This study investigated the leadership styles of principals in Primary Teachers Training Colleges in the Lake Victoria Region of Kenya. It specifically sought to determine the influence of Laissez faire and autocratic leadership styles on organizational performance of PTTCs in Lake Victoria Region of Kenya.

The objectives of study are to: 1) investigate whether Laissez faire leadership is exhibited by principals of PTTCs in Victoria Region of Kenya; 2) investigate whether autocratic leadership is exhibited by principals of PTTCs in Victoria Region of Kenya; 3) establish influence of principals’ laissez-faire leadership on organizational performance of Primary Teachers Training Colleges in Lake Victoria Region of Kenya; 4) examine influence of principals’ autocratic leadership on organizational performance of Primary Teachers Training Colleges in Lake Victoria Region of Kenya.

The following four research questions were formulated to guide the research study:

1) Do principals of primary teachers training colleges in Lake Victoria Region of Kenya practice Laissez faire leadership styles?

2) Do principals of primary teachers training colleges in Lake Victoria Region of Kenya practice autocratic leadership styles?

3) What is the influence of Laissez faire leadership on the organizational climate of PTTCs?

4) What is the influence of autocratic leadership on the organizational climate of PTTCs?

This study was confined only to counties in Lake Victoria Region of Kenya, namely: Migori, Homabay, Kisii, Kisumu and Siaya. The study involved principals and tutors of the nine selected PTTCs only. This study focused only on laissez-faire leadership, autocratic leadership and organizational performance.

The findings of this study is meant to contribute to the existing body of knowledge on the appropriate leadership styles available for principals of PTTCs. Successful principals need multiple lenses and skills in strategizing—looking at old problems in a new light, as well as confronting new challenges with different tools and reactions. Findings of the study are to enrich the literature leadership styles employed by leaders for educational planners and administrators in Kenya.

The conceptual framework in Figure 1 was developed after review of existing literature to investigate the research questions at hand. The diagram underpins the interrelationships between three variables. PTTCs principals’ leadership styles: Laissez faire and autocratic formed the independent variables. Organizational performance has covered PTTCs performances in Primary Teachers Education examinations. Tutors’ demographic characteristics, namely gender, age, educational level, teaching experience, tenure in current PTTC form intervening variable.

One of the many indicators of a successful organization is its effective leadership.

Leading effectively requires competence, skill and suitable leadership styles. Leadership is viewed as the process of influencing, motivating and enabling others to understand and agree to contribute collectively to the effectiveness and success of the organization’s shared objectives of which they are members (Yukl, 2013). According to Armstrong (2012), a leadership style is the approach used by leaders to exercise their leadership function. It is said to be a particular behavior applied by a leader to motivate his or her subordinates to achieve the objectives of the organization (Ng’ethe et al. 2012). The styles of leadership included in this study are laissez-faire and autocratic.

Laissez-faire is a French phrase that means let it be and describes leaders who allow followers to work without supervision (Nwokocha & Iheriohanma, 2015). It is the kind of leadership where the leader is inactive, rather than reactive or proactive. The laissez-faire leadership style, also known as the “hands-off” style or free reign, is one in which the leader (principal) provides little or no direction and gives tutors as much freedom as possible. According to Gill (2014) it means leaving subordinates to complete tasks and jobs in the way they choose without adherence to any strict policies or procedures. Principals who adopt the laissez-faire leadership style exercise little control over the tutors and let the tutors have freedom to carry out their assigned tasks without direct supervision (Wu & Shiu, 2009).

True laissez-faire is in fact “non-leadership” because the leader has almost no influence over the group (Bass, 1999). Bass (1985) describes the Laissez faire leadership style as one in which the leader has no belief in his/her own ability to supervise. He further states that the leader has no clear set goals towards how they may work, do not help the group in making decisions and so leaves too much responsibility with their subordinates. According to Puni et al., (2014), the laissez-faire leader avoids controlling his employees and so only relies on the few available employees who are loyal to get a task done. A Laissez faire leader does not believe in employee development as they believe that employees can take care of themselves (Puni et al., 2014).

