“Knowledge Media Design is a complex design discipline that is focused on tasks and content and one successful implementation of design solutions using human factors engineering and innovative interaction design.”
“We recognize it when we see it.” This lecture seeks to define Knowledge Media Design (KMD) more precisely by identifying and relating common aspects of different projects. The case studies discuss “exergaming” for older people, game-based cognitive assessment, cybersecurity, and improving wellness through virtual reality. From these projects, there are five key components that make them KMD projects: task, context, computation/content, interaction, and implementation. KMD focuses on solving specific tasks using design tools and methods that may vary depending on the context. These designs go beyond just prototypes to develop functioning devices or applications, mixing the technology being used with the delivery of the project’s content. KMD projects also include interactions between a user and the technology, whether than be controlling a video game with a button box or understanding information through data visualization. Finally, a good KMD solution should be implemented in a way that makes the insights and benefits of the project sustainable in practice. Ultimately, KMD is more than just web design; it requires a multidisciplinary approach that incorporates perspectives from psychology, computer science, and engineering.
The Speaker
Mark Chignell, Professor, Industrial Engineering | Department of Mechanical & Industrial Engineering
Related Research
Chignell, M. H., Chung, M.-H., Yang, Y., Cento, G., & Raman, A. (2021). Human Factors in Interactive Machine Learning: A Cybersecurity Case Study. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 65(1), 1495–1499. https://doi.org/10.1177/1071181321651206
Chignell, M., Matulis, H., & Nejati, B. (2020). Motivating Physical Exercise in the Elderly with Mixed Reality Experiences. In N. Streitz & S. Konomi (Eds.), Distributed, Ambient and Pervasive Interactions (Vol. 12203, pp. 505–519). Springer International Publishing. https://doi.org/10.1007/978-3-030-50344-4_36
Chung, M.-H., Chignell, M., Wang, L., Jovicic, A., & Raman, A. (2020). Interactive Machine Learning for Data Exfiltration Detection: Active Learning with Human Expertise. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 280–287. https://doi.org/10.1109/SMC42975.2020.9282831
Jbilou, J., El Bouazaoui, A., Zhang, B., Henry, J. L., McDonald, L., Hall, T., Chang, R., Barton, D., & Chignell, M. H. (2021). Evaluating and Motivating Activation in Long Term Care: Lessons From a Pilot Study. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, 10(1), 42–46. https://doi.org/10.1177/2327857921101016
Moller, H. J., Waterworth, J. A., & Chignell, M. (2020). Returning to Nature: VR Mediated States of Enhanced Wellness. In N. Streitz & S. Konomi (Eds.), Distributed, Ambient and Pervasive Interactions (Vol. 12203, pp. 593–609). Springer International Publishing. https://doi.org/10.1007/978-3-030-50344-4_43
Tong, T., Chignell, M., Tierney, M. C., & Lee, J. (2016). A Serious Game for Clinical Assessment of Cognitive Status: Validation Study. JMIR Serious Games, 4(1), e7. https://doi.org/10.2196/games.5006
Tong, T., Urakami, J., Chignell, M., Tierney, M. C., & Lee, J. S. (2020). Tracking Cognitive Decline with a Serious Game: Benchmarking Against the Mini-Mental State Examination. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 64(1), 6–10. https://doi.org/10.1177/1071181320641002
Wilkinson, A., Tong, T., Zare, A., Kanik, M., & Chignell, M. (2018). Monitoring Health Status in Long Term Care Through the Use of Ambient Technologies and Serious Games. IEEE Journal of Biomedical and Health Informatics, 22(6), 1807–1813. https://doi.org/10.1109/JBHI.2018.2864686
Other Resources
Experiential Centivizer/Physical Centivizer/2RaceWithMe: https://www.centivizer.com/
Centivizer promo video: https://www.youtube.com/watch?v=mCnYXpd_p84