divide: artificial intelligence as a catalyst for health equity in primary care settings,” Int. J. Med. Inform., vol. 204, p. 106051, Dec. 2025, doi: 10.1016/J.IJMEDINF.2025.106051.
[17]A. Farea and F. Emmert-Streib, “Understanding question-answering systems: Evolution, applications, trends, and challenges,” Eng. Appl. Artif. Intell., vol. 156, p. 110997, Sep. 2025, doi: 10.1016/J.ENGAPPAI.2025.110997.
[18]X. Wang, Z. Sun, P. Wang, and B. Wei, “MedicalGLM: A Pediatric Medical Question Answering Model with a quality evaluation mechanism,” J. Biomed. Inform., vol. 165, p. 104793, May 2025, doi: 10.1016/J.JBI.2025.104793.
[19]V. Naidoo and K. K. Chadha, “Culturally responsive AI chatbots: From framework to field evidence,” Computers in Human Behavior: Artificial Humans, vol. 6, p. 100224, Dec. 2025, doi: 10.1016/J.CHBAH.2025.100224.
[20]S. Xiang, B. Liu, X. Jiang, Z. Huang, and Y. Ma, “Knowledge precedence networks: Mining progression patterns of scientific discoveries beyond prerequisites,” Inf. Process. Manag., vol. 63, no. 2, p. 104424, Mar. 2026, doi: 10.1016/J.IPM.2025.104424.
[21]C. Ng and Y. Fung, “Educational Personalized Learning Path Planning with Large Language Models,” Jul. 2024, Accessed: Nov. 12, 2025. [Online]. Available: http://arxiv.org/abs/2407.11773
[22]E. M. Kivuti, D. Kaburu, and K. O. Ogada, “An Interactive Multimedia Model for Developing QOE-Enhanced E-Learning Platforms,” International Journal of Web-Based Learning and Teaching Technologies, vol. 19, no. 1, Oct. 2024, doi: 10.4018/IJWLTT.347662.
[23]J. Linardon et al., “Does the Method of Content Delivery Matter? Randomized Controlled Comparison of an Internet-Based Intervention for Eating Disorder Symptoms With and Without Interactive Functionality,” Behav. Ther., vol. 53, no. 3, pp. 508–520, May 2022, doi: 10.1016/J.BETH.2021.12.001.
[24]L. Lim et al., “Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning,” Comput. Human Behav., vol. 139, p. 107547, Feb. 2023, doi: 10.1016/J.CHB.2022.107547.
[25]A. Gril et al., “The impact of different types of self-regulation scaffolds on learning science with hypermedia,” Comput. Human Behav., vol. 169, p. 108670, Aug. 2025, doi: 10.1016/J.CHB.2025.108670.
[26]G. Kacmaz and A. K. Dubé, “Measuring teacher scaffolding in game-based learning: Emotional and responsibility scaffolds lead while resources and previous game experience shape practices,” Comput. Educ., vol. 237, p. 105393, Nov. 2025, doi: 10.1016/J.COMPEDU.2025.105393.
[27]M. Saud and I. Wahyudi, “Shaping health behavior and social connectedness during COVID-19 through media adaptation strategies in Indonesia,” Vacunas (English Edition), vol. 26, no. 2, p. 500387, Apr. 2025, doi: 10.1016/J.VACUNE.2025.500387.
[28]P. L. Liu, “COVID-19 Information Seeking on Digital Media and Preventive Behaviors: The Mediation Role of Worry,” Cyberpsychol. Behav. Soc. Netw., vol. 23, no. 10, pp. 677–682, Oct. 2020, doi: 10.1089/CYBER.2020.0250.
[29]L. Naamati-Schneider and D. Alt, “Developing AI literacy in medical and health professions education: Exploring ChatGPT, ChatBots development, and simulation-based learning,” Nurse Educ. Pract., vol. 88, p. 104572, Oct. 2025, doi: 10.1016/J.NEPR.2025.104572.
[30]C. R. Dias, M. R. Pereira, and A. P. Freire, “Qualitative review of usability problems in health information systems for radiology,” J. Biomed. Inform., vol. 76, pp. 19–33, Dec. 2017, doi: 10.1016/J.JBI.2017.10.004.
[31]B. McBride, L. T. Nguyen, D. Wiljer, N. C. Vu, C. K. Nguyen, and J. O’Neil, “Development of a Maternal, Newborn and Child mHealth Intervention in Thai Nguyen Province, Vietnam: Protocol for the mMom Project,” JMIR Res. Protoc., vol. 7, no. 1, Jan. 2018, doi: 10.2196/RESPROT.7912.
[32]D. N. Aisyah et al., “Using WhatsApp for Nutrition Surveillance Among Children Under 5 Years in West Java, Indonesia: Cross-Sectional Survey and Feasibility Study,” JMIR Pediatr. Parent., vol. 8, Jan. 2025, doi: 10.2196/58752.
[33]G. Gilano, A. Dekker, and R. Fijten, “Effect of mobile phone messaging on uptake of maternal and child health service in southern Ethiopia: Protocol for cluster randomized controlled trial,” Clinical Nutrition Open Science, vol. 54, pp. 89–99, Apr. 2024, doi: 10.1016/J.NUTOS.2024.02.002.
[34]S. Burrola-Méndez et al., “Development, Implementation, and Usability Evaluation of the CANMI App to Monitor the Quality of Maternal and Child Nutrition Care in Primary Health Units: Mixed Methods Pilot Study,” JMIR Form. Res., vol. 9, Jan. 2025, doi: 10.2196/77539.
