Identifying Turkish students’ profiles of using information and communication technologies and its relationship with their academic achievement: A latent class analysis approach

2021 ◽  
pp. 204275302110609
Author(s):  
Ferit Karakoyun ◽  
Bülent Başaran
Keyword(s):  
Academic Achievement ◽  
Latent Class Analysis ◽  
Information And Communication Technologies ◽  
Science Achievement ◽  
Latent Class ◽  
Student Assessment ◽  
Class Analysis ◽  
International Student Assessment ◽  
High Level ◽  
At Home

In this study, 15-year-old Turkish students’ profiles of using ICT at home and at school were identified, and the extent to which these profiles were associated with their academic achievement was determined. Moreover, the study investigated the effects of the students’ age of first usage of digital device and internet, their gender and their parents’ education level on the students’ ICT usage profiles. In the study, by using Latent Class Analysis, Program for International Student Assessment (PISA) 2018 Turkey data were analyzed ( n = 6890). According to the findings obtained in the study, it was revealed that the students who used ICT resources at high level at home and at school constituted the smallest class (8% of the sample). The students whose mothers’ levels of education were high and those who were male had a higher probability of being a member of the high-level ICT user class. In addition, the students who started using their first digital devices and the Internet at later ages were less likely to be a member of the class using high-level ICT. Finally, the students in the high-level ICT user class had low mathematics, reading, and science achievement scores.

scholarly journals Characterizing Work-Related Smartphone Use at Home and Private Smartphone Use at Work Using Latent Class Analysis

2019 ◽  
Vol 3 (2) ◽  
pp. 187-203 ◽  
Author(s):  
Jonas Dora ◽  
Madelon L. M. van Hooff ◽  
Sabine A. E. Geurts ◽  
Wendela E. Hooftman ◽  
Michiel A. J. Kompier
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
Work Related ◽  
Smartphone Use ◽  
At Home

Latent class analysis of bladder urothelial carcinoma to reveal sub-classes defined by alterations to chromatin and signal transduction networks.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 469-469
Author(s):  
Alex Fichtenholtz ◽  
Alyna Khan ◽  
Jeffrey S. Ross ◽  
Siraj Mahamed Ali ◽  
Vincent A. Miller ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Latent Class Analysis ◽  
Urothelial Carcinoma ◽  
Latent Class ◽  
The United States ◽  
Response To Therapy ◽  
Tumor Type ◽  
Class Analysis ◽  
Bladder Urothelial Carcinoma ◽  
High Level

469 Background: 70,000 new cases of bladder urothelial carcinoma are diagnosed in the United States each year. Previous studies of this disease suggest two divergent pathways of carcinogenesis, with ~70% of cases being driven by alterations in signal transduction pathways (FGFR3, HRAS) and the remainder featuring alterations in cell cycle genes (TP53, RB1). Other studies focus on the high prevalence of alterations in chromatin remodeling genes (ARID1A, CREBBP, EP300) in this tumor type. The relationship between chromatin modifier alterations and the two bladder TCC sub-classes is not yet understood. Methods: Comprehensive genomic profiling (CGP) on 638 clinically confirmed cases of advanced bladder urothelial carcinoma was performed using the FoundationOne platform. The coding exons of 287 cancer-related and 47 introns of 19 genes frequently rearranged in cancer were sequenced and analyzed for base substitutions, insertions, deletions, copy number alterations and select gene fusions. The resultant alteration profiles were analyzed for their information content with an entropy-based approach and the profiles were subjected to hierarchical latent class analysis (LCA). Results: CGP of 488 male and 150 female UCs of median age 66 (min: 29, max: 87) resulted in 3241 detected alterations across 302 unique genes, for a mean of ~5.1 known or likely somatic alterations per sample. The most commonly altered genes were TP53, CDKN2A/B, ARID1A, KDM6A, and MLL2. Information was concentrated in the 33 most frequently altered genes. Multiple high level clusters were defined by combinatorial patterns of alterations in TP53, CDKN2A/B, RB1, and FGFR3. Sub-classes were defined by mutually exclusive alterations in the chromatin modifiers KDM6A, MLL2, and ARID1A. Conclusions: We present a global picture of UC sub-classes that encompasses previously identified local relationships including the mutual exclusivities between FGFR3 and TP53, RB1 and CDKN2A/B, and KDM6A and MLL2. In the context of clinically relevant genomic alterations that auger response to targeted therapies, identification of sub-classes of UC may further delineate response to therapy.

