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1、an empirical investigation into the factorsinfluencing the adoption of an e-learning systemya-ching leeassistant prof.institute of communication managementnational sun yat-sen university5f, 10, lane 230, le-de street, fengshan, kaohsiung, taiwan886 7 7194530; yacleeabstractthis study sets out to inv
2、estigate the factors affecting the adoption of an e-learning system (els), through an extension of the technology acceptance model (tam). the results of the study confirm the original tam findings. this study also discovers that content quality, perceived network externality and course attributes ca
3、n all affect the perceived usefulness of a system. perceived network externality and computer self-efficacy are also shown to be important determinants of the perceived ease of use of the system. recommendations for promoting els adoption are subsequently discussed, along with suggestions for improv
4、ing overall system design.keywords: e-learning system, technology acceptance model (tam), content quality, perceived network externality, course attributes, computer self-efficacy1. introductionin this age of globalization, knowledge acquisition has become the critical means for gaining competitive
5、advantage, and as such, learning has become a crucial element of knowledge acquisition, application and creation (longworth & davies, 1996). the widespread proliferation of internet technologies and applications provides incredible opportunities for the delivery of education and training, and wi
6、th rapidly increasing internet usage, e-learning has now become a portable and flexible new method for learners to gain essential knowledge.e-learning generally refers to methods of learning which use electronic instructional content delivered via the internet, and is a term which is synonymous with
7、 web-based, or online, learning (trombley & lee, 2002). most of the distance education and web-based learning initiated by teachers is integrated into the curricula as a means of enhancing the process and effectiveness of learning at individual levels, essentially as a supplement to the traditio
8、nal face-to-face teaching environment; and indeed, online courses are now also offered at many universities throughout the world (collison et al., 2000). a diverse range of universities have developed their own e-learning systems (els) as a means of delivering instruction through the use of multimed
9、ia, and this is especially true in taiwan, where many public and private universities have developed a single web-based els to supplement their teaching and learning.students within the same universities can now enjoy a unified user-friendly interface and usability, which enables interaction with in
10、structional materials in various formats (text, pictures, sound, video on demand, and so on) anywhere, and at any time, as long as they can log on to the internet. furthermore, given the functionality of message boards, instant message exchanges and video conferencing, they can even interact with te
11、achers and classmates, both individually, and on a simultaneous basis. they can also engage in self-paced learning, taking control over both the process and the content of their learning (trombley & lee, 2002; zhang & zhou, 2003). within these universities, the els are deemed to be a supplem
12、ent to traditional class settings (as opposed to a replacement, as in the case of online courses).a number of studies have already examined e-learning on the internet, with most of these studies investigating the relationship between instructional materials and the structure of such materials, teach
13、ing strategies, the personalities of learners, and the self-control and behavior of students (in terms of their self-discipline when using the internet as a main teaching tool). for example, in their investigation of the relationship between self-controlled learning and the online search behavior of
14、 students in universities, eom and reiser (2000) found that younger students needed a more organized structure of course materials and ongoing help. mcmanus (2000) concluded that the personalities of learners, the structure of the materials, and the teaching strategies, each had some influence on th
15、e ways in which students self-regulated their learning behavior. many of the prior studies have, however, tended to focus on the acceptance of students by course websites on quite a small scale, with many of the course websites being initiated either by individual teachers, or built up for experimen
16、tal test purposes only. examples include the studies by selim (2002) and babenko-mould et al. (2004). the results of these studies have therefore failed to provide an explanation of the situation where students on baccalaureate or graduate programs at higher level teaching institutions (universities
17、) are using els, provided by the establishment, on an ongoing basis. it is clearly of importance, therefore, to gain an understanding of the success factors contributing to the acceptance of e-learning within a university environment. with this as the ultimate aim, this paper sets out to investigate
18、 the acceptance by students of the e-learning systems provided by teaching and learning institutions, with the technology acceptance model (tam) being adopted to investigate the critical factors leading to the effective and efficient adoption of e-learning. the specific objectives of this study are;
19、 (i) to develop an extended tam for the determinants of the acceptance of e-learning; and (ii) to investigate both the direct and indirect effects of these determinants of acceptance. it is felt that the findings of this study should assist instructors and universities to determine the most effectiv
20、e ways to provide a more enhanced learning environment.2. literature reviewbuilding on the theory of reasoned action model, davis (1989) proposed the technology acceptance model (tam) in an effort to explain and predict the adoption and use of information technology at work in 1989. the tam theorize
