Technologies for teaching and learning have expanded over the years, with higher education institutions taking a lead in their application. However, research shows that workshops and training by higher education have focused mainly on skill acquisition on the use of these technologies, leaving out the pedagogical dimension. During COVID-19 pandemic, many institutions that did not have or had very little experience with online learning adopted technology for remote teaching. This development necessitates alignment of current teaching techniques with rapidly changing and expanding digital tools and expectations for online teaching and learning. One of the ways of ensuring success of online learning is e-moderation. E-moderation is a term coined by [12], a known scholar in distance and online approaches to learning. It refers to a wide variety of roles and skills that the online teacher, lecturer or trainer needs to acquire in order to operate efficiently. E-moderation enables teaching to be learner—centred by enabling instructors to provide adequate scaffolds for learners. This study examined three areas of e-moderation, namely, access, motivation and online socialization as provided by instructors of PGDE programme at the University of Nairobi. These areas of e-moderation were adapted from five-stage model by [12], cited in [11]. The five-stage model of e-moderation has Access and motivation at the base of the pyramid. At this stage, e-moderators set up the system and make it accessible to users. They also welcome the learners and encourage them to participate in the programme. Stage two is the Socialization stage, in which bridges are provided to ease interaction in the learning environment. The third stage is Information exchange, in which facilitation is done via learning materials. In stage four, Knowledge construction takes place. The fifth stage is Development, where links are provided outside closed conferences.

The study is anchored on Social Presence Theory (SPT) as expounded by [13]. Inherent in online learning are feelings of isolation among online learners. Lecturers who often take cues by observing learners cannot do this online. Social Presence Theory is therefore applicable as it explains the much-needed connection in a virtual learning environment. SPT is premised on the assumption that communication and media are not identical in their ability to make people in separate locations feel as if they are connected with one another, yet learning is all about communication. The question is: how does an instructor maintain presence in an online learning environment? SPT, when applied to online learning, endeavours to explain how, in a computer-mediated communication, a person is perceived to be “real”. The level of social presence influences the quality of virtual interactions and outcomes. In e-moderation, the interaction between the learner, the medium and the instructor is seen to create the much-needed “presence” in a learning environment, hence the applicability of SPT theory to the study.

The study aimed to establish the contribution of e-moderation in terms of access, motivation and online socialization to student uptake of PGDE online programme at the University of Nairobi as perceived by the learners. The programme is offered fully online and therefore e-moderation is considered an important component in an online learning environment.

1) How does Access influence uptake of PGDE online programme at the University of Nairobi?

2) In what way does Motivation influence uptake of PGDE programme at the University of Nairobi?

3) How does online Socialization influence uptake of PGDE programme at the University of Nairobi?

H1: There is no relationship between access and uptake of PGDE online programme at the University of Nairobi.

H2: There is no relationship between motivation and uptake of PGDE online programme at the University of Nairobi.

H3: There is no relationship between socialization and uptake of PGDE online programme at the University of Nairobi.

[12] puts access and motivation at the base of the ladder in the five-stage model. The e-moderator’s role is to welcome students and encourage them to interact. It is important to note that COVID-19 era brought about a switch to remote education that was often confused with online learning. Providers of remote education, which was a kind of emergency measure should never be expected to be e-moderators who are able to voluntarily provide access and motivation. Successful e-moderators acquire skills through training and experience ([12]). Individual access and participation in online environment go beyond taking content on PowerPoint to a computer. Online learning includes interaction between neural, cognitive, motivational, affective and social processes ([1]). It is the e-moderator’s role to enable this interaction. There should be a deliberate effort at the design stage to in-build access factors into the design of the content. Other than enabling technological access through training, content access that is engaging, collaborative and socially impactful beyond the learning environment is important to the success of an online programme. Setting up the system and inducting learners on technology issues is of course of essence. However, accessing the content is the ultimate aim of a course designer. [3], cited in [12], underscores the need for interaction between participants and the e-moderator. This gives importance to access as not only referring to the systems in place and content but access as it applies to the e-moderator as well. [12] posits that it is this exchange, review and reflection on each other’s ideas that leads to construction of new knowledge. A study done by [3] concluded that online learners are not looking for self-study courses and so contact and interaction remains of great importance. In view of this, an e-moderator should be accessible to learners to respond to issues that arise, such as access to LMS and VLE, welcoming the learners and ensuring that none of the participants are left behind due to technical hitches. In the PGDE programme offered by the University of Nairobi, this role is crucial in enabling learners to use various components of video conferencing facilities like chats, breakaway rooms and LMS functions such as discussion forums, wikis, assignments segments, as well as assessment components.

