The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre- and post-adopters

With the spread of new educational technology such as the interactive whiteboard (IWB) teachers, as potential users, need to adapt their teaching in order to successfully utilize it. Despite considerable efforts in motivating teachers to use new educational technology, there are mixed feelings about whether to accept and use this technology in the classroom or not. In this study we propose to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) with a new moderator variable user type in order to investigate differences in the UTAUT determinants between pre- and post-adopters of IWBs. The results of the study showed significant differences in causal effect sizes between pre- and post-adopters for several paths of the proposed research model. When compared to post-adopters, we can see that for pre-adopters: 1) social influence has a bigger impact on behavioral intentions, 2) performance expectancy more strongly affects attitudes toward using IWBs, and 3) there is a difference in attitudes towards using IWB on users' potential use of IWBs. For post-adopters: 4) the facilitating conditions have a bigger impact on the actual use of IWBs, and 5) behavioral intention is a stronger predictor of the actual use of IWBs when compared with pre-adopters.     

Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study

In this study, secondary school teachers’ acceptance of a digital learning environment (DLE) was investigated. Questionnaires were taken on three times (T1/T2/T3) during the same school year, with the Unified Theory of Acceptance and Use of Technology (UTAUT) as theoretical framework. Next to questionnaires, user-logs were collected during the entire school year. A total of 72 teachers completed a questionnaire on at least one occasion: 64 teachers responded at T1, 41 at T2, and 55 at T3. We first investigated which factors influence teachers’ acceptance of a DLE. The main predictors of DLE acceptance were performance expectancy and social influence by superiors to use the DLE. Effort expectancy and facilitating conditions were of minor importance. We then investigated how well the amount of final observed use could be predicted, and found that at T1 about one third, at T2 about one fourth and at T3 about half of the variance in observed use was predicted by attitude, behavioral intention and self-reported frequency of use. Our study showed that to maximize use of a DLE, its usefulness should be demonstrated, while school boards or principals should strongly encourage teachers to (start to) use the DLE.     

Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory

As with any other information system (IS), the success of online shopping depends largely on customer satisfaction and other factors that will eventually increase customers' loyalty intentions. This article integrates two major variables of technology acceptance model (TAM), trust, and fairness to construct a model for investigating the motivations behind customers' loyalty intentions towards online shopping. The hypothesised model is validated empirically using data collected from 311 customers of an online shopping store. The results indicated that distributive, procedural and interactional fairness were strong predictors of trust, which in turn influenced satisfaction. Distributive fairness and interactional fairness exhibited significant positive effects on satisfaction. Perceived usefulness and satisfaction influenced loyalty intention towards online shopping. Perceived ease of use acts indirectly on loyalty intention through the mediating effect of perceived usefulness. Implications for theory and practice and future research directions are discussed.     

Adoption of e-government services in Turkey

This research aims to investigate underlying factors that play role in citizens' decision to use e-government services in Turkey. UTAUT model which was enriched by introducing Trust of internet and Trust of government factors is used in the study. The model is evaluated through a survey conducted with Turkish citizens who are from different regions of the country. A total of 529 answers collected through purposive sampling and the responses were evaluated with the SEM (Structural Equation Modeling) technique. According to the results, Performance expectancy, Social influence, Facilitating conditions and Trust of Internet were found to have a positive effect on behavioral intention to use e-government services. Additionally, both Trust factors were found to have a positive influence on Performance expectancy of e-government services, a relation which, to our best knowledge, hasn't been tested before in e-government context. Effect of Effort expectancy and Trust of government were found insignificant on behavioral intention. We believe that the findings of this study will guide professionals and policy makers in improving and popularizing e-government services by revealing the citizen's priorities regarding e-government services in Turkey.     

Towards an understanding of the consumer acceptance of mobile wallet

This study seeks to validate a comprehensive model of consumer acceptance in the context of mobile payment. It uses the unified theory of acceptance and use of technology (UTAUT) model with constructs of security, trust, social influence, and self-efficacy. Structural equation modeling is used to construct a predictive model of attitudes toward the mobile wallet. Individuals’ responses to questions about attitude and intention to adopt/use a mobile wallet were collected and analyzed with various factors modified from UTAUT. While the model confirms the classical role of technology acceptance factors (i.e., perceived usefulness and ease of use are key antecedents to users’ attitude), the results also show that users’ attitudes and intentions are influenced by perceived security and trust. In the extended model, the moderating effects of demographics on the relations among the variables were found to be significant. The proposed model brings together extant research on mobile payment and provides an important cluster of antecedents to eventual technology acceptance via constructs of behavioral intention to use and actual system usage.     

