HCC: Small: PedWorkflow: Workflows for Assessing Student Learning

这个教学qorkflow研究项目将创建一个新的混合工作流框架，通过交互式生成和执行各种评估工作流来支持学生学习的有效评估。与许多现有的工作流程系统不同，学生评估的任务包括无法完全自动化的步骤，例如获取成绩，背景和学生调查信息。该系统将协助执行和整合手工步骤的结果。研究步骤将包括：（a）将计算和非计算评估工具作为工作流程组成部分进行基于知识的建模;（B）交互式生成评估工作流程，同时传播和组合来自计算和非计算组成部分的约束;（c）交互式执行混合工作流程，其中包含从非计算组成部分的执行中推断出的新约束。评估将集中在教学工作流技术对学习评估绩效的影响，特别是对本科工程课程教学话语的评估。支持在线学习的教育技术现在受到许多学院和大学的集中支持。除了网络上可供消费的大量信息之外，使用技术进行教学的感知任务给教师带来了相当大的负担，他们必须学会通过新媒体整合适当的学生实践和学习评估。教学工作流程将允许教师很少或根本没有教育评估培训，以执行大规模的复杂的诊断和评估学生的学习正在进行的课程。 促进将学生个人信息整合到评估中将为改善STEM参与、学习和保留指明方向。这一发现将通过与教师和教育专家分享成果和技术来造福社会。拟议的工作也有可能导致一个新的研究领域的电子学习工作流程，类似于工作流技术的方式，电子科学研究与电子科学工作流程。

This pedagogical qorkflow research project will create a novel hybrid-workflow framework that supports efficient assessment of student learning through interactive generation and execution of various assessment workflows. Unlike in many existing workflow systems, the task of student assessment includes steps that cannot be fully automated, such as obtaining grade, background and student survey information. The system will provide assistance in executing and integrating the results of the manual steps. Research steps will include (a) knowledge-based modeling of computational and non-computational assessment tools as workflow components; (b) interactive generation of assessment workflows while propagating and combining constraints from both computational and non-computational components; and (c) interactive execution of hybrid workflows that incorporates new constraints that are inferred from execution of non-computational components. Evaluations will focus on the effects of Pedagogical Workflow technology on learning assessment performance, especially the assessment of pedagogical discourse in undergraduate engineering courses.Educational technology to support online learning is now centrally supported by many colleges and universities. The perceived mandate to use technology for instruction, in addition to the enormous amount of information available for consumption on the Web, places a considerable burden on instructors who must learn to integrate appropriate student practices and learning assessment via the new media. Pedagogical workflows will allow instructors with little or no training in educational assessment to perform large-scale complex diagnosis and assessment of student learning in ongoing lessons. Facilitating the integration of personal student information into assessment will point to directions to improve STEM participation, learning, and retention. The finding will provide benefits to society by sharing results and technology with instructors and educational experts. The proposed work also has the potential to lead to a new research field on e-Learning workflows, similar to the way in which workflow technology transformed e-Science research with e-Science workflows.