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Building on the promise shown in game-based learning research, this paper explores methods for Game-Based Learning Assessments (GBLA) using a variety of educational data mining techniques (EDM). GBLA research examines patterns of behaviors evident in game data logs for the measurement of implicit learning—the development of unarticulated knowledge that is not yet expressible on a test or formal assessment. This paper reports on the study of two digital games showing how the combination of human coding with EDM has enabled researchers to measure implicit learning of Physics. In the game Impulse, researchers combined human coding of video with educational data mining to create a set of automated detectors of students' implicit understanding of Newtonian mechanics. For Quantum Spectre, an optics puzzle game, human coding of Interaction Networks was used to identify common student errors. Findings show that several of our measures of student implicit learning within these games were significantly correlated with improvements in external postassessments. Methods and detailed findings were different for each type of game. These results suggest GBLA shows promise for future work such as adaptive games and in-class, data-driven formative assessments, but design of the assessment mechanics must be carefully crafted for each game.

This paper reports on a research study of 45 classes in US schools (grades 3–8) using Zoombinis, a popular Computational Thinking (CT) learning game for ages 8 to adult. The study examined the relationship among student gameplay, related classroom activity, and the development of students’ CT practices in Zoombinis classes. A combination of research methods, including educational data-mining on game data logs, cluster analysis on teacher logs of classroom activity, and multilevel modeling, was used to determine the impact of the duration and nature of student gameplay, as well as the extent and nature of classroom activity, on student CT practices. Automated detectors of gameplay CT practices built for this research were significant predictors of external post-assessment scores, and thus show promise as implicit assessments of CT practices within gameplay. Students with high duration of gameplay and high gameplay CT practices scored highest on external post-assessment of CT practices, when accounting for pre-assessment scores. This research suggests that Zoombinis is an effective CT learning tool and CT assessment tool for elementary- and middle-school students.

In this paper, we investigate the impact of flow (operationalized as heightened challenge and skill), engagement, and immersion on learning in game-based learning environments. The data was gathered?through a survey from players (N?=?173) of two learning games (Quantum Spectre: N?=?134 and?Spumone: N?=?40). The results show that engagement in the game has a clear positive effect on learning, however, we did not find a significant effect between immersion in the game and learning. Challenge of the game had a positive effect on learning both directly and via the increased engagement. Being skilled in the game did not affect learning directly but by increasing engagement in the game. Both?the challenge of the game and being skilled in the game had a positive effect on both being engaged and immersed in the game. The challenge in the game was an especially strong predictor of learning outcomes. For the design of educational games, the results suggest that the challenge of the game should be able to keep up with the learners growing abilities and learning in order to endorse continued learning in game-based learning environments. Engagement in the game has a positive effect on learning.Immersion in the game does not have a significant effect on learning.Challenge affected learning both directly and via the increased engagement.Skill did not affect learning directly but only via the increased engagement.Perceived challenge was an especially strong predictor of learning outcomes.

Preference for and competence in problem-solving predicted science understanding.Preference for science-related features predicted teens' science understanding.Teens with a stronger science identity negatively evaluated their gaming groups.Competence in games with science-related features predicted science identity.Science games may reinforce self-efficacy and competence in scientific reasoning. This study explored the relationships between identity, science learning, and gaming. A survey of 1502 teenagers assessed gaming preferences, habits, science learning, science and gamer identities. Hierarchical regression analyses revealed that enjoyment of problem-solving games and identifying as a gamer were the strongest predictors for teens' science understanding. Teen preferences for games with science-related features, and competence in problem-solving games were significant predictors of teens' understanding of science. Teens who preferred collaborative social games over science-oriented games were less likely to understand the nature of science. Teens with a stronger science identity were more likely to negatively evaluate their gaming groups, preferred problem-solving games, and claimed greater competence in games with science-related features when compared to those who do not self-identify as science thinkers. Results suggest that games that seek to support those who do not feel successful in science learning should focus on social interaction and involve activities and experiences that could be utilized in the real world rather than problem solving games. Results suggest that science-focused games may reinforce perceived self-efficacy and sense of competence in real world scientific reasoning situations for those already predisposed to feel confident as science thinkers.