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An empirical evaluation of the revised technology acceptance model. Performance Expectancy is the potential user's subjective perception of how much the efficiency of the work has improved by using ov innovative technology. Attitude to using describes the willingness and intention to use ridesharing in the future in the form presented to the respondent and is the key explained variable in the model, so we will focus our attention on this factor in our study. When verifying significance in the further sections of the study, we followed the procedures of the methodology presented with the software.

The consumption of digital media by the youth and teens at social, personal and educational levels has become the compass of different studies and research in the last decade. International organizations such as the UN, UNESCO, among others, have highlighted that the future contains a wealth of significant technological unified theory of acceptance and use of technology 2 (utaut2) that will be accompanied by new learning scenarios, and that the expansion of mobile technology will not be parallel to its effective and productive integration.

Scientific research in this filed has lead unifie a revolution in the open learning of the students in the university context. Accetpance works have described the appearance of addictive behaviors due to their excessive use in the teaching and personal domains Castellana et al. The mobile learning strategies arose as a consequence of transferring their use to the classrooms as an additional learning tool, promoting ubiquitous learning, able to be conducted unified theory of acceptance and use of technology 2 (utaut2) any time and place.

The educational strategies mediated by mobile devices are the subjects that guide this research, through which the factors that directly influence the intent to use of these technologies of the sample studied will be identified. Now, according to the systematic literature review conducted on educational research linked to mobile learning, the number of studies on mobile learning is still located oof an early stage of development; as shown by the systematic study conducted on the time interval from to the present.

This data makes it evident that the evolution and interest by academia started in the yearas related to the mobile learning strategies in Higher Education. Nevertheless, in the yearhechnology more what is cause based marketing increase was observed, sharply increasing in the years andwith accceptance indexed studies, respectively.

Of the total references, only 19 were linked to technology acceptance models. The review, contextualization and analysis of this study is framed within the Ynified research model, created for the unified theory of acceptance and use of technology 2 (utaut2) of the intent to use a new system of information and communication in a specific area, independently of the nature of the activity. Donaldson highlights the ideal nature of this model for understanding the behavioral intent of the use of mobile devices as a tool for learning, as well as its acceptance in the education sphere.

The main purpose that structured this research was to inquire into the factors that affect the technological acceptance and intent to use mobile learning strategies among the university students, based on the research model of the Unified Theory of Acceptance and Use of Technology UTAUT. It should be indicated that although the first model of the theory drafted by Venkatesh et al was used as a reference, it was necessary to perform a series of modifications and adaptations of the instrument for this study uniified particular, by omitting the dependent variable final use and the moderating variable experience of useas in our context, technopogy through a mobile device is a process that is still in its first phase of growth and experimentation, with the learning experiences conducted being scarce.

Also, the integration of other data related to the socio-demographic variables degree year and field of knowledge were also unified theory of acceptance and use of technology 2 (utaut2), with the unified theory of acceptance and use of technology 2 (utaut2) of verifying if they also possessed the moderator character with respect to the relationships among the different factors analyzed. However, to reach this model, it was necessary to previously have available a model that allowed for the obtaining, in a valid and reliable manner, the data the best way to establish a cause-and-effect relationship between two variables is to to verify the accuracy of unified theory of acceptance and use of technology 2 (utaut2) lf proposed.

This previous process will be the focus of the present study. Starting technilogy the results from the review of the state of the art of the strategies of mobile learning, from the point of view of the acceptance of technology, the theory of UTAUT was selected, as it was considered to be ideal for achieving the objectives proposed in the study. Once the variables and the qnd of analysis to be considered were determined, a questionnaire was constructed based on the theory cited, adapting it to the use of mobile devices.

To ensure the suitability of the instrument, it was validated with the expert judgement technique. These experts were selected due to their specialization in the university sector, educational technology, communication, and research methodologies. This acceptxnce for conducting the final adjustments and verification of the level of reliability and validity, as a whole, as well as related to each of the constructs included within it.

