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The group-based synchronously modality reflects a situation where groups of learners work together in real time via the Internet or Intranet; for instance, through videoconferencing. The synchronous mode is appropriate within contexts where Internet is stable. It may include text-based conferencing, and one or two-way audio and videoconferencing. Examples of this include learners engaged in a real-time chat or an audio-videoconference (Naidu, 2006). The group-based asynchronously modality refers to a situation where groups of learners work over the Internet or Intranet but where feedback occurs later; for instance, communication through electronic mail (Romiszowski, 2004; Naidu, 2006). The asynchronous mode is commonly applied in countries, where the Internet infrastructure is too weak or unreliable. Typical examples of this kind of activity include on-line discussions via electronic mailing lists and text-based conferencing within learning management systems (Romiszowski, 2004; Naidu, 2006).

ELearning has been gaining momentum in developed and developing countries alike over the past two decades, especially in response to the rapid advancement of ICT. The ability of new ICT facilities to support multimedia resource-based teaching and learning is fundamental to the growing interest in eLearning, world over (Farahani, 2003; Omwenga, 2004). The revolution in ICT continues to stimulate the design of eLearning courses, which in turn, influences the substance of university education. Statistical projections indicate that enrolment for university education through eLearning was expected to grow consistently from about 900,000 in 2003 to about 15.2 million learners by the end of 2012 (MENON Network, 2007).

The growing interest in eLearning seems to be coming from several directions. First, institutions of higher learning that have traditionally offered distance education perceive eLearning as a logical extension of their distance education activities. Such institutions also consider eLearning as an avenue for improving access to and expanding the market base for their academic programmes (Rosenberg, 2001), while the corporate sector views eLearning as a cost-effective way for staff training and development (Oblinger & Oblinger, 2005; Naidu, 2006). As noted by Kihara (2005), eLearning is fast becoming the ideal mode of university education in this age of knowledge-based economies and globalisation. To remain relevant, universities all over the world will have to redefine their mission and review their curriculum to integrate the use of technology. Similarly, Dunn (2000) asserts that the integration of eLearning is inevitable for institutions of higher learning that wish to remain relevant in the era of technology, while Volery (2000) emphasises the importance of eLearning to the future relevance and survival of universities across the globe.

Despite a high level of interest in eLearning, its integration in developing countries is constrained by inadequacy of necessary workplace infrastructure, including access to computers, reliability of Internet connectivity and access to ICT technical support, due to prohibitive establishment and operational costs.

GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 483 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 Consequently, transition from traditional modes of delivery to eLearning is gradual and requires heavy investments, not only on the necessary infrastructure but also in the development of human resource for technical backing (Naidu, 2005). ELearning is applauded for various reasons, including providing an alternative for learners who want to improve their skills but are unable to attend training centres situated away from their usual residence (Garrison & Anderson, 2003; Shephard, 2008). The method provides access to resource materials round the clock; implying that learners can access and use such materials at the most convenient time, place and pace. Again due to its flexibility, institutions of higher learning are often able to meet learning needs of their students and lecturers at a time, place and pace that are most convenient (Becta, 2003; Oblinger & Oblinger, 2005; Naidu, 2006).

The group-based synchronously eLearning modalities can be used to engage learners in active discussions, sharing ideas and passing information, with fast and accurate feedback (Koo, 2008). Besides, the advancement of ICTs has provided a wide range of software applications and computer conferencing technologies, which enable learners and lecturers to engage in synchronous as well as asynchronous interaction across space, time and pace for collaborative inquiry among students (Oblinger & Oblinger, 2005; Naidu, 2006). The application of multimedia machines, software packages and the internet motivates learners, resulting in better academic performance (Kerka, 2002; Ya-Ching, 2006), while ICTs facilitate the capture and storage of various types of information, including print, audio and video materials, which may not be possible within the spatial and temporal constraints of conventional educational settings (Kerka, 2002).

Preparedness for eLearning at institutions of higher learning is a function of various infrastructural elements, including access to computers at the workplace, reliability of Internet connectivity as well as availability of technical support, just to mention a few. According to Ngai, Poon and Chan (2007), the fundamental obstacle to the growth of eLearning is lack of access to necessary technological workplace infrastructure. Poor or insufficient infrastructure may restrict access to ICT facilities by lecturers, learners and administrators. Similarly, limited access to ICT infrastructure is likely to impair practice, efficiency and effectiveness of eLearning initiatives. Also crucial is the cost of system support and maintenance, as well as the appropriate training of staff to enable them make the most of technology (Ngai et al., 2007).

Studies conducted by Hitt and Hartman (2002), Gulbahar (2005) and Albirini (2006) suggest that preparedness for eLearning significantly associates with access to functional computers at the workplace, which often influences the proportion of lecturers using computers to support delivery of their lessons.

Besides, the adequacy of appropriate computers is also critical in determining the preparedness of lecturers to operate in an eLearning environment.