21、d that perceived usefulness (pu) and perceived ease of use (peou) were two key determinants of technology adoption. davis referred to pu as the degree to which individuals expected that the adoption of a particular technology would enhance their job performance, whilst peou was the degree to which i
22、ndividuals believed that using a particular technology would be simple (davis, 1989). according to the tam (davis, 1989), both pu and peou influence the attitude of individuals towards the use of a particular technology, whilst attitude and pu predict the individuals behavioral intention (bi) to use
23、 the technology. pu is also influenced by peou, since peou can indirectly affect the acceptance of technology through pu, whilst bi is also linked to subsequent adoption behavior. tam also suggests that external variables intervene indirectly, influencing both pu and peou. attitude was subsequently
24、omitted from the model by davis et al. (1989) as a result of its weak correlation with both bi and pu. figure 1 presents davis original version of tam. perceivedusefulnessperceivedease of usebehavioral intentionactualbehaviorexternal variablesusefulnessattitudefigure 1. technology acceptance modelso
25、urce: davis (1989)3. extended tam for e-learning systemsthe technology acceptance model developed by davis (1989) has been widely used, over the past decade, as a means of forecasting the extent to which an innovative technology will be adopted in the field of information systems (is), with the find
26、ings of many studies being consistent with tam applications. in their various applications of the tam, a number of studies have confirmed that user perceptions of usefulness and the ease-of-use of a system are two important antecedents of technology adoption, and have also suggested various ways of
27、broadening the overall applicability of the tam (e.g., davis, 1992; davis et al., 1992; igbaria et al., 1997; gefen & straub, 1997, 2000; venkatesh, 1999; venkatesh & davis, 2000; gefen, 2003; hsu & lu, 2004; ong et al., 2004). however, very few studies have adopted the tam as a model fo
28、r explaining the use of an els designed and provided by schools. a number of studies tended to focus on the acceptance of students by course websites on quite a small scale. for examples, selim (2002) and babenko-mould et al. (2004) tested the two tam constructs of perceived usefulness and perceived
29、 ease-of-use as predictors of user acceptance of course websites, with the results indicating a good fit for the tam. however, pu and peou may not exactly reflect the acceptance of the els provided by universities, since there are other factors that contribute to the adoption of such systems. in thi
30、s paper, an extended model is proposed based on an extension of the tam approach; the extended model includes constructs and relationships which may prove to be important in the context of e-learning. these constructs are: (i) content quality; (ii) perceived network externality; (iii) computer self-
31、efficacy; (iv) course attributes; and (v) a mechanism of competing behavioral intentions to e-learning. the theoretical approach is reviewed below. 3.1. determinants of the e-learning system adoption3.1.1. behavioral intentionaccording to the empirical results reported by ajzen and fishbein (1980),
32、technology acceptance is determined by bi. therefore, within an e-learning context, the adoption of an els is a positive function of the intention to accept the system. 3.1.2. competing behavioral intentionsthe adoption of a new idea or an innovative technology by any group of people is the result o
33、f logical decision making with regard to choice (chu & chiu, 2003). many decision-making theories offer explicit frameworks to assist in making the correct choices (from a logical perspective) from a set of alternatives. although the tam has some considerable strength, in terms of predicting abo
34、ut 40 per cent of the use of a system (venkatesh & davis, 2000), its main ability to predict individual behavior fails to deal with behavioral choices when the individual is faced with alternatives. when considering the use of an els, students may also choose to receive instructional material an
35、d education within classroom (face-to-face) settings, or to make use of educational videos or educational cd-roms. the prediction of technology adoption has to consider alternative setting which may have some impact on eventual adoption behavior (harrison, 1995). in the extended tam for e-learning,
36、as opposed to simply being an indication of the intention to accept the system, the adoption of the els is actually a function of competing intentions, which is determined by a positive function of intention to use the els and the simultaneous negative functions of intention to use competing learnin
37、g media. in other words, actual adoption behavior is the consequence of a choice between bi and cbi to receive education. we therefore propose the following hypotheses based on the foregoing discussion:hypothesis 1: the behavioral intention to accept the e-learning system positively affects user ado
38、ption.hypothesis 2: user adoption is determined by a positive function of intention to use the system and a negative function of other competing behavioral intentions.3.2. determinants of behavioral intentions to adopt the e-learning system3.2.1. perceived usefulness the perceived usefulness (pu) of
39、 a system is defined as the extent to which individuals believe that using the new technology will enhance their task performance. numerous empirical studies have provided support for the proposition that pu is the primary predictor of information technology usage (davis, 1989, 1992; davis et al., 1
40、992; igbaria et al., 1997; gefen & straub, 1997, 2000; venkatesh, 1999; venkatesh & davis, 2000; gefen, 2003; hsu & lu, 2004; ong et al., 2004). an els can be viewed as an information technology device, and students will use the system only if they perceive that its use will enhance thei
