Staff profile

Effie Lai-Chong Law is a full professor of computer science, specialising in Human-Computer Interaction (HCI). Before joining Durham, Effie was a full professor in HCI at the University of Leicester, UK, and Senior Research Fellow at ETH Zurich, Switzerland. Effie earned her PhD degree (major: psychology; minor: computer science) with summa cum laude from the University of Munich (LMU) with a four-year full scholarship awarded by DAAD (German Academic Exchange Service). She completed her Bachelor and Master in Social Science at the University of Hong Kong. 

Effie's long-term research focus is Usability and User Experience (UX) methodologies which she has successfully applied to various areas, including Technology-enhanced Learning (TEL), Affective Computing, and Trustworthy Autonomous Systems (TAS). Effie chaired two COST Actions – MAUSE on usability and TwinTide on UX (2005-2013). She has also played a leading role in a number of EU-funded projects, including UNIVERSAL (FP5 on e-learning brokerage systems), PROLEARN (FP6 Network of Excellence on professional e-learning), iCamp (FP6 on collaborative online learning with social media), ROLE (FP7 on personalised learning environment), 80Days (FP7 on game-based learning), Go-Lab/NextLab (FP7/H2020 on online experimentation), and the current ARETE (H2020 on augmented learning educational systems) and ESA Personalized Space Technology Exercise Platform (P-STEP, 2021-2023). In addition, Effie has been PI/CoI in several national ones, including Representing Reformation (AHRC), Laws in Children's Life (ESRC), IP in the creative industries (AHRC with China), Computer-supported collaborative learning on astronomy online lab (STFC with Malaysia), and the running UKRI TAS Verifiability. 

Effie is an editorial board member of Interacting with Computers (OUP), International Journal of Human-Computer Studies (Elsevier), and Quality and User Experience (Springer). She has published more than 200 peer-reviewed papers in reputed journals and conferences. She has served as scientifc chair and associate chair in several prestigious conferences in HCI, including CHI, NordiCHI, INTERACT, and British HCI.

Effie’s recent research foci are: Multidimensional measurement of UX; Automatic multisensory emotion recognition; Conversational AI (chatbots); Mixed Reality.

Chapter in book

• Thanyadit, S., Heintz, M., Law, E. L.-C., & Mangina, E. (2022). How easy is it to eXtend Reality? A Usability Study of Authoring Toolkits. In T. Ahram, & R. Taiar (Eds.), Human Interaction & Emerging Technologies (IHIET 2022): Artificial Intelligence & Future Applications. AHFE International. https://doi.org/10.54941/ahfe1002707

Conference Paper

• Thanyadit, S., Heintz, M., & Law, E. L.-C. (2023, April). Tutor In-sight: Guiding and Visualizing Students Attention with Mixed Reality Avatar Presentation Tools. Presented at CHI '23: CHI Conference on Human Factors in Computing Systems, Hamburg, Germany
• Alabdulwahab, B., & Lai-Chong Law, E. (2023, August). Empirical Grounding for the Interpretations of Natural User Interface: A Case Study on Smartpen. Presented at INTERACT 2023: 19th International Conference of Technical Committee 13 (Human- Computer Interaction) of IFIP (International Federation for Information Processing), York, UK
• Lai-Chong Law, E., van As, N., & Følstad, A. (2023, August). Effects of Prior Experience, Gender, and Age on Trust in a Banking Chatbot with(out) Breakdown and Repair. Presented at INTERACT 2023: 19th International Conference of Technical Committee 13 (Human- Computer Interaction) of IFIP (International Federation for Information Processing), York, UK
• Law, E. L.-C., Følstad, A., & van As, N. (2022, October). Effects of Humanlikeness and Conversational Breakdown on Trust in Chatbots for Customer Service. Presented at NordiCHI '22: Nordic Human-Computer Interaction Conference, Aarhus, Denmark

Journal Article

• Følstad, A., Law, E. L.-C., & van As, N. (online). Conversational Breakdown in a Customer Service Chatbot: Impact of Task Order and Criticality on User Trust and Emotion. ACM Transactions on Computer-Human Interaction, https://doi.org/10.1145/3690383
• AlSokkar, A. A. M., Law, E. L.-C., AlMajali, D. A., Al-Gasawneh, J. A., & Alshinwan, M. (2024). An Indexed Approach for Expectation-Confirmation Theory: A Trust-based model. Electronic Markets, 34(1), Article 12. https://doi.org/10.1007/s12525-024-00694-3
• Hobert, S., Følstad, A., & Law, E. L.-C. (2023). Chatbots for Active Learning: A Case of Phishing Email Identification. International Journal of Human-Computer Studies, 179, Article 103108. https://doi.org/10.1016/j.ijhcs.2023.103108
• Mousavi, M. R., Cavalcanti, A., Fisher, M., Dennis, L., Hierons, R., Kaddouh, B., Law, E. L.-C., Richardson, R., Ringert, J. O., Tyukin, I., & Woodcock, J. (2023). Trustworthy Autonomous Systems Through Verifiability. Computer, 56(2), 40-47. https://doi.org/10.1109/mc.2022.3192206
• Garcia-Garcia, J. M., Lozano, M. D., Penichet, V. M., & Law, E. L.-C. (2023). Building a three-level multimodal emotion recognition framework. Multimedia Tools and Applications, 82(1), 239-269. https://doi.org/10.1007/s11042-022-13254-8
• Haffejee, S., Vostanis, P., O'Reilly, M., Law, E., Eruyar, S., Fleury, J., Hassan, S., & Getanda, E. (2023). Disruptions, adjustments and hopes: The impact of the COVID‐19 pandemic on child well‐being in five Majority World Countries. Children & Society, 37(1), 8-28. https://doi.org/10.1111/chso.12563
• Law, E. L.-C., Vostanis, P., & O’Reilly, M. J. (2023). Insights from impacts of the digital divide on children in five majority world countries during the COVID-19 pandemic. Behaviour and Information Technology, 42(15), 2696-2715. https://doi.org/10.1080/0144929x.2022.2141136
• 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