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«VOLUM E 1 1, N UM B E R 1 I S SN 2 1 6 8 - 0 6 1 2 F L ASH DR I V E I S SN 1 9 4 1 - 9 5 8 9 ON L I N E T h e In s t it ut e f o r Bu s i n e s s an ...»

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In the case of spreadsheet tools, up to 121 (57.1%) were below average, including 50 (48.5%) participants who were prepared and 71 (65.1%) who were unprepared for eLearning. In connection to this finding, the analysis obtained a computed Chi-square (χ2) value of 5.294 (corrected for continuity), with 1 degree of freedom and a p-value of 0.021. This finding was significant at 0.05 error margin, suggesting up to 95% chance that lecturer’s preparedness for eLearning significantly related to competence in applying spreadsheet tools. Consequently, the null hypothesis (H02), stating that there is no significant relationship between lecturers’ competence in spreadsheet tools and their preparedness for eLearning was rejected.

For presentation tools, Table 5 shows that 122 (57.5%) were below average; this included 48 (46.6%) participants who were prepared for eLearning and 74 (67.9%) who were unprepared. The analysis obtained a computed Chi-square (χ2) value of 8.971 (corrected for continuity), with 1 degree of freedom and a pvalue of 0.003, which is significant at 0.01 error margin; suggesting up to 99% chance that lecturers’ preparedness for eLearning significantly related to their competence in applying presentation tools. In this regard, the null hypothesis (H03) stating that lecturer’s competence in using presentation tools has no significant relationship with their preparedness for eLearning was also rejected.

GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 474 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 Table 5 further shows that 159 (75.0%) participants were below average in the application of statistical analysis tools; this included up to 67 (65.0%) who were prepared for eLearning and 92 (84.4%) who were unprepared. Here, bivariate analysis obtained a computed Chi-square (χ2) value of 9.574 (corrected for continuity), with 1 degree of freedom and a p-value of 0.002, which was significant at 0.01 error margin.

This suggests up to 99% chance that competence in working with statistical analysis tools was one of the factors likely to influence lecturer’s preparedness to function in an eLearning environment. This led to rejection of the null hypothesis (H04), which stated that there is no significant relationship between lecturers’ competence using in statistical analysis tools and their preparedness to apply eLearning.

Table 5: Competence in software tools

–  –  –

The software tools most applied by participants included the internet browsing tools such as Mozilla Firefox and Google Chrome, as well as e-mailing tools such as Yahoo mail, Gmail, Eudora and Microsoft Outlook.

More specifically, Table 5 shows that 168 (79.2%) participants were above average in applying Internet browsing tools, including 86 (83.5%) who were prepared for eLearning and 82 (75.2%) who were unprepared. Bivariate analysis for competence on Internet browsing yielded a computed Chi-square (χ2) value of 1.726 (corrected for continuity), with 1 degree of freedom and a p-value of 0.189, which was not significant. Consequently, the null hypothesis (H05) stating that the relationship between lecturers’ competence in using internet tools and their preparedness to apply eLearning is not statistically significant was not rejected due to insufficiency of empirical evidence.

For e-mailing tools, 167 (78.8%) were above average; including 84 (81.6%) and 83 (76.1%) who were prepared and unprepared for eLearning, respectively. The bivariate analysis obtained a computed Chisquare (χ2) value of 0.631, with 1 degree of freedom and a p-value of 0.427, which was also not significant.

Consequently, those prepared and those unprepared for eLearning were not significantly different in terms of competence in using e-mailing tools. This implies that competence in using e-mailing tools was less likely to influence lecturer’s preparedness for eLearning.

GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 475 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 Impediments to computing competence & preparedness for eLearning Computing competence and preparedness for eLearning are influenced by lack of formal training, inadequacy of time and financial resources to pursue training. Computing competence is also hindered by the ineffectiveness of ICT training programme targeting academic staff, which is perceived to be underfunded, selective and unclear selection criteria. Even those already trained need refresher sessions to catch with technological changes. For instance, those who trained in Microsoft DOS could not affectively work with programmes based on new operating systems such as Windows 7, Windows 8, or Linux.

Computing competence was also hindered by lecturers’ engagement with administrative duties, which consumed the time that could be used to acquire new or improve ICT skills. The heavy workload was exacerbated by mass enrolment in regular and self-sponsored programmes. Work-related pressure and desire to make extra income from self-sponsored programmes were gradually diverting the lecturers’ interest from developing ICT skills. The available time is utilised for teaching various groups of students, marking and performing administrative duties. Lack of opportunity to enhance computing competence was also linked to uncertainty, anxiety and fear of going through the transition to an eLearning mode. Worse still, anxiety is perpetuated by the expectation to try new ideas as well as technological changes and advancement. Consequently, some software tools are perceived to be too complicated; prompting lecturers to stick to the traditional modes, such as pen-paper or chalk-black wall. Similarly, some lecturers perceive the transition to eLearning as threat to their career. Some informants linked the fear and anxiety to lack of consistent technical support and post-training guidance, particularly at the departmental level.





