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Citation

Jessa, M. O., & C., N. M. (2026). Psychometric Assessment of Lecturers' Morale and its Influence on University Students' Academic Achievement in South-South Nigeria. International Journal of Research, 13(3), 394–406. https://doi.org/10.26643/ijr/27

 

Morrison O. Jessa (PhD)

Department of Guidance and Counselling, Delta State University, Abraka, Nigeria

jessa.morrison@delsu.edu.ng

 

 

Nwajei M. C.

Department of Guidance and Counselling, University of Delta Agbor, Nigeria

 

Abstract

This study psychometrically assessed lecturers’ morale and examined its influence on university students’ academic achievement in South-South Nigeria. Three research questions and three hypotheses guided the investigation. The study adopted a correlational research design using an ex post facto approach, since the variables were not manipulated. The population comprised 2,803 lecturers, from which a sample of 696 was selected through purposive and proportionate stratified sampling techniques. Data were collected using a validated, researcher-developed Lecturers’ Morale Questionnaire and a checklist for extracting students’ cumulative grade point averages (CGPA) from departmental records. The instrument was pilot-tested on lecturers in Delta State, and internal consistency reliability was established using Cronbach’s alpha coefficient. Both descriptive and inferential statistics were employed for data analysis. Means and standard deviations were used to answer Research Questions 1 and 2, while the coefficient of determination (R²) addressed Research Question 3. The hypotheses were tested at the .05 level of significance using independent-samples t-tests and Pearson’s product–moment correlation. The findings revealed that lecturers’ morale in South-South Nigeria was moderate, and no statistically significant difference was observed between the states in terms of morale levels. However, students in Edo State recorded significantly higher academic achievement than their counterparts in Bayelsa State. Contrary to expectations, the relationship between lecturers’ morale and students’ academic achievement in both states was not statistically significant. On the basis of these findings, the study recommends proactive engagement by the federal government and university authorities to address the structural causes of industrial actions, improve staff welfare, and enhance institutional stability as part of broader educational quality-assurance and performance-evaluation strategies.

Keywords: Psychometric; Assessment; Lecturers’ Morale; Academic Achievement.

 

 

 

 

Introduction

Education is widely regarded as a vital investment for human capital formation and economic development, and its effectiveness is shaped by the institutional, instructional, and psychosocial environments within which it operates. National development across societies has largely been driven by professionals whose competencies were nurtured through formal educational systems, underscoring the centrality of education to social transformation and economic progress. Consequently, nations continuously strive to provide quality education for their citizens in recognition of its role in sustaining development and improving societal well-being. Higher education institutions, in particular, occupy a strategic position in producing skilled manpower capable of addressing contemporary societal challenges and advancing innovation.

At both micro- and macro-levels, education functions as a powerful agent of change. Individually, higher educational attainment is associated with improved productivity, employability, income prospects, and social mobility, while at the societal level, it contributes to the development of knowledgeable and skilled populations that drive economic growth and stability (Sothan, 2019). Nevertheless, the acquisition of knowledge, values, attitudes, and competencies through education is neither automatic nor effortless; rather, it is a prolonged and demanding process that requires sustained instructional quality, learner engagement, and institutional support. University students are therefore expected to devote considerable time to academic work and to graduate with commendable academic records that reflect meaningful learning.

Within higher education, academic achievement remains a central indicator of educational effectiveness and quality assurance. It is commonly operationalised through continuous assessment scores and cumulative grade point average (CGPA), which serve as psychometric indicators of students’ academic progress and attainment of learning objectives. Empirical evidence suggests that strong academic achievement is associated with favourable post-school outcomes such as higher income, improved employment conditions, and greater career advancement opportunities (Tentama & Abdillah, 2019). Academically successful students have also been shown to demonstrate higher self-esteem and self-efficacy, lower levels of anxiety and depression, and reduced involvement in risky behaviours. Conversely, persistently low academic achievement threatens the credibility of higher education systems and signals weaknesses in instructional processes, learner support structures, and institutional effectiveness.

