Extracting an individual’s knowledge structure is a challenging task as it requires formalization of many concepts and their interrelationships. While there has been significant research on how to represent knowledge to support computational design tasks, there is limited understanding of the knowledge structures of human designers. This understanding is necessary for comprehension of cognitive tasks such as decision making and reasoning, and for improving educational programs. In this paper, we focus on quantifying theory-based causal knowledge, which is a specific type of knowledge held by human designers. We develop a probabilistic graph-based model for representing individuals’ concept-specific causal knowledge for a given theory. We propose a methodology based on probabilistic directed acyclic graphs (DAGs) that uses logistic likelihood function for calculating the probability of a correct response. The approach involves a set of questions for gathering responses from 205 engineering students, and a hierarchical Bayesian approach for inferring individuals’ DAGs from the observed responses. We compare the proposed model to a baseline three-parameter logistic (3PL) model from the item response theory. The results suggest that the graph-based logistic model can estimate individual students’ knowledge graphs. Comparisons with the 3PL model indicate that knowledge assessment is more accurate when quantifying knowledge at the level of causal relations than quantifying it using a scalar ability parameter. The proposed model allows identification of parts of the curriculum that a student struggles with and parts they have already mastered which is essential for remediation.
Impact of blended immersive virtual world and programming curriculum on student perspectives about scientific modeling
EcoMOD uses a design-based research approach to develop and study an elementary curriculum that combines an immersive virtual environment with interactive computer programming interface to support computational modeling, ecosystem science understanding, and causal reasoning. Here we report on changes in students’ perspectives on modeling before and after use of the fifteen day interactive, technology-based curriculum in a 3rd and 4th grade classroom. Pre-post interviews were conducted with ten students, and preliminary results suggest that students demonstrated an increased awareness that models are designed for a purpose, and the purposes students described aligned more closely with scientifically relevant activities like prediction, investigation and explanation. Students also increased in their level of sophistication related to ecosystem science understanding and causal reasoning.
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- Award ID(s):
- 1639545
- NSF-PAR ID:
- 10212784
- Date Published:
- Journal Name:
- Annual meeting program American Educational Research Association
- ISSN:
- 0163-9676
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)more » « less
Abstract -
Extracting an individual’s knowledge structure is a challenging task as it requires formalization of many concepts and their interrelationships. While there has been significant research on how to represent knowledge to support computational design tasks, there is limited understanding of the knowledge structures of human designers. This understanding is necessary for comprehension of cognitive tasks such as decision making and reasoning, and for improving educational programs. In this paper, we focus on quantifying theory-based causal knowledge, which is a specific type of knowledge held by human designers. We develop a probabilistic graph-based model for representing individuals’ concept-specific causal knowledge for a given theory. We propose a methodology based on probabilistic directed acyclic graphs (DAGs) that uses logistic likelihood function for calculating the probability of a correct response. The approach involves a set of questions for gathering responses from 205 engineering students, and a hierarchical Bayesian approach for inferring individuals’ DAGs from the observed responses. We compare the proposed model to a baseline three-parameter logistic (3PL) model from the item response theory. The results suggest that the graph-based logistic model can estimate individual students’ knowledge graphs. Comparisons with the 3PL model indicate that knowledge assessment is more accurate when quantifying knowledge at the level of causal relations than quantifying it using a scalar ability parameter. The proposed model allows identification of parts of the curriculum that a student struggles with and parts they have already mastered which is essential for remediation.more » « less
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null (Ed.)Spatial reasoning skills contribute to performance in many STEM fields. For example, drawing sectional views of three-dimensional objects is an essential skill for engineering students. There is considerable variation in the spatial reasoning skills of prospective engineering students, putting some at risk for compromised performance in their classes. This study takes place in a first-year engineering Spatial Visualization course to integrate recent practices in engineering design education with cognitive psychology research on the nature of spatial learning. We employed three main pedagogical strategies in the course - 1) in class instruction on sketching; 2) spatial visualization training; and 3) manipulation of physical objects (CAD/3D print creations). This course endeavors to use current technology, online accessibility, and implementation of the three pedagogical strategies to bring about student growth in spatial reasoning. This study is designed to determine the effect of adding two different spatial reasoning training apps to this environment. Over 230 students (three sections) participated in our study. In two of the three sections, students received interactive spatial visualization training using either a spatial visualization mobile touchscreen app in one section or an Augmented Reality (AR) app in the other section. Research suggests that there are benefits to using the Spatial Vis Classroom mobile app for college students.The app has been shown to increase student persistence resulting in large learning gains as measured by the Purdue assessment of spatial visualization (PSVT-R), especially for students starting with poor spatial visualization skills. The Spatial Vis Classroom app can be used in the classroom or assigned as homework. The AR app is designed to help users develop their mental rotation abilities. It is designed to support a holistic understanding of 3-dimensional objects, and research has shown that, in combination with a traditional curriculum, it increases students’ abilities also measured by the PSVT-R. Of particular interest, the data suggest that the app overcomes the advantage found by males over females in a traditional class alone focused on spatial reasoning. Both of the course sections were required to use the apps for approximately the same time in class and outside of class. Students in the control section were required to do hand sketching activities in class and outside of class, with roughly the same completion time as for the sections with the apps. Students grades were not affected by using the three different approaches as grading was based on completion only. Based on current literature, we hypothesize that overall benefits (PSVT-R gains) will be comparable across the 3 treatments but there will be different effects on attitude and engagement (confidence,enjoyment, and self-efficacy). Lastly, we hypothesize that the treatments will have different effects on male/female and ethnic categories of the study participants. The final paper will include an analysis of results and a report of the findings.more » « less
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This paper discusses our work in progress aiming to explore how computer simulations can be integrated into the K-12 curriculum of Earth and Environmental science. Several interactive simulations using Netlogo, a multi-agent modeling environment, and Scratch, a visual programming software are being developed with steerable parameters and the corresponding output plots for students to manipulate and interpret the results, respectively. Here, we present two simulations we designed on water cycle and discuss how these may help students learn about the distribution of water and its continuous move in the ecosystem.more » « less
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null (Ed.)Integrating computational thinking and scientific modeling in elementary school is challenging, but provides opportunities to meet important 21st century learning goals. Furthermore, computational modeling deepens the level of understanding of the modeling process and the phenomena being modeled, making science content more accessible. This paper presents findings from EcoMOD, a research project that blends an immersive virtual ecosystem and a 2D modeling environment to support computational modeling and ecosystem science learning in 3rd grade. As part of the study, students filled out pre- and post- surveys about science content understanding, affective measures, and scientific modeling. Findings for the overall student gains across the three dimensions of the surveys suggest that the EcoMOD curriculum was effective in learning ecosystem science content and practice, as well as developing an understanding of the value of computational modeling.more » « less
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