Teachers’ Job Satisfaction and Its Influence on Students’ Academic Performance in Public Secondary Schools: Practical Evidence from Kasese District, Uganda

Research objective

To examine the relationship between teachers’ job satisfaction and students’ academic performance in public secondary schools in Kasese District.

Research design

The study employed a cross-sectional research design, enabling data collection from the sample’s participants at a single point in time (Wang & Cheng, 2020). This approach was chosen for its relative speed and cost-efficiency in implementation.

Research approach

A mixed-methods approach was adopted, integrating both quantitative and qualitative techniques to gain a comprehensive understanding of the research issue. Quantitative data provided objective, measurable, and widely applicable insights, while qualitative data offered detailed, contextual perspectives. The combination of these methods facilitated a richer analysis, enabled validation through triangulation, and supported a more nuanced interpretation of complex concepts. Overall, the use of mixed methods enhanced the credibility, depth, and robustness of the study’s findings.

Target population and sample size

The target population of 1,162 respondents was drawn from eight public secondary schools in Kasese District, picking two schools from each of the four constituencies of Bukonzo West, Bukonzo East, Busongora South, and Busongora North. The population consisted of 8 head teachers, 246 teachers, and 908 senior four students. Senior four students were selected because they had spent four years in school and could provide credible information regarding performance. Students below 18 years were excluded. Therefore, the study employed a sample of 289 respondents using Cochran’s formula (1977) from the target population of 1,162 participants. See Table 1 for study population and Table 2 for sample size determination.

Data collection tools

In this study, data were obtained from both primary and secondary sources. Primary data were collected through interviews with head teachers and closed-ended self-administered questionnaires administered to students and teachers. The questionnaire was based on a five-point Likert scale ranging from 1 = Strongly Disagree, 2 = Disagree, 3 = Moderately Agree, 4 = Agree, to 5 = Strongly Agree, with appropriate alternatives provided in each section. Interviewing was guided by an interview guide. Secondary data, on the other hand, were sourced from journals and various open-access databases where pre-existing information was readily available. Primary data provided the most up-to-date and accurate information, while secondary data provided an opportunity for comparison.

Validity of quantitative

The questionnaire was reviewed and validated by five experts specializing in Education Management and Administration. These experts assessed the instruments for relevance, response consistency, and clarity regarding the study’s objectives. They also examined the items to ensure they aligned with and effectively addressed the research goals. Any necessary corrections suggested by the experts were incorporated into the final version of the questionnaire, particularly in the instructions for data collection.

Validity of qualitative data

The researchers conducted interviews until the saturation point was reached, when respondents began to repeat their responses in reaction to prompting questions. Additionally, the transcribed data were taken back to the respondents to verify their accuracy. If the participants confirmed that the transcripts accurately reflected their statements, the data were considered valid. In cases where discrepancies were identified, the data were reviewed, and necessary corrections were made.

Reliability of quantitative data

A pilot study was conducted to assess the feasibility of the research instruments, identify potential flaws, refine ambiguous items, and ensure alignment with the research objectives. Following this, reliability was evaluated using Cronbach’s Alpha, a widely accepted statistical measure for estimating the internal consistency and reliability of the instrument (Baker, 2020). An alpha coefficient of 0.84 was obtained, indicating a strong internal consistency, which suggests that the data collected through the instrument are reliable and can be confidently generalized to the target population. This approach to reliability testing enhances the credibility of the findings and demonstrates the robustness of the research instrument used in the study.

Reliability of qualitative data

After transcribing the data, the researcher identified the main ideas and then employed thematic analysis to systematically code and categorize the data. To ensure the reliability of the coding process, the identified themes and subthemes were independently reviewed and scored by an interrater. An interrater reliability test was conducted to assess the consistency of theme and subtheme generation between raters. A reliability index of 0.70 or higher was considered acceptable, indicating a satisfactory level of agreement and consistency in the coding process, thus supporting the validity of the qualitative analysis for the research objectives.

