There is a visible difference created by the advancement of technology in the education sector on whether a student likes to learn through a traditional way or distant learning with the help of technology that becomes convenient for them. E-learning can be an effective system if the students are using it for their benefit and exploring its features. This system of education will be helpful for the student such that classroom education will become obsolete if they are getting the required education and learning through technology. E-learning is being used globally, and the technology measurement can be possible when it will be used in the local or international scenario (El-Masri & Tarhini, 2017). Furthermore, e-learning refers to offer, organize and manage learning activities within a system, such as student enrolment, exams, assignments, course descriptions, lesson plans, messages, syllabus, basic course materials, etc. It is the need of the current environment to develop strategies or policies regarding the e-learning to provide education through different means of technology. Elearning implementation cannot be achieved if the different factors are not supportive towards the system. The success of the system is based upon the behavior, attitude, culture, organization, and other factors (Tarhini et al., 2017). These factors determine the success of the system and development (Teo & Noyes, 2014). It is evident and suggested by the researchers that adoption and effective use of technology is much different among the societies, communities, and others (Venkatesh et al., 2012). In the current world of globalization, the adoption of new technology has been increased in the developing countries far most. A report suggested that there is an increased demand for the online learning in continents like Africa, Asia and the Middle East, and along with these developing economies also exists a high demand for elearning. The study results suggested that there is an increase of 17.3% per year in the growth of e-learning acceptance from 2012 to 2016 as compared to the international growth of 7.9%. It is expected that Lao and Thailand will be having a high growth rate of above 50% by the next year. There are few pieces of research that have highlighted the obstacles and challenges faced by the developing nations in the field of education (Ramaiah, (2014).

Several researchers show interest in the adoption and acceptance of technologies in many perspectives, such as computers, E-commerce, mobile commerce, webbased learning, online learning and Internet banking (Gupta et al., 2008). These studies implemented the adoption theories to recognize and measure the individuals and organizations to adopt or reject new technologies. This paper will explain the technology acceptance by the unified theory of acceptance and use of technology (UTAUT2).

Later in the year 2012, UTAUT model was extended by Venkatesh focusing on consumer use context in the place of technology acceptance purpose and use of employees. The new construct such as Hedonic Motivation, Price Value, and Habit were added to the existing model. These additions in the model increased the variance explained by 18% and 12% in behavioral intention and use of technology respectively (Venkatesh et al., 2012). Moreover, Lewis et al. (2013) employing UTAUT2 for addressing the adoption of IT application in higher education institutions in the USA found the significant role of PE, EE, SI, and HT.

In the past, there are several studies being conducted to assess the online learning feature adoption, and different theoretical models and framework were designed to deliver the factors that are affecting the successful adoption and implementation of technology. It is concluded that in the entire model only UTAUT model is highly influential for all the models mentioned above (Venkatesh et al., 2003). Four variables are important in the model of UTAUT, which are performance expectancy, effort expectancy, cultural impact and effective environment; also there are four moderating variables such as demographics (age, gender), experience, and voluntariness. It is proposed that UTAUT2 is being extended by the initial model of UTAUT by induction of four models that are Price, value, hedonic motivation and habit to facilitate the explanatory powers. In this study, the researcher is using the UTAUT2 to analyze the factors that are impacting upon the e-learning adoption in the Libya universities in the context of students (Venkatesh et al., 2003; Venkatesh & Zhang, 2010). Modern studies are using the same features because they are simple, economical and quick to assess the variables (Venkatesh et al., 2012; Venkatesh & Zhang, 2010). It is evident from the previous studies that UTAUT and UTAUT2 did not analyze in the context of developing countries such as Arab and African because it is being tested in the developed countries in the studies (Alalwan et al., 2015). It is criticized that UTAUT is a biased model towards specific countries and their features. The importance of the model of UTAUT2 in the developing countries and using the different cultures will give different approaches and results in the context of the adoption of new technology by the users and others (Venkatesh et al., 2012). The researcher has included the variable of trust as highly important because in the previous studies it has played an important role in order to assess the adoption of the technology (Al Gahtani, 2016, Elmansori et al.,2017). Table 1 shows some of the relevant studies done previously:

Table 1.Some Previous Studies

It is suggested that the performance expectancy is associated with the individual perception that the technology is useful and effective which can resolve the issues that are being done at the workplace (Venkatesh et al., 2012; Waheed et al., 2015). As shown in Table 2, there is a positive impact upon the performance expectancy on the intention towards behavior and reaction. It is evident that technology is not only providing the ease in teaching and learning for the students, it also enables them to become productive and creative to produce quality results. It is the best time for the market to make every possible effort to produce new technology and innovation in the field of education. It is evident that talented students are having the efficiency to meet their requirements of acquiring the knowledge and learning through their behavior (Kahveci, 2010). In the study that is being conducted in the high school regarding the application of the technology, the result of the study suggested that respondents are more attracted towards the technology in acquiring knowledge and using the technology in the normal life every day (Kahveci, 2010).

