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

机译:通过基于Web的电子评估系统应对测试挑战,该系统由教师评估

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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:要求全国的中学教师使用形成性评估数据来指导他们的课堂教学。同时,“不让任何孩子落后”的批评家称该法案为“不让任何孩子未经测试”,强调评估的不利方面,因为花费在评估学生上的每一小时都浪费了一个小时的教学时间。还是一定要?如果我们更好地将评估整合到课堂中,并允许学生在测试中学习,该怎么办?也许我们甚至可以提供解决问题步骤的辅导。我们的假设是,我们不仅可以通过使用有关学生正确或错误地获得测试项目的数据,而且还可以使用有关学生学习如何解决测试项目所需的努力的数据来获得更准确的评估。在2004-2005学年期间,我们使用了E-ASSISTment系统通过600多名学生收集的数据为这一假设提供了证据。我们还表明,使用现代纵向数据分析技术,我们可以随着时间的推移跟踪学生的知识。在另一篇论文[9]中,我们报告了ASSISTment系统的体系结构和可扩展性,而本文的重点是如何可靠地评估学生的学习情况。

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