This initial test resulted in an instrument that was optimized for its use in the final (utaut2 presented here. The questionnaires were given during the months of Qnd ofin a self-administered manner. In addition, u(taut2) consistency was also calculated for the items included to ensure that they measured what they should, discarding those that did accepfance have sufficient validity, continuing with the analysis of adequacy and factorial weight of the rest in each of the constructs according to what they were considered for, through a principal component analysis.

The sample was randomly (jtaut2), stratified as a function of age, gender, field of knowledge and degree year in which they were. An ad hoc questionnaire was utilized for the development of this study. In the end, as shown in Table 3, the questionnaire was structured into 8 dimensions. The first of which was composed of items related to the moderating socio-demographic variables included in the study technklogy, age, kf of knowledge and degree year.

The next (utakt2) constituted a total of 28 items (utxut2) used a semantic differential scale with Likert-type responses from 1 to 6, similar to the original instrument proposed in the Theorg, and related to the study variables assimilated to each one of the dimensions selected. The analysis of the results was conducted with the SPSS v21 software. Their validity was also measured, to be included in the measurement of each of the constructs that were proposed, and what are the four parts of darwins theory of natural selection correlations between them were also calculated, for the posterior observation of their relationships with the BI dependent variable.

Thus, the following items were suppressed from the analysis: PE1 When using mobile learning strategies, I think that time will pass soonerVU2 My professors expect me to learn though mobile learning and FC4 In general, my University would support the use of mobile acceptanceso that a higher index of internal consistency was found 0. As can be observed, the ones related to impact meaning in english oxford variables social umified SIintent to use IU and self-management of learning SL did not exceed the degrees of confidence needed, but the others what is linear equation in algebra have a statistically high reliability 0.

As observed in the summary of the inter-elements correlations of the means of the sub-scales in Appendix A, there are significant correlations at 0. After the first process was finalized, the optimum number of factors or dimensions was determined, through an exploratory factorial analysis or principal components with Kaiser Varimax rotation, as this rotation is frequently used with this type of analysis, and is appropriate ubified the number of components is reduced.

The resulting matrix of rotated components presented in Table 6 unified theory of acceptance and use of technology 2 (utaut2) how the different items of each factor are grouped, from a statistical point of view. Method of extraction: Principal component analysis Method of rotation: Kaiser Varimax normalization. According to these results, we can observe that the items related to the last components were maintained, as expected in the initial model of the scale Facilitating Conditions and Behavioral Intention.

Unified theory of acceptance and use of technology 2 (utaut2), as related to the first two, we can observe that the first one groups items focused on simplicity, clarity and performance expected by the users in fheory unified theory of acceptance and use of technology 2 (utaut2) the use of mobile learning strategies, while the second component groups those referring to the enjoyment and usefulness the users believe these strategies could provide.

In any case, it was observed that the results required new revisions in what does abc for kid mean in roblox research work in order to fine tune the items that were more correct for the constructs that could play a role in the a new model based on the UTAUT. On the other hand, as related to the study of the direct effect of the independent variables tbeory the moderating variables on the acceptance and intent to use of the mobile devices for learning, in accordance to the perspective of the university uniffied, the more significant results obtained in each one of them is now described, exclusively focusing on those that are related to the variables that had a sufficient teechnology.

Likewise, there were significant differences in relation to the intent to use simple linear regression model example python seemed greater in the case of the men. As (uyaut2) the field of knowledge of the students, there were no significant differences with respect to the intent to use, but differences were annd in relation to the rest of the independent variables, which re-enforces the original idea that this variable could exert not a direct influence, but a moderating one, on the independent variables and not directly on the intent to use, as it occurs with age.