The linkage between Internet access and preparedness for eLearning has been documented in various studies, including Volery (2000) and Mercado (2008). Access to a stable Internet connectivity and a dependable computer is crucial for successful integration of eLearning. However, in developing countries, internet reliability remains a critical challenge primarily due to weak bandwidths (Ndume, Tilya & Twaakyondo, 2008). Preparedness for eLearning is influenced by the availability and adequacy of ICT technical support for lecturers. Without such support, those who may not be sure of where to turn for technical assistance may remain apprehensive in using ICT facilities (Preston, 2000). Lecturers operating in environments that are deficient of technical support often cite lack of such as the most critical obstacle to the application of ICT tools in teaching activities (Butler & Sellbom, 2002). A study conducted by Saekow and Samson (2011) also found that technical support was one of the key requirements for successful integration of eLearning initiatives.

The relationship between workplace infrastructure and lecturers’ preparedness for eLearning has been a subject of empirical investigation in many countries. However, very little documentation of the subject has been done in African countries, particularly in Kenya; leading to a dearth of academic literature to inform policy processes and programming. Although the University of Nairobi has been a leading icon in Open GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 484 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 and Distance Learning (ODL) activities within the East African region, eLearning is still at the early stages of development. Transition from the traditional mode to eLearning is constrained by various issues such as limited access to computers by lecturers, weak internet connectivity, inadequate technical support (Kariuki, 2006).

The eLearning idea has been nurtured for more than a decade; however, no academic initiative has fully investigated the influence of workplace infrastructure on lecturers’ preparedness for eLearning. A recent study conducted by Gakuu (2006) noted that although the application of ICT-based instructional modes was limited at the University of Nairobi, lecturers were positive about the integration of eLearning.

However, the study did not establish the linkage between workplace infrastructure and lecturer’s preparedness for eLearning. The key purpose of this study was to highlight infrastructural gaps, as well as ICT support needs among lecturers at the University of Nairobi. More specifically, the study was expected to determine the influence of access to workplace computers reliability of internet connection and timeliness of technical support on lecturers’ preparedness for eLearning.


This study was founded on the positivist philosophy of social research, holding that in social sciences, information derived from sensory experience is the exclusive source of all authoritative knowledge.

Besides, the world is external and objective; and that the observer is independent of the phenomena being observed. The positivist thought assumes that valid knowledge can only be found in scientific knowledge (Ashley & Orenstein, 2005). Based on the positivistic thinking, a cross-sectional survey design with both quantitative and qualitative approaches was applied to guide the research process (Babbie, 1973; Fowler, 1993). Whereas, the quantitative approach elicited information used for descriptive and inferential purposes using self-administered questionnaires, the qualitative approach obtained in-depth information through key informant interviews.

Primary data was collected in May 2011 from lecturers and administrative staff at the University of Nairobi.

Although the study focused on lecturers’ preparedness for eLearning, the inclusion of administrative staff was based on their crucial role in policy formulation, implementation and enforcement, which influence the work environment in which lecturers operate. Their inclusion in the study was purposed to identify policy gaps regarding ICT strategies, plans, budgetary allocations and ICT development, which are likely to influence lecturers’ preparedness to function in an eLearning environment. Unpublished data from the office of Deputy Vice Chancellor, Finance and Administration showed that the University had 958 academic and 108 administrative staff at the time of the study.

With a finite population of lecturers, one of Fisher’s formulae for sample size determination was applied to obtain a sample size of 213 participants. Stratified random sampling was applied to select the lecturers, with the stratification being based on colleges, gender and cadre. This ensured proportionate representation of all colleges; male and female lecturers; as well as assistant lecturers, lecturers, senior lecturers, associate professors and professors. Proportionate samples from each stratum were obtained by first, calculating the sampling fraction, as a quotient of the sample size (ni) and the population (Ni). Table 1 shows the proportionate sample sizes from each college.

From each stratum, simple random sampling was applied to select respondents. In addition, purposive sampling procedure was applied to select administrative staff, based on their availability and accessibility at the time of the study. The sample included 6 principals, 6 deputy principals, 6 registrars, 21 assistant registrars, 20 deans and directors, 13 associate deans and deputy directors; as well as 36 administrative assistants. Three sets of instruments, including a self-administered survey questionnaire for lecturers, a key informant interview schedule for administrators and an observation schedule were used to source the data.

The tools were pretested on 20 lecturers and 10 administrators, which was equivalent to about 10% of the GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 485 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 computed sample sizes for each category. Data was obtained by issuing questionnaires to lecturers, which were collected after two weeks. Administrators were interviewed at their places of work; the investigator sought informed consent from each participant. In this regard, participants were briefed about the study, purpose, potential benefits and that participation was on voluntary terms.

Table 1: Proportionate samples of academic staff for each college

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Both quantitative and qualitative techniques were applied to process and analyse. Quantitative data were analysed at three levels, namely univariate, bivariate and multivariate. Univariate analysis yielded frequency distributions and percentages; bivariate analysis obtained cross tabulations with Chi square (χ2) tests; while multivariate applied binary logistic regression to obtain beta co-efficients and odds ratios. All the quantitative analyses were performed using the Statistical Package for Social Sciences (SPSS) and MsExcel packages. In addition, qualitative data were organised and summarised in line with the thematic areas;

described to produce summary sheets; followed by systematic analysis and interpretation. Details about the methods applied in this study have been described in various publications, including Babbie (1973), Fowler (1993), Aldrich and Nelson (1984), Nachmias and Nachmias (1996), Mugenda and Mugenda (1999), Wuensch (2006), as well as Best and Khan (2004).


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