| dc.description.abstract | Recently there has been a call among researchers, practitioners, and policymakers for the integration of science and engineering education in K-12 curricula. Similarly, computational thinking (CT) has been recognized as a framework for developing computer literacy and computing skills among the Science, Technology, Engineering, and Mathematics (STEM) communities. Meanwhile, open-ended learning environments (OELEs) and artificial intelligence methods are being used extensively to facilitate meaningful and personalized learning. This study investigates the effectiveness of an OELE to support middle school students’ integrated learning of science, engineering, and CT. Using a principled domain-specific modeling language, we designed and implemented an OELE and an earth sciences curriculum that supports this form of integrated learning. CT concepts and practices are instantiated through computational modeling activities, where students build computational models of the runoff phenomenon in urban environments and then use the developed models to solve an engineering task of designing a schoolyard to minimize water runoff while also satisfying the design criteria of cost and accessibility.
A teacher-led classroom study was run with 99 sixth-grade students, and the data collected consists of students’ summative and formative assessments, as well as log data of their activities on the OELE. Our results show that (1) the participants achieved significant learning gains in science, engineering design, and CT concepts and practices; (2) the participants’ learning behaviors and performance across different domains influenced each other in a positive way; and (3) the participants’ learning strategies can be linked to their learning performances. This work has made important advances to integrated science and engineering education. In future work, we plan to extend this curriculum and provide feedback within the OELE to help students become better learners. | |
