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Abstract

Purpose: This study explores advancements in Human-Computer Interaction (HCI), focusing on how AI and VR technologies can enhance long-term emotional engagement, cultural inclusivity, and accessibility. The research seeks to fill gaps in understanding HCI's emotional and social dimensions by addressing how these technologies affect users' cognitive and emotional well-being over time.


Research Design and Methodology: The study uses a qualitative systematic literature review to analyze critical academic and industry research on AI, VR, and HCI. Through a thematic analysis, it identifies trends and challenges in designing more inclusive, emotionally responsive, and culturally adaptive systems.


Findings and Discussion: The study reveals that while AI and VR technologies improve user engagement, there are significant gaps in cultural inclusivity and emotional responsiveness, especially for users with disabilities. It also proposes theoretical models integrating emotional and cultural factors into HCI design, enabling adaptive and personalized user experiences.


Implications: This research shows the need for HCI technologies to prioritize emotional engagement and inclusivity. Practically, these findings can guide the development of more adaptive AI and VR systems that cater to diverse user needs, offering better accessibility and user satisfaction. Future research should explore empirical applications of these theoretical models in specific industries, such as healthcare and education.

Keywords

Human-Computer Interaction Emotional Engagement Cultural Inclusivity Artificial Intelligence Virtual Reality

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How to Cite
Hasyim, H., & Bakri, M. (2024). Advancements in Human-Computer Interaction: A Review of Recent Research. Advances: Jurnal Ekonomi & Bisnis, 2(4), 213–227. https://doi.org/10.60079/ajeb.v2i4.327
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References

