Expert Validation of a Python Test, Reliability, Difficulty and Discrimination Indices

Hector Manuel Belmar Garrido
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引用次数: 1

Abstract

In recent years, different countries have implemented the teaching of computer programming from the first grade in schools, with the aim of incorporating computational thinking as a new way of thinking that is a necessary skill for scientific and technological development, a fundamental axis for development in the 21st century. Recent reviews of the state of the art have shown that this task is only being carried out by countries that have given space to technology and science, incorporating it at the elementary school level. However, developing countries do not yet consider the significance of the issue, so to date they have not taken the necessary steps in this direction. In addition, learning computer programming is fundamental for countries to join technological development, so that they can be creators of technology and not just users of it. The problem is that there is no didactic development for the teaching of programming, nor validated evaluation instruments to quantify the learning of computer programming. The objective of this research is to validate a programming test that evaluates technical skills in the Python programming language. The instrument proposed to be validated is a 90-item test, which after validation by experts was reduced to 70 items, and after the psychometric analysis that considered the calculation of reliability, difficulty and discrimination indexes, resulted in the proposed 45-item instrument, as a standard instrument for the evaluation of learning in the Python programming language. It should be noted that the validation methodology was carried out using the classical theory of psychometric analysis.
专家验证的Python测试,可靠性,难度和辨别指标
近年来,各国从小学一年级开始实施计算机程序设计教学,目的是将计算思维作为一种新的思维方式,作为21世纪科技发展的基本轴所必需的技能。最近对技术状况的审查表明,只有那些给予技术和科学空间并将其纳入小学一级的国家才在执行这项任务。然而,发展中国家还没有考虑到这个问题的重要性,因此迄今为止它们还没有朝着这个方向采取必要的步骤。此外,学习计算机编程是各国参与技术发展的基础,这样他们就可以成为技术的创造者,而不仅仅是技术的用户。问题是,编程教学没有教学发展,也没有有效的评估工具来量化计算机编程的学习。这项研究的目的是验证一个评估Python编程语言技术技能的编程测试。拟验证的工具是一个90项的测试,经专家验证后减少到70项,并经过考虑信度、难度和判别指标计算的心理测量分析,得出拟验证的45项工具,作为评估Python编程语言学习的标准工具。值得注意的是,验证方法是使用经典的心理测量分析理论进行的。
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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