The question of what drives a person to pursue a particular course of action has been a subject of interest among scholars and especially psychologists over the years. In education circles whether the drive is intrinsic or extrinsic learners need motivation in order to achieve their objectives. The subject of motivation is of particular interest to online educators since it requires a highly motivated person to follow through with online education. An article by online learning service provider, [9], identified internal factors (intrinsic) that can demotivate online learners and how e-moderators can minimise such factors. These factors include health issues, personal learning difficulties and low-value course content. E-moderation comes in handy in these circumstances, for example, by providing easy-to-follow study materials, varying teaching approach and dealing with test anxiety. Dealing with test anxiety, which is a common source of demotivation in online learning, can be done by preparing learners to appreciate that tests are not a competition but a preparation for real-life experiences. Tests should therefore be done in such a way that it is deemed to be helpful beyond the learning process. According to [9], external causes of demotivation in online learning include excessive assessment by instructors, negative attitude caused by peers and unnecessary distractions such as poor lighting, interference from people within the learning environment, social media and games. It is believed that knowledge of external and internal DE motivators by e-moderators could go a long way in managing successful online learning. Preparation by e-moderators may include adoption of differentiated curriculum with adequate scaffolds to enable learners navigate the system and sustain interest throughout the learning period. As Lepper and Malone (1997), cited in [4], posit technology can be a motivating factor in itself for online learners for a time but frustrations with technology can reduce intrinsic motivation. Interest aroused by technology can also wane with time. To sustain interest, e-moderators may encourage learner-to-learner support through collaboration. As discussed by [4], [8], technology-mediated learning environment can be complex for learners but through collaboration by use of online tools such as Google docs, chat rooms in video conferences and proper regulation, learners can interact with their peers and dim the feeling of isolation that is common among online learners.

One of the ways in which e-moderation works well in VLE is by scaffolding students in their social interaction. [15] pointed out that online courses are not simply print correspondence in which the content is delivered via Internet. Social interaction should be in-built on teacher-student, teacher-parent and student-student communication. The presence of non-verbal cues in an online environment has been noted to be a starting point in building online social interaction by many scholars, including [15], [8] and [7]. Sustained online interaction among the stakeholders leads to the creation of a community of learners. For peer-to-peer interaction, the role of the e-moderator is to ensure that sustained social interaction is maintained through group projects or activities. With the mediation of web conferencing tools that include webcam as well as chat functions, learners are exposed to real-world scenarios similar to what companies are increasingly using in work place. This further exposes online learners to 21st-century work place experience.

On access, learners were asked whether they got any training on how to use e-class (LMS). Table 1 presents the results obtained.

Table 1. Access to PGDE programme.

Table 1 indicates that 15 (50%) respondents agree that they are facilitated to access the system through online meetings, 6 (20%) disagree that they are facilitated, and 6 (20%) responded neutral. The remaining 3 (10%) strongly disagreed that the university facilitates them. None responded to strongly agree.

Table 1 also indicates responses on availability of technical assistance. On this indicator, 20 (67%) strongly disagreed that there is technical assistance. Eight (27%) disagreed with the statement that there is technical assistance, while 2 (6%) agreed that they get assistance. There were however no responses for strongly agree and none were undecided.

On a non-directional question, respondents were asked what they would recommend to enhance access in the programme. Majority suggested that technical assistance should be enhanced, while others were of the opinion that refresher training should be done frequently on technology training.

Another aspect of e-moderation tested was motivation. Respondents were asked to indicate their level of perception on whether a motivating environment is provided by the university for the learners in the programme. Table 2 presents the findings.

Table 2. Motivation of learners in PGDE programme.

Findings show that 24 (80%) respondents felt that they are not motivated by the university, as they strongly disagreed that the university provides a motivating learning environment for them. Responding to a question on welcome and support, 5 (17%) respondents strongly disagreed, 7 (23%) disagreed, 1 (3%) was neutral 10 (33%) agreed, while 7 (23%) strongly agreed. In response to a non-directional question, the learners pointed out that it is self-motivation that keeps them in the programme.

On the aspect of online socialization, respondents were asked to indicate their agreement on the presence of in-built social media platform in the programme that enables online interaction. They were also asked to indicate whether social media is used to encourage socialization. Table 3 presents findings from respondents.

Table 3. Online socialization and uptake of PGDE programme.

