Zulisman Maksom, Hanif Al-Fatta, Faaizah Shahbodin, Che Ku Nuraini Che Ku Mohd, Fadhlan Faizal Nuruddin
pp. 62-77, download
(https://doi.org/10.55612/s-5002-069-003)
Abstract
Sustainable practice in the creative industries calls for design methods that support innovation without losing sight of human experience and longer-term cultural change. In Open and Distance Learning (ODL), adult learners’ engagement, persistence, and well-being depend on how learning goals, digital tools, institutional rules, communities, roles, and emotional experience work together. This conceptual paper brings Activity-Centered Design (ACD) and Emotional Design into a single theory-synthesis framework, informed by an integrative review of activity theory, temporally extended user experience, adult ODL, and sustainable creative education. The proposed logic moves from diagnosis to design: ACD locates contradictions in the activity system, Emotional Design examines how those contradictions are experienced over time, and the combined lens guides structural and experiential responses. An illustrative online studio case shows how this approach changes decisions about critique, scheduling, tool integration, feedback, community, and recovery for working adult creative practitioners. Design heuristics, candidate evaluation indicators, ethical safeguards, and boundary conditions are also proposed. The framework remains a conceptual proposition for empirical testing; it is not presented as evidence of established effectiveness.
keywords: Activity-Centered Design, Emotional Design, Sustainable Innovation, Open and Distance Learning, Adult Learners, Creative Industries.
References
1. A. R. Norizan, Z. Maksom, and C. P. Naim, “Tackling design issues on elderly smartphone interface design using activity centered design approach,” ARPN Journal of Engineering and Applied Sciences, vol. 9, no. 8, pp. 1190–1196, 2014.
2. P. M. A. Desmet and S. F. Fokkinga, “Beyond Maslow’s pyramid: Introducing a typology of thirteen fundamental needs for human-centered design,” Multimodal Technologies and Interaction, vol. 4, no. 3, article 38, 2020, doi: https://doi.org/10.3390/mti4030038.
3. V. Kaptelinin and B. A. Nardi, “Activity theory as a framework for human–technology interaction research,” Mind, Culture, and Activity, vol. 25, no. 1, pp. 3–5, 2018, doi: https://doi.org/10.1080/10749039.2017.1393089.
4. D. A. Norman, Emotional Design: Why We Love (or Hate) Everyday Things. New York, NY, USA: Basic Books, 2004.
5. J. Wong, M. Baars, D. Davis, T. van der Zee, G.-J. Houben, and F. Paas, “Supporting self-regulated learning in online learning environments and MOOCs: A systematic review,” International Journal of Human–Computer Interaction, vol. 35, nos. 4–5, pp. 356–373, 2019, doi: https://doi.org/10.1080/10447318.2018.1543084.
6. S. Liu, S. Liu, Z. Liu, X. Peng, and Z. Yang, “Automated detection of emotional and cognitive engagement in MOOC discussions to predict learning achievement,” Computers & Education, vol. 181, article 104461, 2022, doi: https://doi.org/10.1016/j.compedu.2022.104461.
7. C.-Y. C. Kwong and D. Churchill, “Applying the Activity Theory framework to analyse the use of ePortfolios in an International Baccalaureate Middle Years Programme Sciences classroom: A longitudinal multiple-case study,” Computers & Education, vol. 200, article 104792, 2023, doi: https://doi.org/10.1016/j.compedu.2023.104792.
8. Y. Wu, X. Xu, J. Xue, and P. Hu, “A cross-group comparison study of the effect of interaction on satisfaction in online learning: The parallel mediating role of academic emotions and self-regulated learning,” Computers & Education, vol. 199, article 104776, 2023, doi: https://doi.org/10.1016/j.compedu.2023.104776.
9. Z. M. Han, C. Q. Huang, J. H. Yu, and C.-C. Tsai, “Identifying patterns of epistemic emotions with respect to interactions in massive online open courses using deep learning and social network analysis,” Computers in Human Behavior, vol. 122, article 106843, 2021, doi: https://doi.org/10.1016/j.chb.2021.106843.
10. M. Klose, P. Handschuh, D. Steger, and C. Artelt, “Not easy to get off track: Motivational trajectories of learners completing a non-formal online course,” Computers in Human Behavior, vol. 159, article 108322, 2024, doi: https://doi.org/10.1016/j.chb.2024.108322.
11. D. Addae, E. Abakah, and D. Amuzu, “Adults who learn online: Exploring the online learning readiness of nontraditional undergraduate students in a Ghanaian university,” International Journal of Educational Research Open, vol. 8, article 100407, 2025, doi: https://doi.org/10.1016/j.ijedro.2024.100407.
12. F. Herzallah, H. T. M. Herz Allah, M. A. Al-Sharafi, and M. Alhayek, “Determinants of long-term e-learning engagement: Integrating expectation confirmation theory and individual innovativeness using PLS-SEM,” Computers in Human Behavior Reports, vol. 20, article 100853, 2025, doi: https://doi.org/10.1016/j.chbr.2025.100853.
13. K. Kubikova, A. Bohacova, J. Slowik, and I. Pavelkova, “Student adaptation to distance learning: An analysis of the effectiveness, benefits and risks of distance education from the perspective of university students,” Social Sciences & Humanities Open, vol. 9, article 100875, 2024, doi: https://doi.org/10.1016/j.ssaho.2024.100875.