Teacher Behaviours Explaining Turkish and Dutch Students’ Mathematic Achievements

2017 ◽  
Vol 6 (2) ◽  
pp. 174
Author(s):  
Seher Yalcın
Keyword(s):  
The Netherlands ◽  
Formative Assessment ◽  
Student Performance ◽  
International Student ◽  
Latent Class ◽  
Student Assessment ◽  
Teacher Behavior ◽  
Student Orientation ◽  
International Student Assessment ◽  
High Level

The purpose of this study was to examine the differences between Turkish and Dutch students’ mathematics achievement and to examine the predictive level of teacher behaviours for student performance. The participants were 3210 students and principals from 168 schools in Turkey and 2541 students and principals from 156 schools in the Netherlands, who attended the Program for International Student Assessment in 2012. According to the results of the multilevel latent class and three-step analyses, for both countries, teacher behavior related to student orientation, teacher focus on student achievement and formative assessment predicted the mathematical achievement. It is seen that a high level of teacher behavior related to student orientation and formative assessment plays an important role in schools’ achievement at very low, low, and low-medium levels for Turkey and at medium and medium-high levels for the Netherlands. Furthermore, it was determined that the students who had low- or medium-level achievement were more affected by teacher characteristics/behaviours.

scholarly journals Should I Stay or Should I Go Home? A Latent Class Analysis of a Discrete Choice Experiment on Hospital-At-Home

2014 ◽  
Vol 17 (5) ◽  
pp. 588-596 ◽  
Author(s):  
Lucas M.A. Goossens ◽  
Cecile M.A. Utens ◽  
Frank W.J.M. Smeenk ◽  
Bas Donkers ◽  
Onno C.P. van Schayck ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Latent Class ◽  
Class Analysis ◽  
Hospital At Home ◽  
At Home

Exploring e-maturity in Italian local governments: empirical results from a three-step latent class analysis

2021 ◽  
pp. 002085232110127
Author(s):  
Luca Tangi ◽  
Mara Soncin ◽  
Tommaso Agasisti ◽  
Giuliano Noci
Keyword(s):  
Latent Class Analysis ◽  
Local Governments ◽  
Latent Class ◽  
Holistic Approach ◽  
Class Analysis ◽  
Business Services ◽  
Secondary Sources ◽  
Novel Approach ◽  
Local Government Level ◽  
High Level

This article undertakes a quantitative and holistic approach to frame a model of e-maturity in local governments, defined as the extent to which technologies permeate public service delivery. Moreover, the study adds evidence on the performance associated with different levels of e-maturity. In so doing, we collect survey data from 814 Italian local governments and integrate it with secondary sources. We propose a new angle for assessing e-maturity at the local government level, where the novel approach is the categorisation of public services on the basis of their final users. The application of a latent class analysis shows that the level of e-maturity is quite limited among Italian local governments and that most of them tend to prioritise government-to-business rather than government-to-citizen services in their digitisation process. A high level of e-maturity is associated with greater effectiveness rather than efficiency. Points for practitioners • When assessing e-maturity, municipalities should treat differently Government to Citizen and Government to Business services. • Currently, municipalities are focused more on the digitization of Government to Business services. • Socio-economic and environmental factors have a partial effect on e-maturity. The size of the municipality and the income per capita are the most significant indicators. • E-maturity raises effectiveness without a clear effect on efficiency. Only when reaching a fully accomplished e-maturity a slight effect on municipalities' expenditures can be detected.

scholarly journals Patterns of compliance with COVID-19 preventive behaviours: a latent class analysis of 20 000 UK adults