Modelling technology acceptance in education: A study of pre-service teachers

The purpose of the study is to build a model that predicts the level of technology acceptance by pre-service teachers at a teacher training institute in Singapore. It examines relationships among variables associated with factors that influence technology acceptance. Data was collected from 475 participants using a survey questionnaire. Employing structural equation modelling, a hypothesized model was tested for model fit in the study. The resulting model is found to have a good fit. Perceived usefulness, attitude towards computer use, and computer self-efficacy have direct effect on pre-service teachers’ technology acceptance, whereas perceived ease of use, technological complexity, and facilitating conditions affect technology acceptance indirectly. These six variables account for approximately 27.1% of the variance of behavioural intention. Perceived usefulness appeared to the strongest determinant of behavioural intention.     

User acceptance of mobile commerce: an empirical study in Macau

This study aims to examine the positive and negative factors that can significantly explain user acceptance of mobile commerce (m-commerce) in Macau. A technology acceptance model for m-commerce with five factors is constructed. The proposed model is tested using data collected from 219 respondents. Confirmatory factor analysis is performed to examine the reliability and validity of the model, and structural equation modelling is performed to access the relationship between behaviour intention and each factor. The acceptance of m-commerce is influenced by factors including performance expectancy, social influence, facilitating conditions and privacy concern; while effort expectancy is insignificant in this case. The results of the study are useful for m-commerce service providers to adjust their strategies for promoting m-commerce services. This study contributes to the practice by providing a user technology acceptance model for m-commerce that can be used as a foundation for future research.     

An empirical investigation of a modified technology acceptance model of IPTV

This study explores the factors influencing the adoption of IPTV, and tests the applicability of the technology acceptance model (TAM) in a new convergent technology. The behavioural constructs from TAM were tested for predicting user acceptance of IPTV. Structural equation modelling was used to analyse data and to design a theoretical model predicting the individual's intention to adopt IPTV. A modified TAM for IPTV proposes that new constructs determine user-perceived usefulness and enjoyment of using IPTV. Although this study confirms the impact of information quality and system quality on consumers' technology experience, it specifically shows that the perceived quality of content and system were found to have a significant effect on users' perceived usefulness and perceived enjoyment. In addition, social influences had a positive effect on the intention to use IPTV. These findings suggest an extension of the TAM model for convergence technologies. This research advances theory and contributes to the foundation for future research aimed at improving the understanding of users' adoption behaviour of convergence technologies. Implications of these findings for practice and research are examined.     

The acceptance and use of computer based assessment

The effective development of a computer based assessment (CBA) depends on students’ acceptance. The purpose of this study is to build a model that demonstrates the constructs that affect students’ behavioral intention to use a CBA. The proposed model, Computer Based Assessment Acceptance Model (CBAAM) is based on previous models of technology acceptance such as Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Usage of Technology (UTAUT). Constructs from previous models were used such as Perceived Usefulness, Perceived Ease of Use, Computer Self Efficacy, Social Influence, Facilitating Conditions and Perceived Playfulness. Additionally, two new variables, Content and Goal Expectancy, were added to the proposed research model. Data were collected from 173 participants in an introductory informatics course using a survey questionnaire. Partial Least Squares (PLS) was used to test the measurement and the structural model. Results indicate that Perceived Ease of Use and Perceived Playfulness have a direct effect on CBA use. Perceived Usefulness, Computer Self Efficacy, Social Influence, Facilitating Conditions, Content and Goal Expectancy have only indirect effects. These eight variables explain approximately 50% of the variance of Behavioural Intention.     

Exploring students' awareness and perceptions: Influencing factors and individual differences driving m-learning adoption

This study investigates students' awareness and perceptions of m-learning and examines the factors affecting students' behavioral intention to adopt m-learning, by using a modified research model that integrate technology acceptance model (perceived usefulness and perceived ease of use) and unified theory of acceptance and use of technology (social influence) along with other factors (m-learning services and mobile limitations). In addition, control (gender, field of study, study level) and moderator variables (mobile capabilities, level of mobile usage, and frequent use of m-services) were introduced to verify the individual differences between respondents on the key factors affecting the adoption and usage of m-learning. Structural equations modeling and path analysis were used to test the hypotheses and the proposed model. The results revealed that perceived usefulness and perceived ease of use were found to be the primary factors driving students' intentions to use m-learning. Both m-learning services and social influence have positive effects on the acceptance of m-learning, while mobile limitations were found to be the main obstacle restraining students' participation in a m-learning environment. Most of the control variables yield no significant differences between students, but all the moderator variables were found to be significant determinants that can influence students to adopt m-learning. Overall, students have great potential to engage and integrate mobile technology into their educational environment.     

