Developing an Integrated Moral-Art Curriculum Module: A Discourse-Based Computational Linguistic Evaluation of Student Outcomes

Authors

  • Jinzhang Leng

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia

    School of Art, Anhui University of Finance & Economics, Bengbu 233030, China

  • Nurfaradilla Mohamad Nasri

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia

  • Khairul Azhar Jamaludin

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia

DOI:

https://doi.org/10.30564/fls.v7i11.11430
Received: 1 August 2025 | Revised: 22 August 2025 | Accepted: 29 August 2025 | Published Online: 22 October 2025

Abstract

Higher education faces increasing demands to develop students' ethical, creative, and emotional capabilities alongside academic mastery. While the World Economic Forum identifies critical thinking, creativity, emotional intelligence, and moral judgment as essential future workforce skills, most university curricula remain compartmentalized, prioritizing cognitive over affective and aesthetic domains. Current educational approaches lack empirically validated frameworks that systematically integrate moral development with artistic learning in digitally enhanced environments. This study designed, implemented, and evaluated an integrated moral-art curriculum module to foster undergraduate students' moral reasoning, creative thinking, and aesthetic sensitivity through blended learning approaches. Using Design and Development Research guided by the ADDIE instructional model, a quasi-experimental pre-post study was conducted with 50 undergraduate students from diverse academic backgrounds across four institution types. The 12-week module combined synchronous classroom instruction with asynchronous digital learning via the Learning Pass platform. Outcomes were assessed through validated pre-post questionnaires and computational linguistic analysis using LIWC and Coh-Metrix tools. Significant improvements occurred across all domains: moral reasoning increased 35.5% (Cohen's d = 0.91), creative thinking rose 32.3%, and aesthetic sensitivity improved 41.4% (d = 0.85). Linguistic analysis revealed enhanced lexical diversity (+16.4%), academic vocabulary (+41.5%), and empathy markers (+42.1%), with reduced anxiety language (−18.2%). Strong inter-domain correlations confirmed the integrated pedagogical framework's theoretical viability. Results provide empirical support for scalable, digitally enhanced interdisciplinary curricula uniting moral and artistic education in higher education contexts.

Keywords:

Moral-Art Education; Blended Learning; Design and Development Research; ADDIE Model; Creative Expression; Aesthetic Skills; Learning Pass; Computational Discourse Analysis

References

[1] Knight, S., Littleton, K., 2015. Discourse Centric Learning Analytics: Mapping the Terrain. Journal of Learning Analytics. 2(1). DOI: https://doi.org/10.18608/jla.2015.21.9

[2] Dowell, N.M., Graesser, A.C., Cai, Z., 2016. Language and Discourse Analysis with Coh-Metrix: Applications from Educational Material to Learning Environments at Scale. Journal of Learning Analytics. 3(3), 72–95. DOI: https://doi.org/10.18608/jla.2016.33.5

[3] Gibson, A., Kitto, K., Bruza, P., 2016. Towards the Discovery of Learner Metacognition From Reflective Writing. Journal of Learning Analytics. 3(2), 22–36. DOI: https://doi.org/10.18608/jla.2016.32.3

[4] Raza, A., 2023. Art and Education: Fostering Creativity and Critical Thinking in Humanity. Journal of Religion and Society. 1(1),13–25. Available from: https://www.islamicreligious.com/index.php/Journal/article/view/19 (cited 31 July 2025).

[5] Emara, M., Hutchins, N., Grover, S., et al., 2021. Examining Student Regulation of Collaborative, Computational, Problem-Solving Processes in Open-Ended Learning Environments. Journal of Learning Analytics. 8(1), 49–74. DOI: https://doi.org/10.18608/jla.2021.7230

[6] Alvarez, C., Zurita, G., Carvallo, A., et al., 2021. Automatic Content Analysis of Student Moral Discourse in a Collaborative Learning Activity. In: Hernández-Leo, D., Hishiyama, R., Zurita, G., et al. (Eds.). Collaboration Technologies and Social Computing, Lecture Notes in Computer Science. Springer International Publishing: Cham, Switzerland. pp. 3–19. DOI: https://doi.org/10.1007/978-3-030-85071-5_1

[7] Jia, Y., Zhou, B., Zheng, X., 2021. A Curriculum Integrating STEAM and Maker Education Promotes Pupils' Learning Motivation, Self-Efficacy, and Interdisciplinary Knowledge Acquisition. Frontiers in Psychology. 12, 725525. DOI: https://doi.org/10.3389/fpsyg.2021.725525