The behavior of a laissez-faire leader makes it difficult to distinguish the leader from the followers. Principals who use this style of leadership believe that there should be no rules and regulations since everybody has inborn sense of responsibility. The philosophical assumption underlying laissez-faire leadership is that naturally human beings are unpredictable and uncontrollable and trying to understand people is a waste of time and energy. Under this style, the principal tries to maintain a low profile, respects all departments and sections within the institution, trying not to create waves of disturbance, and relies on the few available loyalists to get job done (Northouse, 2007).

The laissez-faire principal lives and works with whatever structure is put in place without any suggestions or criticisms. Goals and objectives are established only when necessary and required. Such a principal shuns decision-making as much as possible, and would avoid communication but communicates only when needed. Thus, the business of staff development is not a concern of the Laissez faire leader principal, who believes that tutors can take care of themselves (Rowe, 2007). The laissez-faire leadership style is passive, unassertive and tends to allow self-empowerment among tutors (Harper, 2012). Due to frequent absence and lack of involvement when making important decisions, the laissez-faire principal drives tutors to self-management.

Autocratic leadership style, also called coercive or dictatorship, involves the leader retaining as much power and decision-making authority as possible (Farrell, 2009). In other words, autocratic leadership involves absolute, authoritarian control over a group; such a principal is characterized as domineering. In autocratic leadership style, the principal determines policy and assigns tasks to tutors without consulting them. Wu and Shiu (2009) explained that, autocratic or authoritarian leadership is gained through punishment, threats, demands, orders, rules, and regulations. The tutors working under autocratic principals carry out the principal’s directives without asking questions and there are no group inspired decisions. The principal centralizes authority in decisions making and supervises work in close detailed manner than in general form.

The autocratic leader applies McGregor’s (1966) Theory X which assumes that the average person dislikes work and will avoid it unless directly supervised, the employees must be coerced, controlled and directed to ensure that the organizational objectives are met; the threat of punishment must exist within an organization, and employees prefer to be led this way to avoid responsibility. Autocratic leadership also assumes that people are relatively un-ambitious and their prime driving force is the desire for security (Mat, 2008).

Leadership include unilateral rule-making, task-assignment, and problem solving while the roles of authoritarian followers include adhering to the leader’s instructions without asking question or commenting. Autocratic leaders inform their subordinates on what must be done, how it should be done and when it must be completed. This kind of principal often ignores suggestions made by staff members. When the leader is overbearing, he/she can undermine the egalitarian spirit of an effective team and compromises positive organizational climate. The leader does not have confidence in his subordinates. The leader rarely praises, rather he criticizes a lot, leading to followers’ loss of confidence in him and become less committed to their work. Findings by Boyatzis, Goleman, and Mckee (2002) indicate that the autocratic leadership is the least effective in most situations, because followers become emotionally cold from intimidation and therefore, the work environment is affected negatively.

According to Farlex (2012), it is the actual output/results of an organization obtained when measured against its intended outputs (goals and objectives). Existing labor literature has shown that employees tend to put in their best, work effectively and efficiently if the work environment is conducive and the leadership and corporate executives demonstrate the flexibility that they often demand of their employees (Fernández, 2003). Organizational performance assesses how an organization is able to meet its stated objectives over time. Organizational performance relates to how efficient, effective, relevant and viable an organization is. McNamara et al. (2011) states that organizational performance involves recurring activities that establish organizational goals, monitors progress towards goals and makes adjustments to achieve the goals more effectively and efficiently.

Effectiveness is the measure of the degree to which the institution’s service offered meet the customer’s expectations. Efficiency is the utilization of the resources within appropriate cost structures; relevance is the ability to adapt to changing environments to satisfy the stakeholders’ current needs, while viability is the ability to maintain sustainable operational base for meeting obligations as they fall.

Greenberg (2004) defines workplace demographic characteristics as the variety of differences between people in an organization including race, ethnic group, gender, age, education background, tenure, personality, cognitive style, and organizational function. Bell (cited in Thakur, 2015) also defines demographic characteristics as personal statistics on information such as gender, age, education level, income level, marital status, occupation, religion, birth rate, death rate, average size of family, average age at marriage. Fletchl (2010) points out that the demographic characteristics have an influence on whether employees will be committed to their work or not. He observes that how well the employee performs, how many years they are ready to dedicate in service and how well they act in the best interest of the firm’s objectives heavily depends on how much the organizations take care of the needs that are related to their demographic characteristics. According to Hayles and Mendez (1997) diversity allows increased creativity, a wider range of perspectives, better problem definition, more alternatives and better solutions as noted in Thakur (2015). This study has been delimited to five demographic areas: gender, age, educational level, teaching experience, and tenure in current PTTC.

