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1. Using Students’ Conceptual Models to Represent Understanding of Crosscutting Concepts in an NGSS-Aligned Curriculum Unit About Urban Water Runoff

   https://doi.org/10.1007/s10956-021-09911-6  

   Fick, Sarah J.; McAlister, Anne M.; Chiu, Jennifer L.; McElhaney, Kevin W. (March 2021, Journal of Science Education and Technology)

   null (Ed.)

   Recent science education reforms, as described in the Framework for K-12 Science Education (NRC, 2012), call for three-dimensional learning that engages students in scientific practices and the use of scientific lenses to learn science content. However, relatively little research at any grade level has focused on how students develop this kind of three-dimensional knowledge that includes crosscutting concepts. This paper aims to contribute to a growing knowledge base that describes how to engage students in three-dimensional learning by exploring to what extent elementary students represent the crosscutting concept systems and system models when engaged in the practice developing and using models as part of an NGSS-aligned curriculum unit. This paper answers the questions: How do students represent elements of crosscutting concepts in conceptual models of water systems? How do students’ representations of crosscutting concepts change related to different task-based scaffolds? To analyze students’ models, we developed and applied a descriptive coding scheme to describe how the students illustrated the flow of water. The results show important differences in how students represented system elements across models. Findings provide insight for the kinds of support that students might need in order to move towards the development of three-dimensional understandings of science content. 

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2. Examining how prior knowledge impacts students’ discussions and knowledge construction during computational model building

   https://doi.org/10.3102/IP.22.1891766  

   Snyder, C. (April 2022, Proceedings of the American Educational Research Association Annual Meeting)

   Student discussions have been shown to be beneficial to student learning (Chi & Wylie, 2014), however, the impact of prior knowledge on these discussions is not fully understood. In this research, we analyze students’ synchronous spoken discussions to study how prior knowledge impacted group discussions and knowledge construction while constructing computational models of 1D and 2D motion. We present a method for evaluating the impact of prior knowledge on student discussions and individual work. We illustrate this method through a case study analysis of two groups with students across a spectrum of prior knowledge. Our exploratory findings suggest that students with low prior knowledge greatly benefit from group discussions followed by individual model construction. 

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3. Developing Deliberate Practice for Learning Engineering Dynamics by Analyzing Students’ Mental Models

   Tang, Yan; Bai, Haiyan; Catrambone, Richard (June 2022, ASEE annual conference exposition)

   Practice plays a critical role in learning engineering dynamics. Typical practice in a dynamics course involves solving textbook problems. These problems can impose great cognitive load on underprepared students because they have not mastered constituent knowledge and skills required for solving whole problems. For these students, learning can be improved by being engaged in deliberate practice. Deliberate practice refers to a type of practice aimed at improving specific constituent knowledge or skills. Compared to solving whole problems requiring the simultaneous use of multiple constituent skills, deliberate practice is usually focused on one component skill at a time, which results in less cognitive load and more specificity. Contemporary theories of expertise development have highlighted the influence of deliberate practice (DP) on achieving exceptional performance in sports, music, and various professional fields. Concurrently, there is an emerging method for improving learning efficiency of novices by combining deliberate practice with cognitive load theory (CLT), a cognitive-architecture-based theory for instructional design. Mechanics is a foundation for most branches of engineering. It serves to develop problem-solving skills and consolidate understanding of other subjects, such as applied mathematics and physics. Mechanics has been a challenging subject. Students need to understand governing principles to gain conceptual knowledge and acquire procedural knowledge to apply these principles to solve problems. Due to the difficulty in developing conceptual and procedural knowledge, mechanics courses are among those that receive high DFW rates (percentage of students receiving a grade of D or F or Withdrawing from a course), and students are more likely to leave engineering after taking mechanics courses. Deliberate practice can help novices develop good representations of the knowledge needed to produce superior problem solving performance. The goal of the present study is to develop deliberate practice techniques to improve learning effectiveness and to reduce cognitive load. Our pilot study results revealed that the student mental effort scores were negatively correlated with their knowledge test scores with r = -.29 (p < .05) after using deliberate practice strategies. This supports the claim that deliberate practice can improve student learning while reducing cognitive load. In addition, the higher the students’ knowledge test scores, the lower their mental effort was when taking the tests. In other words, the students who used deliberate practice strategies had better learning results with less cognitive load. To design deliberate practice, we often need to analyze students’ persistent problems caused by faulty mental models, also referred to as an intuitive mental model, and misconceptions. In this study, we continue to conduct an in-depth diagnostic process to identify students’ common mistakes and associated intuitive mental models. We then use the results to develop deliberate practice problems aimed at changing students’ cognitive strategies and mental models. 