Academic performance in Nigeria carries particularly significant implications for students’ future educational and occupational trajectories. Graduates whose CGPA falls below the commonly required benchmark of 2.50 are frequently excluded from postgraduate admission opportunities in many universities, while employers in the public and private sectors often restrict recruitment to candidates who have attained at least a second-class lower degree. Poor academic achievement therefore constrains employability and contributes to broader socioeconomic challenges, including unemployment and underemployment. At a societal level, persistent educational underperformance has been linked to social dislocation, rising crime rates, and various maladaptive behaviours, thereby reinforcing the urgency of identifying school-based factors that influence student achievement.

Research has demonstrated that academic underachievement is associated with a range of adverse psychological and social outcomes, including heightened anxiety, low self-concept, parental stress, and withdrawal from educational participation. For example, Chohan (2018) reported that academic failure among undergraduates in public universities in Pakistan adversely affected students’ self-concept and increased the likelihood of emotional disturbance and eventual dropout. Such findings underscore the necessity for continuous evaluation of the conditions that foster or inhibit academic success in university settings.

Scholars have identified numerous factors that influence students’ academic performance in tertiary institutions, encompassing individual, familial, socioeconomic, instructional, and environmental dimensions. These include psychological variables such as fear, anxiety, motivation, and concentration; social influences such as peer relationships, family background, and home stability; economic constraints and financial stress; learning environment characteristics such as class size and infrastructural adequacy; pedagogical practices; and personal study habits and self-discipline (Crosnoe et al., as cited in Olatunji et al., 2016). While these determinants have been extensively examined, evidence suggests that certain institutional and instructional variables remain under-explored, particularly those relating to lecturers’ professional well-being.

One such variable is lecturers’ morale, conceptualised as the degree of motivation, job satisfaction, emotional well-being, and professional commitment experienced by academic staff in the performance of their duties. Lecturers’ morale reflects their enthusiasm for teaching, engagement in research, willingness to support students, and adherence to professional standards. From an educational measurement and evaluation perspective, lecturers’ morale constitutes a latent construct that can be psychometrically assessed through indicators such as instructional enthusiasm, organisational commitment, workload satisfaction, perceived institutional support, and emotional resilience.

Emerging evidence suggests that lecturers’ morale has substantial implications for the quality of teaching and learning in universities. When lecturers experience low morale, instructional delivery may deteriorate, feedback to students may become irregular, and classroom engagement may decline, thereby weakening the learning experiences available to students (Nwosuji, 2015). Demotivated lecturers may also struggle to create supportive and stimulating academic environments, which can diminish students’ motivation, participation, and persistence in coursework. In addition, lecturers with reduced morale may be less inclined to provide academic mentoring or remedial assistance, leaving students without adequate guidance to overcome learning difficulties and perform optimally (Mustapha & Sadiq, 2016).

Lecturers further function as professional role models whose attitudes and behaviours shape students’ perceptions of academic standards, discipline, and scholarly commitment. Low morale among lecturers may manifest in lateness, poor organisation, or limited engagement with instructional responsibilities, potentially eroding students’ own commitment to academic work. Moreover, lecturers experiencing diminished morale may be less motivated to update course content, experiment with innovative pedagogical strategies, or integrate research-informed practices into teaching, thereby restricting students’ exposure to contemporary knowledge and applied learning experiences (Olape et al., 2017).

Despite these plausible linkages, comparatively few empirical studies—particularly within the South-South geopolitical zone of Nigeria—have systematically examined lecturers’ morale as a measurable construct and evaluated its influence on students’ academic achievement using rigorous psychometric procedures. This gap is especially salient for scholars in educational measurement and evaluation, given the need for reliable instruments to assess lecturers’ morale and valid indicators of student achievement outcomes. Consequently, this study focuses on the psychometric assessment of lecturers’ morale and its influence on the academic achievement of university students in South-South Nigeria, with the aim of generating evidence that can inform instructional improvement, staff welfare policies, and assessment-driven quality assurance practices in higher education.

Research Questions

The following research questions guided the study:

1.                  What is the level of morale of university lecturers among university lecturers in South-south?

2.                  What is the level of academic achievement of university students in South-south?

3.                  What is the relationship between lecturers’ morale and academic achievement of university students in South-south?