Khumalo (2015) in a study of a related topic in South Africa cited several studies on influence of leadership on organizational climate. The studies confirmed that organizational commitment tends to heighten for those employees whose management or leadership give them the opportunity to partake in decision-making (Steyrer, Schiffinger & Lang, 2008), whose leaders are fair (Lo et al., 2010) and are supportive of their employees. At the same time, a number of scholars (e.g. Bushra, Usman & Naveed, 2011; Kim & Brymer, 2011) contended that supervision is one of the significant factors that guide employee commitment to their organization.

Basit et al. (2017) studied the impact of leadership style on employee performance, in a private organization in Malaysia. The results revealed thatLaissezfaire leadership had a positive impact on employee performance, which indicated that employee performance would increase when Laissez faire leadership is applied. As compared with other leadership styles, autocratic leadership (r = −.1685, p < .05) had a negative correlation with employee performance, Laissez faire leadership (r = .241, p < .001) had a weak positive correlation with employee performance, while democratic leadership (r = .581, p < .001) had a strong positive correlation with employee performance. Also, a study by Paisey (2002), on school leadership and its influence on performance showed correlation between the Laissez faire leadership and the school performance in secondary schools in Tanzania established that principals who use the Laissez faire leadership tend to fail to follow up on those they have delegated tasks to and consequently performance declines. Ochieng (2001) established that principals who use the Laissez faire leadership tend to fail to follow up on those they have delegated tasks to and consequently performance declines. They leave everything to the mercy of their staffs, some of whom may lack the necessary skills and competence to execute the work. Others may simply not like to do the work unless they are supervised. This study investigated how Laissez faire leadership influences organizational performance of PTTCs in Lake Victoria region of Kenya.

Nyamboga et al. (2014) studied the impact of principals’ leadership style on the performance of students in public secondary schools in Kenya Certificate of Secondary Education in Tana River County. Schools in the county had displayed varied results with varying leadership styles. The county had had a very low mean score between the years 2005-2009. This was in spite of the fact that schools in the region were endowed with appropriate resources (Nyamboga et al., 2014). The findings of the study revealed that there was a significant relationship between head teachers’ leadership style and students’ performance at KCSE. The principals in Tana River County had an average of autocratic leadership styles which correlated very well with their students’ poor performance. Autocratic leadership style was found to have a significant negative effect on the students’ performance in national examinations. In another study, Nuhu (2010) studied the effect of leadership on employee performance in Kampaka District Council. The result revealed autocratic leadership had a negative correlation with employee performance (r = −.422, p < .001) which was statistically significant. The finding meant that authoritative leadership affected individual performance in a way that compromised efficiency to work. This study investigated the influence of principals’ autocratic leadership style on organizational performance of PTTCs in Lake Victoria Region of Kenya.

Demographic characteristics are widely acknowledged as having a great influence on staff performance. Fletchl (cited in Thakur, 2015) points out that the demographic characteristics have an influence on whether employees will be committed to their work or not. He observes that how well the employee performs, how many years they are ready to dedicate in service and how well they act in the best interest of the firm’s objectives heavily depends on how much the organizations take care of the needs that are related to their demographic characteristics (Thakur, 2015).

According to Jackson (2003) there are many stereotypes in existence concerning the differences in abilities between men and women in many organizations. Andoh, Biako and Afranie (2011) point out importance of recognizing the fact that there are only a few, gender related differences that will affect the performance of men and women. It is observed that while women are good in obeying rules and following instructions, men on the other hand are more aggressive and aim at seeing the results quickly. The differences are however minor and might not be universally adopted as an explanation as to why men and women attain different performance standards (Murray, 2002). Further Murray (2002) added that there are a number of possible explanations to this. Firstly, women are granted a longer maternity leave compared to their male counterparts who just get a few days and sometimes denied depending on the policies of the organizations they are working for. From a cultural context, women are more responsible to immediate family matters such as looking after children more than their male counterparts.

