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Mixed Methods: Positivists are from Mars, Constructivists are from Venus

机译:混合方法:实证主义者来自火星,建构主义者来自金星

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You can't work in Computer Science Education Research for very long without stumbling into a religious war over qualitative versus quantitative methods. Recently, I read a general education paper where the authors were brave (or foolish) enough to advocate "mixed methods". That is, they advocate the use of both quantitative and qualitative methods within a single study. When I started in CSEd, I wanted to do "good old fashioned" positivist, quantitative research. I thought naively that education research should be like physics, or medical research. I suspect this is how most of us start in CSEd research. I now prefer mixed methods. I am drawn to studies which combine "hard numbers" with qualitative data that "makes sense" of the numbers. For example, I was part of a project that studied novice programmers. We collected extensive quantitative data (statistics on "performance" and "doodles"). However, I could not have made any satisfying interpretation of those numbers had we not also collected qualitative ("think out loud") data from the novices.
机译:您不能长期从事计算机科学教育研究工作,而不会陷入定性与定量方法之间的宗教战争。最近,我读了一篇普通教育论文,其中的作者很勇敢(或愚蠢),主张“混合方法”。也就是说,他们主张在单个研究中同时使用定量和定性方法。当我从CSEd开始时,我想进行“老式的”实证主义的定量研究。我天真地认为教育研究应该像物理学或医学研究。我怀疑这就是我们大多数人开始进行CSEd研究的方式。我现在更喜欢混合方法。我被吸引进行结合“硬数字”和“有意义”数字的定性数据的研究。例如,我参与了一个研究新手程序员的项目。我们收集了广泛的定量数据(“性能”和“涂鸦”的统计数据)。但是,如果我们也没有从新手那里收集定性(“大声思考”)数据,我就无法对这些数字做出令人满意的解释。

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