Zhou Shuqi, Traynor Anne
College of Foreign Languages, Donghua University, Shanghai, China.
Department of Educational Studies, Purdue University, West Lafayette, IN, United States.
Front Psychol. 2022 Aug 9;13:892884. doi: 10.3389/fpsyg.2022.892884. eCollection 2022.
This study applied cognitive diagnostic models to assess students' learning progressions in energy. A Q-matrix (i.e., an item attribute alignment table) was proposed based on existing literature about learning progressions of energy in the physical science domain and the Trends in International Mathematics and Science Study (TIMSS) assessment framework. The Q-matrix was validated by expert review and real data analysis. Then, the deterministic inputs, noisy 'and' gate (DINA) model with hierarchical relations was applied to data from three jurisdictions that had stable, defined science curricula (i.e., Australia, Hong Kong, and Ontario). The results suggested that the hypothesized learning progression was consistent with the observed progression in understanding the energy concept. We also found similarities in students' attribute mastery across the three jurisdictions. In addition, we examined the instructional sensitivity of the selected item. We discuss several curriculum-related issues and student misconceptions that may affect students' learning progressions and mastery patterns in different regions of the world.
本研究应用认知诊断模型来评估学生在能量方面的学习进程。基于物理科学领域中有关能量学习进程的现有文献以及国际数学和科学趋势研究（TIMSS）评估框架，提出了一个Q矩阵（即项目属性对齐表）。该Q矩阵通过专家评审和实际数据分析得到了验证。然后，将具有层次关系的确定性输入、噪声“与”门（DINA）模型应用于来自三个拥有稳定、明确科学课程的司法管辖区（即澳大利亚、香港和安大略省）的数据。结果表明，假设的学习进程与在理解能量概念方面观察到的进程一致。我们还发现这三个司法管辖区的学生在属性掌握方面存在相似之处。此外，我们研究了所选项目的教学敏感性。我们讨论了几个可能影响世界各地不同地区学生学习进程和掌握模式的与课程相关的问题以及学生的误解。
