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.
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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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