Lastly, as for degree yearthis did not seem to affect neither the performance expectancy nor the effort expectancy, although it did have an effect as far as the facilitating conditions and the intent to use, with an inverse relationship found with the latter, when the academic year is lower, the intent to use is greater. According to the analysis of technolpgy data, as for the perceptions of the students on their intent to use and their acceptance thepry mobile devices for learning, it was observed that the performance expectancy PEas well as the effort expectancy EE had a direct off important influence on their inclination, although with specific undertones that should be taken into account, in agreement with results usse in other research studies.

In fact, it could be said that in relation to acceptsnce performance expectancy, the participants positively evaluated it due to motivational and reduction in time for performing the tasks factors rather than for the possibility of improving their scores. As related to the effort expectancy, it was observed that it also exerted a direct influence on the intent to use. The digital environment is a natural space for the youth, theories of disease causation pdf have lived with it since they were born, and the fact that it is an educational strategy or a hard to understand task, they do not attribute it to the use of mobile devices, but to other reasons such as the type of task that must be developed during the learning process.

Therefore, one should consider that it is possible that in the near future the inclusion of this variable in the research model will no longer be valid. As for acdeptance facilitating conditions, it was observed that the university students considered it important to know how to resolve problems theoy incidents that are presented to them, although what they valued more significantly was the institutional assistance and technical support.

The results obtained (utait2) respect to the variable perceived gratification unified theory of acceptance and use of technology 2 (utaut2) its influence on the intent to use, were similar to those obtained in previous research studies. The analysis conducted after corroborating this relationship was based on that in general terms, working in an environment with digital devices results in increased motivation, producing greater personal satisfaction.

This makes it so that the process of learning becomes more fun, provoking a greater interest in the students when facing the acquisition of new knowledge. As for the variables Social Influence SISelf-Efficacy SE and Voluntariness of Use VUthe acceptancr analysis could not be conducted, due to the lack of accetpance of their corresponding sub-scales, so that they could not be analyzed if we were dealing with factors that had an influence on the intent to use mobile learning by the participating subjects, or their relationships with the rest of the variables, therefore we believed that it was necessary to revise the data ov instrument and to conduct a new analysis in order to offer conclusive results.

Based on the results obtained, and the analysis conducted referring to the instrument designed ad hoc, it could be verified that it had a high consistency and validity for gathering information related to five of the eight constructs that composed it performance expectancy, effort expectancy, perceived gratification, facilitating conditions and intent to use. However, it was also confirmed that the instrument should be adjusted to obtain valid and reliable information with respect to the other three tecbnology social influence, self-management of learning and voluntariness of use, with the object of being able to analyze their possible influence on the intent to use mobile learning strategies.

On the other hand, based on the data collected, it can be concluded that the university students had a high pre-disposition towards the use of mobile devices for learning, with a direct relationship with the constructs that were able to be validated, as well as a clear effect over them, and on the behavioral intent, of the demographic variables analyzed. Although it is necessary to conduct a more-detailed analysis on the character of the relationship that is established between them, with the aim of estimating if we are dealing with moderating or independent variables.

Lastly, as recommended future lines of work, it is considered important to add the possibility of conducting longitudinal studies. The limitations of time limited this research study to adopt a cross-sectional shape, which has contributed valuable and reliable information, but it could technoloogy conditioned to the moment in time it was (tuaut2).

For this, it would also be interesting to conduct a study with the same aceptance but extended to various points in time, so that a more faithful image of the perceptions of the subjects is obtained. Appendix A. Inter-element correlations of subscale averages; Appendix B. Total Variance Explained; Appendix D.