Hypotheses

The following null hypotheses were tested in the study:

1.                  There is no significant difference between the level of morale of university lecturers among university lecturers in South-south

2.                  There is no significant difference between the level of academic achievement of university students in South-south

3.                  There is no significant relationship between lecturers’ morale academic achievement of university students in South-south

Methods

Research Design

The study adopted a correlational research design employing an ex post facto approach, as neither lecturers’ morale nor students’ academic achievement was manipulated by the researchers. This design was considered appropriate because the study sought to determine the magnitude and direction of relationships between naturally occurring variables and to evaluate the predictive contribution of lecturers’ morale to students’ academic outcomes, as recommended in educational measurement research (Creswell & Creswell, 2022).

Participants

The participants comprised 696 university lecturers drawn from public universities in South-South Nigeria that had existed for at least ten years. The choice of established universities was premised on their relative administrative maturity and stability, which provided an appropriate context for evaluating lecturers’ morale and linking it with students’ academic achievement indicators. Students’ academic achievement data were obtained in the form of official cumulative grade point averages (CGPA) aggregated at departmental level and matched with lecturers who taught core undergraduate courses during the academic session under study.

Sampling Procedure

A combination of purposive and proportionate stratified sampling techniques was employed. First, purposive sampling was used to select only universities that had operated for a minimum of ten years, in line with the objectives of the study and common practices in institutional evaluation research (Fraenkel et al., 2019). Second, proportionate stratified sampling ensured equitable representation of lecturers across the selected universities. The percentage of the 696 sample size relative to the population of eligible lecturers in the selected institutions, estimated at 24.83%, was computed, and participants were drawn proportionately from each institution.

Instruments

Two sources of data were utilized: Lecturers’ Morale Questionnaire (LMQ) and Students’ Academic Achievement Records (CGPA). The Lecturers’ Morale Questionnaire (LMQ) was a researcher-developed psychometric instrument designed to measure lecturers’ perceptions of their motivation, job satisfaction, institutional support, professional commitment, and emotional well-being. The questionnaire consisted of two sections: Section A contains the demographic information, including sex, marital status, institution, and state.

Section B contains 20 morale-related items measured on a 4-point Likert-type scale ranging from 1 (Strongly Disagree) to 4 (Strongly Agree). Higher scores indicated higher perceived morale.

Academic achievement was operationalized as students’ Cumulative Grade Point Average (CGPA) obtained from departmental examination records and standardized on a 5-point grading scale. CGPA was selected because it represents a stable and widely accepted indicator of scholastic attainment in higher education assessment (Aiken & Groth-Marnat, 2021).

Validity of the Instrument

The LMQ was subjected to expert validation to establish content and face validity. Copies of the instrument were submitted to three specialists in Educational Measurement and Evaluation who assessed the clarity of wording, relevance of items to the construct of morale, and adequacy of coverage of the conceptual domain. Based on their recommendations, ambiguous expressions and double-barrelled statements were revised or eliminated, while poorly aligned items were rephrased to enhance construct representation. The final version reflected adequate alignment with theoretical descriptions of morale and motivation in higher education contexts.

Reliability of the Instrument

To determine internal consistency, the LMQ was pilot-tested on 50 lecturers from universities in Delta State who were not part of the main study. The data obtained were analysed using Cronbach’s alpha coefficient, a standard reliability index in psychometric research (Taber, 2018). The analysis yielded an alpha coefficient of .96, indicating excellent internal consistency and suggesting that the items measured a common underlying construct.

Procedure for Data Collection

Data collection was carried out personally by the researchers with the assistance of five trained research assistants. Prior to administration, the assistants were briefed on the purpose of the study, ethical requirements, and procedures for approaching respondents. The researchers and assistants visited the selected universities, distributed the questionnaires to participating lecturers, and retrieved completed copies on site. Where necessary, clarifications were provided to ensure accurate responses. Students’ CGPA data were obtained through departmental offices with institutional permission and matched to lecturers’ courses for analytical purposes.

