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The Analysis of Online Learning Behavior of the Students with Poor Academic Performance in Mathematics and Individual Help Strategies

机译:数学和个人帮助策略中学生在线学习行为的分析

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It is crucially important that educational practitioners and researchers pay attention to the students with poor academic performance and help improve their learning. The behaviors of the students using online learning systems can be used as one important data source to analyze the students' learning behaviors. From the viewpoint of formative assessment, we define one student as a student with poor academic performance during one learning period if this student is classified into a student with poor academic performance in three quarters of all examinations during this period. After screening all students' mathematic exam scores from Grade One to Grade Three of one experiment class in a junior high school in China, six students are identified as students with poor academic performance in math education during nearly three years' study period. They performed worse in most examinations, but not bad in some examinations. Based on the OLAI (Online Learning Activity Index) model proposed by Jia and Yu (2017) to describe the students' online learning activities, we analyze the students' online quiz activity in a web-based interactive learning system by comparing the values of the OLAI dimensions of the students. The data analysis shows that every student had his or her own feature, and thus individual approaches to help each student are suggested. All the poor students had a bad performance in the starting point, i.e. the first exam. Their deficiency in previous study prevented them from understanding new knowledge and should be overcome at first. Overall, their online performance is positively correlated with the normal exam performance. The online quiz activities with instant feedback is helpful for the students with poor academic performance in their normal exams. The more challenging quizzes and the frequent help from teaching assistants online must not lead to better performance in normal exams.
机译:至关重要的是,教育从业者和研究人员关注具有差的学术表现,有助于提高学习的学生。使用在线学习系统的学生的行为可以用作分析学生的学习行为的一个重要数据源。从形成性评估的角度来看,如果该学生分为在此期间的三个季度的三个季度的学习表现差,在一个学习期间,我们将一名学生定义为具有差的学生表现差的学生。在将所有学生的数学考试中筛选到中国初中的一个实验课程中的所有学生的数学考试分数,六名学生被确定为在近三年的学习期间数学教育中学性能差的学生。他们在大多数考试中表现得更糟,但在一些考试中也不错。基于贾和俞(2017年)提出的olai(在线学习活动指数)模型来描述学生的在线学习活动,我们通过比较了基于网络的互动学习系统的学生在线测验活动来比较olai的学生尺寸。数据分析表明,每个学生都有他或她自己的特征,因此提出了各个学生的个人方法。所有可怜的学生在起点中表现不佳,即第一次考试。他们在以前的研究中的缺陷阻止了他们了解新知识,并应该首先克服。总的来说,他们的在线表现与正常考试表现正相关。随着即时反馈的在线测验活动对于学生在正常考试中具有较差的学生,有助于学生。在线教学助理的测验更具挑战性和频繁的帮助不能导致正常考试中的更好表现。

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