scholarly journals PREDICTING THE ADOPTION OF AN ANDROID-BASED CLASS RECORD USING THE UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY MODEL

2020 ◽  
Vol 80 (6) ◽  
pp. 75-90
Author(s):  
Дейв І. Марціал
Keyword(s):  
Teaching And Learning ◽  
Teacher Educators ◽  
Intention To Use ◽  
Unified Theory ◽  
Innovative Teaching ◽  
Use Of Technology ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use ◽  
High Degree ◽  
Structured Questionnaire

Technology adoption is a process that is affected by many variables. To achieve innovative teaching and learning, mClassRecord, an Android-based class record application, was developed and tested. This paper is aimed at predicting the level of adoption of mClassRecord as experienced by the respondents using the Unified Theory of Acceptance and Use of Technology Model. Specifically, this article presents the qualitative analysis of mClassRecord adoption among the respondents in terms of performance expectancy, effort expectancy, attitudes toward using mClassRecord, social influence, facilitating conditions, self-efficacy, anxiety, and behavioral intention to use mClassRecord. The respondents of the study are the 17 teacher educators in higher education institutions in Central Visayas, Philippines. A semi-structured questionnaire was used, which was adapted from the model. Results show that mClassRecord is useful in the classroom. The interaction of teachers with mClassRecord is found to be clear and understandable. The positive comments from the respondents imply that the app is a good idea for teachers. Findings reveal that there is no clear indication that there is a direct influence or support from the school administration. It shows also that the teachers acquire dissimilar skills and even different levels of the same skills. The results indicate that majority of the teachers do not have fear and apprehension in using mClassRecord. Likewise, it implies that there is positive attitude and high degree of intention to use mClassRecord. The study concludes that adoption of mClassRecord is predicted at different stages. There is strong evidence that mClassRecord offers effective and efficient class recording and management. There is promising indication that the teaching tool offers an innovative contribution to teaching.

scholarly journals Factors that influence teachers’ use of GeoGebra for instruction

2016 ◽  
Vol 35 (1) ◽  
Author(s):  
Gerrit H. Stols ◽  
Stephan J. Venter ◽  
Elizabeth M. Louw
Keyword(s):  
Teaching And Learning ◽  
Intention To Use ◽  
Unified Theory ◽  
Software Training ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Actual Use ◽  
Facilitating Conditions ◽  
The Relationship ◽  
Mathematics Software

This study investigated factors that influence teachers’ use of mathematics software (in this case GeoGebra) for teaching and learning. Participants in the study were purposefully selected from a group of teachers that have received software training, have access to computers, and are familiar with the software. Seventy-five respondents completed the structured questionnaires. Multiple regressions were used to investigate the relationship between the four constructs of the Unified Theory of Acceptance and Use of Technology. These constructs are performance expectancy, effort expectancy, social influence, and facilitating conditions on teachers’ intention to use the mathematics software. This study found that the combination of the four above mentioned constructs explained 30% of the variance in respondents’ intention to use the software. Facilitating conditions were not found to directly influence whether or not people actually used the software because all of them have access to computers. Teachers’intention to use GeoGebra was found to predict the actual use of GeoGebra for teaching and learning.Keywords: mathematics; teachers; technology; ICT; software

Determinants of Consumer Intention to Use Online Gambling Services

2016 ◽  
Vol 12 (4) ◽  
pp. 23-37 ◽  
Author(s):  
Nuno Fortes ◽  
António Carrizo Moreira ◽  
João Saraiva
Keyword(s):  
Perceived Risk ◽  
Online Survey ◽  
Online Gambling ◽  
Intention To Use ◽  
Unified Theory ◽  
Convenience Sample ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Usage Behavior ◽  
Facilitating Conditions

Online gambling has skyrocketed in recent years. As such, knowing the determinants of consumer usage behavior is crucial in understanding online gambling services. This study has as main objective the construction of an explanatory model of the online gambling services usage behavior, based on the incorporation of perceived risk in the conceptual framework of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The empirical validation of the model was performed by conducting an online survey to a convenience sample of 212 Portuguese online players. Data were processed using the PLS-SEM methodology. The results evidence that performance expectancy, social influence, facilitating conditions, hedonic motivations, price value, habits, as well as perceived risk influence the intention to use online gambling services.

scholarly journals Application of the unified theory of acceptance and use of technology model to predict dental students’ behavioral intention to use teledentistry

2020 ◽  
Vol 84 (11) ◽  
pp. 1262-1269
Author(s):  
Jafar H. Alabdullah ◽  
Bonnie L. Van Lunen ◽  
Denise M. Claiborne ◽  
Susan J. Daniel ◽  
Cherng‐Jyh Yen ◽  
...  
Keyword(s):  
Behavioral Intention ◽  
Dental Students ◽  
Intention To Use ◽  
Unified Theory ◽  
Use Of Technology ◽  
Behavioral Intention To Use

scholarly journals Factors Influencing Patients’ Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey

