Proposing an Evaluation Task for Identifying Struggling Students in Online Courses

A. Staikopoulos, Owen Conlan
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引用次数: 2

Abstract

This paper describes and proposes a community evaluation task that is designed for evaluating learning systems that can automatically identify different types of problems, that students may encounter with their online courses. As a basis, the learning systems would use logs from an artificial learning environment to analyse the student interactions and behaviour with the online course. The learning systems will also use specific domain models to ensure that the course requirements such as task deadlines and learning content conditions (e.g., pre-requisites) are addressed. As a result, the outputs (identified student problems) can be used by a) the learning systems to provide personalised feedback and direction to students to overcome a problem b) notify an instructor for a more professional support and response c) inform a learning designer for potential problems on the design of the course.
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提出了一项评估任务,以识别在线课程中的困难学生
本文描述并提出了一个社区评估任务,用于评估学习系统,该系统可以自动识别学生在在线课程中可能遇到的不同类型的问题。作为基础,学习系统将使用来自人工学习环境的日志来分析学生与在线课程的互动和行为。学习系统还将使用特定的领域模型来确保满足课程要求,例如任务截止日期和学习内容条件(例如先决条件)。因此,输出(确定的学生问题)可以用于:a)学习系统为学生提供个性化的反馈和指导,以克服问题;b)通知教师以获得更专业的支持和响应;c)通知学习设计师课程设计中的潜在问题。
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