Findings on Table 3 indicate that 14 (48%) of respondents strongly agreed that there is online socialization that enables them to participate in the programme, while 12 (40%) agreed with the statement. Another 3 (10%) were neutral, while 1 (2%) of the respondents strongly disagreed that they had any experience with online socialization at all, indicating strongly disagree. The question on whether the programme has in-built social media platforms that enable socialization, 6 (20%) respondents strongly disagreed, 4 (13%) disagreed, none were neutral, 10 (33%) agreed and 10 (33%) strongly agreed with the statement that the programme has in-built socialization opportunities for leaners.

In order to test hypothesis, inferential analysis using correlation was done and results are presented in Table 4.

Table 4. Model summary.

^aPredictors: (Constant), Online Socialization, Access, Motivation.

In Table 4, R is the square root of R-Squared and is the correlation between the observed and predicted values of dependent variable, implying that the association of 0.900 between contribution of uptake of PGDE online programme at the University of Nairobi as perceived by the learners, which are level of Access, Motivation and Online socialization was strong.

R-Squared is the proportion of the variance in the dependent variable uptake of PGDE online programme that was explained by variations in the independent variable Access, Motivation and Online socialization. This implied that 81.0% of variance or correlation between variables in general but does not reflect the extent to which any particular independent variable Access, Motivation and Online socialization was associated with the uptake of PGDE online programme.

Adjusted R² is called the coefficient of determination, which indicates uptake of PGDE online programme varies with Access, Motivation and Online socialization. In Table 4, the value of adjusted R² is 0.788. This implied that there was a variation of 78.8% of student uptake of PGDE online programme with variation in influence of Access, Motivation and Online socialization and was statistically significant with P = 0.00 < 0.05. Other factors not studied contribute to 21.2% of effective e-moderation.

Table 5. ANOVA.

^aDependent variable: Uptake of PGDE online programme; ^bPredictors: (Constant), Online Socialization, Access, Motivation.

Table 5 gives an F-test to determine whether the model had a good fit for the data. The F-test (F = 36.959, P = 0.00 < 0.05) indicated that the model formed between uptake of PGDE online programme and influence of Access, Motivation and Online socialization had data with significant goodness of fit.

Table 6. Coefficients (a).

^aDependent variable: Uptake of PGDE online programme.

From the values in Table 6, 0.382, −0.299 and −0.065 are the unstandardized coefficients. These were the coefficients that the study would obtain when standardizing all of the variables in the regression, including the dependent and all of the independent variables. By standardizing the variables before running the regression, the study put all of the variables on the same scale and compared the magnitude of the coefficients of the independent to determine which one had more effects on effectiveness of Access, Motivation and Online socialization. The larger betas were associated with the larger t-values and lower P-values.

The column of coefficient shows that the predictor variables are constant, Access, Motivation and Online socialization. The first variable constant of 3.190 represented the constant that predicted value of uptake of PGDE online programme when all other variables were constant at zero (0).

From the above regression model, it was found that student uptake of PGDE online programme would be at 3.190 holding level of Access, Motivation and Online socialization constant at zero.

In Access to PGDE programme, where technical assistance is not readily available when there are challenges in accessing LMS leads to ineffectiveness in the uptake of PGDE online programme by a factor of 0.382 with P-value of 0.000. The findings depict that absence of Access to PGDE programme would undermine student uptake of PGDE online programme by factor of 0.382 with P-value of 0.000. At 5% level of significance and 95% level of confidence, this is statistically significant (P = 0.000 < 0.05) as the P-value is lower than 0.05.

On Motivation of learners in PGDE programme, lack of the university to provide a motivating environment for learners in PGDE programme lowers student uptake of PGDE online programme by a factor of −0.299 with P-value of 0.008. The findings depict that Motivation of learners in PGDE programme would lead to uptake of PGDE online programme by factor of −0.299 with P-value of 0.008. At 5% level of significance and 95% level of confidence, this is statistically significant (P = 0.008 < 0.05) as the P-value is lower than 0.05.

On online socialization and uptake of PGDE programme, social media platforms are inbuilt in the programme that enables interaction among participants, leading to effectiveness of student uptake of PGDE online programme by a factor of −0.065 with P-value of 0.029. The result is statistically significant because the P-value of 0.029 is less than the alpha level of 0.05.

This clearly indicated that there existed a positive relationship between student uptake of PGDE online programme and deficiency in any of the three independent variables: Access, Motivation and Online socialization in e-moderation on student uptake of PGDE online programme and were statistically significant as it had a P-value of 0.000, 0.008 and 0.029, which are smaller than 0.05. The study findings resulted in a linear model.