Data Analysis

Data were analysed using both descriptive and inferential statistics, consistent with psychometric and evaluation research standards (Field, 2022). Research Questions 1 and 2 were answered using mean scores and standard deviations to describe levels of lecturers’ morale and students’ academic achievement. Research Question 3 was addressed using the coefficient of determination (R²) to estimate the proportion of variance in academic achievement explained by lecturers’ morale. Hypotheses 1 and 2 were tested using the independent-samples t-test, where group comparisons were involved. Hypothesis 3 was tested using Pearson’s product–moment correlation coefficient to determine the strength and direction of the relationship between lecturers’ morale and students’ academic achievement. All hypotheses were tested at the .05 level of significance.

Ethical Considerations

Ethical approval was obtained from the relevant institutional authorities prior to data collection. Participation was voluntary, informed consent was secured from all respondents, and confidentiality of responses was assured. No identifying information was included in the dataset, and CGPA records were used strictly for research purposes.

Results

Research Question 1: What is the level of morale of university lecturers among university lecturers in South-south?

Table 1: Mean analysis of the level of morale of university lecturers among university lecturers in South-south

S/N	Level of Lecturers' Moral	N	Mean	SD	Remark
1.	I feel demoralized by the prolonged duration of the national strike	479	3.37	0.91	++
2.	The uncertainty surrounding the outcome of the strike has negatively impacted my morale	479	2.97	0.61	+
3.	I am frustrated with the lack of progress or resolution in the negotiations between stakeholders	479	3.02	0.92	++
4.	The financial strain caused by the strike has significantly affected my moral	479	2.85	0.91	+
5.	I feel undervalued by the government	479	2.49	1.10	-
6.	The disruption to my teaching schedule has lowered my morale	479	2.54	0.87	+
7.	I am concerned about the long - term effects of the strike on the quality of education for students	479	2.86	0.86	+
8.	The lack of transparency from union leaders has contributed to my frustration	479	2.60	0.87	+
9.	I feel conflicted between my commitment to my students and my support for the strike	479	2.78	0.78	+
10.	The impact of the strike on my professional life has taken a toll on my moral	479	2.64	0.91	+
11.	I am disappointed by the perceived lack of support from fellow colleagues during the strike	479	3.69	0.70	++
12.	The emotional stress caused by the strike have affected my overall well- being	479	2.91	0.68	+
13.	I am sceptical about the effectiveness of the strike in achieving its intended goals	479	2.91	0.71	+
14.	The division within the academic community as a result of the strike have dampened my morale	479	2.89	0.85	+
15.	I feel disheartened by the negative portrayal of lecturers in the media during the strike	479	2.88	0.82	+
16.	The sense of powerlessness or helplessness in influencing the outcome of the strike has affected my morale	479	2.80	0.81	+
17.	I am concerned about the reputational damage to the institution as a result of the strike	479	2.90	0.82	+
18.	The lack of clarity regarding the resolution of key issues has contributed to my anxiety and stress	479	2.84	0.79	+
19.	I feel unsupported by the government during the strike	479	2.81	0.81	+
20.	The erosion of trust in the leadership of the academic union has undermined my morale	479	2.66	0.94	+
Average Mean		479	2.87	0.27	+

Key: ++ High; + Moderate; - Low

Table 2 shows the mean analysis of the level of morale of university lecturers among university lecturers in South-south. The result shows that the average mean score is 2.87, with a standard deviation of 0.27. Based on the scoring rubric provided (with remarks such as "++", "+", and "-"), this overall mean falls within the moderate morale category, indicated by the "+" remark. This means that university lecturers in South-south experience a moderately low level of morale as a consequence of national strikes.

Research Question 2: What is the level of academic achievement of university students in South-south?

Table 2: Mean analysis of the level of academic achievement of university students in South-south

	Bayelsa State		Edo State
	Mean	SD	Mean	SD
Session Loss to Strikes	40.79	32.25	40.79	32.25
Graduated	80.46	0.6	84.64	3.41
FRNS	11.15	1.18	3.84	0.55

Table 2 shows the mean analysis of the level of academic achievement of university students in South-south. The result shows that Both South-south recorded the same mean value of 40.79 session loss due to strikes, with a high standard deviation of 32.25. This indicates that students in both states experienced similar and significant disruptions in their academic calendars due to national strikes. The mean graduation rate is slightly higher in Edo State (84.64) compared to Bayelsa State (80.46), suggesting that a greater proportion of students in Edo State successfully completed their programs. The mean value of FRNS is considerably higher in Bayelsa State (11.15) compared to Edo State (3.84), with standard deviations of 1.18 and 0.55 respectively. This result implies that while both states experienced an equal level of session loss due to national strikes, the academic achievement of students in Edo State appears relatively higher than in Bayelsa State. Edo students not only have a higher graduation rate but also a significantly lower failure rate.