41、r performance. such performance enhancement may be measured in terms of learning productivity (or learning efficiency), the effectiveness of learning, and improvements in grades. in the context of e-learning, therefore, pu refers to the extent to which students believe that using the els will enhanc
42、e their learning performance. pu will therefore have an influence on their intention to accept and adopt the els, either directly, or indirectly (through peou). 3.2.2. perceived ease of usethe perceived ease of use (peou) of a system is defined as the degree to which an individual believes that usin
43、g a particular technology will be free of effort. the results of many of the prior empirical studies have demonstrated that peou has a positive correlation with bi, both directly (davis, 1989, 1992; gefen & straub, 1997, 2000; venkatesh, 1999; venkatesh & davis, 2000; gefen, 2003) and indire
44、ctly, through pu (davis, 1989, 1992; igbaria et al., 1995, 1999; venkatesh, 1999; venkatesh and davis, 2000). however, its effect on technology usage intentions decreases when users become more familiar with the system, or in those cases where the complexity of the system is very low (venkatesh &
45、; davis, 2000). therefore, in the context of e-learning, peou is defined as the degree to which a student believes that the use of an els will be free of effort, and peou will similarly affect a students intention to accept the els. based upon the prior research, the following hypotheses are propose
46、d:hypothesis 3: perceived usefulness positively affects the intention of users to accept an e-learning system.hypothesis 4: perceived ease of use has a positive effect on the perceived usefulness of an e-learning system.hypothesis 5: perceived ease of use has a positive effect on the intention of us
47、ers to accept the e-learning system.3.3. perceived content qualitythe results of many empirical studies have also indicated that information quality is important in determining users level of satisfaction with the system, which in turn leads to system utilization (delone & mclean, 1992; kateratt
48、anakul & siau, 1999; mckinney et al., 2002). there are two dimensions of content quality, content richness and update regularity. the first of these, content richness positively affects learners level of satisfaction with the course (burns et al., 1990; arbaugh, 2000). the richness of the endors
49、ed course content within an els can be provided by educational software on a cd-rom; however, what makes the els different is the extent to which learners can adapt the system, as opposed to simply using traditional learning methods. cd-roms should therefore have a close association with the content
50、 quality available through the latest internet technology. the internet offers content richness far beyond that which any other technology can offer, since the entire information content of the internet is available as complementary course content. the special characteristics of internet hyperlinks
51、and interactivity allow students and teachers to share and access numerous resources, in addition to the fundamental course contents (boisvert, 2000; peterman, 2000; chew, 2002). an els has greater appeal to students because of the richness of content provided by the internet, as compared to traditi
52、onal learning methods. students themselves, teachers, and classmates, can search through the related content on the internet, and then share it on the system. if a student who was a potential user of the system perceived that the content quality on the els was high, there would be a high probability
53、 of that student regarding the content as having a positive effect on learning, and therefore, that the student would adopt the system. it is therefore reasonable to assume that content quality on the els has a positive association with students adoption of the system. the second dimension relates t
54、o update regularity. the internet has become a new focus for major software companies, such as microsoft, to improve their product quality, since it attracts many potential customers to accept and buy new software products, largely because they know that the product quality can be continually enhanc
55、ed simply by downloading the files online (szajna, 1996). by the same token, course content on the els can be updated anytime, anywhere. burns et al. (1990), arbaugh (2000) and chen et al. (2003) each found that learner satisfaction would be enhanced significantly if they could obtain updated e-lear
56、ning content on a regular basis. updated content, and new content, may lead students to feel that the els is a useful means of gaining new knowledge and learning. this research therefore hypothesizes that update regularity positively affects utilization of the els by students. hypothesis 6: perceive
57、d content quality positively affects perceived usefulness.3.4. perceived network externalityderived from metcalfes law, network externality relates to an increase in the value of a product or service to a consumer, not because of the inherent quality of the product or service, but because of increas
58、ing numbers of others adopting it (katz and shapiro, 1985). for example, the value of the internet increases as it allows more people to communicate and exchange information with other participants; its popularity, in turn, attracts more users to that technology. several studies which have examined
59、the effects of network externality on the adoption of information technology from the aspect of critical mass, have referred to the level of importance of a consumers perception of the adoption of the technology by other consumers (luo & strong, 2003; hsu & lu, 2004). in the context of e-learning, this perception can also create bandwagon effects. in other words, if students perceive
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