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S. Wu, “The Development and Challenges of Computational Thinking Board Games,” 2018 1st International Cognitive Cities Conference (IC3), Okinawa, 2018, pp. 129-131.
Savvani S., Liapis A. (2019) A Participatory Approach to Redesigning Games for Educational Purposes. In: Liapis A., Yannakakis G., Gentile M., Ninaus M. (eds) Games and Learning Alliance. GALA 2019. Lecture Notes in Computer Science, vol 11899. Springer, Cham
Use of a board game format to promote interprofessional learning. Heather Schmucka, Mary KayArvinb
Peter Drake and Kelvin Sung. 2011. Teaching introductory programming with popular board games. In Proceedings of the 42nd ACM technical symposium on Computer science education (SIGCSE ’11). Association for Computing Machinery, New York, NY, USA, 619–624. DOI:https://doi.org/10.1145/1953163.1953338
Wang, H., Chen, W., & Sun, C. (2020). Play Teaches Learning?: A Pilot Study on How Gaming Experience Influences New Game Learning. In P. Isaias, & K. Blashki (Eds.), Interactivity and the Future of the Human-Computer Interface (pp. 147-168). Hershey, PA: IGI Global. doi:10.4018/978-1-7998-2637-8.ch008

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Kosa M., Spronck P. (2019) Towards a Tabletop Gaming Motivations Inventory (TGMI). In: Zagalo N., Veloso A., Costa L., Mealha Ó. (eds) Videogame Sciences and Arts. VJ 2019. Communications in Computer and Information Science, vol 1164. Springer, Cham
Sousa M., Bernardo E. (2019) Back in the Game. In: Zagalo N., Veloso A., Costa L., Mealha Ó. (eds) Videogame Sciences and Arts. VJ 2019. Communications in Computer and Information Science, vol 1164. Springer, Cham
Simons, A., Wohlgenannt, I., Weinmann, M. et al. Good gamers, good managers? A proof-of-concept study with Sid Meier’s Civilization. Rev Manag Sci (2020). https://doi.org/10.1007/s11846-020-00378-0

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Expectation Confirmation in Technology Use

abstract:
We propose a model to study expectation confirmation in information systems. The proposed model is based on the assimilation-contrast model and prospect theory, and suggests that both are needed to account for the magnitude and direction of the deviations between experiences and expectations. Using the technology acceptance model’s (TAM) primary construct—namely, perceived usefulness—expectations and experiences were conceptualized and operationalized to test our model. Data were collected in a field study from 1,113 participants at two points in time. Using polynomial modeling and response surface analysis, we demonstrated that our model offers a good explanation of the relationship among information systems expectations, experiences, and use. We discuss theoretical and practical implications.

http://isr.journal.informs.org/content/early/2011/06/16/isre.1110.0357.abstract