Research Question 3: What is the relationship between lecturers’ morale and academic achievement of university students in South-south?

Table 3: Correlation analysis the relationship between lecturers’ morale and academic achievement of university students in South-south

State	Variable	N	Mean	SD	r	r2	r2%	Remark
Bayelsa	Lecturers’ Morale	696	59.98	5.71	-0.14	0.2	2	Small Negative Relationship
	Academic Achievement		80.47	0.62
Edo	Lecturers’ Morale	696	61.43	8.36	-0.36	0.13	13	Moderate Negative Relationship
	Academic Achievement		84.56	3.51

Table 3 shows a correlation analysis the relationship between lecturers’ morale and academic achievement of university students in South-south. The result shows that in Bayelsa State, the correlation coefficient of -0.14 indicates a small negative relationship between lecturers' morale and students' academic achievement. This suggests that as lecturers’ morale declines, there is a slight corresponding decline in students’ academic achievement. The coefficient of determination (r² = 0.02) implies that only 2% of the variation in academic performance is accounted for by lecturers’ morale, while the remaining 98% is explained by other factors.

In Edo State, the correlation coefficient of -0.36 reflects a moderate negative relationship between lecturers’ morale and academic achievement. This stronger inverse relationship indicates that a drop in lecturers’ morale more significantly affects students’ academic performance compared to Bayelsa. The r² value of 0.13 signifies that 13% of the variance in students’ academic achievement can be explained by variations in lecturers’ morale, which is a more substantial proportion than in Bayelsa. This finding suggests that in Edo, the academic success of university students is more sensitive to the psychological and professional wellbeing of their lecturers.

Hypothesis 1: There is no significant difference between the level of morale of university lecturers among university lecturers in South-south

Table 4: t-test analysis of the difference between the level of morale of university lecturers among university lecturers in South-south

State	n	Mean	SD	df	t-value	p-value	Remark
Bayelsa	328	2.86	0.27	694	0.571	0.573	Not Significant
Edo	368	2.93	0.40
α = 0.05

Table 4 shows an independent samples t-test, which was used to compare the difference between the level of morale of university lecturers among university lecturers in South-south. The result shows that the difference is not statistically significant. The mean morale score for lecturers in Bayelsa State is 2.86 with a standard deviation of 0.27, while in Edo State, the mean is slightly higher at 2.93 with a standard deviation of 0.40. With a combined degrees of freedom (df) of 694, the calculated t-value is 0.571 and the corresponding p-value is 0.573. Since the p-value exceeds the conventional alpha level of 0.05, the null hypothesis stating that there is no significant difference in lecturers’ morale between the two states is retained.

Hypothesis 5: There is no significant difference between the level of academic achievement of university students in South-south

Table 5: t-test analysis of the difference between the level of academic achievement of university students in South-south

State	n	Mean	SD	df	t-value	p-value	Remark
Bayelsa	328	80.47	0.62	694	4.592	0.000	Significant
Edo	368	84.56	3.51
α = 0.05

Table 5 shows an independent samples t-test, which was used to compare the difference between the level of academic achievement of university students in South-south. The result shows a statistically significant difference between the two states. The mean academic achievement score of university students in Bayelsa State is 80.47 with a standard deviation of 0.62, while students in Edo State recorded a higher mean of 84.56 with a standard deviation of 3.51. The degrees of freedom (df) for the test is 694, with a calculated t-value of 4.592 and a p-value of 0.000. Given that the p-value is far below the alpha level of 0.05, the null hypothesis is rejected. This implies that there is a significant difference between the level of academic achievement between university students in South-south. The direction of the mean difference suggests that students in Edo State perform significantly better academically than their counterparts in Bayelsa State.

