• Andalibi, N., Buss, J.: The human in emotion recognition on social media: attitudes, outcomes, risks. In: Conference on Human Factors in Computing Systems – Proceedings, 1–16 (2020).https://doi.org/10.1145/3313831.3376680

• Beńitez-Guerrero, E., Mezura-Godoy, C., Montańe-Jiḿenez, L.G.: Context-aware mobile collaborative systems: conceptual modeling and case study. Sensors (Switzerland)12(10), 13491–13507 (2012).https://doi.org/10.3390/s121013491

  Article  Google Scholar 

• BibExcel (n.d.).https://homepage.univie.ac.at/juan.gorraiz/bibexcel/

• Bradley, N.A., Dunlop, M.D.: Toward a multidisciplinary model of context to support context-aware computing. Hum.-Comput. Interact.20(4), 403–446 (2005).https://doi.org/10.1207/s15327051hci2004_2

  Article  Google Scholar 

• Chen, Z., He, Q., Liu, L., Lan, D., Chung, H.M., Mao, Z.: An artificial intelligence perspective on mobile edge computing. In: Proceedings – 2019 IEEE International Conference on Smart Internet of Things, SmartIoT 2019, pp. 100–106 (2019).https://doi.org/10.1109/SmartIoT.2019.00024

• Cheng, S., Liu, Y.: Eye-tracking based adaptive user interface: implicit human-computer interaction for preference indication. J. Multimodal User Interfaces5(1–2), 77–84 (2012).https://doi.org/10.1007/s12193-011-0064-6

  Article  Google Scholar 

• CiteSpace: (n.d.)http://cluster.cis.drexel.edu/~cchen/citespace/

• Daily, S.B., et al.: Affective Computing: Historical Foundations, Current Applications, and Future Trends, pp. 213–231 (2017).https://doi.org/10.1016/B978-0-12-801851-4.00009-4

• Edward, L., Lourdeaux, D., Barthès, J.P.: Cognitive modeling of virtual autonomous intelligent agents integrating human factors. In: Proceedings – 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology – Workshops, WI-IAT Workshops 2009, vol. 3, pp. 353–356 (2009).https://doi.org/10.1109/WI-IAT.2009.300

• Eyben, F., et al.: Emotion on the road-necessity, acceptance, and feasibility of affective computing in the car. Adv. Human-Comput. Interact.2010, 263593 (2010).https://doi.org/10.1155/2010/263593

  Article  Google Scholar 

• Gruson, D., Helleputte, T., Rousseau, P., Gruson, D.: Data science, artificial intelligence, and machine learning: Opportunities for laboratory medicine and the value of positive regulation. Clin. Biochem.69(April), 1–7 (2019).https://doi.org/10.1016/j.clinbiochem.2019.04.013

  Article  Google Scholar 

• Ho, J., Intille, S.S.: Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In: CHI 2005: Technology, Safety, Community: Conference Proceedings – Conference on Human Factors in Computing Systems, pp. 909–918 (2005).https://doi.org/10.1145/1054972.1055100

• Jiang, Y., et al.: Computational approaches for understanding, generating, and adapting user interfaces. In: Conference on Human Factors in Computing Systems – Proceedings (2022).https://doi.org/10.1145/3491101.3504030

• Kanade, S.G., Duffy, V.G.: A Systematic literature review of game-based learning and safety management. In: Duffy, V.G. (ed.) HCII 2020. LNCS, vol. 12199, pp. 365–377. Springer, Cham (2020).https://doi.org/10.1007/978-3-030-49907-5_26

  Chapter  Google Scholar 

• Kanade, S.G., Duffy, V.G.: Use of virtual reality for safety training: a systematic review. In: Duffy, V.G. (eds.) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Health, Operations Management, and Design. HCII 2022. Lecture Notes in Computer Science, vol. 13320. Springer, Cham (2022).https://doi.org/10.1007/978-3-031-06018-2_25

• Li, H., Jyri, S., Jian, M., Kuifei, Y.: Research on context-aware mobile computing. In: Proceedings – International Conference on Advanced Information Networking and Applications, AINA, pp. 24–30 (2008).https://doi.org/10.1109/WAINA.2008.115

• Lin, P., Van Brummelen, J.: Engaging teachers to co-design integrated ai curriculum for k-12 classrooms. In: Conference on Human Factors in Computing Systems – Proceedings (2021).https://doi.org/10.1145/3411764.3445377

• Lindley, J., Akmal, H.A., Pillling, F., Coulton, P.: Researching AI legibility through design. In: Conference on Human Factors in Computing Systems – Proceedings, pp. 1–13 (2020).https://doi.org/10.1145/3313831.3376792

• Long, D., Magerko, B.: What is AI literacy? competencies and design considerations. In: Conference on Human Factors in Computing Systems – Proceedings, pp. 1–16 (2020).https://doi.org/10.1145/3313831.3376727

• Salvendy, G., Karwowski, W.: Handbook of human factors and ergonomics. In: Handbook of Human Factors and Ergonomics (2021).https://doi.org/10.1002/9781119636113

• Tolmeijer, S., Christen, M., Kandul, S., Kneer, M., Bernstein, A.: Capable but amoral? comparing AI and human expert collaboration in ethical decision making. In: Conference on Human Factors in Computing Systems – Proceedings (2022).https://doi.org/10.1145/3491102.3517732

• Van Maanen, P.P., Lindenberg, J., Neerincx, M.A.: Integrating human factors and artificial intelligence in the development of human-machine cooperation. In: Proceedings of the 2005 International Conference on Artificial Intelligence, ICAI’05, 1(May 2014), pp. 10–16 (2005)

  Google Scholar 

• VOSviewer (n.d.).https://www.vosviewer.com/

• Wang, D., Churchill, E., Maes, P., Fan, X., Shneiderman, B., Shi, Y., Wang, Q.: From human-human collaboration to Human-AI collaboration: Designing AI systems that can work together with people. In: Conference on Human Factors in Computing Systems – Proceedings, pp. 1–6 (2020).https://doi.org/10.1145/3334480.3381069

• Wang, D., Yang, Q., Abdul, A., Lim, B.Y.: Designing theory-driven user-centric explainable AI. In: Conference on Human Factors in Computing Systems – Proceedings, 1–15 (2019).https://doi.org/10.1145/3290605.3300831

• Woolf, B., Arroyo, I., Lan, A., Garn, M., Dede, C.: Data-Directed Education: The Future of AI in Education (2022)

  Google Scholar 

• Yang, Q., Steinfeld, A., Rosé, C., Zimmerman, J.: Re-examining whether, why, and how human-ai interaction is uniquely difficult to design. In: Conference on Human Factors in Computing Systems – Proceedings, pp. 1–13 (2020).https://doi.org/10.1145/3313831.3376301

• Zolyomi, A., Snyder, J.: Social-emotional-sensory design map for affective computing informed by neurodivergent experiences. Proc. ACM on Hum.-Comput. Interact.5(CSCW1), 1–37 (2021).https://doi.org/10.1145/3449151

  Article  Google Scholar 

Download references