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首页> 外文会议>2012 Frontiers in Education Conference. >Application of item response theory (IRT) for the generation of adaptive assessments in an introductory course on object-oriented programming
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Application of item response theory (IRT) for the generation of adaptive assessments in an introductory course on object-oriented programming

机译：项目响应理论（IRT）在面向对象编程入门课程中用于生成自适应评估的应用

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Assessment process in one of the most important issues in the learning process and in many cases it is the process that define the sequence of the instruction because it measures the performance of the student in the educational process. In last decades the inclusion of TICs in teaching-learning process has facilitated to address the diversity of students and teachers features. Learning technologies enhance have permitted to adapt the different ways of learning and teaching that coexist in the educational context through the generation of adaptations process as well as user modeling process. This paper describes the item response theory and how it can be applied in a test scenario of an online course for the generation of adaptive assessments within a course of introduction to Object Oriented Programming from items (assessment questions), which are available in online repositories. Being a probabilistic theory the article describes the variables to consider and how to calculate the probability that a student answers correctly a specific item, which is known as the student proficiency level or theta, based on a skill test and their previous answers. In other papers write for the authors it is described the experience of working with fedora commons repositories, which are distributed across a network, in order to have enough questions to be applied properly normalized in the adaptation process. These questions are described under the Dublin Core standard. The main contributions of this project are the implementation of a probabilistic theory in the generation of adaptive assessment and use of distributed repositories that allow the reusability of items properly parameterized. A second phase of the research includes the implementation of the project (APIP) Accessible Profile Portable Item, allowing standardization of assessment items in a suitable format in the LOM.
机译：评估过程是学习过程中最重要的问题之一，在很多情况下，它是定义教学顺序的过程，因为它可以衡量学生在教育过程中的表现。在过去的几十年中，将TIC纳入教学过程中有助于解决学生和教师功能的多样性。通过生成适应过程以及用户建模过程，增强了学习技术，可以适应在教育环境中共存的不同学习和教学方式。本文介绍了项目响应理论，以及如何将其应用到在线课程的测试场景中以生成适应性评估，该课程是从项目（评估问题）开始的面向对象编程入门课程，在线知识库中提供了这些知识。作为一种概率理论，本文描述了要考虑的变量，以及如何根据技能测试和他们先前的答案计算学生正确回答特定项目的概率，这被称为学生熟练程度或theta。在其他为作者撰写的论文中，描述了使用fedora commons存储库（在整个网络中分布）的经验，以便有足够的问题可以在适应过程中正确归一化。这些问题在都柏林核心标准下进行了描述。该项目的主要贡献是在生成自适应评估中使用概率论，并使用分布式存储库，这些存储库允许正确设置参数的项目的可重用性。研究的第二阶段包括项目（APIP）可访问配置文件便携式项目的实施，从而允许在LOM中以合适的格式对评估项目进行标准化。

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