Shortage of modern and efficient computers at the workplace was also a key factor impeding lecturers’ computing competence. Obsolete machines are not only time wasting but also reinforcing fear and anxiety about their ability to cope with teaching and learning challenges that are likely to come with eLearning. To cope with shortage of computers, some staff members are using their personal computers to undertake University work. Still on infrastructure, computing competence and preparedness for eLearning is impeded by unreliable internet connectivity. Computing competence and preparedness for eLearning was further influenced by lack of ICT centres at the departmental level, where academic staff could go for quick consultation. This was particularly necessary because of staffing shortage, which makes it difficult for lecturers to access technical support at the shortest notice. Given that some lecturers are loaded with administrative duties and classes, delays in technical support only widen distance between them and computers.

In addition, computing competence and preparedness for eLearning is affected by lack or inadequacy of eLearning resources. Also critical is the shortage of specialised eLearning facilities, particularly online learning management systems (LMS) such as Blackboard, WebCT, FirstClass, Moodle and Lotus Learning Space, among others. LMS have the potential to save costs, time and can help to improve the effectiveness of learning processes. Other resource materials that should be considered by the University include specialised libraries where lecturers can access information to help them improve skills, as well as videoconferencing facilities.

SUMMARY AND CONCLUSIONS

The purpose of this study was to determine the influence of computing competence in various software tools on lecturers’ preparedness for eLearning. The study found that participants whose competence in working with word processing tools was above average were likely to be better prepared for eLearning than those whose competence was below average (computed χ2=30.089; df=1; p-value=0.000). Multivariate analysis indicated that participants who competence in word processing tools was above average had about

5.7 the odds of being prepared for eLearning as those whose competence was below average. Preparedness for eLearning significantly related to competence in applying spreadsheet tools (computed χ2=5.294; df=1;

GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 476 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 p-value=0.02. Participants whose competence on spreadsheets was above average were about 2.2 times as likely to be prepared for eLearning as those whose competence was below average.

Lecturers’ preparedness for eLearning significantly associated with competence in working with presentation tools (computed χ2=8.971; df=1; p-value=0.003). In this regard, those whose competence was above average had about 5.1 times the odds of being prepared for eLearning as those whose competence was below average. Competence in working with statistical analysis tools was one of the factors likely to influence lecturer’s preparedness to function in an eLearning environment (computed χ2=9.574; df=1; pvalue=0.002). In this regard, participants whose competence in statistical analysis tools was above average were about 1.7 times as likely to be prepared for eLearning, as those whose competence was below average.

Finally, lecturer’s preparedness for eLearning and competence in Internet browsing tools was not significant (computed χ2=1.726; df=1; p-value=0.189).

Training in computing skills is essential for lecturers’ preparedness for eLearning. Although up to 73.5% of the participants had accessed some training in various software tools, more than two-thirds had not benefitted from training provided by the University. Most participants financed their own training in commercial colleges; however, basic computer training in Kenya has been commercialised to the extent that most commercial institutions barely meet the minimum threshold for curriculum delivery.

Consequently, even those who had trained were still not competent enough to function in an eLearning setting. At the University of Nairobi, computing competence training is provided by the School of Computing and Informatics. However, most academic staff were yet to benefit from the initiative, on account of issues such as funding constraints, lack of awareness, as well as preoccupation with academic and administrative duties.

Lack of time to undergo training is a reality that should also be considered to create room for academic staff. This is particularly critical for departments experiencing over-enrolment in self-sponsored programmes. Structuring the training programme and harmonising its schedules with academic semesters is one of the critical measures that should be considered to enable lecturers acquire skills necessary for an eLearning environment. Other critical options include making the University training programme continuous to take care of refresher needs as well as staff attrition.

The effort to prepare academic staff to function in an eLearning setting should consider issues such as uncertainty and anxiety of going through the transition process from traditional modes of delivery to the eLearning mode. Anxiety is particularly perpetuated by the fear of trying out new ideas as well as technological changes. Unmanaged feeling of anxiety is likely to precipitate reluctance and resistance to transit to eLearning. Anxiety is also likely to prevent academic staff from accepting training, as well as influence negatively the perception on the ease of using technology in teaching and learning processes. This calls for change management to help lecturers adjust accordingly in favour eLearning.

Change is a fearful process that is also filled with anxiety. People fear that change may bring new challenges or deprive them of certain opportunities or privileges. To ensure that all lecturers share in the vision of eLearning and walk along with the change process, sustained sensitisation and education is an indispensable pre-requisite. Sustained sensitisation is particularly necessary because changing mindset takes time and cannot be achieved over night. Besides academic staff, the change process should target top leaders of the University. As a matter of fact, change can be realised faster when leaders and administrators become role models. They should undergo training in computing and eLearning processes to inspire their junior colleagues.

Considering the requirements for an effective eLearning system, there is no doubt that it is a costly initiative, particularly to resource-poor countries. However, eLearning remains important for lecturers and learners to develop competencies necessary for tackling social and economic development challenges experienced in GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 477 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 the 21st century. In other words, eLearning has the potential to enhance digital literacy skills and creating knowledge-based economies required for socio-economic development as envisaged in international and national blueprints.

ACKNOWLEDGEMENT

We are grateful to the University of Nairobi for granting the opportunity for to the first author to pursue the PhD degree in Distance Education. Secondly, we thank all the participants who took their time to provide the requisite information. Thirdly, we are indebted to Tom Odhiambo, an independent research consultant for reviewing the manuscript.

BIOGRAPHY

Nicholas Kut Ochogo is a lecturer at the University of Nairobi. He holds a Master’s degree in Project Planning and Management from the University of Nairobi and a doctorate degree from the University of Nairobi.



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