Applying the UTAUT2 to predict the acceptance of blended learning by university students

Abstract

PurposeThe study applied the Unified Theory of Technology Acceptance and Use Theory 2 (UTAUT2) to predict blended learning acceptance by students in universities in Zimbabwe. Blended learning is a heterogeneous mode of teaching and learning that combines face-to-face (F2F) and online modes. Owing to advances in technology, and recently, the advent of pandemics, such as COVID-19, the need for multimodal teaching approaches, such as blended learning, to enhance access to education in universities has become very important.Design/methodology/approachA quantitative approach that used a structured questionnaire for data collection from a sample of 432 postgraduate students was used. Data validation was done using confirmatory factor analysis (CFA). The structural equation modelling technique was used for data analysis.FindingsResults showed that out of the seven factors of the UTAUT2, the factors such as performance expectancy, effort expectancy, social influences, facilitating conditions and hedonic motivation significantly and positively influenced the behavioural intentions of students in universities to accept blended learning. On the other hand, habit and price value did not significantly influence university students' behavioural intentions to accept the bended learning mode. It was further shown in the study that behavioural intentions significantly influenced the acceptance of blended learning by university students. In light of the above results, it was concluded that the UTAUT2 could be used to predict the acceptance of blended learning by university students.Research limitations/implicationsThe main study limitation was that it was only carried out at universities that had information and communication technology (ICT) infrastructure challenges owing to the fact that the economic situation in Zimbabwe is depressed. Limited ICT infrastructure in the universities might have had some impact on the nature of behavioural intentions of students to accept blended learning as a learning mode. Further research could be carried out in countries with better economies that are able to fund ICT infrastructures of their universities and to establish whether the results of the current study could either be confirmed, disconfirmed or enriched.Practical implicationsThe paper suggests that universities need to increase investment in ICT infrastructure as well as in capacitating students with the necessary ICT skills for the effective use of institutional ICT when learning using the blended learning mode. Without adequate and appropriate ICT infrastructure as well as necessary ICT skills, students may develop low motivation levels and negative attitudes towards blended learning, which may eventually may affect their acceptance of the learning mode.Originality/valueThere is no known study that has been conducted using the UTAUT2 to establish antecedents of behavioural intentions of students to accept blended learning in the context of Zimbabwean universities. This study therefore opens new ground on factors influencing the acceptance of blended learning in the context of Zimbabwean universities. Also, the results showed that habit and price value do not significantly contribute to the behavioural intentions of university students to accept blended learning, which is not consistent with findings of past studies. This inconsistency opens new opportunities for further studies on the conditions under which these two factors can be used to significantly contribute to the development of behavioural intentions of students to accept blended learning.

Acceptance factors of Zara's shopping app among fashion consumers during COVID‐19

“…Hedonic Motivation (HM) is defined as the fun or pleasure derived from the use of technology and, according to previous works, it can be stated that this is a very influential factor concerning the consumer's intention to use the technology (Alalwan et al, 2018; Baabdullah et al, 2019; Brown & Venkatesh, 2005; Hamari & Koivisto, 2015). This is also corroborated in a current work (Rudhumbu, 2022). Based on the above, the following hypothesis can be formulated:Hypothesis Hedonic motivation positively affects the consumer's intention to use the Zara app .…”

“…In 2012 Venkatesh et al demonstrated through UTAUT2 that this variable has a notable influence with respect to the intention to use (Cabrera‐Sánchez & Villarejo‐Ramos, 2018). Other studies have also corroborated this positive effect (Agarwal & Sahu, 2022; Rudhumbu, 2022).…”

“…To this end, UTAUT established that the app will be used to a greater or lesser extent depending on how simple or complicated it is (Cabrera‐Sánchez & Villarejo‐Ramos, 2018). Different previous works establish their conclusions in the same direction (Al‐Gahtani et al, 2007; Arenas‐Gaitán et al, 2016) as well as current works (Rudhumbu, 2022) and therefore, the following hypothesis can be formulated:Hypothesis Effort expectancy positively affects the consumer's intention to use the Zara app .…”

“…Different previous works establish their conclusions in the same direction (Al-Gahtani et al, 2007;Arenas-Gaitán et al, 2016) as well as current works (Rudhumbu, 2022) and therefore, the following hypothesis can be formulated: Hypothesis 4. Effort expectancy positively affects the consumer's intention to use the Zara app.…”

Digital transformation in times of crisis: Challenges, attitudes, opportunities and lessons learned from students’ and faculty members’ perspectives

“…Various studies in different contexts have been conducted by using UTAUT to investigate the factors influencing emerging technologies such a mobile technology, artificial intelligence, wearable technology and smart technology (Aytekin et al, 2022;Lin et al, 2022;Mishra et al, 2022). The justification of using the first version of UTAUT rather than the extended ones such as UTAUT 2 and 3 was the variance of prediction of the first version was the highest 70% (Gunasinghe and Nanayakkara, 2021) where the other versions between 62 to 66% (Rudhumbu, 2022;Tetteh et al, 2022).…”