Methods of data collection

For the collection of quantitative data, a structured questionnaire was employed to gather information from participants regarding teachers’ attitudes towards job satisfaction and their influence on students’ academic performance in public secondary schools within Kasese district. The use of questionnaires was justified by their efficiency in collecting data from a large sample, enabling the straightforward statistical analysis of responses to identify patterns, trends, and correlations. Additionally, this approach is cost-effective and time-efficient, making it particularly suitable for capturing a broad perspective on the research variables and facilitating a comprehensive understanding of the phenomena under investigation. To obtain qualitative insights, semi-structured interviews with head teachers and focus group discussions with students were conducted. The interviews were designed as one-on-one sessions, allowing participants to express their views, experiences, and perceptions in their own words, with responses recorded and later transcribed for thematic analysis. Focus group discussions provided a platform for moderated, interactive conversations among groups of students, encouraging the exchange of diverse perspectives and collective insights. Both qualitative methods yielded rich, detailed data that were analyzed thematically to explore deeper meanings and contextual factors relevant to the research objectives.

Methods of data analysis

This study was conducted in eight public secondary schools in Kasese District, with the distribution of head teachers, teachers, and students across schools summarized in Table 1. A stratified sampling strategy allocated the sample across respondent groups and schools, and sample size computation and allocation by stratum are shown in Table 2. Data collection involved questionnaires administered to teachers and students, alongside semi-structured interviews and focus group discussions with head teachers and students; achieved sample sizes and response rates by group are presented in Table 3. Quantitative data were analyzed in IBM SPSS Statistics version 25.0 using both descriptive and inferential techniques: results were produced at a significance level of 0.05, descriptive findings were displayed in frequency distribution tables, and inferential analyses employed the Pearson product–moment correlation coefficient and multiple regression to determine the strength of linear relationships and the extent to which independent variables contributed to variation in the dependent variable. Qualitative data were analyzed thematically: audio recordings were transcribed verbatim; transcripts were coded and categorized according to the study’s objectives and emerging themes; accuracy and validity were enhanced through respondent verification (member checking) with discrepancies reviewed and corrected; and interrater reliability was examined by involving multiple reviewers to confirm consistency in the development of themes and sub-themes aligned with the study’s aims.

Response rate

Initially, the study was planned to collect data from 289 respondents that were 60 teachers for the questionnaire survey, 221 students for the focus group discussion, and 8 head teachers for interviews. However, complete data for both qualitative and quantitative were 237 respondents who included 169 students, 60 teachers, and 8 head teachers, as summarized in Table 3 below. This high response rate suggests that the data collected is reliable and adequately represents the perspectives of teachers, Headteachers, and students regarding teachers’ job satisfaction and students’ academic performance in public secondary schools in Kasese, Uganda. Therefore, the findings derived from these responses provide a strong basis for analyzing the study’s objectives and drawing meaningful conclusions. See Table 3.

Background characteristics

The background information of teachers in selected public secondary schools in Kasese District provides essential insights into their demographic characteristics and professional experiences, which are fundamental in understanding their perspectives on job satisfaction and academic performance. The data on the background characteristics of respondents are given in Table 4 below. Table 4 indicates that most teachers (41.7%) were aged 30-39, followed by those aged 40-49 (36.7%). Fewer were aged 20-29 (10.0%) and 50+ (11.7%). The majority of the teachers were female (56.7%), with males only 43.3%. Regarding experience, most teachers were 16-20 years (31.7%), while others had 6-10 years (21.7%) or over 20 years (21.7%). The majority (78.3%) taught in grant-aided schools, while 21.7% were in seed schools. The distribution of teaching subjects shows 31.7% were in basic sciences, 21.7% in humanities, 15.0% in languages, and 3.3% in vocational studies.

The background statistics provide essential context for understanding how teachers’ job satisfaction influences academic performance in public secondary schools in Kasese District. For example, the predominance of teachers aged 30-39 suggests a relatively young and energetic workforce, which may be more adaptable to innovative leadership approaches, while the varying years of experience suggest differing levels of satisfaction and responsiveness to motivation interventions. The dominance of basic science teachers indicates potential leadership focus on STEM-related academic improvements, which may depict the recent intervention to attract more scientists through the enhancement of their salaries to improve their job satisfaction. Lastly, the distribution of background characteristics reflects a diverse representation of teachers across various age groups, experience levels, and subject areas. This diversity ensures a well-rounded collection of perspectives, which enhances the reliability of the findings since it is an incorporation of insights from educators with different professional backgrounds and experiences. These factors shape how leadership influences teacher motivation, satisfaction, instructional quality, and ultimately, student performance. See Table 4.