In one study, Thakur (2015) sought to determine the influence of demographic characteristics on performance of academic employees at Kenyatta University in Kenya. Data was collected from the academic staff (Full Professor, Associate Professor, Senior lecturer, lecturer and Tutorial fellows) at Kenyatta University. From the study findings, majority (65%) of the academic staff were male while 35% were female. The finding confirmed that gender plays a critical role in employee’s performance. From the above results however, this has not yet been fully achieved given the identified gap between the male and female performance.

The decline of mental abilities from early adulthood is a universal phenomenon. A large body of evidence supports the notion that cognitive abilities decline from some stage in adulthood (Skirbekk, 2003). Physical abilities, mental abilities, education and job experience form an individual’s productivity potential. Combined with organization’s characteristics, these factors determine job performance. Productivity reductions at older ages are particularly strong for work tasks where problem solving, learning and speed are needed, while in jobs where experience and verbal abilities are important, older individuals’ maintain a relatively high productivity level (Skirbekk, 2003).

A study by Thakur (2015) of the academic staff at Kenyatta University found that most (47%) of the respondents were aged between 40 - 64 years, 43% were 39 years and below while 10% were aged between 65 - 78 years, implying that majority of the academic staff at Kenyatta University were aged between 40 - 64 years. The result also established that the age category of 31 to 40 that performs the best also constitutes the highest population per age category among the employees working at Kenyatta University. This indicates that the university is aware of the age factor in as far as productivity is concerned. Although several writers dispute the idea of age as a determinant of productivity, this research proved otherwise. From results above, age is a key determinant of employee performance.

The current times are seeing education take the central stage in employment. Most employers insist on certain minimum educational qualifications before considering one for a particular job. The recent high rates of unemployment in many countries are seeing graduates into accepting jobs that they are either under-qualified or overqualified for (Silva, 2009). According to Easterlin (2007) the skills gained through education are a mark of performance level that an employee can exhibit. However, different fields of specialization are needed in order to meet the labour needs within learning institutions. Griffin & Moorhead (2011) argued there is a twofold implication to this especially when performance is concerned. Firstly, non-specialized workers might make more errors that can reflect in their work as poor performance standards due to the lack of the basic conceptual background of what they are doing; their productivity level can also be low by virtue of this. Secondly, the level of motivation can be low especially to those who are forced to work in departments that they are less willing to work in but have been forced by circumstances to do so (Griffin & Moorhead, 2011). This can result in low motivation and poor performance.

Thakur (2015) study which sought to establish the level of education of the respondents, found that majority (58%) of the respondents had PhD as their highest level of education while 42% had Master’s degree as their highest level of education. This implied that majority of the academic staff at Kenyatta University had PhD as their highest level of education. This is expected of the universities because education qualification highly influences their performance at work. The fact that all the academic staff held at least a Master’s Degree was indicative of the value that the university attached on education in as far as employee performance is concerned.

Employee’s working experience can have a great impact on whether they will perform better or not. Gaining work experiences within an organization means both the employer and employee relationship is sustainable in as far as achieving the goals of the organization is concerned (Yeatts & Hyten, 1998). A study of San Diego public school teachers between 1997 and 2000 in elementary, middle, and high school found a statistically insignificant relationship between teaching experience and gains in student achievement in math and reading. More specifically, the authors did not find a statistically significant difference between the effectiveness of a fully credentialed elementary teacher with more than 10 years of experience and teachers with fewer years of experience (Kini & Podolsky, 2016). Unfortunately, the authors did not isolate the returns to experience because they only reported the gains related to the interaction of teachers’ credentials (i.e., full, emergency, intern) and their experience. In addition, the authors grouped teachers with 10 or more years of experience together, which limits the inferences that can be drawn about experience past 10 years because the effects of teachers throughout this wide period of time are conflated. The study also found that teachers constantly improved teaching effectiveness until the 21st year. The most effective teachers had 19 - 24 years of experience at grade level and were associated, holding all other variables constant, with increased student reading achievement (effect size = .40). These highly experienced teachers were twice as effective as teachers with at least more than five years of experience (effect size = .20).