[8] Alic, S., Demszky, D., Mancenido, Z., et al., 2022. Computationally Identifying Funneling and Focusing Questions in Classroom Discourse. In Proceedings of the 17th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2022), Seattle, DC, USA, 15 July 2022; pp. 224–233. DOI: https://doi.org/10.18653/v1/2022.bea-1.27

[9] Demszky, D., Hill, H., 2023. The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts, in: Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), Toronto, Ont, Canada, 13 July 2023; pp. 528–538. DOI: https://doi.org/10.18653/v1/2023.bea-1.44

[10] Shin, J., Balyan, R., Banawan, M.P., et al., 2023. Pedagogical discourse markers in online algebra learning: Unraveling instructor's communication using natural language processing. Computers & Education. 205, 104897. DOI: https://doi.org/10.1016/j.compedu.2023.104897

[11] Dornauer, V., Netzer, M., Kaczkó, É., et al., 2024. Automatic Classification of Online Discussions and Other Learning Traces to Detect Cognitive Presence. International Journal of Artificial Intelligence in Education. 34(2), 395–415. DOI: https://doi.org/10.1007/s40593-023-00335-4

[12] Chandler, C., Breideband, T., Reitman, J.G., et al., 2024. Computational Modeling of Collaborative Discourse to Enable Feedback and Reflection in Middle School Classrooms. In Proceedings of the 14th Learning Analytics and Knowledge Conference, Kyoto, Japan, 18 March 2024; pp. 576–586. DOI: https://doi.org/10.1145/3636555.3636917

[13] Garg, R., Han, J., Cheng, Y., et al., 2024. Automated Discourse Analysis via Generative Artificial Intelligence. In Proceedings of the 14th Learning Analytics and Knowledge Conference, Kyoto, Japan, 18 March 2024; pp. 814–820. DOI: https://doi.org/10.1145/3636555.3636879

[14] Donnelly, P.J., Blanchard, N., Olney, A.M., et al., 2017. Words matter: automatic detection of teacher questions in live classroom discourse using linguistics, acoustics, and context. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference, Vancouver, B.C., Canada, 13 March 2017; pp. 218–227. DOI: https://doi.org/10.1145/3027385.3027417

[15] Kaliisa, R., Dolonen, J.A., 2023. CADA: a teacher-facing learning analytics dashboard to foster teachers' awareness of students' participation and discourse patterns in online discussions. Technology, Knowledge and Learning. 28(3), 937–958. DOI: https://doi.org/10.1007/s10758-022-09598-7

[16] Wang, D., Zheng, Y., Li, J., et al., 2025. Parameter-Efficiently Fine-Tuning Large Language Models for Classroom Dialogue Analysis. IEEE Transactions on Learning Technologies. 18, 542–555. DOI: https://doi.org/10.1109/TLT.2025.3567995

[17] Hardiman, M.M., JohnBull, R.M., Carran, D.T., et al., 2019. The effects of arts-integrated instruction on memory for science content. Trends in Neuroscience and Education. 14, 25–32. DOI: https://doi.org/10.1016/j.tine.2019.02.002

[18] Egana-delSol, P., 2023. The impacts of a high-school art-based program on academic achievements, creativity, and creative behaviors. npj Science of Learning. 8(1), 39. DOI: https://doi.org/10.1038/s41539-023-00187-6

[19] Kyomugisha, A., 2024. The Impact of Art-Based Learning on Curriculum Enhancement. NEWPORT INTERNATIONAL JOURNAL OF CURRENT ISSUES IN ARTS AND MANAGEMENT. 5(3), 26–30. DOI: https://doi.org/10.59298/NIJCIAM/2024/5.3.26300

[20] Nishino, M., 2017. The challenge of developing meaningful curriculum initiatives for moral education in Japan. Journal of Moral Education. 46(1), 46–57. DOI: https://doi.org/10.1080/03057240.2016.1276438

[21] Waage, I.Ó., 2025. Cultivating virtue literacy in visual arts classes: Reflection on a fine-arts intervention aimed at moral education in a lower-secondary school in Iceland. Journal of Moral Education. 54(2), 257–276. DOI: https://doi.org/10.1080/03057240.2023.2290977

[22] Mátyás, T., 2023. Comparative Discourse Analysis of Moral Dilemmas of Students Attending Hungarian Schools of Three Models. The New Educational Review. 71(1), 216–226. DOI: https://doi.org/10.15804/tner.23.71.1.17

[23] Tian, X., Tang, Y., 2025. From Awareness to Behavior: The Empirical Effects of Real Problem-Oriented Learning in Civic and Moral Education. SAGE Open. 15(2), 21582440251338948. DOI: https://doi.org/10.1177/21582440251338948

[24] Li, Y., Wang, X., 2023. Discussion on the integration of moral education into the curriculum of environmental art design under the background of ‘five education simultaneously'. Advances in Higher Education. 7(3). DOI: 10.18686/ahe.v7i33.12013. Available from: https://ojs.usp-pl.com/index.php/ADVANCES-IN-HIGHER-EDUCATION/article/viewFile/12013/11504 (cited 31 July 2025).