14. E. Martinez Marroquin and B. Senadji, “Activity theory as framework for analysis of workplace learning technologies: The case of generative AI conversational agents,” International Journal of Information and Learning Technology, vol. 42, no. 4, pp. 353–365, 2025, doi: https://doi.org/10.1108/IJILT-07-2024-0141.
15. K. Shingjergji, D. Iren, C. Urlings, and R. Klemke, “Affective computing in online higher education: A systematic literature review,” Computers and Education: Artificial Intelligence, vol. 10, article 100499, 2026, doi: https://doi.org/10.1016/j.caeai.2025.100499.
16. N. Bosch, S. D’Mello, R. Baker, J. Ocumpaugh, V. Shute, M. Ventura, L. Wang, and W. Zhao, “Automatic detection of learning-centered affective states in the wild,” in Proceedings of the 20th International Conference on Intelligent User Interfaces, Atlanta, GA, USA, 2015, pp. 379–388, doi: https://doi.org/10.1145/2678025.2701397.
17. P. Goodyear and L. Carvalho, “The analysis of complex learning environments,” in Rethinking Pedagogy for a Digital Age: Principles and Practices of Design, 3rd ed., H. Beetham and R. Sharpe, Eds. Abingdon, UK: Routledge, 2019, pp. 49–65, doi: https://doi.org/10.4324/9781351252805-4.
18. C. Dede, The Role of Digital Technologies in Deeper Learning. Boston, MA, USA: Jobs for the Future, 2014.
19. E. Blevis, “Sustainable interaction design: Invention & disposal, renewal & reuse,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’07), San Jose, CA, USA, 2007, pp. 503–512, doi: https://doi.org/10.1145/1240624.1240705.
20. E. Karapanos, J. Zimmerman, J. Forlizzi, and J.-B. Martens, “User experience over time: An initial framework,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’09), Boston, MA, USA, 2009, pp. 729–738, doi: https://doi.org/10.1145/1518701.1518814.
21. N. Besana, P. G. Krogh, M. G. Petersen, and D. Spallazzo, “Expanding the concept of sustainable interaction design: A systematic review,” Sustainability, vol. 16, no. 17, article 7486, 2024, doi: https://doi.org/10.3390/su16177486.
22. E. Jaakkola, “Designing conceptual articles: Four approaches,” AMS Review, vol. 10, nos. 1–2, pp. 18–26, 2020, doi: https://doi.org/10.1007/s13162-020-00161-0.
23. R. J. Torraco, “Writing integrative literature reviews: Guidelines and examples,” Human Resource Development Review, vol. 4, no. 3, pp. 356–367, 2005, doi: https://doi.org/10.1177/1534484305278283.
24. T. Kvan, “The pedagogy of virtual design studios,” Automation in Construction, vol. 10, no. 3, pp. 345–353, 2001, doi: https://doi.org/10.1016/S0926-5805(00)00051-0.
25. A. Iranmanesh and Z. Onur, “Mandatory virtual design studio for all: Exploring the transformations of architectural education amidst the global pandemic,” International Journal of Art & Design Education, vol. 40, no. 1, pp. 251–267, 2021, doi: https://doi.org/10.1111/jade.12350.
26. A. Iranmanesh and Z. Onur, “Generation gap: Learning from the experience of compulsory remote architectural design studio,” International Journal of Educational Technology in Higher Education, vol. 19, article 40, 2022, doi: https://doi.org/10.1186/s41239-022-00345-7.
27. A. Murray, J. Fox, J. Sleight, and P. Oldfield, “The online studio: Cultures, perceptions and questions for the future,” International Journal of Art & Design Education, vol. 42, no. 1, pp. 108–124, 2023, doi: https://doi.org/10.1111/jade.12451.
28. R. Bridgstock, “Professional capabilities for twenty-first century creative careers: Lessons from outstandingly successful Australian artists and designers,” International Journal of Art & Design Education, vol. 32, no. 2, pp. 176–189, 2013, doi: https://doi.org/10.1111/j.1476-8070.2013.01756.x.
29. M. Hassenzahl and N. Tractinsky, “User experience—A research agenda,” Behaviour & Information Technology, vol. 25, no. 2, pp. 91–97, 2006, doi: https://doi.org/10.1080/01449290500330331.
30. Y. Engeström, “Expansive learning at work: Toward an activity theoretical reconceptualization,” Journal of Education and Work, vol. 14, no. 1, pp. 133–156, 2001, doi: https://doi.org/10.1080/13639080020028747.
31. D. J. MacInnis, “A framework for conceptual contributions in marketing,” Journal of Marketing, vol. 75, no. 4, pp. 136–154, 2011, doi: https://doi.org/10.1509/jmkg.75.4.136.
32. E. B.-N. Sanders and P. J. Stappers, “Co-creation and the new landscapes of design,” CoDesign, vol. 4, no. 1, pp. 5–18, 2008, doi: https://doi.org/10.1080/15710880701875068.
33. M. S. Knowles, E. F. Holton III, and R. A. Swanson, The Adult Learner: The Definitive Classic in Adult Education and Human Resource Development, 8th ed. Abingdon, UK: Routledge, 2015, doi: https://doi.org/10.4324/9781315816951.
34. L. Stark and J. Hoey, “The ethics of emotion in artificial intelligence systems,” in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 2021, pp. 782–793, doi: https://doi.org/10.1145/3442188.3445939.
35. N. DiBerardino and L. Stark, “(Anti)-intentional harms: The conceptual pitfalls of emotion AI in education,” in Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023, pp. 1386–1395, doi: https://doi.org/10.1145/3593013.3594088.