The number of years that one has spent within an organization can have an impact on whether they will perform better or not. In addition to gaining work experience, many years of work within an organization indicate that the employer and employee relationship is sustainable in as far as achieving the goals of the organization is concerned (Yeatts & Hyten, 1998). Over 40 years of teacher productivity research suggests that the simple assumption that “more is better” requires greater nuance; experience effects are complex and depend on a number of factors. Evidence from CALDER studies using rich state datasets provides new insight into the effects of teacher experience (Rice, 2010). Several key findings emerge, some confirming previous understandings and others raising new questions. These findings have important policy implications. Experience matters, but more is not always better. The impact of experience is strongest during the first few years of teaching; after that, marginal returns diminish (Rice, 2010). A number of CALDER studies confirm findings from existing research that, on average, brand new teachers are less effective than those with some experience under their belts (Harris & Sass, 2007; Ladd, 2008). Early-career experience has a clear payoff in teacher effectiveness, and the impact is stronger than the effect of most other observable teacher-related variables including advanced degrees, teacher licensure tests scores, National Board certification at the elementary level, and class size (Ladd, 2008; Sass, 2007). Teachers show the greatest productivity gains during their first few years on the job, after which their performance tends to level off. A study using New York City data illustrates the diminishing marginal returns to experience (Boyd et al., 2007).

The target population was all the 254 tutors teaching in the nine selected PTTCs. They comprised 9 principals and 245 other tutors. The respondents held professional certification from universities and other educational institutions recognized by the Kenya government. Tutors in public PTTCs were employed by the Teachers Service Commission (TSC) while those in private contracted locally by the Boards of Management (BoMs) of those PTTCs. The PTTCs are preferred because they have defined administrative structures. Also, they offer the same Primary 1 (P1) course and have legal mandate to operate given by the government of Kenya. Their top leadership structures are almost similar and they are likely to exhibit elaborate relationships between the study variables.

A sample of 234 was obtained from each PTTC. They comprised 9 principals and 225 other members of staff. The formula adopted was the one used by Krejcie & Morgan (1970) article “Determining Sample Size for Research Activities” (Educational and Psychological Measurement). Its advantage was that PTTCs with a smaller number of tutors were all the tutors were selected, and those PTTCs with a large number of tutors had an appropriate number sampled.

The study employed a multistage sampling procedure. The researcher first used cluster sampling (Creswell, 2003) to get the nine PTTCs from the four counties of Lake Victoria Region. Five public and five private PTTCs were selected for the study. Gender was also considered to ensure both male and female tutors were selected. Purposive non-random sampling, also described as “judgmental” sampling (Mason & Griffin, 2002) was also employed in which participants were chosen on the basis that they exhibited particular features or experiences that enabled detailed understanding of the central themes and puzzles the researcher wished to study. The logic of using purposive sampling was to select information-rich respondents. In-depth information-rich cases are those from which one can learn a great deal issues of central importance to the purpose of the research, thus the term purposive sampling (Mason & Griffin, 2002).

The study used primary data which was collected using one research instrument, namely, questionnaires.

To determine the validity of the items in the research instruments, a pilot study was conducted to the respondents from each category of the subjects. Cronbach’s alpha for all the variables were above .7 which is acceptable. The values were interpreted using the following criteria: α > .9 excellent, .9 > α > .8 good, .8 > α > .7 acceptable, .7 > α > .6 questionable, and .6 > α > .5 poor (George & Mallery, 2010). Results for Laissez faire leadership (α = .77) and autocratic leadership (α = .70) indicated acceptable reliabilities.

Data collected from the respondents was then checked for completeness. The data obtained from the research questionnaires were analyzed by SPSS version 20. This method of data analysis allowed the researcher to analyze huge amounts of data (Laws et al., 2003). Descriptive analysis was used because the researcher wanted to compare the responses of different groups (Creswell, 2009) and the data were mainly in terms of numbers. Tabulation was a part of the technical procedure wherein the classified data were put in the form of tables (Kothari, 2004). The study presented the means, frequencies, percentages, and standard deviations of participants that belonged to specific categories including gender, age, education level, teaching experience, years of stay in current PTTC, current rank and category of PTTC.