[25] Caldarera, J., 2025. Moral education in the context of the arts. Frontiers in Education. 9, 1419335. DOI: https://doi.org/10.3389/feduc.2024.1419335

[26] Escala, N., Ángel Herrera-Pavo, M., Guitert, M., et al., 2024. Educational experiences integrating the arts into teaching practice in primary education in Ecuador. Thinking Skills and Creativity. 54, 101671. DOI: https://doi.org/10.1016/j.tsc.2024.101671

[27] Tang, H., Wang, Y., 2021. Moral Education Curriculum Reform for China's Elementary and Middle Schools in the Twenty-First Century: Past Progress and Future Prospects. ECNU Review of Education. 4(4), 727–742. DOI: https://doi.org/10.1177/2096531120923416

[28] Watson, A., 2020. Methods Braiding: A Technique for Arts-Based and Mixed-Methods Research. Sociological Research Online. 25(1), 66–83. DOI: https://doi.org/10.1177/1360780419849437

[29] Farah, N., 2020. Automatic Analysis of Language Use in K-16 STEM Education and Impact on Student Performance [Doctoral Dissertation].University of Washington: Washington, DC, USA. Available from: https://digital.lib.washington.edu/researchworks/items/492a6dda-c1fa-4289-9991-b4ee25b8072f (cited 31 July 2025).

[30] Cobos, R., Jurado, F., Blazquez-Herranz, A., 2019. A Content Analysis System That Supports Sentiment Analysis for Subjectivity and Polarity Detection in Online Courses. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje. 14(4), 177–187. DOI: https://doi.org/10.1109/RITA.2019.2952298

[31] Jesionkowska, J., Wild, F., Deval, Y., 2020. Active Learning Augmented Reality for STEAM Education—A Case Study. Education Sciences. 10(8), 198. DOI: https://doi.org/10.3390/educsci10080198

[32] Cauthorn, R., Nillas, L.A., Arts Integration and Student Engagement. 2020. Available from: https://scholars.iwu.edu/en/publications/arts-integration-and-student-engagement (cited 31 July 2025).

[33] Reilly, J.M., Schneider, B., 2019. Predicting the Quality of Collaborative Problem Solving through Linguistic Analysis of Discourse. International Educational Data Mining Society. Available from: https://files.eric.ed.gov/fulltext/ED599226.pdf (cited 31 July 2025).

[34] G. Okoye, K., Daruich, S.D.N., De La O, J.F.E., et al., 2023. A Text Mining and Statistical Approach for Assessment of Pedagogical Impact of Students' Evaluation of Teaching and Learning Outcome in Education. IEEE Access. 11, 9577–9596. DOI: https://doi.org/10.1109/ACCESS.2023.3239779

[35] Alkhadim, G.S., Cimetta, A.D., Marx, R.W., et al., 2021. Validating the Research-Based Early Math Assessment (REMA) among rural children in Southwest United States. Studies in Educational Evaluation. 68, 100944. DOI: https://doi.org/10.1016/j.stueduc.2020.100944

[36] J. Zhukov, V., Popova, O., Altukhova, A., et al., 2025. Moral and Ethical Culture of a Future Art Teacher. Revista Romaneasca pentru Educatie Multidimensionala. 17(1), 138–158. DOI: https://doi.org/10.18662/rrem/17.1/944

[37] Luo, R., Li, J., Zhang, X., et al., 2024. Effects of applying blended learning based on the ADDIE model in nursing staff training on improving theoretical and practical operational aspects. Frontiers in Medicine. 11, 1413032. DOI: https://doi.org/10.3389/fmed.2024.1413032

[38] Thambu, N., 2021. Developing Higher Order Thinking Skills through Blended Learning among Moral Education Students. Turkish Journal of Computer and Mathematics Education (TURCOMAT). 12(3), 808–819. DOI: https://doi.org/10.17762/turcomat.v12i3.788

[39] Shakeel, S.I., Al Mamun, M.A., Haolader, M.F.A., 2023. Instructional design with ADDIE and rapid prototyping for blended learning: validation and its acceptance in the context of TVET Bangladesh. Education and Information Technologies. 28(6), 7601–7630. DOI: https://doi.org/10.1007/s10639-022-11471-0

