Combining Summative and Formative Evaluation Using Automated Assessment

J. English, T. English
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引用次数: 4

Abstract

[This Proceedings paper was revised and published in the 2019 issue of the journal Issues in Informing Science and Information Technology, Volume 16] Aim/Purpose: Providing both formative and summative assessment that allows students to learn from their mistakes is difficult in large classes. This paper describes an automated assessment system suitable for courses with even 100 or more students. Background: Assessment is a vital part of any course of study. Ideally students should be given formative assessment with feedback during the course so students and tutors can identify weaknesses and focus on what needs improvement before summative assessment, which results in a grade. This paper describes and automated assessment system that lessens the burden of providing formative assessment in large classes. Methodology: We used Checkpoint, a web-based automated assessment system, to grade assignments in a number of different computer science courses. Contribution: The students come from diverse backgrounds, with a wide range of ages, previous qualifications and technical skills, and our approach allows the students to work at their own pace according to their individual needs, submitting their solutions as many times as they wish up to a deadline, using feedback provided by the system to help identify and correct their mistakes before trying again. Findings: Use of automated assessment allows us to achieve the goals of both summative and formative assessment: we allow students to learn from their mistakes without incurring a penalty, while at the same time awarding them a grade to validate their efforts. The students have an overwhelmingly positive view about our use of automated assessment, and their comments support our views on the assessment process. Recommendations for Practitioners: Because of the increasing number of students in today’s courses, we recommend using automated assessment wherever possible.
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结合总结性和形成性评估使用自动化评估
[这篇论文被修订并发表在2019年的《信息科学与信息技术问题》杂志上,第16卷]目的/目的:在大班教学中,提供形成性和总结性评估,让学生从错误中学习是很困难的。本文介绍了一种适用于100人以上课程的自动评估系统。背景:评估是任何课程学习的重要组成部分。理想情况下,学生应该在课程中得到有反馈的形成性评估,这样学生和导师就可以在总结性评估之前找出弱点,并关注需要改进的地方,而总结性评估最终会得出一个分数。本文介绍了一种减轻大班形成性评估负担的自动化评估系统。方法:我们使用基于网络的自动评估系统Checkpoint对许多不同计算机科学课程的作业进行评分。贡献:学生来自不同的背景,年龄,以前的资格和技术技能范围广泛,我们的方法允许学生根据自己的个人需求按照自己的节奏工作,在截止日期前尽可能多地提交他们的解决方案,使用系统提供的反馈来帮助识别和纠正他们的错误,然后再尝试。发现:使用自动化评估使我们能够实现总结性和形成性评估的目标:我们允许学生从错误中学习而不会受到惩罚,同时给他们一个分数来验证他们的努力。学生们对我们使用的自动评估有非常积极的看法,他们的意见支持我们对评估过程的看法。对从业者的建议:由于当今课程的学生数量不断增加,我们建议尽可能使用自动评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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