What are they thinking? Automated analysis of student writing about acid-base chemistry in introductory biology.

What are they thinking? Automated analysis of student writing about acid-base chemistry in introductory biology.
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DOI:
10.1187/cbe.11-08-0084
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发表时间:
2012
期刊:
CBE life sciences education
影响因子:
--
通讯作者:
Urban-Lurain M
Urban-Lurain M
中科院分区:
其他
文献类型:
--
作者:
Haudek KC;Prevost LB;Moscarella RA;Merrill J;Urban-Lurain M

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学生的写作可以提供更好的洞察力,他们的思想比多项选择题。然而,资源的限制往往阻止教师在大型本科科学课程中使用写作评估。我们调查了使用计算机软件来分析学生的写作,并揭示学生的想法,在生物学导论课程的化学。学生被要求预测生物官能团的酸碱行为,并解释他们的答案。学生的解释由两名独立的评分员进行评分。还使用SPSS调查文本分析和与评估项目相关的科学相关术语和词汇类别的自定义库分析了响应。这些分析揭示了学生的概念联系,学生解释这些主题的困难,以及学生思想的异质性。我们通过将学生访谈与词法分析相关联来验证词法分析。我们使用判别分析来创建分类函数,确定了七个关键的词汇类别,预测专家评分(评分员与专家的信度= 0.899)。这项研究表明,计算机化的词汇分析可能是有用的自动分类大量的学生开放式的反应。词汇分析为教师提供了对学生思维的独特见解,以及从多项选择题或阅读个人回答中难以获得的全班视角。
Students’ writing can provide better insight into their thinking than can multiple-choice questions. However, resource constraints often prevent faculty from using writing assessments in large undergraduate science courses. We investigated the use of computer software to analyze student writing and to uncover student ideas about chemistry in an introductory biology course. Students were asked to predict acid–base behavior of biological functional groups and to explain their answers. Student explanations were rated by two independent raters. Responses were also analyzed using SPSS Text Analysis for Surveys and a custom library of science-related terms and lexical categories relevant to the assessment item. These analyses revealed conceptual connections made by students, student difficulties explaining these topics, and the heterogeneity of student ideas. We validated the lexical analysis by correlating student interviews with the lexical analysis. We used discriminant analysis to create classification functions that identified seven key lexical categories that predict expert scoring (interrater reliability with experts = 0.899). This study suggests that computerized lexical analysis may be useful for automatically categorizing large numbers of student open-ended responses. Lexical analysis provides instructors unique insights into student thinking and a whole-class perspective that are difficult to obtain from multiple-choice questions or reading individual responses.
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