Motivation plays a key role in effective learning but motivation needs to be sustained through feedback responses, reflection, and active involvement in order for learning to take place. This work focuses on incorporating active methods of teaching such as game-based learning and simulation-based learning. Game theme-based instructional (GTI) modules produce better results than traditional learning techniques because it increases motivation and engagement of students as they learn interactively. This work is aimed at assessing the motivation and engagement of undergraduate students for GTI modules in introductory data structure courses. This paper discusses the design, implementation, and evaluation of a GTI module to teach the linked list and binary tree data structure. For the design and development of GTI modules, we have incorporated FDF (four-dimensional framework) and constructive approach for learning. The GTI modules were evaluated based on the five components of the Science Motivation Questionnaire II (SMQII). We have also performed an ANOVA test for evaluating the motivation based on familiarity with other virtual reality games and the t-test for evaluating the motivation of students when they use GTI modules as a learning tool. The results of the evaluation of GTI modules shows that instructional modules can efficiently promote learning by encouraging the students’ participation.
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“The role of achievement goal orientation on metacognitive processes in game-based learning.”
Abstract. To examine relations between achievement goal orientation—a construct of motivation, metacognition and learning, multiple data channels were collected from 58 students while problem solving in a game-based learning environment. Results suggest students with different goal orientations use metacognitive processes differently but found no differences in learning. Findings have implications for measuring motivation using multiple data channels to design adaptive game-based learning environments.
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- Award ID(s):
- 1761178
- NSF-PAR ID:
- 10106711
- Date Published:
- Journal Name:
- International Conference on Artificial Intelligence in Education
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Motivation plays a key role in effective learning but motivation needs to be sustained through feedback responses, reflection, and active involvement in order for learning to take place. This work focuses on incorporating active methods of teaching such as game-based learning and simulation-based learning. Game theme-based instructional (GTI) modules produce better results than traditional learning techniques because it increases motivation and engagement of students as they learn interactively. This work is aimed at assessing the motivation and engagement of undergraduate students for GTI modules in introductory data structure courses. This paper discusses the design, implementation, and evaluation of a GTI module to teach the linked list and binary tree data structure. For the design and development of GTI modules, we have incorporated FDF (four-dimensional framework) and constructive approach for learning. The GTI modules were evaluated based on the five components of the Science Motivation Questionnaire II (SMQII). We have also performed an ANOVA test for evaluating the motivation based on familiarity with other virtual reality games and the t-test for evaluating the motivation of students when they use GTI modules as a learning tool. The results of the evaluation of GTI modules shows that instructional modules can efficiently promote learning by encouraging the students’ participation.more » « less
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This Work-in-Progress paper focuses on the qualitative aspects of a larger mixed-methods study about GeoExplorer, a game-based learning aspect of a mixed reality educational environment where students participate in a mock internship with the goal to complete a geotechnical mission involving Cone Penetration Testing, a civil engineering field technique students traditionally get very little exposure to due to its complexity and cost. This work seeks to understand how mixed reality learning environments, specifically game-based learning, support (i) creation of individualized hands-on learning opportunities, particularly during the pandemic-driven remote learning paradigm, and (ii) students' development along various noncognitive axes - confidence and motivation. Methods of narrative analyses and grounded theory are used to identify emergent themes in interviews with 10 undergraduate civil engineering students who experienced GeoExplorer in their required geotechnical engineering courses. Our preliminary findings indicate that the GeoExplorer activity was perceived by students as a novel learning experience, particularly welcomed in a time of remote learning, that motivates them to engage more with content and creates individualized hands-on experiences. Students describe how the activity affects their perceived confidence, often gendered, regarding their ability to perform civil engineering fieldwork. Further analyses of these findings may shed light on the ways in which mixed reality learning environments support equitable learning opportunities for all students.more » « less
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null (Ed.)Effective gamification can only be based on understanding the relationship between learner motivation and the game elements which are used to gamify learning activities. Although frequently mentioned, Virtual Currency (VC) remains underused and scarcely studied in educational gamification. As a motivational affordance, VC can be thought of as supporting different types of motivation, but currently, there is a lack of empirical studies which investigate this. Recognizing this gap, the purpose of our study was to empirically investigate whether and how gamifying learning activities with virtual currency can engender motivation for out-of-class practicing and what type of motivation. In the limited research others have conducted, VC has been studied largely in combination with other game elements, which does not allow reaching reliable conclusions about the impact of the individual elements. For this reason, we studied the effects of VC in a gamified Discrete Math course isolated from other game elements. The study showed that using VC to gamify practicing increased students’ practicing activity, which resulted in improved academic performance. The study also revealed that while gamified practicing did not increase students’ intrinsic motivation, it supported internalization of motivation towards this learning activity.more » « less
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Self-regulated learning conducted through metacognitive monitoring and scientific inquiry can be influenced by many factors, such as emotions and motivation, and are necessary skills needed to engage in efficient hypothesis testing during game-based learning. Although many studies have investigated metacognitive monitoring and scientific inquiry skills during game-based learning, few studies have investigated how the sequence of behaviors involved during hypothesis testing with game-based learning differ based on both efficiency level and emotions during gameplay. For this study, we analyzed 59 undergraduate students’ (59% female) metacognitive monitoring and hypothesis testing behavior during learning and gameplay with CRYSTAL ISLAND, a game-based learning environment that teaches students about microbiology. Specifically, we used sequential pattern mining and differential sequence mining to determine if there were sequences of hypothesis testing behaviors and to determine if the frequencies of occurrence of these sequences differed between high or low levels of efficiency at finishing the game and high or low levels of facial expressions of emotions during gameplay. Results revealed that students with low levels of efficiency and high levels of facial expressions of emotions had the most sequences of testing behaviors overall, specifically engaging in more sequences that were indicative of less strategic hypothesis testing behavior than the other students, where students who were more efficient with both levels of emotions demonstrated strategic testing behavior. These results have implications for the strengths of using educational data mining techniques for determining the processes underlying patterns of engaging in self-regulated learning conducted through hypothesis testing as they unfold over time; for training students on how to engage in the self-regulation, scientific inquiry, and emotion regulation processes that can result in efficient gameplay; and for developing adaptive game-based learning environments that foster effective and efficient self-regulation and scientific inquiry during learning.more » « less
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