“I can’t search on Google for answers”: validity evidence of a developed computer-based assessment application

Elok Putri Nimasari, Rohfin Andria Gestanti, Khoiru Nurfitri
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引用次数: 1

Abstract

While learning management systems have been increasingly used as innovative ways to teach students in the post-COVID-19 pandemic, academic dishonesty is still in crisis. The open-access facility has the potential intervention in academic dishonesty. This study reported validity evidence of a developed computer-based assessment application to combat academic dishonesty: 1) measuring the development of high-order-thinking-skill (HOTS) test items; 2) examining the test item's validity integrated into the application; and 3) reporting the program analysis of the anti-cheating application for English for Specific Purposes (ESP) class assessment. This mixed-method study used focus group discussion and reading tests to collect the data. Pearson product-moment and black box analysis were used to measure test-item validity and application. The quantitative result revealed that test items were developed according to authentic journal texts and HOTS question characteristics and were statistically proven valid and reliable. Simplifying the authentic text empirically enabled EFL students to have an easier ESP reading comprehension complexity level. The black box analysis showed that the auto-lock screen feature prevented suspicious cheating access. This study contributed to extending practical and theoretical research on technology-enhanced language learning (TELL) by providing an innovative anti-cheating technology application.
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“我无法在谷歌上搜索答案”:开发的基于计算机的评估应用程序的有效性证据
尽管在新冠肺炎疫情后,学习管理系统越来越多地被用作创新的教学方式,但学术诚信仍处于危机之中。开放获取设施有可能对学术不诚实行为进行干预。本研究报告了一种基于计算机的评估应用程序的有效性证据,该应用程序旨在打击学术不诚实行为:1)测量高阶思维技能(HOTS)测试项目的发展;2) 检查集成到应用程序中的测试项目的有效性;以及3)报告针对特定用途英语(ESP)课堂评估的反作弊应用程序的程序分析。这项混合方法研究采用了焦点小组讨论和阅读测试来收集数据。采用皮尔逊乘积矩和黑箱分析法对测试项目的有效性和应用进行了测量。定量结果表明,测试项目是根据真实的期刊文本和HOTS问题特征开发的,并且在统计上被证明是有效和可靠的。从经验上简化真实文本可以使EFL学生获得更容易的ESP阅读理解复杂性水平。黑匣子分析显示,自动锁定屏幕功能防止了可疑的欺骗访问。本研究提供了一种创新的反作弊技术应用,有助于扩展技术增强语言学习(TELL)的实践和理论研究。
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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