STTR Phase I: Spiral Assessment Loop for Rubrics

STTR 第一阶段：量规螺旋评估循环

• 批准号: 0740700
• 负责人: Leigh Flagg
• 金额: $ 15万
• 依托单位: Sentar, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0740700&HistoricalAwards=false
• 关键词: STTR; Phase; Spiral; Assessment; Loop

This Small Business Technology Transfer (STTR) Phase 1 project seeks to improve educational assessment rubrics. Accreditation requires adequate assessment rubrics to substantiate expected student outcomes. Faculty struggle with specifying outcomes and their rubrics, due to inexperience and lack of proper tools. Our first research objective is to accumulate and classify expected outcomes, including common assessment techniques, e.g. survey, portfolio, and projects, and associated rubrics to evaluate if expectations are exceeded, met, or not met. Classification leads to the second objective defining a many-to-many mapping of outcomes to rubrics. The third objective initiates controlled customization of outcomes, rubrics, and mappings for better evaluation coverage and to satisfy accreditation goals for continuous assessment improvement. The proposed effort defines SALR (Spiral Assessment Loop for Rubrics), based on the spiral model for software engineering, to generate, test, and evaluate assessment rubrics. SALR uses the resulting outcome classification ontology from which the mapping of outcomes to rubrics emerges coupled with current evaluations of achievement to determine needed changes. The anticipated results are documented classification of outcomes, assessment techniques and rubrics for computer science and some broader engineering sciences, ontologically based mappings of outcomes to rubrics, and spiral assessment loop prototype for commercial development.Universities can benefit from software-based rubrics development and evaluation scaled to the collegiate level. Curriculum-based rubrics immediately inform faculty of assessment issues and needed improvements. Commercial software can provide quick and easy storage, retrieval, and evaluation performed on a semester, exam, or project basis. Students are well-served by achieving success in critical education aspects. With performance-based rubrics at hand, students can understand expectations and how to reach them. Without explicit expectations, all may be surprised at failed outcomes. Unfortunately, few in higher education know how to construct proper rubrics. Current tools do not scale to university levels. Thus, rubrics must often be tailored or created from scratch. Thus, this research and development effort can remove barriers to assessment, benefiting faculty and student understanding of successful outcomes.

这一小型企业技术转让(STTR)第一阶段项目旨在改进教育评估准则。认证需要充分的评估标准，以证实预期的学生成绩。由于缺乏经验和缺乏适当的工具，教员们很难确定结果及其规则。我们的第一个研究目标是积累和分类预期结果，包括常见的评估技术，例如调查、投资组合和项目，以及用于评估是否超出、满足或未达到预期的相关标准。分类导致了第二个目标，定义了结果与类比的多对多映射。第三个目标是启动结果、标准和映射的受控定制，以获得更好的评估覆盖面，并满足持续评估改进的认证目标。该工作基于软件工程的螺旋模型定义了SALR(螺旋评估循环)，以生成、测试和评估评估标准。SALR使用由此产生的成果分类本体，从该本体中出现了将成果映射到类比的方法，并结合当前对绩效的评价来确定所需的变化。预期的结果是计算机科学和一些更广泛的工程科学的成果分类、评估技术和标准，基于本体论的成果到标准的映射，以及商业开发的螺旋评估循环原型。大学可以从基于软件的标准开发和评估中受益，并扩展到大学水平。以课程为基础的校规会立即向教员通报评估问题和需要改进的地方。商业软件可以提供快速、方便的存储、检索和按学期、考试或项目执行的评估。学生在批判性教育方面取得成功，对他们有利。有了基于绩效的标准，学生们就可以理解期望以及如何实现期望。如果没有明确的预期，所有人都可能会对失败的结果感到惊讶。不幸的是，在高等教育中，很少有人知道如何构建适当的规则。目前的工具不能扩展到大学水平。因此，Rubrics通常必须量身定做或从头开始制作。因此，这种研究和开发努力可以消除评估的障碍，有利于教师和学生对成功结果的理解。