[35]S. Till et al., “Digital Health Technologies for Maternal and Child Health in Africa and Other Low- and Middle-Income Countries: Cross-disciplinary Scoping Review With Stakeholder Consultation,” J. Med. Internet Res., vol. 25, Jan. 2023, doi: 10.2196/42161.
[36]A. Mimoudi, “Generative AI to bridge the educational divide: Personalized learning and challenges,” Social Sciences & Humanities Open, vol. 12, p. 102140, Jan. 2025, doi: 10.1016/J.SSAHO.2025.102140.
[37]Y. Liu et al., “Toward a Large Language Model-Driven Medical Knowledge Retrieval and QA System: Framework Design and Evaluation,” Engineering, vol. 50, pp. 270–282, Jul. 2025, doi: 10.1016/J.ENG.2025.02.010.
[38]A. Tarifa and C. Chabir, “How scenarios can impact small models for QA task in education?,” Procedia Comput. Sci., vol. 270, pp. 4003–4013, Jan. 2025, doi: 10.1016/J.PROCS.2025.09.525.
[39]M. A. Borroto and F. Ricca, “SPARQL-QA-v2 system for Knowledge Base Question Answering,” Expert Syst. Appl., vol. 229, p. 120383, Nov. 2023, doi: 10.1016/J.ESWA.2023.120383.
[40]S. Jin, X. Lian, H. Jung, J. Park, and J. Suh, “Building a deep learning-based QA system from a CQA dataset,” Decis. Support Syst., vol. 175, p. 114038, Dec. 2023, doi: 10.1016/J.DSS.2023.114038.
[41]S. Palmer et al., “Policy, Systems, and Environmental Changes in Child Nutrition Programs: A Systematic Literature Review,” Advances in Nutrition, vol. 15, no. 1, p. 100116, Jan. 2024, doi: 10.1016/J.ADVNUT.2023.09.004.
[42]S. Chen, E. Turanoglu Bekar, J. Bokrantz, and A. Skoogh, “AI-enhanced digital twins in maintenance: Systematic review, industrial challenges, and bridging research–practice gaps,” J. Manuf. Syst., vol. 82, pp. 678–699, Oct. 2025, doi: 10.1016/J.JMSY.2025.07.006.
[43]J. Dobreva et al., “RAGCare-QA: A benchmark dataset for evaluating retrieval-augmented generation pipelines in theoretical medical knowledge,” Data Brief, vol. 63, p. 112146, Dec. 2025, doi: 10.1016/J.DIB.2025.112146.
[44]A. Simpson, L. Reynolds, I. Light, and J. Attenborough, “Talking with the experts: Evaluation of an online discussion forum involving mental health service users in the education of mental health nursing students,” Nurse Educ. Today, vol. 28, no. 5, pp. 633–640, Jul. 2008, doi: 10.1016/J.NEDT.2007.09.009.
[45]B. D. Unis et al., “Nursing curricula in Indonesia and Scandinavia: What can we learn from each other to strengthen nursing education,” Nurse Educ. Today, vol. 149, p. 106657, Jun. 2025, doi: 10.1016/J.NEDT.2025.106657.
[46]R. D. Guntur, M. Lobo, D. M. Sihotang, Y. P. Bria, and D. Kusumaningrum, “Health Education Campaign to Improve Malaria Knowledge, Prevention, and Treatment Behaviors in Rural East Nusa Tenggara Province, Indonesia: Protocol for a Cluster-Assigned Quasi-Experimental Study,” JMIR Res. Protoc., vol. 14, Jan. 2025, doi: 10.2196/66982.
[47]A. Bahattab, M. Hanna, G. T. Voicescu, I. Hubloue, F. Della Corte, and L. Ragazzoni, “e-Learning Evaluation Framework and Tools for Global Health and Public Health Education: Protocol for a Scoping Review,” JMIR Res. Protoc., vol. 12, no. 1, Jan. 2023, doi: 10.2196/49955.
[48]D. Corral and S. K. Carpenter, “Effects of retrieval practice on retention and application of complex educational concepts,” Learn. Instr., vol. 100, p. 102219, Dec. 2025, doi: 10.1016/J.LEARNINSTRUC.2025.102219.
[49]X. Zhang, Y. Lv, J. Zhang, W. Admiraal, and Y. Liu, “How Teachers’ Self-efficacy and self-directed learning beliefs shape their teaching quality: A network analysis,” Teach. Teach. Educ., vol. 170, p. 105295, Feb. 2026, doi: 10.1016/J.TATE.2025.105295.
[50]C. P. Thompson and M. A. Hughes, “The Effectiveness of Spaced Learning, Interleaving, and Retrieval Practice in Radiology Education: A Systematic Review,” Journal of the American College of Radiology, vol. 20, no. 11, pp. 1092–1101, Nov. 2023, doi: 10.1016/J.JACR.2023.08.028.
[51]A. Bangor, P. Kortum, and J. Miller, “Determining What Individual SUS Scores Mean: Adding an Adjective Rating Scale,” 2009.
[52]A. Granić and N. Marangunić, “Technology acceptance model in educational context: A systematic literature review,” 2019, Blackwell Publishing Ltd. doi: 10.1111/bjet.12864.
[53]F. Rangraz Jeddi, E. Nabovati, R. Bigham, and R. Farrahi, “Usability evaluation of a comprehensive national health information system: A heuristic evaluation,” Inform. Med. Unlocked, vol. 19, p. 100332, Jan. 2020, doi: 10.1016/J.IMU.2020.100332.
[54]B. Maqbool and S. Herold, “Potential effectiveness and efficiency issues in usability evaluation within digital health: A systematic literature review,” Journal of Systems and Software, vol. 208, p. 111881, Feb. 2024, doi: 10.1016/J.JSS.2023.111881.

International Journal of Modern Education and Computer Science (IJMECS)