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. 2022 Mar 31;8(4):e09200.
doi: 10.1016/j.heliyon.2022.e09200. eCollection 2022 Apr.

Technology and instructor dimensions, e-learning satisfaction, and academic performance of distance students in Ghana

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Technology and instructor dimensions, e-learning satisfaction, and academic performance of distance students in Ghana

Ahmed Bossman et al. Heliyon. .

Abstract

E-learning is soon expected to be widely used as a teaching and learning method in the mainstream for educational institutions. Given the relative preparedness of advanced economies, the conclusions about their implementation level with e-learning are incomparable with emerging countries. Emerging economies must, therefore, be aware of the issues to consider when formulating successful adoption or implementation strategies. However, empirical studies that bring forth these relevant factors are out of context. In a single framework, we model the structural relationships between the drivers of e-learning satisfaction and the performance of distance learning students in a frontier economy, Ghana. With 388 validated responses gathered from an online survey across the country between 29 May 2021 and 25 June 2021, we employ the Smart-PLS estimator to process and analyse the data. We explicate that the substantial drivers of e-learning satisfaction and performance among distance learning students include technology anxiety, instructor factors, course quality, technology quality, and ease of use. Our findings divulge that perceived learner satisfaction mediates the relationships between the drivers of satisfaction and learning outcomes of distance learning students in Ghana such that technology anxiety and instructor factors would not essentially enhance learner performance in the absence of e-learning satisfaction. Consequently, system quality, reflected by the information system success model must be supplemented by satisfaction, drawn from the expectation-confirmation theory, to fully explain the impact of efficient e-learning systems on learning outcomes. Not only does ease of use create satisfaction, but it also boosts performance. We, therefore, recommend institutions to develop regular training for both facilitators and students and also adopt user-friendly online platforms to aid patronage by learners.

Keywords: Distance education system; Instructor factors; Learning outcomes; Technology anxiety; e-learning satisfaction.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Conceptualised model of expected relationships. Notes: TA – technology anxiety; ID – instructor dimension; CQ – course quality; EU – ease of use; TQ – technology quality; SAT – satisfaction; PFM – performance.
Figure 2
Figure 2
Structural model, path coefficients, and t-statistics. Notes: path coefficients in regular texts; t-statistics in parenthesis; R-squared values are in white fonts. TA – technology anxiety; ID – instructor dimension; CQ – course quality; EU – ease of use; TQ – technology quality; SAT – satisfaction; PFM – performance.

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