Hypothesis 3: There is no significant relationship between lecturers’ morale academic achievement of university students in South-south

Table 6: Correlation analysis the relationship between lecturers’ morale and academic achievement of university students in South-south

State	Variable	n	Mean	SD	R	r2	r2%	p-value	Remark
Bayelsa	Lecturers’ Morale	696	2.86	0.27	-0.14	0.2	2	0.602	Not Significant
	Academic Achievement		80.47	0.62
Edo	Lecturers’ Morale	696	2.93	0.40	-0.36	0.13	13	0.173	Not Significant
	Academic Achievement		84.56	3.51
α = 0.05

Table 6 shows a Pearson’s correlation analysis the relationship between lecturers’ morale and academic achievement of university students in South-south. The result shows in Bayelsa State, the Pearson correlation coefficient (r) between lecturers’ morale and academic achievement of university students is -0.14, indicating a very weak negative relationship. The coefficient of determination (r²) is 0.02, meaning that only 2% of the variance in students’ academic achievement can be explained by lecturers’ morale. The p-value is 0.602, which is greater than the alpha level of 0.05. This indicates that the observed relationship is not statistically significant. In Edo State, the correlation coefficient (r) is -0.36, which suggests a moderate negative relationship. The coefficient of determination (r²) is 0.13, showing that 13% of the variation in students’ academic achievement is accounted for by lecturers’ morale. The p-value here is 0.173, which, like in Bayelsa, is greater than 0.05. Thus, the relationship is also not statistically significant. Since the p-values in both states are higher than the significance level (α = 0.05), the null hypothesis is retained for both South-south. This implies that lecturers’ morale does not have a statistically significant impact on the academic achievement of university students in these two states.

Discussions

The findings of this study indicate that the overall level of lecturers’ morale in South-South Nigeria was moderate, as reflected by the grand mean score obtained from the Lecturers’ Morale Questionnaire. This outcome suggests that although lecturers did not uniformly report extreme demoralization, there was substantial evidence of psychological strain, professional dissatisfaction, and reduced occupational enthusiasm attributable to prolonged industrial actions. The corresponding hypothesis, which revealed no statistically significant difference in morale levels across the states studied, further suggests that morale-related challenges are systemic rather than localized, reflecting shared governance structures, funding mechanisms, and labour relations frameworks across public universities in the region.

From an evaluation standpoint, the absence of statistically significant differences across states implies measurement invariance in morale perceptions, meaning that lecturers in different institutional contexts responded similarly to the morale indicators captured by the instrument. This uniformity may stem from the centralized nature of higher education administration in Nigeria, where remuneration policies, strike negotiations, and welfare agreements are negotiated nationally rather than institutionally. Consequently, lecturers across South-South universities appear to experience comparable disruptions to teaching schedules, financial instability, emotional exhaustion, and professional uncertainty following recurrent strike actions. The moderate morale level observed can further be interpreted in light of structural constraints confronting Nigerian universities. Persistent delays in salary payments, non-implementation of negotiated welfare packages, and limited institutional autonomy have remained dominant triggers of industrial disputes. Such conditions undermine professional identity and job satisfaction—two psychometrically salient dimensions of morale—while simultaneously constraining career progression, research productivity, and international collaboration opportunities. The post-strike academic environment, often characterized by compressed calendars, increased workload, and emotionally distressed students, likely exacerbates occupational burnout and erodes the intrinsic rewards associated with teaching and mentoring. These pressures appear to be widely shared across universities in the South-South zone, thereby accounting for the observed homogeneity in morale levels.

The present findings are consistent with Ogunode et al. (2022), who documented heightened psychological stress, reduced motivation, and disruptions to academic programmes among Nigerian academics following prolonged strike actions. Similarly, Offor et al. (2024) reported that the 2022 ASUU strike precipitated financial hardship and emotional exhaustion among lecturers in South-East Nigeria, with attendant implications for morale and professional engagement. These converging results lend empirical support to the argument that industrial actions exert sustained and deleterious effects on academic staff well-being across geopolitical regions. Regarding students’ academic achievement, the study revealed significant differences between states, with universities in Edo State recording higher graduation rates and lower failure rates than those in Bayelsa State. This statistically significant disparity underscores the presence of contextual and institutional variations in educational effectiveness within South-South Nigeria. From an evaluative perspective, such differences may reflect unequal distribution of academic resources, infrastructural development, staff strength, and academic cultures across institutions.

