2017
DOI: 10.21449/ijate.319486
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Using the 2006 PISA Questionaire to Evaluate the Measure of Educational Resources: A Rasch Measurement Approach

Abstract: Article InfoSchool educational resources are key when studying school improvement due to their influence on learning outcomes. Because of this, careful attention should be given to the way educational resources are operationalized and measured. Using the 2006 PISA American sample containing 166 schools, this study aims to validate the 13-item PISA School Educational Resource Scale with Rasch analysis. Winsteps software was used in the analysis and results were used to evaluate how well the instrument measured … Show more

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Cited by 4 publications
(6 citation statements)
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“…It is explained based on the underlying logic that subjects have a higher probability of correctly answering (i.e., endorsing) easier items and a lower probability of correctly answering more difficult ones [41]. Rasch analysis has been successfully used in multiple disciplines including human sciences, health [42], mathematics [43], and education [44]. Recently, the field of geoscience has witnessed an increasing number of Rasch analysis applications [45].…”
Section: Discussionmentioning
confidence: 99%
“…It is explained based on the underlying logic that subjects have a higher probability of correctly answering (i.e., endorsing) easier items and a lower probability of correctly answering more difficult ones [41]. Rasch analysis has been successfully used in multiple disciplines including human sciences, health [42], mathematics [43], and education [44]. Recently, the field of geoscience has witnessed an increasing number of Rasch analysis applications [45].…”
Section: Discussionmentioning
confidence: 99%
“…Applying the MFRM (Linacre, 1989) to evaluate judge severity in the CR scoring process addresses the limitations of CTT approaches (Boone et al, 2016). MFRM is an extension of the Rasch model (Rasch, 1960(Rasch, , 1980 that is widely applied in STEM education in the construction of large-scale MC assessments such as the Programme for International Student Assessment (PISA) (e.g., Liu, Sun, Yuan, & Bradley, 2017) and Trends in International Mathematics and Science Study (TIMMS) (e.g., Harwell, Moreno, Phillips, Buzey, Moore, & Roehrig, 2015). This model has been increasingly applied in science education to study and construct learning progressions of students understanding of science concepts (e.g., Fulmer, 2015;Herman-Abbel & DeBoer, 2018).…”
Section: Many-faceted Rasch Model For Analyzing Constructed-responses In Stemmentioning
confidence: 99%
“…Beyond the classroom, there are also essential factors in the school environment that support student learning and achievement (Gimenez & Ciobanu, 2021;Liu et al, 2017;Saeki & Quirk, 2015;Laftman et al, 2017). For example, Gimenez and Ciobanu (2021) concluded that the peer effect is essential for academic performance.…”
Section: Introductionmentioning
confidence: 99%
“…The class composition according to gender or race, students' ability, and their socio-economic levels are the most commonly used characteristics to measure peer effect. Furthermore, each school has different learning resources, including basic infrastructure, materials, and teaching resources (Liu et al, 2017). These issues were frequently linked to school financing sources and the overall quantity of resources available.…”
Section: Introductionmentioning
confidence: 99%