Combining Takaful Domain and UI/UX Expertise: A Dual-Expert Review of a Shariah-Compliant Conversational Agent for Islamic Financial Literacy among Marginalized Communities
Keywords:
Dual-Expert Review, Shariah-Compliant Chatbot, Conversational Agent, Islamic Financial Literacy, Takaful, Formative Usability Evaluation, Chatbot Usability ScaleAbstract
Shariah-compliant chatbots are increasingly used to explain Islamic financial products such as Takaful, yet their interfaces are typically modelled on generic chat applications and evaluated only after release through end-user questionnaires. This practice is problematic for marginalized users with uneven financial, digital and language literacy, who are the least able to articulate why an interface fails, and in a faith-based domain a failure of clarity is also a failure of trust. Usability evaluation alone cannot judge whether content, tone and branding suit the Shariah context, while domain review alone cannot diagnose interaction problems. To address this gap, this study proposes and applies a dual-expert review that combines Takaful domain experts from the Malaysian Takaful Association (MTA) with academic UI/UX experts in the formative evaluation of SCAI, a bilingual mobile conversational agent. Domain experts were engaged through a focus group after a prototype demonstration, while UI/UX experts tested the prototype independently and were interviewed with an eleven-item protocol mapped to QUIS, USE and Chatbot Usability Scale (BUS) constructs. Thematic and root-cause analysis yielded four themes: visual design and branding, navigation and interface interaction, language consistency and accessibility, and conversational interaction. Each theme was traced to implemented refinements through a construct-mapped traceability matrix and triangulated against end-user ratings of the refined application (n = 33). The two expert groups surfaced complementary rather than redundant issues: domain experts judged legitimacy, whereas UI/UX experts judged operability. The study contributes four design principles for Shariah-sensitive conversational interfaces, namely legitimacy cues, provenance transparency, linguistic completeness and expectation setting, and argues that in this domain usability is part of how users judge Shariah assurance rather than a cosmetic concern.
References
Annamalai, S., Kuo, W. S., Che Omar, A., Yusof, N., & Abd Muin, M. A. (2026). SCAI: User acceptance of a Shariah-compliant conversational agent for promoting Islamic financial literacy among marginalized communities [Manuscript submitted for publication]. School of Multimedia Technology and Communication, Universiti Utara Malaysia.
Borsci, S., Malizia, A., Schmettow, M., van der Velde, F., Tariverdiyeva, G., Balaji, D., & Chamberlain, A. (2022). The Chatbot Usability Scale: The design and pilot of a usability scale for interaction with AI-based conversational agents. Personal and Ubiquitous Computing, 26(1), 95–119. https://doi.org/10.1007/s00779-021-01582-9
Braun, V., & Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. https://doi.org/10.1080/14780887.2020.1769238
Busari, S. A. (2025). Maqasid al-Shariah-based strategies for enhancing digital adoption among B40 Muslim entrepreneurs. Journal of Islamic Finance, 14(1).
Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014). The use of triangulation in qualitative research. Oncology Nursing Forum, 41(5), 545–547. https://doi.org/10.1188/14.ONF.545-547
Chin, J. P., Diehl, V. A., & Norman, K. L. (1988). Development of an instrument measuring user satisfaction of the human-computer interface. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 213–218). ACM. https://doi.org/10.1145/57167.57203
DiCicco-Bloom, B., & Crabtree, B. F. (2006). The qualitative research interview. Medical Education, 40(4), 314–321. https://doi.org/10.1111/j.1365-2929.2006.02418.x
Elwy, A. R., Wasan, A. D., Gillman, A. G., Johnston, K. L., Dodds, N., McFarland, C., & Greco, C. M. (2020). Using formative evaluation methods to improve clinical implementation efforts: Description and an example. Psychiatry Research, 283, 112532. https://doi.org/10.1016/j.psychres.2019.112532
Fogg, B. J., Soohoo, C., Danielson, D. R., Marable, L., Stanford, J., & Tauber, E. R. (2003). How do users evaluate the credibility of Web sites? A study with over 2,500 participants. In Proceedings of the 2003 Conference on Designing for User Experiences (pp. 1–15). ACM. https://doi.org/10.1145/997078.997097
Følstad, A., Araujo, T., Law, E. L.-C., Brandtzaeg, P. B., Papadopoulos, S., Reis, L., Baez, M., Laban, G., McAllister, P., Ischen, C., Wald, R., Catania, F., Meyer von Wolff, R., Hobert, S., & Luger, E. (2021). Future directions for chatbot research: An interdisciplinary research agenda. Computing, 103(12), 2915–2942. https://doi.org/10.1007/s00607-021-01016-7
Hertzum, M., & Jacobsen, N. E. (2001). The evaluator effect: A chilling fact about usability evaluation methods. International Journal of Human-Computer Interaction, 13(4), 421–443. https://doi.org/10.1207/S15327590IJHC1304_05
Hwang, G.-J., & Chang, C.-Y. (2023). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 31(7), 4099–4112. https://doi.org/10.1080/10494820.2021.1952615
Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), Article 248. https://doi.org/10.1145/3571730
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Krueger, R. A., & Casey, M. A. (2015). Focus groups: A practical guide for applied research (5th ed.). SAGE Publications.