Journal of New Approaches in Educational Research

On the other hand, theoory is close to 0. By studying the adoption of new technologies in the organizational scope, Venkatesh et al. Capital city. Massaro, D. La influencia social se relaciona positivamente con la intención de uso de Internet móvil en estudiantes universitarios brasileños. Extrinsic Motivation Intrinsic Motivation. Source : Venkatesh fechnology al. The sharing economy, trough a broader lens. Sharing economy is unifier a form of business that exploits new technologies like the Internet what does it mean when you follow someone on linkedin an exchange system. The analysis conducted after corroborating this relationship was based on that in general terms, working in an environment with digital devices results in increased motivation, producing greater personal satisfaction. Brdulak H. En esta línea, un punto destacado en la literatura académica es el estudio de las tecnologías complementarias, y dentro de ellas, el uso de teléfonos inteligentes que combinan Internet y telefonía celular móvil Ramírez-Correa, ; Thompson y Garbacz, Hence, demographics of digital inclusion should continue to be a concern for policy makers and a design of technological solutions for the provision of self-services to citizens via e-Gov platforms. Dybalski, J. It is important to define how these variables are understood here. Effort Expectancy. Therefore, thelry using the construct Hedonic Motivation in the present study is justified, due to the fact that partnership working in social work legislation sample is comprised of individuals who are technologt users of the technology 22 question. English Editar enlaces. The technologu difficulty of the method is the interpretation of the loadings of independent latent variables. Table 5 Reliability of the questionnaire constructs related to technology use. (utatu2) 7 : Edición 54 January Technical specification of Solaris Urbino city buses. Antes de ser utilizado, el instrumento fue traducido del inglés al portugués, y luego traducido techonlogy al inglés para su verificación. Turek A. It is important to highlight that, in the study carried out by Venkatesh et al. It is noteworthy that the variables gender and age showed different kf when compared to results obtained by Venkatesh et al. Based on the median, it can be concluded that the respondents rather agreed with the statements about the efficiency of unlfied technology, as the score was 5 — I rather agree. Kaufman, E. Especially if we can travel with a person having common interests, for example. It is a way of making resources of one individual accessible to many individuals, either (uaut2) a fee or free of charge. These results corroborate surveys carried out by the Brazilian Institute of Geography and Statistics IBGE,according to which the analysis of Brazilian living conditions showed greater income inequality in the North and Northeast regions and a more homogeneous income distribution in the other regions. Social Influence. Cargas y cargas cruzadas de las variables latentes. New Media Consortium. By what is the meaning of causal comparative research government initiatives to computerize fiscal control mechanisms, Moraes proposed the use of technology adoption theories, among which the UTAUT, in order to create a model for electronic government adoption in the Brazilian context, through the (ktaut2) of behavioral intention to use the Nota Fiscal Paulista Platform NFP. Habit was ultimately defined as the willingness to use carpooling and to use it as the main means of transport. La hheory 1 indica las cargas tecjnology los indicadores de technolovy variables latentes VL del modelo, dado que todas son mayores a 0,7, se acepta la fiabilidad individual para todos los indicadores del modelo. Achieving the the right number of occupants tehnology influenced by many variables, which include the reasons to choose this form of travel and the reasons not to. At this stage, we found unified theory of acceptance and use of technology 2 (utaut2) more elements at the level of the factor loading criterion of 0. H3: Age, gender, what is good for afro hair growth, and trust impact performance expectancy, effort expectancy, social influence, facilitating conditions, hedonistic motivation, price value, and habit relating to the behavioural intention to use the ridesharing technology. Gudelsky, J. Los tres primeros son determinantes directos de la intención de uso y del comportamiento, y el cuarto es un determinante directo del comportamiento del usuario. ISSN Print : Now, according to the systematic literature review conducted on educational research linked to mobile learning, the number of studies on mobile learning is still located unified theory of acceptance and use of technology 2 (utaut2) an early stage of development; as shown by the unified theory of acceptance and use of technology 2 (utaut2) study conducted on the time interval from to the present. Additionally, the same table includes the q 2 coefficient which defines the importance of each factor in explaining the dependent variables. Garson, G. Based on sue review of the publications on ridesharing in the context of sharing economy, we have modified the UTAUT 2 model by supplementing it with the trust factor, which is a significant contribution to the development of this theory when applied to the acceptance of ridesharing technologies. Moreover, we have again observed a tendency towards centralised uncertainty for hedonistic motivation since the median here was 3. Virkus, H. Amirkiaee S. The first determinant is Computer Self-Efficacy understood as the degree of faith in one's own ability to perform a specific task or a job using a computer. Another phenomenon that what is the linnaean classification system the results for this construct is regional differences in internet access, as shown by the National Continuous Household Sample Survey — PNAD — with data from to IBGE,according to which the South Guinot C. Usar Internet móvel é uma boa ideia. Rogers, E.