10.2196/15023 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e15023 ◽  
Author(s):  
Yiyu Zhang ◽  
Chaoyuan Liu ◽  
Shuoming Luo ◽  
Yuting Xie ◽  
Fang Liu ◽  
...  
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Diabetes Management ◽  
Intention To Use ◽  
Unified Theory ◽  
Research Model ◽  
Web Based ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Facilitating Conditions

Background Diabetes poses heavy social and economic burdens worldwide. Diabetes management apps show great potential for diabetes self-management. However, the adoption of diabetes management apps by diabetes patients is poor. The factors influencing patients’ intention to use these apps are unclear. Understanding the patients’ behavioral intention is necessary to support the development and promotion of diabetes app use. Objective This study aimed to identify the determinants of patients’ intention to use diabetes management apps based on an integrated theoretical model. Methods The hypotheses of our research model were developed based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT). From April 20 to May 20, 2019, adult patients with diabetes across China, who were familiar with diabetes management apps, were surveyed using the Web-based survey tool Sojump. Structural equation modeling was used to analyze the data. Results A total of 746 participants who met the inclusion criteria completed the survey. The fitness indices suggested that the collected data fit well with the research model. The model explained 62.6% of the variance in performance expectancy and 57.1% of the variance in behavioral intention. Performance expectancy and social influence had the strongest total effects on behavioral intention (β=0.482; P=.001). Performance expectancy (β=0.482; P=.001), social influence (β=0.223; P=.003), facilitating conditions (β=0.17; P=.006), perceived disease threat (β=0.073; P=.005), and perceived privacy risk (β=–0.073; P=.012) had direct effects on behavioral intention. Additionally, social influence, effort expectancy, and facilitating conditions had indirect effects on behavioral intention that were mediated by performance expectancy. Social influence had the highest indirect effects among the three constructs (β=0.259; P=.001). Conclusions Performance expectancy and social influence are the most important determinants of the intention to use diabetes management apps. Health care technology companies should improve the usefulness of apps and carry out research to provide clinical evidence for the apps’ effectiveness, which will benefit the promotion of these apps. Facilitating conditions and perceived privacy risk also have an impact on behavioral intention. Therefore, it is necessary to improve facilitating conditions and provide solid privacy protection. Our study supports the use of UTAUT in explaining patients’ intention to use diabetes management apps. Context-related determinants should also be taken into consideration.

scholarly journals Auto Mechanic Students’ Perceptions and Readiness toward Mobile Learning in Thailand

2018 ◽  
Vol 12 (5) ◽  
pp. 28
Author(s):  
Ekkalak Issaramanoros ◽  
Jintavee Khlaisang ◽  
Pakawan Pugsee
Keyword(s):  
Mobile Learning ◽  
Behavioral Intention ◽  
Teaching And Learning ◽  
Intention To Use ◽  
Personal Innovativeness ◽  
Use Of Technology ◽  
Rural And Urban ◽  
Effort Expectancy ◽  
Education Gap ◽  
Behavioral Intention To Use

Access to quality education is now a huge challenge in Thailand with ever-increasing inequality between rural and urban populations. Existing teaching and learning facilities are no longer adequate. Mobile learning has been suggested as a sustainable and appropriate delivery mechanism to reduce this rural/urban education gap. Students are supplied with their own mobile device at no cost to learners or their families. Opportunities offered through mobile learning to auto mechanic education in Thailand were explored. Data from 384 auto mechanic students were collected and descriptive and multiple regression analyses were performed based on the unified theory of acceptance and use of technology 2 (UTAUT2) model. Results showed that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation and personal innovativeness were positively related to behavioral intention to use mobile learning. Furthermore, effort expectancy, hedonic motivation and personal innovativeness were the most significant predictors of behavioral intention to use mobile learning. Auto mechanic students in Thailand had positive perceptions toward mobile learning and the effect of students’ effort expectancy provided a better explanation for the adoption of mobile learning in auto mechanic education.

scholarly journals Technology Supporting Nursing at Homecare – Seems to Be Lacking

2020 ◽  
Author(s):  
Eija Kivekäs ◽  
Santtu Mikkonen ◽  
Samuli Koponen ◽  
Kaija Saranto
Keyword(s):  
Internet Of Things ◽  
Historical Perspective ◽  
Intention To Use ◽  
Unified Theory ◽  
Home Setting ◽  
Medical Technologies ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Facilitating Conditions