Universities in Edo State, including the University of Benin and Ambrose Alli University, have historically benefited from relatively stronger infrastructural bases, longer institutional histories, and broader programme accreditation portfolios, factors that are often associated with enhanced instructional quality and student learning outcomes. These conditions may facilitate more stable academic calendars, greater access to learning materials, and increased exposure to experienced faculty members. Conversely, younger universities in Bayelsa State may still be contending with infrastructural deficits, limited funding streams, and evolving administrative systems, which could constrain instructional delivery and student engagement, thereby contributing to lower academic performance indices. This interpretation aligns with Igbinedion and Igbinedion (2022), who reported that students in Edo State universities tended to enter with stronger admission credentials and subsequently demonstrated higher academic success, suggesting that input quality and institutional maturity jointly shape achievement outcomes.

The correlational analysis further revealed a negative relationship between lecturers’ morale and students’ academic achievement in both states, although the magnitude of this association differed contextually—being stronger in Edo State and weaker in Bayelsa State. However, the corresponding hypothesis tests indicated that these relationships did not attain statistical significance, implying that lecturers’ morale, while educationally meaningful, may not function as a standalone predictor of students’ academic outcomes across institutional contexts. From a psychometric and systems-evaluation perspective, this pattern points to a multivariate causation framework in which morale interacts with other determinants—such as instructional resources, administrative efficiency, student preparedness, learning technologies, and peer influences—to shape achievement. In Bayelsa State, the weak association may suggest that students have developed compensatory learning strategies, including reliance on peer networks, private tutoring, or digital resources, which potentially buffer the instructional consequences of lecturers’ low morale. In Edo State, the comparatively stronger association implies that students may be more directly dependent on lecturer engagement, mentoring, and feedback, thereby rendering morale fluctuations more consequential for academic performance.

The absence of statistically significant relationships across states may also reflect measurement-level considerations, including restricted variability in morale scores, contextual suppression effects, or the influence of unmeasured mediating variables such as instructional quality, workload intensity, or institutional climate. These findings underscore the importance of modelling lecturers’ morale within broader structural equation or multilevel analytic frameworks rather than treating it as a singular explanatory variable. The present results diverge from the findings of Bada and Jibia (2022), who reported a significant negative correlation between lecturers’ attitudes and undergraduate academic performance, and from Bambi (2020), who observed a strong positive association between teachers’ morale and students’ academic outcomes in Financial Accounting. Such discrepancies may be attributable to disciplinary differences, institutional contexts, measurement instruments, or analytic strategies employed across studies, reinforcing the need for continued psychometric refinement of morale scales and cross-contextual validation in Nigerian higher education research.

Conclusion and Recommendations

Based on the findings, the study concludes that university lecturers in South-South Nigeria generally exhibit a moderate level of morale, reflecting widespread psychological strain and professional dissatisfaction linked to systemic challenges within the public university system. Although students’ academic achievement differed significantly across states, with Edo State recording superior outcomes compared to Bayelsa State, lecturers’ morale did not significantly vary across states and did not independently predict students’ academic achievement. Consequently, the following recommendations were made:

1.                  Government agencies should institute regular staff-welfare audits and morale-monitoring systems, including periodic psychometric assessments, timely salary disbursement mechanisms, and structured staff-support programmes, to proactively identify morale decline and prevent escalation into industrial disputes.

2.                  Regulatory bodies and state governments should conduct comparative institutional evaluations of universities across South-South Nigeria

3.                  Future institutional monitoring frameworks should adopt multivariate evaluation models such as hierarchical linear modelling or structural equation modelling that incorporate lecturers’ morale alongside teaching quality, learning resources, student preparedness, and administrative effectiveness to generate more precise explanations of achievement outcomes.

 

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