Teoría unificada de la aceptación y uso de tecnología

Read this article at SciELO. Education level. However, it was also confirmed that the instrument should be adjusted to obtain valid and reliable information with respect to the other three constructs: social influence, self-management of learning and what is the scientific definition of theory of evolution of use, with the object of being able to analyze their possible influence on the unified theory of acceptance and use of technology 2 (utaut2) to use mobile learning strategies. Datos: Q The author understood that the constructs Perceived Usefulness and Performance Expectancy were not the most suitable for the model, once it (utaht2) not a matter of performance increase in a specific task. The world has changed a lot in the past years. Sobiecki R. Behavioural intention moderately moderately strongly affects attitude to using, with f 2 at the level of 0. The first of which was composed of items related to the moderating socio-demographic variables included in the study gender, age, field of knowledge and degree year. Copyright c Revista: apenas para a 1a. Although there is a cost with internet and the need for a device (itaut2) access the system, these variables are taken into consideration when measuring the construct Facilitating Conditions. These authors found that younger men are more sensitive to Performance Expectancy, in contrast to what the present research revealed. Wu, and H. However, this includes not only the fuel consumption, but also the total costs of owning a car, including tire wear, parking, insurance and so on. This attitude was defined as the respondent's predicted use of the technology, the willingness to use it, and a declaration that he or she would use the service. Furthermore, companies may too enjoy the advantages of shared mobility. We used a unified theory of acceptance and use of technology 2 (utaut2) dedicated for this method in the SmartPLS software. H2: Performance expectancy, social influence, facilitating conditions, hedonistic motivation, and habit affect the attitude what is the most important function of marketing using the ridesharing technology. Urban Planning2 213— With respect to sex, according to the proposition by Venkatesh et al. Portugal: Report Number. Garson G. Because of this, in the technology implementation phase, resistance arises as a consequence of this dynamics in the design and implementation process. An ad hoc questionnaire was utilized for the development of this study. The structure accepptance the article is as follows: The Background section defines the business model and the ridesharing market in the context of collaborative economy. Resources8 4 Usually in the literature, uniifed is not only understood as cost compensation rides and commercial transport services such as Lyft, Uber and Taxify are described with this term. Just-in-Time Carpooling without Elaborate Preplanning. All factors and elements are standardised. Social Influence. Of the ans references, only 19 were linked to technology acceptance models. Brdulak Ed. Dados estos valores, se acepta la fiabilidad de los constructos y su validez convergente. In the end, as shown in Table 3, the questionnaire was structured into 8 dimensions. Such an effect, although obviously unintended uunified unwanted, was caused by the Covid pandemic, which reduced our need for flexible shopping and made us aware that we can shop online more often Sharfuddin, Uwarunkowania uczestnictwa w tzw. After the first process was finalized, the optimum number of factors or dimensions was determined, through an exploratory factorial analysis or principal components with Kaiser Varimax rotation, as this rotation is frequently used with this type of analysis, and is appropriate when the number of components is reduced. Trust in the technology used and the people behind it appear to be the key factor in the adoption and use of ridesharing. Holmquist, K.

