Leibniz Institute for Educational Trajectories, Bamberg, Germany.
Johannes Kepler University Linz, Linz, Austria.
PLoS One. 2021 Jan 29;16(1):e0245884. doi: 10.1371/journal.pone.0245884. eCollection 2021.
This registered report protocol elaborates on the theory, methods, and material of a study to identify latent profiles of competence development in reading and mathematics among German students in upper secondary education. It is expected that generalized (reading and mathematical competence develop similarly) and specialized (one of the domains develops faster) competence profiles will be identified. Moreover, it is hypothesized that students' domain-specific interest and educational history will predict membership of these latent profiles as these factors influence the students' learning environments. For this study, we will use data from the German National Educational Panel Study, including students from ninth grade in secondary schools (expected N = 14,500). These students were tracked across six years and provided competence assessments on three occasions. The latent profiles based on the students' reading and mathematical competences will be identified using latent growth mixture modeling. If different types of profiles can be identified, multinomial regression will be utilized to analyze whether the likelihood of belonging to a certain competence development profile is influenced by students' domain-specific interest or educational history. As this protocol is submitted before any analyses were conducted, it will provide neither results nor conclusions.
本注册报告详细阐述了一项研究的理论、方法和材料，该研究旨在确定德国高中学生阅读和数学能力发展的潜在特征。预计将确定一般（阅读和数学能力发展相似）和专门（一个领域发展更快）的能力特征。此外，假设学生的特定领域兴趣和教育背景将预测这些潜在特征的成员资格，因为这些因素会影响学生的学习环境。对于这项研究，我们将使用德国国家教育面板研究的数据，包括来自中学九年级的学生（预计 N = 14,500）。这些学生在六年中被跟踪，并在三个时间点提供能力评估。基于学生阅读和数学能力的潜在特征将使用潜在增长混合建模来确定。如果可以确定不同类型的特征，将使用多项回归来分析学生特定领域的兴趣或教育背景是否会影响属于特定能力发展特征的可能性。由于本协议在进行任何分析之前提交，因此不会提供结果或结论。