Results for descriptive statistics on teachers’ job performance

Descriptive statistics offered valuable context by illustrating teachers’ perceptions regarding their job performance and academic performance, facilitating the subsequent inferential analysis. The assessment of job performance was conducted using 13 different items, each rated on a five-point scale from 1 to 5 (where 1 = Strongly Disagree, 2 = Disagree, 3 = Moderately Agree, 4 = Agree, and 5 = Strongly Agree). The results for these items are summarized in Table 5 below.

Overall, teachers’ job satisfaction hovered around a neutral to slightly positive level, with a pooled mean score of 3.57. Responses ranged from disagreement to strong agreement. For instance, satisfaction with salary (TC01) had an average of 3.30, with 53.3% of teachers agreeing or strongly agreeing that they were satisfied with their pay, although 28.3% expressed dissatisfaction. The perception of salary adequacy for basic needs (TC02) scored a mean of 3.20, with 38.4% agreement contrasted by 43.4% disagreement. The perception of pay competitiveness (TC03) was relatively low, with a mean of 2.80; over half (53.3%) disagreed that their salaries match those of their peers. Belief that pay appropriately reflects individual contribution (TC04) was slightly above neutral, with a mean of 3.11, showing mixed views; 38.3% agreed, while an equal percentage disagreed.

Promotion opportunities and recognition received more favorable ratings: 51.6% agreed that promotions are fair (TC05, mean 3.37), 60.0% felt that advancement is merit-based (TC06, mean 3.63), and 63.3% expressed satisfaction with recognition and rewards (TC08, mean 3.85). Opportunities for professional development (TC07) garnered an average of 3.29, with a 53.3% agreement rate. Working conditions (TC11) and perceived fairness of benefits (TC13) also received majority support, with mean scores of 3.65 and 3.60, respectively. In contrast, statements related to the links between non-promotion and civility (TC09, mean 3.05), as well as overall job commitment (TC10, mean 3.18), showed less consensus among teachers, reflected in larger standard deviations, which indicated diverse experiences across the sample.

Among the 13 items, the mean scores ranged from a low of 2.80 for salary competitiveness (TC03) to a high of 3.85 for recognition and rewards (TC08). The overall average score of 3.57 suggests a moderate level of job satisfaction among teachers. Variability in responses was captured by standard deviations, which ranged from 1.04 (TC08) up to 1.59 (fairness of benefits, TC12). Items related to pay competitiveness, promotion fairness, and non-monetary rewards tended to have more dispersed responses, indicating diverse experiences, while areas such as recognition (TC08) and professional development (TC07, SD = 1.07) showed greater consensus. In summary, teachers generally feel supported in aspects like merit-based promotion and recognition, but many remain divided over the adequacy and competitiveness of their salaries, possibly reflecting discrepancies between salary levels for humanities and science teachers, the latter of whom earn considerably more. These quantitative findings are corroborated by insights from focus group discussions and interviews, where responses largely align with those summarized in Table 5.

Descriptive statistics for students’ academic performance

The results related to students’ academic performance are summarized in Table 6, which presents data using frequencies, percentages, means, and standard deviations. Across all eleven items, a significant majority of teachers expressed agreement or strong agreement that their job satisfaction positively influences student performance. Agreement levels ranged from 73.8% to 92.7%, with mean scores falling between 4.03 and 4.37. For instance, item SA01 had 82.3% agreement (mean 4.10), SA02 88.2% (4.15), SA03 89.7% (4.35), SA04 92.7% (4.25), SA05 79.4% (4.30), SA06 89.7% (4.30), SA07 80.9% (4.37), SA08 89.7% (4.22), SA09 82.4% (4.32), SA10 80.9% (4.03), and SA11 73.8% (4.25). The standard deviations, consistently below 1.2 and frequently under 1.0, suggest a strong consensus among teachers. Notably, teachers rated their own engagement and professional development impacts highly, with means of 4.35 and 4.36, respectively. The connection between school facilities and student performance also received robust ratings, averaging 4.25. These findings reinforce the perception that in Kasese’s public secondary schools, factors such as motivation, support, leadership, and skills acquired through training, which contribute to teacher job satisfaction, are seen as key drivers in enhancing students’ academic outcomes.