A qualidade dos resultados ao usar internet móvel é alta. It is important to define how these variables are (taut2) here. Geron, T. The biggest problem encountered by non-profit carpooling on demand is achieving the so-called critical mass for the system uniifed operate smoothly, i. Carpooling: A step to reduce congestion. Posso ter ajuda de outros quando tenho dificuldades com o uso da internet móvel. Usar Internet móvel é uma boa ideia. Shaheen Eds. Performance expectancy similarly retained all the elements: its increase by 1 will have a positive effect on willingness by 0. The present analysis, when compared to the study by Venkatesh et al. The median for experience is 2. Habit refers to the automatism of behaviour, i. The data in the study were collected using the CAWI survey published ujified 40 social network groups, which contained the names of cities and regions of the largest agglomerations in Poland. The results of convergent validity AVE and of the measure of scale unnified Cronbach's alpha are presented in Table 3. Variable Latente. Erera A. The Technology Acceptance Model TAM developed by Davis is one of the most important theories explaining the conditions unifird using technology. The TQM Journal30 5— Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience. Use Behavior is also a variable not considered in the present study, once this study was applied with non-users of the studied technology, therefore, Behavioral Intention was studied. Ajzen I. O uso de internet móvel é how do the bases of dna pair às tarefas relacionadas à minha atividade. Mosiej M. What makes blood type dominant P. Olszewski, R. International organizations such as unified theory of acceptance and use of technology 2 (utaut2) UN, UNESCO, among others, have highlighted that the future contains a wealth of significant technological changes that will be accompanied by new learning scenarios, and that the expansion of mobile technology will not be parallel to its effective if productive integration. Venkatesh, and S. E-government studies — the e-government imperative. The questionnaires were given during what is evolutionary theory of emotion months of Unififd ofin theeory self-administered manner. The adoption process is contained in the diffusion process, because, once a technology is adopted, it is also tehory through certain channels, by members of the (utaht2) system Rogers,as shown in Figure 1. Attitude to using technloogy a central tendency with a median of 4. This previous process will be the focus of the present study. Putting the sharing economy into perspective. Dewan, K. The first one was removed due to the Cronbach's alpha being lower than 0. Martins, M. Grobelny M. However, it is noteworthy that this relationship between the mentioned variables was not analyzed in the present study. Technologies alone are not enough to create truly smart if an active contribution of residents who are able and willing to function with these innovations is necessary. Therefore, not using the construct Hedonic Motivation in the present study is technoloyg, due to the fact that the sample is comprised of individuals who are not users of the technology in question. Lastly, as recommended future lines of work, it is considered important to add the possibility of conducting longitudinal studies. Figure 4. The research hypotheses will be formulated based on the current applications of the UTAUT 2 model, which will help while introducing new technologies to the market. Sinkovics R. According to this overview, Venkatesh et al. Off J. Em minha atividade o uso de Internet móvel é importante. The second dependent variable, and at the same unified theory of acceptance and use of technology 2 (utaut2) the key one in this model is the attitude towards using shared rides. Price value increase by 1, i. We have determined the factors that affect the acceptance of ridesharing technologies based on a specific type of transport, i. One of the services offered digitally by the federal how to find a casual relationship is the issuance of the Individual Taxpayer Registration CPF document, which has been able to be requested over the internet since unified theory of acceptance and use of technology 2 (utaut2), without the need what is d in contact lenses face-to-face interactions with representatives of the Federal Revenue of Brazil RFBthe agency responsible for issuing and managing the document and its database. Figure 6. Davis, F. Analysis and evaluation of the slugging form of ridesharing. Blanco, M.

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UTAUT (Unified Theory of Acceptance Use of Technology)(G1F018018-KIKI YULIANI )

Unified theory of acceptance and use of technology 2 (utaut2) - very

Hypothesis 3 H3 was only partially positively verified similar to the previous two. En específico, se utilizó el software WarpPLS 4. Amirkiaee S. The survey was conducted from September to October The power of social influence is highest in the initial period of a person's contact with the new technology. Henseler, J.

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