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Addressing the Testing Challenge with a Web-Based E-Assessment System that Tutors as it Assesses

机译:通过评估的辅导员来解决基于Web的电子评估系统的测试挑战

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Secondary teachers across the country are being asked to use formative assessment data to inform their classroom instruction. At the same time, critics of No Child Left Behind are calling the bill "No Child Left Untested" emphasizing the negative side of assessment, in that every hour spent assessing students is an hour lost from instruction. Or does it have to be? What if we better integrated assessment into the classroom, and we allowed students to learn during the test? Maybe we could even provide tutoring on the steps of solving problems. Our hypothesis is that we can achieve more accurate assessment by not only using data on whether students get test items right or wrong, but by also using data on the effort required for students to learn how to solve a test item. We provide evidence for this hypothesis using data collected with our E-ASSISTment system by more than 600 students over the course of the 2004-2005 school year. We also show that we can track student knowledge over time using modern longitudinal data analysis techniques. In a separate paper [9], we report on the ASSISTment system's architecture and scalability, while this paper is focused on how we can reliably assess student learning.
机译:各国各地的教师被要求使用形成性评估数据来通知其课堂教学。与此同时,没有儿童的批评者留下留下的是票据“没有孩子未被遗忘”强调评估的负面方面,因为评估学生的每一小时都是从教学中丢失的一小时。还是必须是?如果我们更好地融入课堂,我们将允许学生在测试期间学习怎么办?也许我们甚至可以为解决问题的步骤提供辅导。我们的假设是,我们可以不仅可以使用关于学生是否正确或错误的测试项目的数据来实现更准确的评估,而是使用关于学生学习如何解决测试项目所需的努力的数据。我们使用在2004 - 2005年学年的历程中由我们的电子协助系统收集的数据提供了与我们的电子协助系统收集的数据提供了证据。我们还表明,我们可以使用现代纵向数据分析技术跟踪学生知识。在一个单独的论文中,我们报告了辅助系统的架构和可扩展性,而本文专注于我们如何可靠地评估学生学习。

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