The use of welfare technologies in the home setting has drawn increased attention in healthcare. From a historical perspective, medical technologies were designed for hospital settings. Digitalization and internet of things have changed the structure of our society. The aim of this paper is to describe the factors that determine a user’s intent to adopt new welfare technologies in the context of homecare. The phenomenon was being examined by the unified theory of acceptance and use of technology. This study was to show that performance expectancy, effort expectancy, and facilitating conditions are significant factors in determining a user’s intention to use new welfare technologies. While, the use of welfare technologies was rare in homecare.

scholarly journals Determinants of Fitness App Usage and Moderating Impacts of Education-, Motivation-, and Gamification-Related App Features on Physical Activity Intentions: Cross-sectional Survey Study (Preprint)

2020 ◽  
Author(s):  
Yanxiang Yang ◽  
Joerg Koenigstorfer
Keyword(s):  
Physical Activity ◽  
Behavioral Intention ◽  
Unified Theory ◽  
Physically Active ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
And Gender ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

BACKGROUND Smartphone fitness apps are considered promising tools for promoting physical activity and health. However, it is unclear which user-perceived factors and app features encourage users to download apps with the intention of being physically active. OBJECTIVE Building on the second version of the Unified Theory of Acceptance and Use of Technology, this study aims to examine the association of the seven determinants of the second version of the Unified Theory of Acceptance and Use of Technology with the app usage intentions of the individuals and their behavioral intentions of being physically active as well as the moderating effects of different smartphone fitness app features (ie, education, motivation, and gamification related) and individual differences (ie, age, gender, and experience) on these intentions. METHODS Data from 839 US residents who reported having used at least one smartphone fitness app were collected via a web-based survey. A confirmatory factor analysis was performed, and path modeling was used to test the hypotheses and explore the influence of moderators on structural relationships. RESULTS The determinants explain 76% of the variance in the behavioral intention to use fitness apps. Habit (<i>β</i>=.42; <i>P</i>&lt;.001), performance expectancy (<i>β</i>=.36; <i>P</i>&lt;.001), facilitating conditions (<i>β</i>=.15; <i>P</i>&lt;.001), price value (<i>β</i>=.13; <i>P</i>&lt;.001), and effort expectancy (<i>β</i>=.09; <i>P</i>=.04) were positively related to behavioral intention to use fitness apps, whereas social influence and hedonic motivation were nonsignificant predictors. Behavioral intentions to use fitness apps were positively related to intentions of being physically active (<i>β</i>=.12; <i>P</i>&lt;.001; <i>R<sup>2</sup></i>=0.02). Education-related app features moderated the association between performance expectancy and habit and app usage intentions; motivation-related features moderated the association of performance expectancy, facilitating conditions, and habit with usage intentions; and gamification-related features moderated the association between hedonic motivation and usage intentions. Age moderated the association between effort expectancy and usage intentions, and gender moderated the association between performance expectancy and habit and usage intentions. User experience was a nonsignificant moderator. Follow-up tests were used to describe the nature of significant interaction effects. CONCLUSIONS This study identifies the drivers of the use of fitness apps. Smartphone app features should be designed to increase the likelihood of app usage, and hence physical activity, by supporting users in achieving their goals and facilitating habit formation. Target group–specific preferences for education-, motivation-, and gamification-related app features, as well as age and gender differences, should be considered. Performance expectancy had a high predictive power for intended usage for male (vs female) users who appreciated motivation-related features. Thus, apps targeting these user groups should focus on goal achievement–related features (eg, goal setting and monitoring). Future research could examine the mechanisms of these moderation effects and their long-term influence on physical activity.

Dynamic Analysis of UTAUT

2016 ◽  
Vol 11 (3) ◽  
pp. 40-54
Author(s):  
Wejdan Abualbasal ◽  
Emad Abu-Shanab ◽  
Heba Al-Quraan
Keyword(s):  
Longitudinal Study ◽  
New Technology ◽  
Intention To Use ◽  
Unified Theory ◽  
Cross Sectional ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Adoption Of New Technology ◽  
Facilitating Conditions

The technology adoption domain is rich with studies that utilized a cross-sectional snapshot of subjects' perceptions regarding the adoption of new technology. This research tried to implement a longitudinal study that took three measures within 4 months to estimate the influence of time and experience on students' perceptions. The study adopted a modified version of the Unified Theory of Acceptance and use of Technology (UTAUT) with effort expectancy, performance expectancy, facilitating conditions, and locus of control predicting the intention to use Microsoft Project. Results supported the UTAUT and its prediction. Also, this study fitted two types of dynamic research typologies (learning curve and equilibrium circles) to the UTAUT relationships and across time.

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