  1. Azofeifa, J. D., Noguez, J., Ruiz, S., Molina-Espinosa, J. M., Magana, A. J., & Benes, B. (2022). Systematic review of multimodal human–computer interaction. Informatics, 9(1), 13. https://doi.org/10.3390/informatics9010013
  2. Bag, S., Srivastava, G., Bashir, M. M. Al, Kumari, S., Giannakis, M., & Chowdhury, A. H. (2022). Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion. Benchmarking: An International Journal, 29(7), 2074–2098. https://doi.org/10.1108/BIJ-07-2021-0415
  3. Bailey, D. E., Faraj, S., Hinds, P. J., Leonardi, P. M., & von Krogh, G. (2022). We are all theorists of technology now: A relational perspective on emerging technology and organizing. Organization Science, 33(1), 1–18. https://doi.org/10.1287/orsc.2021.1562
  4. Baranyi, P., Csapo, A., & Sallai, G. (2015). Cognitive infocommunications (coginfocom). Springer.
  5. Beer, P., & Mulder, R. H. (2020). The effects of technological developments on work and their implications for continuous vocational education and training: A systematic review. Frontiers in Psychology, 11(May). https://doi.org/10.3389/fpsyg.2020.00918
  6. Diederich, S., Brendel, A. B., Morana, S., Diederich, S., Brendel, A. B., Morana, S., & Kolbe, L. (2022). On the Design of and Interaction with Conversational Agents : An Organizing and Assessing Review of Human-Computer Interaction Research On the Design of and Interaction with Conversational Agents : An Organizing and Assessing Review of Human-Computer Interaction Research. 23(1), 96–138. https://doi.org/10.17705/1jais.00724
  7. Doshi-velez, F., & Kim, B. (2017). Towards A Rigorous Science of Interpretable Machine Learning. Ml, 1–13. https://doi.org/10.48550/arXiv.1702.08608
  8. Ejaz, A., Rahim, M., & Khoja, S. A. (2019). The Effect of Cognitive Load on Gesture Acceptability of Older Adults in Mobile Application. 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 979–986. https://doi.org/10.1109/UEMCON47517.2019.8992970
  9. Fitrianto, I., & Saif, A. (2024). The Role of Virtual Reality in Enhancing Experiential Learning : A Comparative Study of Traditional and Immersive Learning Environments. 2(2), 97–110. https://doi.org/10.59944/postaxial.v2i2.300
  10. Grubert, J., Langlotz, T., Zollmann, S., & Regenbrecht, H. (2017). Towards Pervasive Augmented Reality: Context-Awareness in Augmented Reality. IEEE Transactions on Visualization and Computer Graphics, 23(6), 1706–1724. https://doi.org/10.1109/TVCG.2016.2543720
  11. Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S., & Yang, G.-Z. (2019). XAI—Explainable artificial intelligence. Science Robotics, 4(37), eaay7120. https://doi.org/10.1126/scirobotics.aay7120
  12. Guzmán García, C. (2021). Understanding the role of nontechnical skills in minimally invasive surgery and their integration in technology enhanced learning environments. Telecomunicacion. https://doi.org/10.20868/UPM.thesis.69221.
  13. Heroux, M., Bernholdt, D., McInnes, L. C., Cary, J., Katz, D., Raybourn, E., & Rouson, D. (2023). Basic Research Needs in The Science of Scientific Software Development and Use: Investment in Software is Investment in Science. https://www.osti.gov/servlets/purl/1846009/
  14. Hu, H., Feng, X., Shao, Z., Xie, M., Xu, S., Wu, X., & Ye, Z. (2019). Application and Prospect of Mixed Reality Technology in Medical Field. Current Medical Science, 39(1), 1–6. https://doi.org/10.1007/s11596-019-1992-8
  15. Hulsen, T. (2023). Explainable Artificial Intelligence (XAI): Concepts and Challenges in Healthcare. AI (Switzerland), 4(3), 652–666. https://doi.org/10.3390/ai4030034
  16. Iskandar, A., Winata, W., Kurdi, M. S., Sitompul, P. H. S., Kurdi, M. S., Nurhayati, S., Hasanah, M., & Haluti, F. (2023). Peran Teknologi Dalam Dunia Pendidikan. Yayasan Cendekiawan Inovasi Digital Indonesia.
  17. Javaid, A., Rasool, S., & Maqsood, A. (2024). Analysis of Visual and Vestibular Information on Motion Sickness in Flight Simulation. Aerospace, 11(2), 1–22. https://doi.org/10.3390/aerospace11020139
  18. Johnson, J. (2020). Designing with the mind in mind: simple guide to understanding user interface design guidelines. Morgan Kaufmann.
  19. Jung, H.-T., Park, T., MAhyar, N., Park, S., Ryu, T., Kim, Y., & Lee, S. I. (2020). Rehabilitation games in real-world clinical settings: Practices, challenges, and opportunities. ACM Transactions on Computer-Human Interaction (TOCHI), 27(6), 1–43. https://doi.org/10.1145/3418197
  20. Katona, J. (2021). applied sciences A Review of Human – Computer Interaction and Virtual Reality Research Fields in Cognitive InfoCommunications. https://doi.org/10.3390/APP11062646
  21. Kozyreva, A., Lewandowsky, S., & Hertwig, R. (2020). Citizens Versus the Internet : Confronting Digital Challenges With Cognitive Tools. https://doi.org/10.1177/1529100620946707
  22. Liang, C. A., Munson, S. A., & Kientz, J. A. (2021). Embracing Four Tensions in Human-Computer Interaction Research with Marginalized People. 28(2). https://doi.org/10.1145/3443686
  23. Lidwell, W., Holden, K., & Butler, J. (2010). Universal principles of design, revised and updated: 125 ways to enhance usability, influence perception, increase appeal, make better design decisions, and teach through design. Rockport Pub.
  24. Lindner, P. (2021). Better, Virtually: the Past, Present, and Future of Virtual Reality Cognitive Behavior Therapy. International Journal of Cognitive Therapy, 14(1), 23–46. https://doi.org/10.1007/s41811-020-00090-7
  25. Mirza, A. U. (2024). Exploring the Frontiers of Artificial Intelligence and Machine Learning Technologies. In Exploring the Frontiers of Artificial Intelligence and Machine Learning Technologies (Issue April). https://doi.org/10.59646/efaimlt/133
  26. Molnar, C. (2020). Interpretable machine learning. Lulu. com.
