Contextualizing Plans: Aligning Students Goals and Plans During Game-Based Inquiry Science Learning

被引:0
|
作者
Wiedbusch, Megan [1 ]
Dever, Daryn [1 ]
Goslen, Alex [2 ]
Carpenter, Dan [2 ]
Marano, Cameron [1 ]
Smith, Kevin [1 ]
Azevedo, Roger [2 ]
机构
[1] Univ Cent Florida, Orlando, FL 32832 USA
[2] North Carolina State Univ, Raleigh, NC 27606 USA
来源
LEARNING AND COLLABORATION TECHNOLOGIES, PT II, LCT 2024 | 2024年 / 14723卷
基金
美国国家科学基金会;
关键词
Game-based learning; Goal Setting; Planning;
D O I
10.1007/978-3-031-61685-3_9
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A key aim for science education is the improvement of scientific reasoning through inquiry-based learning which asks students to "think and act like scientists". This requires the regulation of specific skills and abilities such as identifying problems, generating hypotheses and evidence, and drawing conclusions. Goal setting and planning can help learners regulate their learning as they engage with scientific inquiry, especially within investigative exploration. Contemporary work on scaffolds for science inquiry-learning requires we (1) understand how students set goals and plans, (2) measure the quality of goals and plans, and (3) develop adaptive intelligent goal and planning scaffolds. This paper presents the development of a new planning scaffold used by 101 middle school students during interactions with CRYSTAL ISLAND, a game-based learning environment designed to teach students about microbiology and through scientific inquiry. We map student goals and plans from the scaffold to a series of epistemic scientific reasoning activities to use in conjunction with online trace data of student behaviors to analyze student goal setting and planning constructed throughout the game. This study describes the development of an analytical mapping approach between (sub)goals and (sub)activities to measure student plan quality build using a planning scaffold. We report on the use of the scaffold as well as implications for future development of an adaptive and intelligent version of the tool. This work highlights that online-trace data should be contextualized to (sub)goals, and the design of intelligent and adaptive goal and planning tools should be dynamic to account for open-ended exploration that differs across learners.
引用
收藏
页码:113 / 128
页数:16
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