Clarke International University, Kampala, Uganda.
BMC Med Educ. 2022 Sep 10;22(1):671. doi: 10.1186/s12909-022-03735-7.
During the recent Coronavirus pandemic, many universities realized that the traditional delivery of educational content was not adequate in the context of imposed restrictions. Adoption of e-learning was one obvious way to foster continuity of learning. Despite its rapid implementation during the lockdown in Uganda, it was not known whether health professional students were willing to adopt e-learning as a way to foster continuity of learning. We, therefore, adopted a Technology Acceptance Model to determine the predictors for the adoption of e-learning using learner and information technology variables.
A cross-sectional study among 109 health professional students ≥18 years of age at Clarke International University was conducted. Adoption of e-learning was measured as a self-report. Data were obtained using a smart survey and descriptively summarized. The differences in the study outcome were compared using the chi-square test. The factors that independently influenced the adoption of e-learning were determined using binary logistic regression and reported as adjusted odds ratios (aORs) with a 95% confidence interval (CI).
Of the 109 respondents, 71 (65.1%) adopted e-learning. Our data showed low odds of adoption of e-learning among participants in first year (aOR, 0.34: 95%CI, 0.14-0.79), low e-learning expectations (aOR, 0.01: 95%CI, 0.01-0.34), no confidence in using IT devices (aOR, 0.16: 95%CI, 0.00-0.77), no prior experience in e-learning (aOR, 0.11: 95%CI, 0.02-0.68), not considering e-learning flexible (aOR, 0.25:95%CI, 0.08-0.86) and high cost of internet (aOR, 0.13: 95%CI, 0.02-0.84).
We identified predictors of e-learning adoption which include having completed at least 1 year of study, high e-learning expectations, confidence in using IT devices, prior experience in e-learning, considering e-learning to be flexible and internet access. This information can be used by universities to enhance infrastructure and prepare potential e-learners.
在最近的冠状病毒大流行期间，许多大学意识到，在实施限制的情况下，传统的教育内容传递方式不够充分。采用电子学习是促进学习连续性的一种明显方式。尽管在乌干达封锁期间迅速实施，但尚不清楚卫生专业学生是否愿意采用电子学习来促进学习的连续性。因此，我们采用技术接受模型，使用学习者和信息技术变量来确定采用电子学习的预测因素。
在 Clarke International 大学对 109 名年龄在 18 岁及以上的卫生专业学生进行了横断面研究。采用自我报告来衡量电子学习的采用情况。使用智能调查获得数据，并进行描述性总结。使用卡方检验比较研究结果的差异。使用二元逻辑回归确定独立影响电子学习采用的因素，并报告调整后的优势比（aOR）和 95%置信区间（CI）。
在 109 名受访者中，有 71 名（65.1%）采用了电子学习。我们的数据显示，在第一年学习的参与者中，电子学习的采用几率较低（aOR，0.34：95%CI，0.14-0.79），电子学习期望较低（aOR，0.01：95%CI，0.01-0.34），对使用 IT 设备没有信心（aOR，0.16：95%CI，0.00-0.77），没有电子学习经验（aOR，0.11：95%CI，0.02-0.68），不认为电子学习灵活（aOR，0.25：95%CI，0.08-0.86），以及互联网费用较高（aOR，0.13：95%CI，0.02-0.84）。
我们确定了电子学习采用的预测因素，包括已完成至少 1 年的学业、对电子学习的高期望、对使用 IT 设备的信心、电子学习经验、认为电子学习具有灵活性以及互联网接入。这些信息可被大学用来加强基础设施并为潜在的电子学习者做好准备。