  27. Montana, J. I., Matamala-gomez, M., Maisto, M., Mavrodiev, P. A., Cavalera, C. M., Diana, B., Mantovani, F., & Realdon, O. (2020). The benefits of emotion regulation interventions in virtual reality for the improvement of wellbeing in adults and older adults: A systematic review. Journal of Clinical Medicine, 9(2). https://doi.org/10.3390/jcm9020500
  28. Morgado-Ramirez, D. Z., Barbareschi, G., Kate Donovan-hall, M., Sobuh, M., Elayyan, N., Nakandi, B. T., Tamale Ssekitoleko, R., Olenja, J., Nyachomba Magomere, G., & Daymond, S. (2020). Disability design and innovation in computing research in low resource settings. Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility, 1–7. https://doi.org/10.1145/3373625.3417301
  29. Müller, R., Schischke, D., Graf, B., & Antoni, C. H. (2023). How can we avoid information overload and techno-frustration as a virtual team? The effect of shared mental models of information and communication technology on information overload and techno-frustration. Computers in Human Behavior, 138, 107438. https://doi.org/https://doi.org/10.1016/j.chb.2022.107438
  30. Nazar, M., Alam, M. M., Yafi, E., & Su’ud, M. M. (2021). A Systematic Review of Human–Computer Interaction and Explainable Artificial Intelligence in Healthcare With Artificial Intelligence Techniques. IEEE Access, 9, 153316–153348. https://doi.org/10.1109/ACCESS.2021.3127881
  31. Norman, D. (2007). Emotional design: Why we love (or hate) everyday things. Basic books.
  32. Ntoa, S., Margetis, G., Antona, M., & Stephanidis, C. (2023). Digital Accessibility in Intelligent Environments BT - Human-Automation Interaction: Manufacturing, Services and User Experience (V. G. Duffy, M. Lehto, Y. Yih, & R. W. Proctor (eds.); pp. 453–475). Springer International Publishing. https://doi.org/10.1007/978-3-031-10780-1_25
  33. O’Brien, H. L., Roll, I., Kampen, A., & Davoudi, N. (2022). Rethinking (Dis)engagement in human-computer interaction. Computers in Human Behavior, 128, 107109. https://doi.org/https://doi.org/10.1016/j.chb.2021.107109
  34. Or, C. K., Holden, R. J., & Valdez, R. S. (2023). Human Factors Engineering and User-Centered Design for Mobile Health Technology: Enhancing Effectiveness, Efficiency, and Satisfaction BT - Human-Automation Interaction: Mobile Computing (V. G. Duffy, M. Ziefle, P.-L. P. Rau, & M. M. Tseng (eds.); pp. 97–118). Springer International Publishing. https://doi.org/10.1007/978-3-031-10788-7_6
  35. Owens, E., Sheehan, B., Mullins, M., Cunneen, M., & Ressel, J. (2022). Explainable Artificial Intelligence (Xai) in Insurance: A Systematic Review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4088029
  36. Pang, C., Wang, Z. C., & McGrenere, J. (2021). Technology adoption and learning preferences for older adults: Evolving perceptions, ongoing challenges, and emerging design opportunities. Conference on Human Factors in Computing Systems - Proceedings. https://doi.org/10.1145/3411764.3445702
  37. Purificato, E., Lorenzo, F., Fallucchi, F., & De Luca, E. W. (2023). The Use of Responsible Artificial Intelligence Techniques in the Context of Loan Approval Processes. International Journal of Human–Computer Interaction, 39(7), 1543–1562. https://doi.org/10.1080/10447318.2022.2081284
  38. Rakkolainen, I., Farooq, A., Kangas, J., Hakulinen, J., Rantala, J., Turunen, M., & Raisamo, R. (2021). Technologies for multimodal interaction in extended Reality—a scoping review. Multimodal Technologies and Interaction, 5(12). https://doi.org/10.3390/mti5120081
  39. Sarma, D., & Bhuyan, M. K. (2021). Methods, Databases and Recent Advancement of Vision-Based Hand Gesture Recognition for HCI Systems: A Review. SN Computer Science, 2(6), 436. https://doi.org/10.1007/s42979-021-00827-x
  40. Schuetz , S . W . and Venkatesh, V. . (2020). The Rise of Human Machines : How Cognitive Computing Systems Challenge Assumptions of User-System. Journal of the Association for Information Systems, 460–482. https://ssrn.com/abstract=3680306
  41. Shank, D. B., Graves, C., Gott, A., Gamez, P., & Rodriguez, S. (2019). Feeling our way to machine minds: People’s emotions when perceiving mind in artificial intelligence. Computers in Human Behavior, 98, 256–266. https://doi.org/https://doi.org/10.1016/j.chb.2019.04.001
  42. Stephanidis, C., Salvendy, G., Antona, M., Chen, J. Y. C., Dong, J., Duffy, V. G., Fang, X., Fidopiastis, C., Fragomeni, G., Fu, L. P., Guo, Y., Harris, D., Ioannou, A., Jeong, K. (Kate), Konomi, S., Krömker, H., Kurosu, M., Lewis, J. R., Marcus, A., Meiselwitz, G., Moallem, A., Mori, H., Fui-Hoon Nah, F., Ntoa, S., Rau, P.-L. P., Schmorrow, D., Siau, K., Streitz, N., Wang, W., Yamamoto, S., Zaphiris, P., & Zhou, J. (2019). Seven HCI Grand Challenges. International Journal of Human–Computer Interaction, 35(14), 1229–1269. https://doi.org/10.1080/10447318.2019.1619259
  43. Sun, H. (2012). Cross-cultural technology design: Creating culture-sensitive technology for local users. OUP USA.
  44. Tao, L. (2024). HUMAN – COMPUTER INTERACTION IN VIRTUAL REALITY Інформатизація вищої освіти The main research materials. 112–117. https://doi.org/10.32347/2412-9933.2024.57.112-117
  45. Tulshan, A. S., & Dhage, S. N. (2019). Survey on Virtual Assistant: Google Assistant, Siri, Cortana, Alexa BT - Advances in Signal Processing and Intelligent Recognition Systems (S. M. Thampi, O. Marques, S. Krishnan, K.-C. Li, D. Ciuonzo, & M. H. Kolekar (eds.); pp. 190–201). Springer Singapore. https://doi.org/10.1007/978-981-13-5758-9_17
  46. Wang, D., Guo, Y., Liu, S., Zhang, Y., Xu, W., & Xiao, J. (2019). Haptic display for virtual reality: progress and challenges. Virtual Reality & Intelligent Hardware, 1(2), 136–162. https://doi.org/https://doi.org/10.3724/SP.J.2096-5796.2019.0008
  47. Wilhelm, A. G. (2006). Digital nation: Toward an inclusive information society. mit Press.
  48. Zulfiqar, F., Raza, R., Khan, M. O., Arif, M., Alvi, A., & Alam, T. (2023). Augmented Reality and its Applications in Education: A Systematic Survey. IEEE Access, 11, 143250–143271. https://doi.org/10.1109/ACCESS.2023.3331218