Comparing technology acceptance of K-12 teachers with and without prior experience of learning management systems: A Covid-19 pandemic study

Covid-19 pandemic has caused a massive transformation in K-12 settings towards online education. It is important to explore the factors that facilitate online teaching technology adoption of teachers during the pandemic. The aim of this study was to compare Learning Management System (LMS) acceptance of Finnish K-12 teachers who have been using a specific LMS as part of their regular teaching before the Covid-19 pandemic (experienced group) and teachers who started using it for emergency remote teaching during the pandemic (inexperienced group). Based on the Unified Theory of Acceptance and Use of Technology framework, a self-report questionnaire was administered to 196 teachers (n_experienced = 127; n_{inexperienced} = 69). Our findings showed no difference between the two groups of teachers in terms of performance expectancy, effort expectancy, LMS self-efficacy and satisfaction. However, the experienced group had higher behavioural intention to use LMS in the future, reported receiving higher online teaching support and displayed higher online teaching self-efficacy in terms of student engagement, classroom management, instructional strategies and ICT skills. For the experienced group, the most significant predictor of satisfaction with LMS was performance expectancy whereas for the inexperienced group, it was the effort expectancy. In terms of behavioural intention to use LMS in the future, the most significant predictor was the performance expectancy for both groups. Further, support was also a significant predictor of behavioural intention for the inexperienced group. Overall, our findings indicate that teachers should not be regarded as a unified profile when managing technology adoption in schools.     

The effects of education compatibility and technological expectancy on e-learning acceptance

Discerning what influences a student’s acceptance of e-learning is still unclear and has not been well investigated. On the basis of the expectancy-value theory, much effort has been put into identifying the effectual factors regarding the technological expectancy of students. However, aside from technological usage, the adoption of an e-learning system still must consider learning behavior. Thus, researchers should take into consideration both technological and learning expectancies of students while investigating e-learning acceptance. Following mainstream literature on information system acceptance, this study postulates that a student’s behavioral intention to accept an e-learning system is determined both by his or her technological expectancy and educational compatibility. Four primary factors, that is, performance expectancy, effort expectancy, social influence, and facilitating conditions, specified in the Unified Theory of Acceptance and Use of Technology (UTAUT) are used to reflect the technological expectancy of students. Further, educational compatibility, which refers the congruence of e-learning systems with the unique leaning expectancies of students, is integrated with the UTAUT to form a new theoretical model for e-learning acceptance. An empirical survey is conducted to examine the proposed model. A total of 626 valid samples were collected from the users of an e-learning system. The findings show that both technological expectancy and educational compatibility are important determinants of e-learning acceptance. However, educational compatibility reveals a greater total effect on e-learning acceptance than does technological expectancy. Implications and practical guidelines for both e-learning developers and practitioners are subsequently presented.     

What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model

This study presents an extended technology acceptance model (TAM) that integrates innovation diffusion theory, perceived risk and cost into the TAM to investigate what determines user mobile commerce (MC) acceptance. The proposed model was empirically tested using data collected from a survey of MC consumers. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to examine the reliability and validity of the measurement model. Our findings indicated that all variables except perceived ease of use significantly affected users’ behavioral intent. Among them, the compatibility had the most significant influence. Furthermore, a striking, and somewhat puzzling finding was the positive influence of perceived risk on behavioral intention to use. The implication of this work to both researchers and practitioners is discussed.     

Exploring pre-service teachers' use of technology: The technology acceptance model and expectancy–value theory

Understanding how prepared teachers are to use technology to enhance their teaching can assist researchers to support them better, yet the theoretical basis for understanding teachers' self-beliefs is in need of stronger empirical support. The first objective of this study was to replicate and extend prior research that empirically tested portions of the technology acceptance model (TAM) amongst pre-service teachers. The second objective was to empirically test an alternative set of antecedents of behavioural intentions to use technology based on the expectancy–value theory (EVT). Four theoretical models were tested using structural equation modelling with a sample of pre-service teachers (N = 249). Results provide support for the TAM and the extended TAM models, however, no support was found for the combined EVT and TAM models. We discuss the implications to promote teacher integration of technology in the classroom by creating facilitating conditions.     

Teachers' acceptance and use of an educational portal

In this study, teachers' acceptance and use of an educational portal is assessed based on data from two sources: usage data (number of logins, downloads, uploads, reactions and pages viewed) and an online acceptance questionnaire. The usage data is extracted on two occasions from the portal's database: at survey completion (T1) and twenty-two months later (T2). Framework for this study is C-TAM-TPB (Combined Technology Acceptance Model and Theory of Planned Behavior). 919 usable responses from teachers are obtained. Based on the observed use data at T1, four types of portal users are distinguished: ‘new’ (N = 37), ‘light’ (N = 641), ‘medium’ (N = 201), and ‘heavy’ (N = 40). Path analyses show that all predictor variables in C-TAM-TPB influence teachers' portal acceptance, but their significance level varies depending on the user type. The strongest predictors of behavioral intention to use the portal are attitude (‘new’) and perceived usefulness (‘light’, ‘medium’ and ‘heavy’), with variance explained ranging from .39 (‘medium’) to .71 (‘heavy’). The observed use data show that the portal is primarily used to search for and download material, rather than for sharing material or information. The use data at T2 show that teachers become more efficient in their search behavior and that the majority of the teachers use the portal more frequently. Guidelines are proposed to policymakers and school boards aiming to introduce a similar technology to teachers.     