Kuhail, M. A., Alturki, N., Alramlawi, S., & Alhejori, K. (2023). Interacting with educational chatbots: A systematic review. Education and Information Technologies, 28(1), 973–1018. https://doi.org/10.1007/s10639-022-11177-3
Kumar, B. A., Chand, S. S., & Goundar, M. S. (2024). Usability testing of mobile learning applications: A systematic mapping study. International Journal of Information and Learning Technology, 41(2), 113–129. https://doi.org/10.1108/IJILT-03-2023-0029
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20, Article 56. https://doi.org/10.1186/s41239-023-00426-1
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications.
Luger, E., & Sellen, A. (2016). “Like having a really bad PA”: The gulf between user expectation and experience of conversational agents. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 5286–5297). ACM. https://doi.org/10.1145/2858036.2858288
Lund, A. M. (2001). Measuring usability with the USE questionnaire. Usability Interface, 8(2), 3–6.
Lynn, M. R. (1986). Determination and quantification of content validity. Nursing Research, 35(6), 382–385. https://doi.org/10.1097/00006199-198611000-00017
Malterud, K., Siersma, V. D., & Guassora, A. D. (2016). Sample size in qualitative interview studies: Guided by information power. Qualitative Health Research, 26(13), 1753–1760. https://doi.org/10.1177/1049732315617444
Medhi, I., Patnaik, S., Brunskill, E., Gautama, S. N. N., Thies, W., & Toyama, K. (2011). Designing mobile interfaces for novice and low-literacy users. ACM Transactions on Computer-Human Interaction, 18(1), Article 2. https://doi.org/10.1145/1959022.1959024
Mohd Thas Thaker, H., Lacheheb, Z., Lechumanan, B., Duasa, J., & Taghizadeh-Hesary, F. (2026). Examining factors influencing chatbot adoption in Takaful industry: Malaysian evidence. International Journal of Islamic and Middle Eastern Finance and Management, 19(3), 614–637.
Munisamy, A., Sahid, S., & Hussin, M. (2022). A financial literacy model of Malaysian B40 households: The case of financial well-being, education level and socioeconomic status. Proceedings, 82(1), 64. https://doi.org/10.3390/proceedings2022082064
Nawang, W. R. W., Johari, F., Shukor, S. A., Shahwan, S., & Abdullah, M. (2025). Islamic financial literacy in Malaysia: Evidence from a young Muslim population. Global Business and Management Research, 17(3), 127–138.
Nielsen, J. (1994). Heuristic evaluation. In J. Nielsen & R. L. Mack (Eds.), Usability inspection methods (pp. 25–62). John Wiley & Sons.
Nielsen, J., & Landauer, T. K. (1993). A mathematical model of the finding of usability problems. In Proceedings of the INTERACT ’93 and CHI ’93 Conference on Human Factors in Computing Systems (pp. 206–213). ACM. https://doi.org/10.1145/169059.169166
Nordheim, C. B., Følstad, A., & Bjørkli, C. A. (2019). An initial model of trust in chatbots for customer service: Findings from a questionnaire study. Interacting with Computers, 31(3), 317–335. https://doi.org/10.1093/iwc/iwz022
Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033
Osman, I., Syed Alwi, S. F., Rehman, M. A., Muda, R., Hassan, F., Hassan, R., & Abdullah, H. (2024). The dilemma of millennial Muslims towards financial management: An Islamic financial literacy perspective. Journal of Islamic Marketing, 15(1), 59–78.
Polit, D. F., & Beck, C. T. (2006). The content validity index: Are you sure you know what’s being reported? Critique and recommendations. Research in Nursing & Health, 29(5), 489–497. https://doi.org/10.1002/nur.20147
Rapp, A., Curti, L., & Boldi, A. (2021). The human side of human-chatbot interaction: A systematic literature review of ten years of research on text-based chatbots. International Journal of Human-Computer Studies, 151, 102630. https://doi.org/10.1016/j.ijhcs.2021.102630
W3C. (2023). Web Content Accessibility Guidelines (WCAG) 2.2. World Wide Web Consortium. https://www.w3.org/TR/WCAG22/
Wollny, S., Schneider, J., Di Mitri, D., Weidlich, J., Rittberger, M., & Drachsler, H. (2021). Are we there yet? A systematic literature review on chatbots in education. Frontiers in Artificial Intelligence, 4, 654924. https://doi.org/10.3389/frai.2021.654924