Table 2. Performance Expectancy

It is associated with the easiness of the system that can be used. The variables are having importance in the voluntary and mandatory setting about the models and it is evident as the literature suggests that these constructs are helpful after the training analysis (Venkatesh et al., 2003).

The influential educational atmosphere urges the students to learn, get motivation, offer different options, in accessing the knowledge at any time. It is suggested from the previous studies that e-learning is having a high prospect among the talented students and by this way they are able to develop their capabilities and skills to acquire knowledge through the use of technology. A study was conducted on the younger talented students including their parents to assess and analyze whether the technological coursework is beneficial for the students or not. The results of the study suggested that talented students are more keen to interact with web-based knowledge and learning, and having an interest in the online course outline than the older talented students (Periathiruvadi & Rinn, 2012; Heine et al., 2015).

Online learning is highly effective and beneficial to the students currently as that will help them to use their skills to access the higher education as well. It is important in online teaching that teachers should be highly capable of providing the knowledge to the highly talented students (1Ng & Nicholas, 2010). The highly essential factors are being identified during the studies. It is suggested that developing a critical approach online is a very effective way of designing that kind of outline of the subjects that will increase the ability of the individual towards critical thinking and reflection about their experience of learning. As summarized in Table 3, the findings of the study suggest that it will be more effective for those students who are having online courses and produce quality achievements if they are making progress towards the learning environment. The completion of the task was 75% but it was 25% when they were having open learning environment (Periathiruvadi & Rinn, 2012).

Table 3. Effort Expectancy

The most effective features are being derived from the students who were about the knowledge of need and motivation to get good marks; they suggest that online learning is the best way to score good marks in their education. The students of online learning are having more flexibility and more option to learn rather than they are for attending the school (Romero et al., 2013).

In the case of effort expectancy, it is having a positive impact on the individual perception regarding the ease of use, and effort is highly correlated with the usage (Waheed et al., 2015). On the similar lines it is suggested that there is a positive impact among the factors of effort expectancy and behavioral intention to utilize electronic governance technology (Vinodh & Mathew, 2012). Raman and Don (2013) agreed that effort expectancy on the junior school teachers accepts the Learning Management System (LMS). It is suggested from the results that LMS is the best way for the students who are getting knowledge and education without having efforts to utilize the LMS.

Social influence impacts the individuals due to the other people's perception of the user's intention or attitude (Venkatesh et al., 2003). As presented in Table 4, it is evident that employees are being affected by their colleague's perceptions regarding electronic government services that ultimately impact upon the behavioral intention of the individual to use the electronic government services (Al Shafi et al., 2009).

It is evident from the literature the talented students (Terry et al., 2008) develops the perception about perfection and if it is not fulfilled, then it is felt by the user that his or her selfesteem becomes low. A study was conducted to undertake the construct correlation among self-concept and academic performance with 210 talented students (McCoach & Siegle, 2003). The results of the study suggested that the positive approach of the students increases their performance at the academic level. Social affiliation, interaction and cooperation increase the selfesteem and intellectual level of the students. Talented students are having their capabilities because of the social interaction and world knowledge (Riska, 2010).

Table 4. Social Influence/p>

The issue regarding the accessibility and availability is to use the resource supporting the users to use the technology (Venkatesh et al., 2003). It is evident if the students are not having support or access to technology, with no awareness and limited resources, then it will be difficult for the students to access the technology (Nanayakkara, 2007).

Table 5 shows another study which found the facilitating environment and using the web to get solutions for the questions in the educational context (Deng et al., 2011). It is necessary for the students to get assistance from the teachers who influence upon the LMS utilization which explains that the scenario of facilitating environment is affiliated with the effort expectancy adversely (Venkatesh et al., 2003).

Table 5. Facilitating Conditions

Additionally, the use of the system exists due to the support of the organizational and technical infrastructure. Three variables can be taken from the model.

In the case of UTAUT model, it is evident that the variance can be 70%, in the case of intention while in the other models the variance could be a maximum of 40%. Researchers also illustrated the limitation of the validity that should be upon the measures which are being taken for the process and it is being recommended that future research should be producing more appropriate and validated measure for the variables that confirm the validity and revalidate the extension (Venkatesh et al., 2003).

