一种评估算法导论课程自我效能的工具

Proceedings of the 2017 ACM Conference on International Computing Education Research Pub Date : 2017-08-14 DOI:10.1145/3105726.3106171

Holger Danielsiek, Laura Toma, J. Vahrenhold

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引用次数: 44

摘要

我们报告了一种工具的开发和验证，以评估自我效能在入门算法课程。该仪器是根据Ramalingam和Wiedenbeck之前的工作设计的，并在多机构设置中进行了评估。我们对使用该仪器获得的分数进行了统计评估，并将我们的发现与有效的心理测量方法进行了比较。这些分析表明我们的发现与自我效能理论一致，从而提出了结构效度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An Instrument to Assess Self-Efficacy in Introductory Algorithms Courses

We report on the development and validation of an instrument to assess self-efficacy in an introductory algorithms course. The instrument was designed based upon previous work by Ramalingam and Wiedenbeck and evaluated in a multi-institutional setup. We performed statistical evaluations of the scores obtained using this instrument and compared our findings with validated psychometric measures. These analyses show our findings to be consistent with self-efficacy theory and thus suggest construct validity.

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Proceedings of the 2017 ACM Conference on International Computing Education Research

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