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1. Game Data for the Paint Fever game

   https://doi.org/10.6084/m9.figshare.24422308  

   Altay Turkoglu, Ayca Turkoglu (January 2023, figshare)

   Game data collected through the "Paint Fever" game generated at the GRIST Lab for NSF Project 1901721 

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2. Game redesign in no-regret game playing

   https://doi.org/10.24963/ijcai.2022/461  

   Ma, Yuzhe; Wu, Young; Zhu, Xiaojin (January 2022, The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence)
3. Game Dynamics as the Meaning of a Game

   Papadimitriou, Christos and (June 2018, SIGecom exchanges)
4. The Derby Game: An Ordering-based Colonel Blotto Game

   https://doi.org/10.1145/3490486.3538367  

   Gaonkar, Akash; Raghunathan, Divya; Weinberg, S. Matthew (July 2022, ACM Conference on Economics and Computation)
5. In-Game Actions to Promote Game-Based Math Learning Engagement

   https://doi.org/10.1177/0735633119878611  

   Moon, Jewoong; Ke, Fengfeng (September 2019, Journal of Educational Computing Research)

   Game-based learning (GBL) has increasingly been used to promote students’ learning engagement. Although prior GBL studies have highlighted the significance of learning engagement as a mediator of students’ meaningful learning, the existing accounts failed to capture specific evidence of how exactly students’ in-game actions in GBL enhance learning engagement. Hence, this mixed-method study was designed to examine whether middle school students’ in-game actions are likely to promote certain types of learning engagement (i.e., content and cognitive engagement). This study used and examined the game E-Rebuild, a single-player three-dimensional architecture game that requires learners’ application of math knowledge. Using in-depth gameplay behavior analysis, this study sampled a total of 92 screen-recorded and video-captured gameplay sessions attended by 25 middle school students. We adopted two analytic approaches: sequential analysis and thematic analysis. Whereas sequential analysis explored which in-game actions by students were likely to promote each type of learning engagement, the thematic analysis depicted how certain gameplay contexts contributed to students’ enhanced learning engagement. The study found that refugee allocation and material trading actions promoted students’ content engagement, whereas using in-game building tools and learning support boosted their cognitive engagement. This study also found that students’ learning engagement was associated with their development of mathematical thinking in a GBL context. 

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