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4. Developing Deliberate Practice for Learning Engineering Dynamics by Analyzing Students’ Mental Models

   Tang, Yan; Bai, Haiyan; Catrambone, Richard (June 2022, ASEE annual conference exposition)

   Practice plays a critical role in learning engineering dynamics. Typical practice in a dynamics course involves solving textbook problems. These problems can impose great cognitive load on underprepared students because they have not mastered constituent knowledge and skills required for solving whole problems. For these students, learning can be improved by being engaged in deliberate practice. Deliberate practice refers to a type of practice aimed at improving specific constituent knowledge or skills. Compared to solving whole problems requiring the simultaneous use of multiple constituent skills, deliberate practice is usually focused on one component skill at a time, which results in less cognitive load and more specificity. Contemporary theories of expertise development have highlighted the influence of deliberate practice (DP) on achieving exceptional performance in sports, music, and various professional fields. Concurrently, there is an emerging method for improving learning efficiency of novices by combining deliberate practice with cognitive load theory (CLT), a cognitive-architecture-based theory for instructional design. Mechanics is a foundation for most branches of engineering. It serves to develop problem-solving skills and consolidate understanding of other subjects, such as applied mathematics and physics. Mechanics has been a challenging subject. Students need to understand governing principles to gain conceptual knowledge and acquire procedural knowledge to apply these principles to solve problems. Due to the difficulty in developing conceptual and procedural knowledge, mechanics courses are among those that receive high DFW rates (percentage of students receiving a grade of D or F or Withdrawing from a course), and students are more likely to leave engineering after taking mechanics courses. Deliberate practice can help novices develop good representations of the knowledge needed to produce superior problem solving performance. The goal of the present study is to develop deliberate practice techniques to improve learning effectiveness and to reduce cognitive load. Our pilot study results revealed that the student mental effort scores were negatively correlated with their knowledge test scores with r = -.29 (p < .05) after using deliberate practice strategies. This supports the claim that deliberate practice can improve student learning while reducing cognitive load. In addition, the higher the students’ knowledge test scores, the lower their mental effort was when taking the tests. In other words, the students who used deliberate practice strategies had better learning results with less cognitive load. To design deliberate practice, we often need to analyze students’ persistent problems caused by faulty mental models, also referred to as an intuitive mental model, and misconceptions. In this study, we continue to conduct an in-depth diagnostic process to identify students’ common mistakes and associated intuitive mental models. We then use the results to develop deliberate practice problems aimed at changing students’ cognitive strategies and mental models. 

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5. Examining the timing of metacognitive monitoring judgments in a game-based learning environment.

   Nietfeld, J. L. (March 2022, Proceedings from the Annual meeting of International, Technology, Education and Development Conference)

   The purpose of the current study was to analyze the impact of delayed monitoring judgments on both monitoring accuracy and science knowledge in a game-based learning environment called MISSING MONTY. Fifth-grade students from public schools in the USA were randomly assigned to either an immediate monitoring (IM) (n = 142) condition or to a delayed monitoring (DM) condition (n = 171). All students completed a pre and posttest of science knowledge and made item-level confidence judgments on each test. The students then played MISSING MONTY for approximately 2-5 weeks depending upon class schedule. During gameplay students visited various animal researchers, read informational texts, and completed knowledge and monitoring challenges. In the IM condition, students rated their confidence on a 100-point scale immediately following each item. In the DM condition, the students first completed the knowledge challenge and then provided monitoring judgments following the completion of all items. Results showed significant improvements for science knowledge and monitoring accuracy for both groups, however no significant differences were found between the two conditions Thus, MISSING MONTY appeared to have positive effects on both resultant science knowledge and monitoring accuracy regardless of when monitoring was assessed. Implications for the design of learning environments and SRL will be discussed. 

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