2021 ◽  
pp. jech-2021-216876
Author(s):  
Liam Wright ◽  
Andrew Steptoe ◽  
Daisy Fancourt
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Multinomial Logistic Regression ◽  
Social Study ◽  
Self Report ◽  
Class Analysis ◽  
Cross Sectional ◽  
Social Distancing ◽  
Personality Predictors ◽  
High Level

BackgroundGovernments have implemented a range of measures to tackle COVID-19, primarily focusing on changing citizens’ behaviours in order to lower the transmission of the virus. Few studies have looked at the patterns of compliance with different measures within individuals: whether people comply with all measures or selectively choose some but not others. Such research is important for designing interventions to increase compliance.MethodsWe used cross-sectional data from 20 947 UK adults in the COVID-19 Social Study collected from 17 November to 23 December 2020. Self-report compliance was assessed with six behaviours: mask wearing, hand washing, indoor household mixing, outdoor household mixing, social distancing and compliance with other guidelines. Patterns of compliance behaviour were identified using latent class analysis, and multinomial logistic regression was used to assess demographic, socioeconomic and personality predictors of behaviour patterns.ResultsWe selected a four-latent class solution. Most individuals reported similar levels of compliance across the six behaviour measures. High level of compliance was the modal response. Lower self-reported compliance was related to young age, high risk-taking behaviour, low confidence in government and low empathy, among other factors. Looking at individual behaviours, mask wearing had the highest level of compliance while compliance with social distancing was relatively low.ConclusionResults suggest that individuals choose to comply with all guidelines, rather than some but not others. Strategies to increase compliance should focus on increasing general motivations to comply alongside specifically encouraging social distancing.

scholarly journals Latent Class Analysis of Recurrent Events in Problem-Solving Items

2018 ◽  
Vol 42 (6) ◽  
pp. 478-498 ◽  
Author(s):  
Haochen Xu ◽  
Guanhua Fang ◽  
Yunxiao Chen ◽  
Jingchen Liu ◽  
Zhiliang Ying
Keyword(s):  
Problem Solving ◽  
Latent Class Analysis ◽  
Recurrent Events ◽  
Latent Class ◽  
Complex Problem ◽  
Class Analysis ◽  
Complex Problem Solving ◽  
Climate Control ◽  
Process Data ◽  
International Student Assessment

Computer-based assessment of complex problem-solving abilities is becoming more and more popular. In such an assessment, the entire problem-solving process of an examinee is recorded, providing detailed information about the individual, such as behavioral patterns, speed, and learning trajectory. The problem-solving processes are recorded in a computer log file which is a time-stamped documentation of events related to task completion. As opposed to cross-sectional response data from traditional tests, process data in log files are massive and irregularly structured, calling for effective exploratory data analysis methods. Motivated by a specific complex problem-solving item “Climate Control” in the 2012 Programme for International Student Assessment, the authors propose a latent class analysis approach to analyzing the events occurred in the problem-solving processes. The exploratory latent class analysis yields meaningful latent classes. Simulation studies are conducted to evaluate the proposed approach.

scholarly journals A Partial Simulation Study of Phantom Effects in Multilevel Analysis of School Effects: The Case of School Socioeconomic Composition

2021 ◽  
pp. 004912412098619
Author(s):  
Hao Zhou ◽  
Xin Ma
Keyword(s):  
Academic Achievement ◽  
Hierarchical Linear Modeling ◽  
Science Achievement ◽  
International Student ◽  
Student Assessment ◽  
The United States ◽  
Linear Modeling ◽  
Real World Data ◽  
International Student Assessment ◽  
School Ses

Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe the phenomenon in which the effects of student SES and school SES disappear once prior academic achievement is added to the model. In the present analysis, partial simulation (i.e., simulated data are used together with real-world data) was employed to examine the phantom effects of student SES and school SES on science achievement, using the national sample of the United States from the 2015 Programme for International Student Assessment. The results showed that the phantom effects of student SES and school SES are rather real. The stronger the correlation between prior science achievement and (present) science achievement, the greater the chance that the phantom effects occur.

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