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首页> 外文期刊>Journal of Statistics Education >Improving Self-Efficacy in Statistics: Role of Self-Explanation & Feedback
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Improving Self-Efficacy in Statistics: Role of Self-Explanation & Feedback

机译:改善统计自我效能:自我解释和反馈的作用

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Novice problem solvers often fail to recognize structural similarities between problems they know and a new problem because they are more concerned with the surface features rather than the structural features of the problem. The surface features are the story line of the problem whereas the structural features involve the relationships between objects in the problem. We used an online technology to investigate whether students' self-explanations and reception of feedback influenced recognition of similarities between surface features and structural features of statistical problems. On average students in our experimental group gave 12 comments in the form of self-explanation and peer feedback. Students in this Feedback group showed statistically significantly higher problem scores over the No-Feedback group; however, the mean self-efficacy scores were lower for both groups after the problem solving experiment. The incongruence in problem scores with self-efficacy scores was attributed to students' over-rating of their abilities prior to actually performing the tasks. This process of calibration was identified as an explanation for the statistically significant positive correlation between problem solving scores and post self efficacy scores for the Feedback group (p .01).
机译:新手问题解决者常常无法意识到他们所知道的问题与新问题之间的结构相似性,因为他们更关注表面特征而不是问题的结构特征。表面特征是问题的故事情节,而结构特征涉及问题中对象之间的关系。我们使用一种在线技术来调查学生的自我解释和反馈的接受是否影响对统计问题的表面特征和结构特征之间相似性的识别。实验组中的学生平均以自我解释和同伴反馈的形式给出了12条评论。在反馈组中,学生的问题得分在统计上明显高于无反馈组;然而,在解决问题的实验之后,两组的平均自我效能感得分都较低。问题得分与自我效能得分的不一致是由于学生在实际执行任务之前对他们的能力的高估。校准的过程被认为是对反馈组的解决问题评分与自我效能得分之间统计上显着正相关的解释(p <.01)。

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