Hedonic motivation refers to the fun or pleasure derived from using technology. In the original UTAUT, the extrinsic motivation associated with a technology use decision is represented as performance expectancy (Venkatesh et al., 2012). However, modeling users' motivation in case of consumer usage setting, such as m-learning, solely on extrinsic motivation would be an insufficient conceptualization. According to motivation theory, intrinsic or hedonic motivation plays an important role in determining technology use in the consumer technology use context. In fact, hedonic motivation was found as a key predictor of technology acceptance in many consumer use settings (Limayem et al., 2007). Table 6 presents hedonic motivation used as constructs in the study (Lewis et al., 2013; Raman & Don, 2013).

Table 6. Hedonic Motivation

Previous experience is the prominent feature in forecasting the habit (Limayem et al., 2007). Habit is considered as the perceptional approach of the individual that shows the previous experience (Venkatesh et al., 2012). Habit explains in the scenario of technology and information system that people consistently do activities according to their behavior because they are aware of it through their experience (Limayem et al., 2007). The significance of the habit as a variable in the research is that because it depends upon the behavioral intention that enables the researcher to perform certain behavior repeatedly pertaining to the habit of the individual. Previous research in the context of habit persistence is certain which reduces automatically (Limayem et al., 2007). It is evident that the individual uses the technology continuously which becomes a habit that suggests that the individual has persistent action reflecting through the behavior intention of the individual (Bandyopadhyay & Fraccastoro, 2007). Table 7 presented studies using habit as a construct with acceptance of e-leaning technology done by (Lewis et al., 2013; Raman & Don, 2013).

Table 7. Habit

A study was conducted in 2014 in Tanzania with the purpose of analyzing those features that urge students to use the online system effectively, or in other words online Learning Management System (LMS) (Lwoga and Komba, 2014). The researcher analyzes the important feature that predicts the actual and continuous use of the electronic learning system intentionally, and issues in using the online learning system due to the management staff using the LMS to deliver the electronic courses, tasks and information through it. The researcher has used research tools such as interviews and questionnaires. The questionnaire was given with a sample size of 300 third-year undergraduate students, and the filled questionnaires were 77%. In the case of interviews, the researcher conducted interviews with 20 college members to facilitate and merge the results of the questionnaire as well. The researcher has used the exploratory factor analysis (EFA) for the validity and reliability to test the model; also, the researcher used the regression model to test the hypotheses of the study with the help of SPSS software. The researcher has developed the model which is based on the UTAUT and using different variables such as self-efficacy, effort expectancy, performance expectancy, social impact, facilitating conditions use, and consistent use of intentions. The results of the study suggested that use is being analyzed through the feature of self-efficacy, but the consistent use intention of using the web learning is being predicted by performance expectancy, effort expectancy, social impact, self-efficacy, and actual utilization of the system. Issues in the use of online management system are due to the lack of infrastructure because LMS is not user-friendly. Ineffective implementation of LMS rules, lack of technical and management support, lack of knowledge or access to the technology, resistance to accepting the change, and lack of consideration towards the development of electronic-based courses and usage of online learning. The results of this study will be effective and helpful for the elearning supporters, and university management will be identifying and highlighting the issues that are reducing the effect and influence of e-learning on students. The study is based on the model of UTAUT in which consistent use intention and self-efficacy is an added variable that increases the scope and value of the UTAUT model which will be having an impact and influence effectively on the elearning system in Tanzania, because on this topic more studies are not being conducted. Table 8 highlighted the results of the study implemented with a familiar environment to analyze the consistent use of e-learning systems adequately (Lwoga and Komba, 2014).

The behavior intention is being defined as an individual concept towards interaction with the given behavior (Cegarra et al., 2014). Behavior intention is a specific attitude being undertaken by the question such as; I intend towards by using the five-point Likert scale to test and measure the strength of intention. Behavior intention is the opposite of aspirations and self-forecasting (Armitage et al., 2002; Schaper & Pervan, 2009).

Table 8. Behavioral intention

This paper presents an overview of the Unified Theory of Acceptance and Use of Technology (UTAUT2). Also, the aim of this paper is to review the related studies regarding the adoption of e-learning technology, and on the other hand to review the studies that have been carried out on the adoption of learning technology based on the Unified Theory of Acceptance and Use of Technology (UTAUT2).The study found that the UTAUT2 model is highly influential for all the models such as UTAUT, TAM and TRA. Many studies that have been carried out in both developing and developed countries indicated that effort expectancy, performance expectancy, social influence, facilitating conditions, habit and hedonic motivation affect positively and significantly on the behavioral intention to adopt e-learning technology. Also, the findings discussed might make the future studies in e-learning adoption much easier when choosing which factors are more effective, more important, and would be used and tested. Moreover, this study might be helpful for the education sectors in developing countries while adopting and understanding eleaning Systems.