TEACHER EFFECTS ON HIGH SCHOOLACADEMIC ACHIEVEMENT SCORES: A CASE STUDY OF BUSIA COUNTY, KENYA

2021 ◽  
pp. 131-139
Author(s):  
Julius Maiyo ◽  
Manasi Echaune
Keyword(s):  
Academic Achievement ◽  
Hierarchical Linear Modeling ◽  
Teacher Commitment ◽  
Achievement Scores ◽  
Linear Modeling ◽  
Teacher Effects ◽  
Education Production Function ◽  
Education Production ◽  
Descriptive Survey

ABSTRACT This study sought to analyze teacher effects on high school academic achievement scores in Busia County, Kenya. The study was based on the education production function theory. A descriptive survey research design was employed. A sample of 236 teachers and 755 students was used. Self administered questionnaires were used to collect data and test re-test was used to ascertain reliability of the instrument. Descriptive statistics namely; percentages, frequencies, mean, and standard deviations were used to carry out preliminary data analysis. Inferential statistics specifically correlation and regression coefficients were then used to test hypotheses. Hierarchical linear modeling was used to model effect of selected teacher variables on school academic achievement scores. Findings of the study were presented in tables and figures. Findings of the study suggested that the number of teachers, teacher commitment and teachers covering missed lessons had statistically significant effects on school academic achievement scores. Key words: Teacher Variables, Academic Achievement Scores, Kenya

scholarly journals Examining the Relations Between Self-Regulation and Achievement in Third-Grade Students

2016 ◽  
Vol 42 (2) ◽  
pp. 97-109 ◽  
Author(s):  
Stephanie L. Day ◽  
Carol McDonald Connor
Keyword(s):  
Academic Achievement ◽  
Working Memory ◽  
Inhibitory Control ◽  
Hierarchical Linear Modeling ◽  
Self Regulation ◽  
Scoring Systems ◽  
Third Grade ◽  
Linear Modeling ◽  
Third Grade Students ◽  
Study Results

Children with stronger self-regulation skills generally demonstrate greater overall success in school both academically and socially. However, there are few valid and reliable measures of self-regulation in middle elementary school. Such a measure could help identify whether a child is truly having difficulties. Thus, the Remembering Rules and Regulation Picture Task (RRRP) was developed. The aim of this study was to develop scoring systems for the RRRP and then to examine the associations between RRRP and independent measures of self-regulation and academic achievement in mathematics and reading. Children ( N = 282) from 34 third-grade classrooms in Florida participated in this study. Results revealed that the RRRP captured three constructs: working memory, attentional flexibility, and inhibitory control. Hierarchical linear modeling (HLM) demonstrated that the RRRP was significantly and positively associated with other measures of self-regulation. The RRRP was significantly and positively associated with mathematics and reading as well. The RRRP appears to be a promising measure of children’s self-regulation skills.

scholarly journals Examining the Effects of Students and School Variables on PISA 2012 Problem-Solving Achievement in Turkey

2017 ◽  
Vol 2 (5) ◽  
Author(s):  
Emine Yavuz ◽  
Hakan Yavuz Atar
Keyword(s):  
Problem Solving ◽  
Hierarchical Linear Modeling ◽  
School Attendance ◽  
Hierarchical Linear Model ◽  
School Level ◽  
School Type ◽  
Achievement Scores ◽  
Linear Modeling ◽  
Problem Solving Skills ◽  
Pisa 2012

Problem-solving skills are very important in ensuring effective participation in public life regard and schools play an important role in helping students develop problem-solving skills. The purpose of this study is to determine the student and school level variables that effect students’ problem solving skills using a two-level Hierarchical Linear Modeling (HLM). The data in this study is belongs to 4848 students in 170 schools who participated PISA 2012. Gender, school attendance, openness to problem-solving and perseverance to reach solution variables constituted the student level variables whereas school type, educational resources, dropout rates and student/math teacher ratio variables constituted the school level variables. The findings indicated that all the variables but openness and perseverance have statistically significant effect on students’ PISA 2012 problem-solving achievement scores. The results of the analysis indicate that 54 percent of the variability in the problem-solving achievement scores is attributed to the differences between the mean achievement of the schools. Keywords: PISA; Problem solving; School effect; Two-level Hierarchical Linear Model (HLM) 

The Relation Between the Academic Achievement of Students With Emotional and Behavioral Disorders and Teacher Characteristics

2017 ◽  
Vol 43 (1) ◽  
pp. 213-222 ◽  
Author(s):  
Nicholas A. Gage ◽  
Reesha Adamson ◽  
Ashley S. MacSuga-Gage ◽  
Timothy J. Lewis
Keyword(s):  
Academic Achievement ◽  
Students With Disabilities ◽  
Behavioral Disorders ◽  
Hierarchical Linear Modeling ◽  
Teacher Characteristics ◽  
Years Of Experience ◽  
Linear Modeling ◽  
Data Set ◽  
Nationally Representative ◽  
Students With Ebd

Teachers of students with emotional and/or behavioral disorders (EBD) are less experienced and more likely to have emergency certification than teachers of students with other disabilities. Yet, to date, research has not examined the relation between the academic achievement of students with EBD and characteristics associated with highly qualified teachers (teachers’ education level, certification status, and years of experience). Using a nationally representative longitudinal data set of students with disabilities, this study examined the relation between teacher characteristics and the academic achievement of students with EBD. Using hierarchical linear modeling, the study found low academic achievement for students with EBD, null effects for change in achievement across time, and null effects for the relation between (a) teachers’ educational level, certification status, and years of experience and (b) student academic achievement. Results indicate further research is needed to examine whether and how teacher characteristics may impact the academic achievement of students with EBD.

scholarly journals Spatial Heterogeneity of Plant Diversity within and between Neighborhoods and Its Implications for a Plant Diversity Survey in Urban Areas

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 416
Author(s):  
Yuebo Su ◽  
Cheng Gong ◽  
Bowen Cui ◽  
Peipei Guo ◽  
Zhiyun Ouyang ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Plant Species ◽  
Plant Diversity ◽  
Hierarchical Linear Modeling ◽  
Urban Areas ◽  
Urban Neighborhoods ◽  
Linear Modeling ◽  
The Mean ◽  
Neighborhood Scale

The spatial heterogeneity of plant diversity at the neighborhood scale has less been understood, although it is very important for the planning and management of neighborhood landscape. In this case study of Beijing, we conducted intensive investigations of the plant diversity in different neighborhoods along a rural–urban gradient. The results showed that the mean numbers of plant species per neighborhood were 30.5 for trees, 18.8 for shrubs, and 31.9 for herbs, respectively. There were significant logarithmic relationships between the numbers of species and patch area, indicating that larger patches within neighborhoods could harbor more plant species. Hierarchical linear modeling showed that the variations in plant diversity within neighborhoods were higher than those between neighborhoods. The number of species increased logistically with both the number of patches within neighborhoods and the number of neighborhoods, suggesting that it is important to sample a sufficient number of patches within neighborhoods, as well as a sufficient number of neighborhoods in order to sample 90% of the plant species during the investigation of plant diversity in urban neighborhoods. So the hierarchical design of sampling should be recommended for investigating plant diversity in urban areas.

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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