Intention to Use and Satisfaction of e-Learning for Training in the Corporate Context

Esterhuyse, Maxine; Scholtz, Brenda; Venter, Danie

doi:10.28945/3610

Cited by 34 publications

(34 citation statements)

References 63 publications

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“…The ability to stay at home was the major advantage of e-learning for the students in this study which was similar to the study conducted in Poland [ 16 ]. Apart from this, the reduction in accommodation and transport costs was a key benefit of e-learning in this study which is similar to another study [ 17 ]. When courses are available entirely online, distance does not become a major factor in getting education because physical presence is not required in college [ 18 ].…”

Section: Discussionsupporting

confidence: 90%

Nursing students’ attitude on the practice of e-learning: A cross-sectional survey amid COVID-19 in Nepal

2021

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Introduction In present days, the use of information technology (IT) in education is unquestionable. The mounting advancement of IT has changed the scenario of education. With the emergence of the current COVID-19 situation, it has undoubtedly provided a solution to most of our educational needs when all educational institutions remained closed due to the pandemic. This study aims to identify the nursing students’ attitude towards the practice of e-learning amidst COVID-19. Methods A descriptive web-based cross-sectional study was conducted among nursing students with a sample size of 470. A self-administered validated questionnaire along with a standard tool to measure the attitude was used for data collection. Data were analyzed using SPSS. Results The mean ± SD age of the respondents was 20.91± 1.55 years. The majority (76.4%) of the respondents used mobile for their study and 90.4% used Wi-Fi for the internet source. The main advantage of e-learning was stated as the ability to stay at home (72.1%) followed by the reduced cost of accommodation and transport (51.3%) whereas the internet problem (81.7%) was the major disadvantage followed by technical issues (65.5%). Only about 34% of the students found e-learning as effective as traditional face-to-face learning. The mean scores for the domains: perceived usefulness, intention to adapt, distant use of e-learning, ease of learning, technical support, and learning stressors were 3.1, 3.1, 3.8, 2.9, 2.9, and 2.5 respectively. Overall, 58.9% had a favorable attitude regarding e-learning. There was no significant association of overall attitude regarding e-learning with selected socio-demographic variables whereas it was positively associated with all of its six domains. All the domains were positively correlated with each other except for ease of learning with technical support and distant use, and technical support with learning stressor and distant use. Learning stressor versus distant use was negatively correlated with each other. Conclusion Though e-learning was implemented as a substitute during the pandemic, almost half of the nursing students showed a positive attitude regarding e-learning. The majority of the students had internet problems and technological issues. If e-learning can be made user-friendly with reduced technical barriers supplemented with programs that can enhance practical learning abilities, e-learning can be the vital alternative teaching method and learning in the nursing field.

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Section: Discussionsupporting

confidence: 90%

Nursing students’ attitude on the practice of e-learning: A cross-sectional survey amid COVID-19 in Nepal

2021

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“…Structural Equation modelling is a combination of Exploratory Factor Analysis (EFA) and multiple regression which also helps identify the causal relationship (Ullman et al 2001 ). Some of the items of the constructs were adapted from other studies (Eyitayo 2011 ; Esterhuyse et al 2016 ) and hence instead of using EFA, Confirmatory Factor Analysis (CFA) is used in this study to understand whether the data fit into the hypothesized measurement model (Thompson 2004 ). Factor analysis using varimax rotation was done initially to determine the number of factors which had an eigen value higher than 1.…”

Section: Methodsmentioning

confidence: 99%

Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam

Maheshwari

2021

Educ Inf Technol

148

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Educational institutions worldwide had to shift the teaching delivery mode from face to face to online teaching during COVID-19. Most of the universities in Vietnam were based on face to face learning until the sudden outbreak of COVID-19. This research study was conducted with 145 respondents and Structural Equation Model (SEM) was used for data analysis. The participants were undergraduate and post-graduate students in public and private universities who studied online during the pandemic in Vietnam. The purpose of this study was to understand what factors have an impact on students’ intentions to study online. The results show that institutional support and perceived enjoyment (satisfaction) affects the students’ intentions to study the course online in the future. Perceived enjoyment (PE) affects the online learning intentions (OLI) and PE is affected by ICT infrastructure and internet speed and access. Hence, this research adds new research variable defined as extrinsic factors (ICT infrastructure and access to the internet), which indirectly influences students’ intentions to learn online. Given the increased use of smart phones with this generation, it is advisable to integrate mobile technology in online learning and QR codes can be one of the ways to integrate that in the course materials. It is further recommended that to increase the perceived enjoyment of the students with the online learning, the lecturers might be encouraged to use videos, audios and instant messaging to contact and provide the feedback to the students. It is important for universities to prepare for any such future crisis. This study results will provide a useful insight to design the online courses effectively by considering all the factors impacting students’ intention and satisfaction.

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“…perceived usefulness, perceived ease of use, attitude measures were based on (Liu et al , 2009). Satisfaction and intention to use was adapted from (Esterhuyse et al , 2016). Perceived ease of use, perceived usefulness and attitude toward using the behavioral intention to use were derived from the original TAM model proposed by Fred Davis.…”

Section: Methodsmentioning

confidence: 99%

Understanding user perception toward artificial intelligence (AI) enabled e-learning

Kashive¹,

Powale²,

Kashive³

2020

IJILT

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PurposeThe purpose of this study is to explore the perception of the users concerning the role of artificial intelligence (AI) in enhancing personal learning profile (PLP), personal learning network (PLN) and personal learning environment (PLE) and their effect on the perceived ease of use, perceived effectiveness and perceived usefulness for enhancing the overall attitude and satisfaction of the e-learning.Design/methodology/approachThe data were collected from students and professionals who have ever used the e-learning module, and smart partial least square-structural equational modeling (PLS-SEM) is used to see relations between the different variables.FindingsIt was seen that the PLE is affecting both perceived ease of use and perceived usefulness. The research has shown that perceived ease of use showed a mediating effect between PLE and attitude and satisfaction. Further satisfaction mediates between perceived ease of use and intention. PLP has come out to significantly impacting perceived effectiveness. The multigroup analysis also showed that the attitude and satisfaction level affecting intention to use the e-learning module differ across the two groups of learners, i.e. gender and type of learners.Research limitations/implicationsThe data are collected from students and professionals who have ever used the e-learning module and wholly based on their perceptions, leading to self-perception bias.Originality/valueThe current research is trying to integrate the user perception of PLP, PLN, PLE into the framework of the technology acceptance model and see how they impact the overall attitude and satisfaction of the learners. AI can be used to improve them and make e-learning more adherent to the users. AI can play an essential role in generating the right environment by matching the profile of the learner.

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Intention to Use and Satisfaction of e-Learning for Training in the Corporate Context

Cited by 34 publications

References 63 publications

Nursing students’ attitude on the practice of e-learning: A cross-sectional survey amid COVID-19 in Nepal

Nursing students’ attitude on the practice of e-learning: A cross-sectional survey amid COVID-19 in Nepal

Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam

Understanding user perception toward artificial intelligence (AI) enabled e-learning

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