Linear Model for Access: Y = 0.382 − 0.000 X₁ + ε

Linear Model for Motivation: Y= 0.299 + 0.008 X₂ + ε

Linear Model for Online Socialization: Y = 0.065 + 0.029 X₃+ ε

where X₁ = Access, X₂ = Motivation, X₃ = Online Socialization.

Hypothesis was tested using the multiple regressions model in Table 6 and results are presented as follows:

H1:There is no relationship between access and uptake of PGDE online programme at the University of Nairobi.

The findings depict that Access to PGDE programme would lead to uptake of PGDE online programme by factor of 0.382 with P-value of 0.000. At 5% level of significance and 95% level of confidence this is statistically significant (P = 0.000 < 0.05) as the P-value is lower than 0.05.

The study therefore rejects the null hypothesis, implying that there is significant relationship between access and uptake of PGDE online programme at the University of Nairobi. On the basis of these statistics, the study concludes that there is significant positive relationship between access and uptake of PGDE online programme at the University of Nairobi.

H2:There is no relationship between motivation and uptake of PGDEonline programme at the University of Nairobi.

The findings depict that Motivation would lead to uptake of PGDE online programme by factor of −0.299 with P-value of 0.008. At 5% level of significance and 95% level of confidence this is statistically significant (P = 0.008 < 0.05) as the P-value is lower than 0.05. The study therefore rejects the null hypothesis, implying that there is significant relationship between motivation and uptake of PGDE online programme at the University of Nairobi.

On the basis of these statistics, the study concludes that there is significant positive relationship between Motivation and uptake of PGDE online programme at the University of Nairobi.

H3:There is no relationship between online socialization and uptake ofPGDE online programme at the University of Nairobi.

The findings depict that online socialization would lead to uptake of PGDE online programme by factor of −0.065 with P-value of 0.029 at 5% level of significance and 95% level of confidence, this is statistically significant (P = 0.029 < 0.05) as the P-value is lower than 0.05. The study therefore rejects the null hypothesis, implying that there is significant relationship between online socialization and uptake of PGDE online programme at the University of Nairobi. On the basis of these statistics, the study concludes that there is significant positive relationship between online socialization and uptake of PGDE online programme at the University of Nairobi.

4.6.1. Access to PGDE Online Programme

Form the findings on access to the programme, 50% of respondents agree that there are online meetings held to train them on how to access the university LMS but when it comes to technical assistance when they face challenges, 67% strongly feel that they do not get support. This view is reflected in the suggestions made by respondents that technical assistance needs to be enhanced, as well as refresher training on LMS access. Frustrations with technology in an online environment can be a deterrent factor to many learners. As [3] suggests, technical assistance should be readily available to learners, especially in LMS and VLE environments. This concurs with [1], who posited that online learning is simply not putting content on PowerPoint online but access should be enhanced to ensure that there is meaningful interaction with all the aspects of learning in the system. In view of this, it is imperative that for meaningful engagement, the university needs to put in place e-moderators who are tech savvy to assist learners when need arises. This will not only minimise frustrations felt by learners online but will also cut down time wastage for all parties involved.

4.6.2. Motivation and Uptake of PGDE Online Programme

Motivation, whether internal or external, is a documented factor in facilitating learning. In online learning environment, it is even more crucial since the sense of aloneness is pronounced. From the results, 80% of respondents feel that PGDE facilitators do not motivate them. In a non-directional question, they said it is self-motivation that keeps them in the programme. [12] recommends a strong technical and information support for online learners as well as strong motivation and encouragement. This will enable them to put on necessary time and effort. Access and motivation are at the base of five-stage model, purposely to underscore the importance of the two factors in e-moderation. When 80% of learners in a cohort feel lack of support in terms of motivation, it is time the university re-think how this aspect of e-moderation can be implemented. Moreover, as [10] put it, motivation is influenced by a wide variety of personal, social and economic circumstances. It is therefore important that an institution builds scaffolds that would help learners reach out when pressed with such issues.

4.6.3. Socialization and Uptake of PGDE Online Programme

Inherent in online learning is often the feeling of isolation. In fact, naysayers of this mode of education often point out that education is a social phenomenon and should therefore be done in a social environment. In online socialization, the learners not only establish their social identity but also find others with whom to interact. [5] in an article “Community by Design”) identifies community building as a number one factor in designing online courses, asserting that humans do not learn in a void since learning is a social event. The university should leverage on available social media platforms such as WhatsApp groups, Facebook and Instagram among others to enhance social interaction among the students.