Uncovering the productivity in critical thinking during Science, Technology, Engineering, and Mathematics (STEM) education through the use of game-based learning, employing sequence mining techniques
In a recent study, the efficiency of game completion in adaptive game-based learning environments, specifically Crystal Island, was evaluated[1]. Crystal Island is an educational game designed to engage learners in scientific inquiry through problem-solving tasks embedded within the gameplay.
The research focused on metacognitive monitoring and scientific reasoning, two key cognitive processes that significantly influence the efficiency of game completion. Metacognitive monitoring refers to learners' awareness and regulation of their own thinking processes during gameplay, such as monitoring understanding, strategies, and task progress[2]. Effective metacognitive monitoring allows players to identify when they do not understand a concept or approach, prompting them to adjust their strategies, seek help, or review information, leading to more efficient navigation of the game’s challenges and faster completion times.
Scientific reasoning, on the other hand, involves the ability to formulate hypotheses, design experiments, interpret data, and draw conclusions. Crystal Island specifically targets these skills by embedding scientific inquiry tasks directly into its narrative and gameplay. Strong scientific reasoning skills enable learners to progress more efficiently as they can better synthesize information and make sound decisions within the game context.
The study aimed to understand participants' hypothesis testing behavior using sequential pattern mining and differential sequence mining[1]. The findings suggest that more efficient participants had significantly lower instance support values of the PartiallyRelevant-Relevant to Relevant-Relevant and PartiallyRelevant-PartiallyRelevant to Relevant-Partially Relevant sequences compared to less efficient participants[1]. This implies that efficient participants tested significantly fewer partially-relevant and irrelevant items than less efficient participants.
The study's results have implications for designing adaptive game-based learning environments that scaffold participants based on in-game behaviors. By tailoring challenges based on the learner’s current skills, these environments can foster deeper cognitive engagement, leading to more efficient game completion and potentially, deeper learning outcomes.
While the study does not discuss the impact of the findings on student engagement or overall learning outcomes, it underscores the importance of metacognitive monitoring and scientific reasoning in navigating complex educational games adaptively and effectively. The study involved 64 undergraduate participants, and the data was analysed from log files using sequence mining[1].
In conclusion, the study highlights the significant role of metacognitive monitoring and scientific reasoning in enhancing adaptive learning environments. By promoting self-regulation and effective scientific reasoning, learners can complete educational games like Crystal Island more efficiently, leading to potentially deeper learning outcomes.
[1] References not provided in the bullet points.
In the study of adaptive game-based learning environments, such as Crystal Island, emphasis was placed on education-and-self-development skills like metacognitive monitoring and scientific reasoning, critical for learning in STEM-education. Effective metacognitive monitoring and strong scientific reasoning allowed participants to learn more efficiently, leading to faster completion times and potentially, deeper learning outcomes.
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