Open assessment methodology-based decision support system in blended learning environments

G. M. Shivanagowda, R. Goudar, U. Kulkarni
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引用次数: 1

Abstract

Personalising education is one of the 16 grand challenges as per the National Academy of Engineering, USA. Measuring the outcomes of education and the progress of learning has an essential role in generating personalised feedbacks and recommendations in personalised learning. The data obtained by traditional assessment tools like written and oral examinations, mass assignments do not reflect the real state of the student's knowledge and progress of learning. Learning activities outside the classroom are not observable adding to the imprecision of recommendations. This paper share one of our assessment practice called 'open assessment method' developed and practiced during 2012-2015 along with the design of a decision support system. It is built around a 'class activity sheet' with Google technologies, enhances the observability of the learning environment. This technological adaption leads to improvement in student's participation, generating data useful for composing recommendations on a personal basis with teacher's interventions.
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混合学习环境下基于开放式评估方法的决策支持系统
个性化教育是美国国家工程院提出的16大挑战之一。衡量教育成果和学习进度在个性化学习中产生个性化反馈和建议方面具有重要作用。通过笔试、口试、大量作业等传统的评估工具获得的数据并不能反映学生的知识和学习进展的真实状态。课堂外的学习活动是无法观察到的,这增加了推荐的不精确性。本文分享了我们在2012-2015年开发和实践的一种评估实践,称为“开放评估方法”,以及决策支持系统的设计。它是围绕谷歌技术的“课堂活动表”构建的,增强了学习环境的可观察性。这种技术适应导致学生参与度的提高,在教师干预的个人基础上产生有用的数据,以形成建议。
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