Inferential statistics

The inferential analysis involved an overall evaluation of the model through model summary statistics, significance testing via ANOVA, and an examination of regression coefficients to understand the impact of the predictor variable.

Model summary

This section discusses the results of the regression analysis, focusing on several key statistics: the correlation coefficient (R), the coefficient of determination (R²), the adjusted R², and the proportion of variance in students’ academic performance explained by teachers’ job performance. Additionally, it includes the standard error of the estimate, which indicates the average difference between observed data points and the model’s predicted values.

According to Table 7, the analysis identified a modest positive relationship between the independent variable (teacher commitment) and the dependent variable (students’ academic performance), with a correlation coefficient of R = 0.299. The model explained approximately 9% of the variability in student performance, as indicated by the R² value of 0.090. After adjusting for the model’s complexity, the adjusted R² was 0.074, reflecting a slight correction. The standard error of the estimate was 0.674, meaning that, on average, the actual student performance scores deviate from the predicted scores by about 0.674 points on the performance scale. A lower standard error would suggest a better fit, with predictions more closely matching actual observations.

The statistical output also indicated that the model is significant (p = 0.020), signifying that teacher commitment significantly predicts student performance. The model explains a small portion of the total variance (2.591 out of 28.917), leaving most variability unexplained (residual = 26.326). The F-value of 5.71 suggests the model’s predictive power is better than a model with no predictors, indicating the relationship is meaningful.

Further, the regression coefficients revealed that the predictor variable (VAR00068, representing teacher commitment) makes a significant contribution to predicting student performance. The unstandardized coefficient (B = 0.241, p = 0.020) indicates that a one-unit increase in teacher commitment corresponds to an approximate 0.241 increase in student performance, assuming other variables are constant. The standardized coefficient (β = .299) reflects a moderate positive relationship, and the t-value of 2.389 with a p-value less than 0.05 confirms the significance of this predictor. The intercept (B = 3.449) suggests that when teacher commitment is zero, the expected student performance score is 3.449.

Qualitative findings

The qualitative findings were in agreement with the quantitative results. Interviews with Headteachers reveal that respondents generally hold a strong and positive perception of the influence of teachers’ job satisfaction on students’ academic performance. Many acknowledged that when job satisfaction is low, teachers’ commitment and student academic performance tend to decrease, but when teachers are motivated and their satisfaction and commitment levels improve, they increase their effort, and academic performance improves too. For example, Respondent H03 said, “Student performance has been gradually improving … increased teacher commitment …” Another respondent said, “Teachers still go the extra mile to supervise student projects …” adding that this increases efficiency of instruction and motivates students to perform better.

However, some head teachers reported facing numerous challenges that hinder their ability to motivate teachers. Similarly, teachers encounter obstacles that diminish their job satisfaction factors, which collectively contribute to poor performance in certain schools. For example, one respondent said, “We face several challenges, including inadequate incentives and motivation for teachers … and frequent teacher transfers.” (Respondent H07), while another said, “Teachers often face these challenges alone, which can be discouraging…” (Respondent H04).

Besides, findings from Focus Group Discussions show that students’ voices closely mirror the survey’s overwhelmingly positive scores relating to job satisfaction and academic performance. Students generally express that committed and satisfied teachers increase their motivation, boost their confidence, and encourage them to put in more effort, leading to improved academic performance. Conversely, a lack of teacher investment leads to decreased interest and lower grades. This can be illustrated by some of the students’ responses as below:

Another student said:

Another student explained that when teachers experience job satisfaction, they tend to be more committed and work harder, which in turn leads to improved performance. The student said:

Recommendations

This study sounds a serious call for policymakers to not only measure performance but also invest in interventions that improve the conditions of teachers to make good performance more feasible and sustainable. Therefore, currently, interventions such as reforming promotion pathways, investing in equitable professional development, and addressing salary disparities, especially between science and humanities teachers, could greatly energize teachers and enhance learning outcomes in ways that standardized tests and examinations alone cannot capture. All said and moving forward, exploring the longitudinal impacts of motivational reforms or expanding the exploration to other districts for comparative insights could be a focus for future researchers. In addition, future research could isolate the influence of leadership, community involvement, or learner readiness to more fully unpack the ecosystem of performance, as this would be greatly valuable. In conclusion, one clear message from this study is that when teachers thrive, students also rise.