[40] Leng, J., Nasri, N.M., Jamaludin, K.A., 2025. Application of Learning Pass Information Technology Platform in Blended Teaching Module on Integrated Moral-art Education. Membrane Technology. 25–33. DOI: https://doi.org/10.52710/mt.194

[41] Kardosod, A., Rattanakanlaya, K., Noppakun, L., et al., 2023. Developing a blended learning curriculum using a digital notebook application for a surgical nursing practicum: The ADDIE model. Belitung Nursing Journal. 9(2), 192–197. DOI: https://doi.org/10.33546/bnj.2324

[42] Nurhayati, N., Ampera, D., Chalid, S., et al., 2021. Development of Blended Learning Type and Flipped Classroom-Based Cultural Arts Subjects. International Journal of Education in Mathematics, Science and Technology. 9(4), 655–667. DOI: https://doi.org/10.46328/ijemst.1975

[43] Noermanzah, N., Suryadi, S., 2020. Improving students' ability to analyze discourse through the moodle-based blended learning method. English Review: Journal of English Education. 9(1), 81–94. DOI: https://doi.org/10.25134/erjee.v9i1.3781

[44] Yang, C., Xu, D., Yin, S., 2022. Construction of moral education in college English with blended learning in the “internet+era.” SHS Web of Conferences. 140, 01036. DOI: https://doi.org/10.1051/shsconf/202214001036

[45] Almelhi, A.M., 2021. Effectiveness of the ADDIE Model within an E-Learning Environment in Developing Creative Writing in EFL Students. English Language Teaching. 14(2), 20. DOI: https://doi.org/10.5539/elt.v14n2p20

[46] Leupen, S.M., Kephart, K.L., Hodges, L.C., 2020. Factors Influencing Quality of Team Discussion: Discourse Analysis in an Undergraduate Team-Based Learning Biology Course. CBE—Life Sciences Education. 19(1), ar7. DOI: https://doi.org/10.1187/cbe.19-06-0112

[47] Dennehy, D., Conboy, K., Babu, J., 2023. Adopting Learning Analytics to Inform Postgraduate Curriculum Design: Recommendations and Research Agenda. Information Systems Frontiers. 25(4), 1315–1331. DOI: https://doi.org/10.1007/s10796-021-10183-z

[48] Quarshie, B., Amponsah, A., Boakye-Ansah, D., 2022. Blended pedagogies: The challenges of Visual Arts education. Journal of African History, Culture and Arts. 2(2), 94–103. DOI: https://doi.org/10.57040/jahca.v2i2.124

[49] Silalahi, P., 2020. Design and Development Blended Learning Approach for Student Low Achievement in Mathematics. In Proceedings of the First International Conference on Applied Science and Technology (iCAST 2018), Manado, Indonesia, 2018. DOI: https://doi.org/10.2991/assehr.k.200813.015

[50] Huang, C., Han, Z., Li, M., et al., 2021. Sentiment evolution with interaction levels in blended learning environments: Using learning analytics and epistemic network analysis. Australasian Journal of Educational Technology. 37(2), 81–95. DOI: https://doi.org/10.14742/ajet.6749

[51] Seage, S.J., Türegün, M., 2019. The Effects of Blended Learning on STEM Achievement of Elementary School Students. International Journal of Research in Education and Science. 6(1), 133. DOI: https://doi.org/10.46328/ijres.v6i1.728

[52] Yu, Z., Xu, W., Sukjairungwattana, P., 2022. Meta-analyses of differences in blended and traditional learning outcomes and students' attitudes. Frontiers in Psychology. 13, 926947. DOI: https://doi.org/10.3389/fpsyg.2022.926947

[53] Spatioti, A.G., Kazanidis, I., Pange, J., 2022. A Comparative Study of the ADDIE Instructional Design Model in Distance Education. Information. 13(9), 402. DOI: https://doi.org/10.3390/info13090402

[54] De Bruijn-Smolders, M., Prinsen, F.R., 2024. Effective student engagement with blended learning: A systematic review. Heliyon. 10(23), e39439. DOI: https://doi.org/10.1016/j.heliyon.2024.e39439

Downloads

How to Cite

Leng, J., Nasri, N. M., & Jamaludin, K. A. (2025). Developing an Integrated Moral-Art Curriculum Module: A Discourse-Based Computational Linguistic Evaluation of Student Outcomes. Forum for Linguistic Studies, 7(11), 663–685. https://doi.org/10.30564/fls.v7i11.11430