The Meaningful Learning in the Laboratory Instrument (MLLI) was designed to measure students’ expectations before and after their laboratory courses and experiences. Although the MLLI has been used in various studies and laboratory environments to investigate students’ cognitive and affective laboratory expectations, the authors of the instrument reported a discrepancy between the intended factor structure of the MLLI and the factor structure suggested by the data collected in preliminary studies. Therefore, the aim of this study was to investigate the validity and reliability evidence related to data collected with the MLLI, especially that related to structural validity. Evidence to support structural validity would provide greater meaning for the reporting and interpretation of MLLI scores. In this study, two possible a priori models for the factor structure of data collected from multiple institutions with the MLLI were investigated using confirmatory factory analysis (CFA). This initial investigation found poor data-model fit for each of the two tested models. Cognitive interviews and free response items were then used to inform modifications to the two a priori structures, and a third alternative structure, which included a negative method factor, was also investigated. Once a best fitting model was identified, further model revisions were informed by a combination of modification indices and qualitative data. Evidence of adequate-to-good data model fit was found for the final revised version of the MLLI, deemed the MLLIv2. Additionally, evidence of both internal structure validity and single administration reliability were found for each of the MLLIv2 factors. The structure of the data from these items leads to scale scores that likely represent student expectations that contribute to meaningful learning and student expectations that detract from meaningful learning. As the results of this study provide the first psychometrically supported scales for MLLI data, they have implications on the future reporting and analyses of MLLI scores.

中文翻译：

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调查支持实验室有意义学习仪器（MLLI）收集的数据的有效性和可靠性的证据

实验室仪器中的有意义学习 (MLLI) 旨在衡量学生在实验室课程和体验之前和之后的期望。尽管 MLLI 已被用于各种研究和实验室环境中，以调查学生的认知和情感实验室期望，但该工具的作者报告说，MLLI 的预期因子结构与初步研究中收集的数据所建议的因子结构之间存在差异。因此，本研究的目的是调查与 MLLI 收集的数据相关的有效性和可靠性证据，特别是与结构有效性相关的证据。支持结构有效性的证据将为 MLLI 分数的报告和解释提供更大的意义。在本研究中，使用验证性工厂分析 (CFA) 对从 MLLI 多个机构收集的数据的因子结构的两种可能的先验模型进行了研究。初步调查发现，两个测试模型的数据模型拟合度都很差。然后使用认知访谈和自由回答项目来告知对两个先验结构的修改，并且还研究了第三个替代结构，其中包括否定方法因素。一旦确定了最佳拟合模型，就会通过修改指数和定性数据的组合来通知进一步的模型修订。MLLI 的最终修订版本（被视为 MLLIv2）找到了足够到良好数据模型拟合的证据。此外，还发现了每个 MLLIv2 因子的内部结构有效性和单次给药可靠性的证据。这些项目的数据结构产生的量表分数可能代表有助于有意义学习的学生期望和有损有意义学习的学生期望。由于这项研究的结果为 MLLI 数据提供了第一个心理测量支持的量表，因此它们对未来 MLLI 分数的报告和分析具有影响。