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1. Scaffolding Evidence-Based Reasoning in a Technology Supported Engineering Design Activity

   Rebello, C.M. (January 2019, The 13th Conference of the European Science Education Research Association (ESERA))

   Engineering Design (ED) challenges are increasingly used as a context to learn science. Research shows that there is a need for strategies that facilitate learners to identify, apply, and reflect on ways scientific principles can inform creation and evaluation of ED solutions. We investigate the use of contrasting cases and argumentation scaffolds to facilitate use of evidence-based reasoning in a CAD supported ED tasks. Elementary education majors in a physics course analyzed solutions to an ED problem in two conditions: 1) identify similarities and differences, 2) evaluate and produce an argument for a “good” design solution. We found that the argumentation condition used scientific evidence-based reasoning significantly more frequently in their responses than the control. Results indicate that the contrasting cases with argumentation scaffolds shows promise in facilitating students’ use of evidence-based reasoning in their ED tasks. 

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2. A Simple Extension of Answer Set Programs to Embrace Neural Networks (Extended Abstract)

   https://doi.org/10.4204/EPTCS.325  

   Yang, Zhun; Ishay, Adam; Lee, Joohyung (September 2020, Electronic proceedings in theoretical computer science)

   Ricca, Francesco et (Ed.)

   The integration of low-level perception with high-level reasoning is one of the oldest problems in Artificial Intelligence. Today, the topic is revisited with the recent rise of deep neural networks. However, it is still not clear how complex and high-level reasoning, such as default reasoning, ontology reasoning, and causal reasoning, can be successfully computed by these approaches. The latter subject has been well-studied in the area of knowledge representation (KR), but many KR formalisms, including answer set programming (ASP), are logic-oriented and do not incorporate high-dimensional feature space as in deep learning, which limits the applicability of KR in many practical applications. 

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3. Examining the Literacy Practices of Electrical Engineers: A Comparative Case Study

   Green, T.; Wilson-Lopez, A.; Minichiello, A. (April 2019, American Education Research Association (AERA) Annual Meeting)

   This study, part of a larger research project focused on disciplinary literacy within engineering (Authors, 2018), is a comparative case study of the literacy practices of two electrical engineers. The goal of this comparative case study was to understand how electrical engineers read, write, and evaluate multi-representational texts in the context of their professional lives. We used the findings from this study to construct a model of disciplinary literacy in electrical engineering, whose purpose is to prepare students for the electrical engineering workforce by teaching them to interpret and produce texts using authentic disciplinary frameworks. This paper examines the literacy practices of two electrical engineers to answer the following research questions: (1) What texts do the electrical engineers read and write? (2) What disciplinary frameworks do they use to read and write different texts? (3) How do engineers use internet searches to locate and evaluate information? (4) What role does argumentation have with respect to their literacy practices? 

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4. Analyzing teacher supports for collective argumentation in integrative STEM classrooms.

   Welji, S. (June 2022, ASEE annual conference)

   The Next Generation Science Standards [1] recognized evidence-based argumentation as one of the essential skills for students to develop throughout their science and engineering education. Argumentation focuses students on the need for quality evidence, which helps to develop their deep understanding of content [2]. Argumentation has been studied extensively, both in mathematics and science education but also to some extent in engineering education (see for example [3], [4], [5], [6]). After a thorough search of the literature, we found few studies that have considered how teachers support collective argumentation during engineering learning activities. The purpose of this program of research was to support teachers in viewing argumentation as an important way to promote critical thinking and to provide teachers with tools to implement argumentation in their lessons integrating coding into science, technology, engineering, and mathematics (which we refer to as integrative STEM). We applied a framework developed for secondary mathematics [7] to understand how teachers support collective argumentation in integrative STEM lessons. This framework used Toulmin’s [8] conceptualization of argumentation, which includes three core components of arguments: a claim (or hypothesis) that is based on data (or evidence) accompanied by a warrant (or reasoning) that relates the data to the claim [9], [8]. To adapt the framework, video data were coded using previously established methods for analyzing argumentation [7]. In this paper, we consider how the framework can be applied to an elementary school teacher’s classroom interactions and present examples of how the teacher implements various questioning strategies to facilitate more productive argumentation and deeper student engagement. We aim to understand the nature of the teacher’s support for argumentation—contributions and actions from the teacher that prompt or respond to parts of arguments. In particular, we look at examples of how the teacher supports students to move beyond unstructured tinkering (e.g., trial-and-error) to think logically about coding and develop reasoning for the choices that they make in programming. We also look at the components of arguments that students provide, with and without teacher support. Through the use of the framework, we are able to articulate important aspects of collective argumentation that would otherwise be in the background. The framework gives both eyes to see and language to describe how teachers support collective argumentation in integrative STEM classrooms. 

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5. Networking frameworks: a method for analyzing the complexities of classroom cultures focusing on justifying

   https://doi.org/10.1007/s10649-021-10026-3  

   Thanheiser, Eva; Melhuish, Kathleen; Sugimoto, Amanda; Rosencrans, Brenda; Heaton, Ruth (June 2021, Educational Studies in Mathematics)

   null (Ed.)

   Abstract In this paper, we network five frameworks (cognitive demand, lesson cohesion, cognitive engagement, collective argumentation, and student contribution) for an analytic approach that allows us to present a more holistic picture of classrooms which engage students in justifying. We network these frameworks around the edges of the instructional triangle as a means to coordinate them to illustrate the observable relationships among teacher, students(s), and content. We illustrate the potential of integrating these frameworks via analysis of two lessons that, while sharing surface level similarities, are profoundly different when considering the complexities of a classroom focused on justifying. We found that this integrated comparison across all dimensions (rather than focusing on just one or two) was a useful way to compare lessons with respect to a classroom culture that is characterized by students engaging in justifying. 

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