scholarly journals Appropriate Internet Use Behavior (AIUB) of Thai Preservice Teachers: A Hierarchical Linear Model (HLM) Analysis

2022 ◽  
Vol 15 (1) ◽  
pp. 489-508
Author(s):  
Paitoon Pimdee ◽  
◽  
Punnee Leekitchwatana ◽  
Author(s):  
Punnee Leekitchwatana ◽  
Paitoon Pimdee

The research used a hierarchical linear model to develop a model to study the variables of appropriate Internet use of 2,400 Thai high school students from 48 high schools. Furthermore, the groups were divided into one group of 1,200 students in science related programs, while the second group of 1,200 students were in a non-science related program. The data collection instrument was a reliability questionnaire which was determined to range between 0.75-0.97. Data were analysed using statistical averages, standard deviation, and analysis of hierarchical linear models (HLM). The research found that Thai high school students have appropriate Internet use behaviour at a very appropriate level, while the HLM of appropriate Internet use behaviour of students contained two predictive variables at both the student level and school level. These included the four student predictive variables of ability, characteristic, family, and student grade point average (GPA). At the school level in the HLM, there were two predictor variables including friends and schools, which had a direct influence and an indirect influence, respectively. There were also six capacity variables having both positive influence and statistical significance.


2020 ◽  
Vol 146 (2) ◽  
pp. 04020010 ◽  
Author(s):  
Liyuan Zhao ◽  
Shuxian Wang ◽  
Jialing Wei ◽  
Zhong-Ren Peng

2017 ◽  
Vol 20 (1) ◽  
pp. 70-76
Author(s):  
Barbara St. Pierre Schneider ◽  
Ed Nagelhout ◽  
Du Feng

Background: To report the complexity and richness of study variables within biological nursing research, authors often use tables; however, the ease with which consumers understand, synthesize, evaluate, and build upon findings depends partly upon table design. Objectives: To assess and compare table characteristics within research and review articles published in Biological Research for Nursing and Nursing Research. Method: A total of 10 elements in tables from 48 biobehavioral or biological research or review articles were analyzed. To test six hypotheses, a two-level hierarchical linear model was used for each of the continuous table elements, and a two-level hierarchical generalized linear model was used for each of the categorical table elements. Additionally, the inclusion of probability values in statistical tables was examined. Results: The mean number of tables per article was 3. Tables in research articles were more likely to contain quantitative content, while tables in review articles were more likely to contain both quantitative and qualitative content. Tables in research articles had a greater number of rows, columns, and column-heading levels than tables in review articles. More than one half of statistical tables in research articles had a separate probability column or had probability values within the table, whereas approximately one fourth had probability notes. Conclusions: Authors and journal editorial staff may be generating tables that better depict biobehavioral content than those identified in specific style guidelines. However, authors and journal editorial staff may want to consider table design in terms of audience, including alternative visual displays.


Biometrika ◽  
1980 ◽  
Vol 67 (3) ◽  
pp. 613-619 ◽  
Author(s):  
A. F. M. SMITH ◽  
I. VERDINELLI

2006 ◽  
Vol 14 ◽  
pp. 34
Author(s):  
Raciel Acevedo Alvarez ◽  
Nuria Mairena Rodríguez

The present study analyzes the variables that are intrinsically linked with the student, professor and class environment in relation to the university educational evaluation questionnaires. The participants in the study were 374 students with an age mean of 19.9 and 29 professors with an age mean of 36 from 3 different departments at the Universidad de Costa Rica (UCR) at the city of Guanacaste. The hierarchical lineal models were used for the data analysis, a quantitative methodology which facilitates the evaluation of the determinants which affect the results of the study. However, only four of these determinants were associated with the evaluation concerned, class size, enrolment year, department type and forecasted achievement levels. The results obtained from the study demonstrate that these kinds of evaluation are valid despite the results being slightly affected by a range of factors from externalities to teacher competence.


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