Several moral principles were applied while interacting with respondents including being respectful, fair and promoting healthy relationships. The researcher was cautious and avoided hurting the respondents. The researcher explained and clarified all issues pertaining to the study. There was openness to and honesty with the research participants. The researcher explained to participants the purpose of the study and other information they needed. This step increased their willingness to participate. The researcher maintained confidentiality and also explained the benefits which participants could derive from the research. The researcher obtained “informed consent” letter from the university. Respondents’ anonymities were preserved to avoid possible embarrassment for providing certain information (Jonser, 2002).

In Table 2, the results revealed that Laissez faire and autocratic leadership styles were less exhibited by principals of PTTCs in Lake Victoria Region of Kenya. The overall means for the four statements of Laissez faire leadership was 2.16 with a standard deviation of .923, while the overall mean for the four statements on autocratic leadership was 2.78 with a standard deviation .959.

In Table 3, the results reveal that organizational performance had a moderate mean of 3.22. The standard deviations of .718 showed acceptable range.

In Table 4, the correlation shows the correlation shows that Laissez faire leadership had a weak negative correlation with organizational performance (r = −.203; p = .005 < .05). Similarly, autocratic leadership had a weak negative correlation with organizational performance (r = −.184; p = .011 < .05). The p-values (p < .005 and p < .011) show a statistically significant correlation between Laissez faire and autocratic leadership styles and organizational performance.

Source: Survey data (2019).

Source: Survey data (2019).

**Correlation is significant at the .01 level (2-tailed). *Correlation is significant at the .05 level (2-tailed). Source: SPSS output, 2019.

The regression results of the model are presented in Table 5, R = .237 (R² = .056) shows that a combination of Laissez faire and autocratic leadership styles account for 5.6% decrease in organizational performance. Individually, R² = .041 (R = .203) shows that Laissez faire leadership alone accounts for 4.1% decrease in organizational performance, while R² = .034 (R = .184) shows that autocratic leadership alone accounts for 3.4% decrease in organizational performance. The full model containing all predictors was statistically significant because the p-values of .004, .005 and .011 are less than the significant level of .05. Also, according to Field (2013), Durbin-Watson values less than 1 or more than 3 is a cause of concern. Thus, Durbin values 2.200, 2.181 and 2.151 suggest that there is no auto-correlation in our model.

Table 6 presents the analysis of variance (ANOVA) or model fit results. For

^a1Predictors: (Constant), Autocratic leadership, Laissez faire leadership; ^a2Predictors: (Constant), Laissez faire leadership; ^a3Predictors: (Constant), Autocratic leadership; ^bDependent Variable: Organizational Performance. Source: SPSS output, 2019.

^a1Predictors: (Constant), Laissez faire leadership, Autocratic leadership; ^a2Predictors: (Constant), Laissez faire leadership; ^a3Predictors: (Constant), Autocratic leadership; ^bDependent Variable: Organizational performance. Source: SPSS output, 2019.

organizational performance (F(2, 190) = 5.655; p = .004 < .05) meaning the model has power to predict organizational performance significantly from leadership scores. However, the very low regression sum (5.555) as compared the very high residual sum (93.319) indicates that the model does not explain most of the variation in the organizational performance.

For Laissez faire leadership (F(1, 191) = 8.194; p = .005 < .05) meaning the model has power to predict organizational performance significantly from Laissez faire leadership scores. However, the very low regression sum (4.067) as compared the very high residual sum (94.806) indicates that the model does not explain most of the variation in the organizational performance.

For autocratic leadership (F(1, 191) = 6.668; p = .011 < .05) meaning the model has power to predict organizational performance significantly from autocratic leadership scores. However, the very low regression sum (3.335) as compared the very high residual sum (95.538) indicates that the model does not explain most of the variation in the organizational performance.

The model to be tested was

^aDependent Variable: Organizational performance. Source: Field data, 2019.

