A latent profile analysis and structural equation modeling of the instructional quality of mathematics classrooms based on the PISA 2012 results of Korea and Singapore

Yi, Hyun Sook; Lee, Yuree

doi:10.1007/s12564-016-9455-4

Cited by 39 publications

(33 citation statements)

References 22 publications

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“…Only a minority of studies reported on learning outcomes related to specific mathematics or science knowledge. We recognise that the measurement of learning in mathematics and science is not unproblematic (Duit & Treagust, 2003;Yi & Lee, 2017). Nevertheless, the impact of studies in this field would be increased if more studies reported on mathematics or science learning outcomes arising from specific pedagogical interventions combined with the use of apps.…”

Section: Focus On Student Learning Outcomesmentioning

confidence: 98%

Mobile learning for science and mathematics school education: A systematic review of empirical evidence

Bano

Zowghi

Kearney

et al. 2018

Computers & Education

231

146

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The ubiquity, flexibility, ease of access and diverse capabilities of mobile technologies make them valuable and a necessity in current times. However, they are under-utilized assets in mathematics and science school education. This article analyses the high quality empirical evidence on mobile learning in secondary school science and mathematics education. Our study employed a Systematic Literature Review (SLR) using well-accepted and robust guidelines. The SLR resulted in the detailed analysis of 49 studies (60 papers) published during 2003-2016. Content and thematic analyses were used to ascertain pedagogical approaches, methodological designs, foci, and intended and achieved outcomes of the studies. The apps and technologies used in these studies were further classified for domain, type and context of use. The review has highlighted gaps in existing literature on the topic and has provided insights that have implications for future research.

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Section: Focus On Student Learning Outcomesmentioning

confidence: 98%

Mobile learning for science and mathematics school education: A systematic review of empirical evidence

Bano

Zowghi

Kearney

et al. 2018

Computers & Education

231

146

View full text Add to dashboard Cite

show abstract

“…It also suggests that different profiles of ICT use exist, therefore contrasting the null hypothesis that there is only one latent profile. At the same time, the decrease in information criteria with larger numbers of profiles is natural as model complexity increases (Yi & Lee, 2016). Against this background, Morin and Marsh (2015) proposed using an "elbow plot" in order to present the changes in information criteria with increasing numbers of profiles.…”

Section: Latent Profile Analysismentioning

confidence: 99%

Students' profiles of ICT use: Identification, determinants, and relations to achievement in a computer and information literacy test

Scherer

Rohatgi

Hatlevik

2017

Computers in Human Behavior

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Current debates on students' use of information and communication technology (ICT) have brought to attention profiles and purposes of ICT use in either school-related or recreational contexts. Examining these two contexts at the same time, the present study seeks to identify student profiles of ICT use on the basis of the Norwegian International Computer and Information Literacy Study (ICILS) 2013 data (N = 2,426). In order to explore profiles of ICT use in schools and at home for different purposes such as recreation, study purposes, exchanging information, and social communication, we take a person-centered approach and apply latent profile analysis. These analyses revealed two independent user profiles and showed that background characteristics (i.e., gender, immigration status) and motivational constructs (i.e., self-efficacy, interest, and enjoyment in ICT) play a significant role in determining profile membership. Significant differences between the user profiles in students' computer and information literacy test performance did not exist. Given that the coverage of ICT at home and in schools has increased substantially over the last decades, the identification of user profiles informs teachers and parents about whether or not students exploit these opportunities to the same extent. Implications for future research and practice are discussed.

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“…As research indicated that there could be two causal directions between them (Carey et al, 2016); MA also leads to lower level of mathematics attitudes and they often go together and reduce mathematics involvement and achievement (Hembree, 1990). Many other cultural factors could influence mathematics performance, such as the gender and race stereotypes, instruction quality and learning time, teacher and parent expectation (e.g., Ganley and Vasilyeva, 2014; Leslie et al, 2015; Yi and Lee, 2016). This may explain why the relationship between MA and mathematics performance among different countries is not consistent, for instance, Finland demonstrated low level of MA and high mathematics achievement, while Korea had high MA but high level of mathematics performance too.…”

Section: Discussionmentioning

confidence: 99%

Profiles of Mathematics Anxiety Among 15-Year-Old Students: A Cross-Cultural Study Using Multi-Group Latent Profile Analysis

2019

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Using PISA 2012 data, the present study explored profiles of mathematics anxiety (MA) among 15-year old students from Finland, Korea, and the United States to determine the similarities and differences of MA across the three national samples by applying a multi-group latent profile analysis (LPA). The major findings were that (a) three MA profiles were found in all three national samples, i.e., Low MA, Mid MA, and High MA profile, and (b) the percentages of students classified into each of the three MA profiles differed across the Finnish, Korean, and American samples, with United States having the highest prevalence of High MA, and Finland the lowest. Multi-group LPA also provided clear and useful latent profile separation. The High MA profile demonstrated significant poorer mathematics performance and lower mathematics interest, self-efficacy, and self-concept than the Mid and Low MA profiles. Same differences appeared between the Mid and Low MA profiles. The implications of the findings seem clear: (1) it is possible that there is some relative level of universality in MA among 15-year old students which is independent of cultural context; and (2) multi-group LPA could be a useful analytic tool for research on the study of classification and cultural differences of MA.

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A latent profile analysis and structural equation modeling of the instructional quality of mathematics classrooms based on the PISA 2012 results of Korea and Singapore

Cited by 39 publications

References 22 publications

Mobile learning for science and mathematics school education: A systematic review of empirical evidence

Mobile learning for science and mathematics school education: A systematic review of empirical evidence

Students' profiles of ICT use: Identification, determinants, and relations to achievement in a computer and information literacy test

Profiles of Mathematics Anxiety Among 15-Year-Old Students: A Cross-Cultural Study Using Multi-Group Latent Profile Analysis

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