Related Experiment Video
Updated: Jul 11, 2025

06:52
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
6.4K
A Parallel Process Growth Curve Analysis of Teacher-Student Relationships and Academic Achievement
Daniel B Hajovsky1, Steven R Chesnut2, Morgan K Sekula1
1Texas A&M University, College Station, TX, USA.
The Journal of Genetic Psychology
|November 10, 2023
Summary
Positive teacher-student relationships (TSR) in kindergarten boost academic achievement through third grade. Negative relationships hinder early academic success, highlighting the importance of supportive teacher-student connections for student growth.
Area of Science:
- Developmental Psychology
- Educational Psychology
- Child Development
Background:
- Teacher-student relationships (TSR) are crucial for academic outcomes.
- Longitudinal co-development of TSR and achievement in elementary grades is understudied.
- Most research focuses on reading and math, neglecting other subjects.
Purpose of the Study:
- To examine the longitudinal growth trajectories of teacher-student closeness and conflict.
- To investigate the simultaneous development of TSR and achievement in science, reading, and mathematics.
- To analyze these trends from kindergarten to third grade.
Main Methods:
- Utilized parallel process growth curve models (PPGCMs).
- Analyzed data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010-2011 (N=13,490).
- Tracked children from kindergarten through third grade.
Main Results:
- Kindergarten teacher-student closeness positively predicted achievement in science, reading, and math, and its growth.
- Kindergarten teacher-student conflict negatively predicted achievement and its growth.
- Child sex, socioeconomic status, and racial/ethnic identity influenced TSR and achievement trends.
Conclusions:
- Early teacher-student relationships significantly impact academic trajectories.
- Supportive relationships foster achievement growth, while conflict impedes it.
- Demographic factors play a role in the co-development of TSR and achievement.
Related Concept Videos
Correlations
32.8K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
32.8K
Comparing Experimental Results: Student's t-Test
1.6K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
1.6K
Longitudinal Research
12.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.0K
Cross-Sectional Research
11.3K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
11.3K
Multiple Bar Graph
5.2K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
5.2K
Longitudinal Studies
171
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
171