Y = β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + ε

where:

Y = the predicted value for organizational performance

Β₀ = the y-intercept of regression line (the level of organizational performance in the absence of demographic factors) (3.762)

Β₁ = the slope of the regression line of Laissez faire leadership (the regression line is decreasing) (−.124)

Β₂ = the slope of the regression line autocratic leadership (the regression line is decreasing) (−.097)

X₁ = Laissez faire leadership (−.157)

X₂ = Autocratic leadership (−.130)

Ε = Error term (.172+ .058 + .056 = .286)

Y 1 = β 0 + β 1 X 1 + β 2 X 2 + ε

Table 8 below shows the performance of the nine colleges in PTE Examinations from 2016 to 219. The performance was examined using a 9-point scale ranging from 1 for best performance and 9 for worst performance. The ranking according to college mean grade is as follows. In first position was COL-01 with a mean grade of 4.98. In second was COL-05 with a mean grade of 5.11, third was COL-09 with a mean grade of 5.28, fourth was COL-04 with a mean grade of 5.37, fifth was COL-03 with a mean grade of 5.39, sixth was COL-06 with a mean grade of 5.44, seventh was COL-02 with a mean grade of 5.52, eighth was COL-07 with a mean grade of 5.54, ninth was COL-08 with a mean grade of 5.65. Despite not having more adequate infrastructural and instructional facilities, public PTTCs still performed better in Primary Teacher Education national examinations with an average mean of 5.27 as compared to private PTTCs with an average mean of 5.65. The finding has supported the position taken by the tutors who took part in the questionnaire survey whose result was a mean score of 3.1 which was an average performance.

Overall, the findings revealed that public PTTCs performed better than private PTTCs in PTE examinations. These results could be attributed to the fact that public PTTCs had better learning facilities and more established staffs. However, the findings were not in agreement with the tutors’ responses in the questionnaire that PTTCs in Lake Victoria Region of Kenya perform above average (3.61) in co-curricular activities.

Source: Field data (2019).

In Table 9, the correlation shows that demographic factors had negligible correlation with organizational performance. Gender (r = −.042, p = .560 > .05); age (r = −.038, p = .600 > .05); education level (r = .062, p = .390 > .05); teaching experience (r = −.045, p = .537 > .05); and lastly years of stay in current PTTC (r = .062, p = .391 > .05). None of the demographic factors was statistically significant at 5% because the p-values of .560, .600, .390, .537 and .391 are more than the significant level of .05.

In Table 10, a summary of multiple linear regression results of the model for the demographic factors are presented. The R² = .009 shows that demographic factors account for only .9% variation in organizational performance. Also, Durbin value of 2.073 suggests that there is no auto-correlation in our model.

Table 11 presents the analysis of variance (ANOVA) or model fit results. For demographic factors (F(5, 187) = .343; p = .886 > .05) meaning the model does not have power to predict organizational performance significantly from demographic scores. Also, the very low regression sum (.899) as compared the very high residual sum (97.974) indicates that the model does not explain the variation in the organizational performance.

The model to be tested was

Y 2 = β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + β 5 X 5 + ε

where:

Y₂ = the predicted value for organizational performance

**Correlation is significant at the .01 level (2-tailed).

^aPredictors: (Constant), Years in current TTC, Gender, Educational level, Age, Teaching experience; ^bDependent Variable: Organizational performance. Source: Field data, 2020.

^aDependent Variable: Organizational performance; ^bPredictors: (Constant), Years in current TTC, Gender, Educational level, Age, Teaching experience.

Β₀ = the y-intercept of regression line (the level of organizational performance in the absence of demographic factors) (3.252)

Β₁ = the slope of the regression line of gender (the regression line is decreasing) (−.057)

Dependent Variable: Organizational performance. Source: Fiend data, 2019.

Β₂ = the slope of the regression line age (the regression line is decreasing) (−.005)

Β₃ = the slope of the regression line of educational level (the regression line is increasing) (.053)

Β₄ = the slope of the regression line of teaching experience (the regression line is constant) (.000)

Β₅ = the slope of the regression line of stay in current PTTC (the regression line is decreasing) (.022)

X₁ = Gender (−.041)

X₂ = Age (−.015)

X₃ = Educational level (.052)

X₄ = Teaching experience (.001)

X₅ = Years of stay in current PTTC (−.057)

ε = Error term

Y 2 = β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + β 5 X 5 + ε