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Zexuan Pan; Maria Cutumisu – British Journal of Educational Psychology, 2024
Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…
Descriptors: Artificial Intelligence, Secondary School Students, Life Satisfaction, Foreign Countries
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Wang, Yi; King, Ronnel; Haw, Joseph; Leung, Shing on – Journal for the Study of Education and Development, 2023
Although Macau students have consistently been recognized as top performers in international assessments, little research has been conducted to explore the various factors that are associated with their achievement. This paper aimed to identify factors that could best predict Macau students' reading achievement using PISA 2018 data provided by…
Descriptors: Foreign Countries, High School Students, Reading Achievement, Predictor Variables
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Pedro San Martin Soares – Journal of Psychoeducational Assessment, 2024
Brazil's education system lags behind international standards, with two-fifths of students scoring below the minimum level of proficiency in mathematics, science, and reading. Thus, this study combined machine learning with traditional statistics to identify the most important predictors and to interpret their effects on proficiency in the PISA…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, International Assessment
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Bernardo, Allan B. I.; Cordel, Macario O., II; Lucas, Rochelle Irene G.; Teves, Jude Michael M.; Yap, Sashmir A.; Chua, Unisse C. – Education Sciences, 2021
Filipino students ranked last in reading proficiency among all countries/territories in the PISA 2018, with only 19% meeting the minimum (Level 2) standard. It is imperative to understand the range of factors that contribute to low reading proficiency, specifically variables that can be the target of interventions to help students with poor…
Descriptors: Foreign Countries, English (Second Language), Reading Ability, Artificial Intelligence
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Koyuncu, Ilhan – Journal of Curriculum and Teaching, 2020
This study aimed to examine the importance levels of mathematics-specific trend variables in PISA (Programme for International Student Assessment) 2003 and 2012 in predicting mathematics performance across years with a two-step analysis method. The sample of the study was 9703 Turkish students (N[subscript 2003]=4855 and N[subscript 2012]=4848)…
Descriptors: International Assessment, Foreign Countries, Secondary School Students, Achievement Tests
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Chung Hyewon; Kim, Jung-In; Jung, Eunjin; Park, Soyoung – International Journal of Educational Psychology, 2022
The Program for International Student Assessment (PISA) aims to provide comparative data on 15-year-olds' academic performance and well-being. The purpose of the current study is to explore and compare the variables that predict the reading literacy and life satisfaction of U.S. and South Korean students. The random forest algorithm, which is a…
Descriptors: Comparative Education, Predictor Variables, Literacy, Life Satisfaction
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Kismiantini; Setiawan, Ezra Putranda; Pierewan, Adi Cilik; Montesinos-López, Osval Antonio – Journal on Mathematics Education, 2021
Shifting students to a growth mindset can increase their achievements. Nevertheless, only a few studies have been conducted on this topic in developing countries. This study aims to examine the relationship between growth mindset, school context, and mathematics achievement in Indonesia. Using a multilevel model on the PISA 2018 data, this study…
Descriptors: Foreign Countries, International Assessment, Achievement Tests, Secondary School Students
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Immekus, Jason C.; Jeong, Tai-sun; Yoo, Jin Eun – Large-scale Assessments in Education, 2022
Large-scale international studies offer researchers a rich source of data to examine the relationship among variables. Machine learning embodies a range of flexible statistical procedures to identify key indicators of a response variable among a collection of hundreds or even thousands of potential predictor variables. Among these, penalized…
Descriptors: Foreign Countries, Secondary School Students, Artificial Intelligence, Educational Technology
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Bozak, Ali; Aybek, Eren Can – International Journal of Contemporary Educational Research, 2020
The present study aims to determine which analysis technique-Artificial Neural Networks (ANNs) or Logistic Regression (LR) Analysis-is better at predicting the science literacy success of the 15-year Turkish students who participated in PISA research carried out in 2015 by using learning time spent on science, test anxiety, environmental…
Descriptors: Artificial Intelligence, Networks, Regression (Statistics), Achievement Tests
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Gabriel, Florence; Signolet, Jason; Westwell, Martin – International Journal of Research & Method in Education, 2018
Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
Descriptors: Artificial Intelligence, Mathematics Instruction, Numeracy, Models
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Tariq, Vicki N.; Qualter, Pamela; Roberts, Sian; Appleby, Yvon; Barnes, Lynne – International Journal of Mathematical Education in Science and Technology, 2013
This empirical study explores the roles that Emotional Intelligence (EI) and Emotional Self-Efficacy (ESE) play in undergraduates' mathematical literacy, and the influence of EI and ESE on students' attitudes towards and beliefs about mathematics. A convenience sample of 93 female and 82 male first-year undergraduates completed a test of…
Descriptors: Emotional Intelligence, Self Efficacy, Undergraduate Students, Mathematics Instruction
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Hunt, Earl; Wittmann, Werner – Intelligence, 2008
What is the relation between the cognitive competence of a national population that nation's economic prosperity? Lynn and Vanhanen [Lynn, R. & Vanhanen, T. (2002). "IQ and the wealth of nations." Westport, CT: Praeger.] presented data pointing to an exceptionally strong relationship between IQ scores and Gross Domestic Product per…
Descriptors: Economic Impact, Correlation, Intelligence, Cognitive Ability