A Multi-phase development of the Electric Circuit Concepts Diagnostic tool: Phase I

该项目旨在通过创建一种新的基于网络的诊断反馈工具来加强电气工程电路的教与学，从而服务于国家利益。全国所有工程专业的学生，无论他们打算学什么专业，都必须参加一门关于电路的课程。许多学生带着对工程概念的误解进入工程课堂。这些误解必须克服，因为学习能力要求学生建立在准确的先前知识的基础上。一些教师依靠被称为概念清单的多项选择题测试来识别学生的误解。他们希望从学生的概念清单分数中收集信息，并调整他们的教学方法，以更好地满足特定学生群体的学习需求。然而，要求学生完成概念清单的教师可能不会从使用这些清单中完全受益。例如，教师可能缺乏解释概念清单结果的技能，或者可能没有时间调整他们的教学以反映学生的学习需求。此外，很难确定概念清单的结果是否表明学生还不知道这个概念或对它有误解。这种区别很重要，因为获取新知识和纠正误解需要不同的教和学方法。这个项目的目标是通过开发一个名为电路概念诊断(ECCD)的增强型概念清单工具来克服一些概念清单的限制。ECCD将是一种新的基于网络的诊断反馈工具，它使用基于计算机的测试和自动化评估来衡量更广泛内容领域的先前知识。因此，ECCD有潜力提供超越现有电路概念清单的知识诊断能力。项目目标包括：(I)提供一个即时和多用途的反馈系统，以报告学生对电路和电力的先验知识；(Ii)区分缺乏先验知识和误解的可能性很高；以及(Iii)使用多维知识概况计划来报告学生的先验知识和误解。为了实现这些目标，项目组将整合认知诊断建模、多层测试框架和计算机辅助测试的能力，以实现项目目标。将元认知纳入拟议工作是一项新颖的工作，可能有助于增加关于在工程教育中使用元认知以及促进终身学习技能的文献。这项工作还可作为在工程学以外的其他工程领域和STEM领域开发增值概念清单的框架。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过参与的学生学习路径，该计划支持有前景的实践和工具的创建、探索和实施。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national interest by creating a novel web-based diagnostic feedback tool to enhance teaching and learning about electrical engineering circuits. All engineering students nationwide, regardless of their intended engineering specialization, are required to enroll in a course on electrical circuits. Many students enter engineering classrooms with misconceptions about engineering concepts. These misconceptions must be overcome since the ability to learn requires the student to build upon accurate prior knowledge. Some instructors rely on multiple choice tests called concept inventories to identify students’ misconceptions. They hope to glean information from students’ concept inventory scores and adjust their teaching approaches to better meet the learning needs for that specific student cohort. However, instructors who require students to complete concept inventories may not benefit fully from using them. For example, instructors may lack skills to interpret concept inventory results or may not have time to adjust their teaching to reflect the students' learning needs. Furthermore, it can be difficult to determine whether results from concept inventories indicate that a student does not yet know the concept or has misconceptions about it. Such differentiation is important because gaining new knowledge and correcting misconceptions require different teaching and learning approaches. The goal of this project is to overcome some concept inventory limitations by developing an augmented concept inventory tool called the Electric Circuit Concepts Diagnostic (ECCD). The ECCD will be a novel web-based diagnostic feedback tool that uses computer-based testing and automated assessment to measure prior knowledge across broader content areas. As a result, the ECCD has the potential to deliver knowledge diagnostic capabilities beyond those of existing electric circuit concept inventories.Project objectives include: (i) provision of an immediate and multi-purpose feedback system for reporting about students’ prior knowledge regarding circuits and electricity; (ii) differentiation, with a high probability of accuracy, between a lack of prior knowledge and misconceptions; and (iii) use of a scheme of multidimensional knowledge profiles to report on students’ prior knowledge and misconceptions. To achieve these objectives, the project team will integrate the affordances of cognitive diagnostic modeling, multi-tier testing frameworks, and computer-assisted testing to realize project objectives. The inclusion of metacognition in the proposed work is novel and could contribute to the growing literature on use of metacognition in engineering education as well as the promotion of skills for lifelong learning. The work may also serve as a framework for developing value-added concept inventories in other engineering fields and STEM domains beyond engineering. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.