The effects of organizational learning environment factors on e-learning acceptance

Workplace learning is an important means of employees’ continuous learning and professional development. E-learning is being recognized as an important supportive practice for learning at work. Current research on the success factors of e-learning in the workplace has emphasized on employees’ characteristics, technological attributes, and training design elements, with little attention to workplace contextual effects. The study aims to investigate the impacts of organizational learning environment factors, including managerial support, job support, and organizational support, on employees’ motivation to use a workplace e-learning system. A model was proposed based on the expectancy theory of training motivation and the social influences and facilitating conditions in technology acceptance models. The model was tested on sample data collected from mainland China using Structural Equation Modeling and Moderated Structural Equation Modeling. The results suggested that employees’ perceived managerial support and job support had a significant impact on their perceived usefulness of the e-learning system for individual learning, and that perceived organizational support had a significant influence on the perceived usefulness of the e-learning system for social learning. Perceived usefulness for individual learning was found to completely mediate the environmental influences on individuals’ motivation to use the system, while perceived usefulness for social learning made partial mediation in the effects of the environmental factors on intention to use. In addition, perceived job support was found to have moderating effects on the relationship between employees’ perceived usefulness of the e-learning system and their intention to use the system. Consistent with previous findings, employees’ perceptions about the usefulness of the e-learning system have significant effects on their intention to use the system in the work setting.     

Applying the Technology Acceptance Model to Social Networking Sites (SNS): Impact of Subjective Norm and Social Capital on the Acceptance of SNS

With their heavy traffic and technological capabilities, social networking sites (SNS) introduced a new means of building and maintaining perceived social capital. This study aims to identify underlying factors and causal relationships that affect behavioral intention to use SNS. For this purpose, this research developed an extended technology acceptance model, incorporating subjective norm and perceived social capital for predicting SNS acceptance and usage. Exploratory correlation and path analyses were conducted to identify the relationships between five constructs: perceived usefulness, perceived ease of use, subjective norm, perceived social capital, and intention to use. The results showed that perceived usefulness and perceived ease of use had robust effects on the user's intention to use SNS. The research findings also demonstrated that subjective norm and perceived social capital were significant predictors of both perceived usefulness and perceived ease of use and therefore should be considered as potential variables for extending the technology acceptance model.     

Moderating effects of Job Relevance and Experience on mobile wireless technology acceptance: Adoption of a smartphone by individuals

My study extended TAM to include individuals’ intention to use mobile wireless technology (MWT). It added two new constructs, Perceived Cost Savings and Company's Willingness to Fund, and two causal relationships, Job Relevance and Experience, as moderating effects. The 286 sets of data collected in an online survey were tested against the model using SEM. Results supported my new model: the new constructs and variables accounted for 62.7% of the variance found in an individual's behavioral intention to use MWT. The path coefficients between the constructs ranged from 0.26 to 0.85 also supporting the model.     

Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning

Collaborative technologies support group work in project-based environments. In this study, we enhance the technology acceptance model to explain the factors that influence the acceptance of Google Applications for collaborative learning. The enhanced model was empirically evaluated using survey data collected from 136 students enrolled in a full-time degree program that used Google Applications to support project work. According to the research results, determinants of the technology acceptance model are the major factors influencing the adoption of the technology. In addition, the subjective norm represented by peers is found to significantly moderate the relationship between attitude and intention toward the technology. However, our results do not show a significant effect of subjective norms represented by instructors and mass media on students' intentions to use the technology. The ability to share information in the collaborative learning environment is found to influence intention and behavior toward the Google Applications platform.     

Behavioral intention,use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning

Widespread implementation of e-learning systems – learning management systems, virtual learning environments – across higher education institutions has aroused great interest on the study of e-learning acceptance. Acceptance studies focus on the predictors of system adoption and use, with behavioral intention to use the system as a proxy for actual use. This study proposes a TAM3-based model – with the inclusion of two additional variables: personal innovativeness in the domain of information technology and perceived interaction – to study the factors influencing the acceptance of e-learning systems. Attention is also brought towards the role of behavioral intention, especially in its relation with use behavior. In order to do so, two different settings were considered: higher education and lifelong learning; data was gathered from a survey administrated to Spanish graduate and lifelong learning students, and partial least squares analysis was used to test the research model. Results supported TAM relations, except for the intention-behavior linkage, and unveiled a dual nature of perceived usefulness – with one component related to efficiency and performance, and another component related to flexibility. The adequacy of applying TAM3-based models in educational contexts and suitability of actual system usage measures are also discussed.