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We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

To support teachers in providing all students with opportunities to engage in engineering learning activities, research must examine the ways that elementary teachers support how diverse learners engage with engineering ideas and practices. This study focuses on two teachers' verbal supports in classroom discussions across two class sections of a four-week, NGSS-aligned unit that challenged students to redesign their school to reduce water runoff. We examine the research question: How and to what extent do upper-elementary teachers verbally support students' engagement with engineering practices across diverse classroom contexts in an NGSS-aligned integrated science unit? Classroom audio data was collected daily and coded to analyze support through different purposes of teacher talk. Results reveal the purpose of teachers’ talk often varied between the class sections depending on the instructional activity and indicate that teachers utilized a variety of supports toward students' engagement in different engineering practices. In one class, with a large percentage of students with individualized educational plans, teachers provided more epistemic talk about the engineering practices to contextualize the particular activities. For the other class, with a large percentage of students in advanced mathematics, teachers provided more opportunities for students to engage in discussion and support for students to do engineering. This difference in supports may decrease the opportunities for some students to rigorously engage in engineering ideas and practices. This study can inform future research on the kinds of educative supports needed to guide teaching of integrated engineering activities for diverse students. 

Computational Thinking (CT) can play a central role in fostering students' integrated learning of science and engineering. We adopt this framework to design and develop the Water Runoff Challenge (WRC) curriculum for lower middle school students in the USA. This paper presents (1) the WRC curriculum implemented in an integrated computational modeling and engineering design environment and (2) formative and summative assessments used to evaluate learner’s science, engineering, and CT skills as they progress through the curriculum. We derived a series of performance measures associated with student learning from system log data and the assessments. By applying Path Analysis we found significant relations between measures of science, engineering, and CT learning, indicating that they are mutually supportive of learning across these disciplines. 

This paper analyzes students’ design solutions for an NGSS aligned earth sciences curriculum, the Playground Design Challenge (PDC), for upper-elementary school (grade 5 and 6) students.We present the underlying computational model and the user interface for generating design solutions for a school playground that has to meet cost, water runoff, and accessibility constraints. We use data from the pretest and posttest assessments and activity logs collected from a pilot study run in an elementary school to evaluate the effectiveness of the curriculum and investigate the relations between students’ behaviors and their learning performances. The results show that (1) the students’ scores significantly increased from pretest to posttest on engineering design assessments, and (2) students’ solution-generation and testing behaviors were indicative of the quality of their design solutions as well as their pre-post learning gains. In the future, tracking such behaviors online will allow us to provide adaptive scaffolds that help students improve on their engineering design solutions. 

There is increasing interest in broadening participation in computational thinking (CT) by integrating CT into pre-college STEM curricula and instruction. Science, in particular, is emerging as an important discipline to support integrated learning. This highlights the need for carefully designed assessments targeting the integration of science and CT to help teachers and researchers gauge students’ proficiency with integrating the disciplines. We describe a principled design process to develop assessment tasks and rubrics that integrate concepts and practices across science, CT, and computational modeling. We conducted a pilot study with 10 high school students who responded to integrative assessment tasks as part of a physics-based computational modeling unit. Our findings indicate that the tasks and rubrics successfully elicit both Physics and CT constructs while distinguishing important aspects of proficiency related to the two disciplines. This work illustrates the promise of using such assessments formatively in integrated STEM and computing learning contexts.