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Addressing drop-out and sustained effort issues with large practical groups using an automated delivery and assessment system

机译:使用自动化的交付和评估系统,与大型实践小组一起解决辍学和持续努力的问题

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摘要

The acquisition of programming skills specially in introductory programming courses poses an important challenge for freshmen students of engineering programs. These courses require students to devote a sustained effort during the whole course and a failure to do so may contribute to not passing the course. However, it is difficult for the teaching staff to deploy measures to enforce a pattern of continuous work without significantly increasing the required management tasks. A significant reduction of this workload can be achieved with the automation of time consuming tasks such as the delivery of activities or submission grading. This paper presents a case of study where a technology based orchestration of learning scripts was applied in a large enrollment course to promote student sustained effort through the course and keep the workload on teaching staff within reasonable margins. The orchestration system, based on IMS Learning Design and Generic Service Integration, automatically evaluated the student submissions and gradually unlocked the following activities depending on the received results. Such system was used during a semester supporting 425 students and 8 instructors. The analysis of the case of study followed a mixed method based on qualitative and quantitative data, and revealed a significant reduction of the orchestration workload on the teaching staff, allowing the strategy of continuous work to be applied in a course with high enrollment. Additionally, the application of these techniques show statistically significant differences in the drop out rate with respect to previous editions of the course.
机译:特别是入门编程课程的编程技能的获得,对工程专业的新生来说是一个重要的挑战。这些课程要求学生在整个课程中投入不懈的努力,否则可能会导致不及格。但是,在不显着增加所需的管理任务的情况下,教学人员很难采取措施来实施一种连续工作模式。通过自动化耗时的任务(例如活动的交付或提交评分),可以大大减少这种工作量。本文介绍了一个案例研究,其中在大型注册课程中应用了基于技术的学习脚本编排,以促进学生在整个课程中的持续努力,并使教职员工的工作量保持在合理范围内。编排系统基于IMS学习设计和通用服务集成,可以自动评估学生提交的内容,并根据收到的结果逐步解锁以下活动。这个系统在一个学期中使用了425名学生和8位讲师。对研究案例的分析采用了基于定性和定量数据的混合方法,显示了编排人员的编排工作量显着减少,从而使连续工作的策略适用于高入学率的课程。另外,这些技术的应用显示出与该课程的先前版本相比,辍学率在统计学上有显着差异。

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