Browsing by Author "Eryilmaz, Nurullah"

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    A critical evaluation of alignment optimization for improving cross- national comparability in international large-scale assessments
    (2025) Sandoval-Hernández, Andrés; Carrasco Ogaz, Diego Alonso; Eryilmaz, Nurullah
    This study critically examines the use of alignment optimization to improve cross-national comparability of teacher and principal scales from the Teaching and Learning International Survey (TALIS) 2018. By investigating key psychometric properties, including dimensionality, reliability, and measurement invariance, the study highlights critical challenges in international large-scale assessments. While unidimensionality and high internal consistency were established for all scales, traditional multiple-group confirmatory factor analysis (MGCFA) suggested that scalar invariance could not be fully established for most scales, raising concerns about the robustness of cross-national comparisons under strict invariance assumptions. In contrast, alignment optimization emerged as a flexible and robust method, significantly enhancing the comparability of principal scales, all of which met alignment criteria. However, persistent challenges were identified for many teacher scales, which fell below alignment thresholds, emphasizing unresolved methodological complexities. This study demonstrates the transformative potential of alignment optimization for advancing psychometric rigor in global educational research and underscores the need for innovative approaches to address lingering comparability issues in international assessments.
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    Survey data on the impact of COVID-19 on parental engagement across 23 countries
    (Policy Press, 2021) Osorio Saez, Eliana Maria; Eryilmaz, Nurullah; Sandoval Hernandez, Andres; Lau, Yui yip; Barahona, Elma; Bhatti, Adil Anwar; Ofoe, Godfried Caesar; Ordonez, Levi Astul Castro; Ochoa, Artemio Arturo Cortez; Pizarro, Rafael Angel Espinoza; Aguilar, Esther Fonseca; Isac, Maria Magdalena; Dhanapala, K. V.; Kameshwara, Kalyan Kumar; Contreras, Ysrael Alberto Martinez; Mekonnen, Geberew Tulu; Mejia, Jose Fernando; Miranda, Catalina; Moh'd, Shehe Abdalla; Ulloa, Ricardo Morales; Morgan, K. Kayon; Morgan, Thomas Lee; Mori, Sara; Nde, Forti Ebenezah; Panzavolta, Silvia; Parcerisa, Lluis; Paz, Carla Leticia; Picardo, Oscar; Pineros, Carolina; Rivera Vargas, Pablo; Rosa, Alessia; Saldarriaga, Lina Maria; Aberastury, Adrian Silveira; Tang, Y. M.; Taniguchi, Kyoko; Trevino, Ernesto; Celis, Carolina Valladares; Villalobos, Cristobal; Zhao, Dan; Zionts, Allison
    This data article describes the dataset of the International COVID-19 Impact on Parental Engagement Study (ICIPES). ICIPES is a collaborative effort of more than 20 institutions to investigate the ways in which, parents and caregivers built capacity engaged with children's learning during the period of social distancing arising from global COVID-19 pandemic. A series of data were collected using an online survey conducted in 23 countries and had a total sample of 4,658 parents/caregivers. The description of the data contained in this article is divided into two main parts. The first part is a descriptive analysis of all the items included in the survey and was performed using tables and figures. The second part refers to the construction of scales. Three scales were constructed and included in the dataset: "parental acceptance and confidence in the use of technology", "parental engagement in children's learning" and "socioeconomic status". The scales were created using Confirmatory Factor Analysis (CFA) and Multi-Group Confirmatory Analysis (MG-CFA) and were adopted to evaluate their cross-cultural comparability (i.e., measurement invariance) across countries and within subgroups. This dataset will be relevant for researchers in different fields, particularly for those interested in international comparative education. (C) 2021 The Author(s). Published by Elsevier Inc.