Computers & Education 53 (2009) 1320–1329 Contents lists available at ScienceDirect Computers & Education journal homepage: www.elsevier.com/locate/compedu Learners’ acceptance of e-learning in South Korea: Theories and results Byoung-Chan Lee a, Jeong-Ok Yoon b, In Lee c,* a b c Department of Business Administration, Graduate School of Business Administration, Keimyung University, South Korea Graduate School of Education, Keimyung University, South Korea Department of Information Systems and Decision Sciences, College of Business and Technology, Western Illinois University, Macomb, IL 61455, United States a r t i c l e i n f o Article history: Received 16 February 2009 Received in revised form 18 June 2009 Accepted 21 June 2009 Keywords: E-learning Service quality Playfulness Technology acceptance a b s t r a c t One of the most significant changes in the field of education in this information age is the paradigm shift from teacher-centered to learner-centered education Along with this paradigm shift, understanding of students’ e-learning adoption behavior among various countries is urgently needed South Korea’s dense student population and high educational standards made investment in e-learning very cost-effective However, despite the fact that South Korea is one of the fastest growing countries in e-learning, not much of the research results have been known to the globalized world By investigating critical factors on e-learning adoption in South Korea, our study attempts to fill a gap in the individual country-level e-learning research Based on the extensive literature review on flow theory, service quality, and the Technology Acceptance Model, our study proposes a research model which consists of four independent variables (instructor characteristics, teaching materials, design of learning contents, and playfulness), two belief variables (perceived usefulness and perceived ease of use), and one dependent variable (intention to use e-learning) Results of regression analyses are presented Managerial implications of the findings and future research directions are also discussed Ó 2009 Elsevier Ltd All rights reserved Introduction One of the most significant changes in the field of education during the information age is the paradigm shift from teacher-centered to learner-centered education The emergence of electronic learning (e-learning) has further facilitated the wide adoption of learner-centered education and other changes in educational practices E-learning has drawn significant attention from educational institutions, educational software developers, and business organizations due to the potential educational and cost benefits Such benefits are reduced education cost, consistency, timely content, flexible accessibility, and convenience (Cantoni, Cellario, & Porta, 2004; Kelly & Bauer, 2004) Educational values can be also enhanced by customizing content for the learners’ needs (Engelbrecht, 2003) Many educational institutions are now offering innovative online degree programs, expanding their educational territories without time and space barriers, and complementing their traditional offline class with web-based online educational tools For-profit and non-profit organizations are increasingly replacing traditional offline job training with online training programs They claim that online training saves training costs and enhances learning effectiveness by delivering high-quality training services The success of e-learning in large part depends on the implementation of an educational model which addresses the learners’ needs and educational objectives Designing good e-learning services is a complicated task and requires a multidisciplinary approach While a number of studies have investigated success factors and benefits of e-learning, there is still a lack of empirical studies that focus on the relationships among e-learning service factors and learners’ acceptance (Liaw, 2008; Liu, Liao, & Pratt, 2009; Pituch & Lee, 2006; Sánchez-Franco, Martínez-López, & Martín-Velicia, 2009) The development of e-learning in South Korea is strongly related to the rapid growth of its Information and Communications Technology (ICT) industry (Misko, Choi, Hong, & Lee, 2005) High-quality e-learning services have been rapidly developed due to the nation-wide telecommunication infrastructure and high-speed Internet Korean government has been one of the driving forces behind the rapid growth of e-learning In 2001, the ‘Law for Developing On-Line Digital Contents Industry’ was enacted to promote digital contents for education and to produce IT professionals * Corresponding author Tel.: +1 309 298 1409; fax: +1 309 298 1696 E-mail address: I-Lee@wiu.edu (I Lee) 0360-1315/$ - see front matter Ó 2009 Elsevier Ltd All rights reserved doi:10.1016/j.compedu.2009.06.014 B.-C Lee et al / Computers & Education 53 (2009) 1320–1329 1321 South Korea’s highly dense population and high literacy rate of over 97% provides cost-effective conditions for investment in e-learning Due to the great interest of the general public in education, Korea’s enrollment rate in higher education is over 70% The high enrollment rate and dense student population make investments in e-learning cost-effective Realizing the potential benefits of e-learning, companies in South Korea are increasingly adopting e-learning to train their employees and to improve their productivity While the diffusion of e-learning in South Korea is rapidly progressing, little of this has been known to the international field of e-learning E-learning has become an important educational method in the internationalization of higher education Increasing number of foreign students are taking online courses from abroad and obtaining online degrees (Hannon & D’Netto, 2007; Huynh, Umesh, & Valacich, 2003) Many higher education institutions in the US are developing degree programs overseas because of academic and business reasons (Bollag, 2006) In South Korea, leading universities such as Korea University and Yonsei University also established and plan to establish branch campuses in the US Therefore, it is increasingly important to promote individual country-level e-learning research in a global society By investigating e-learning adoption in South Korea from student perspectives, our study attempts to fill a gap in the individual country-level e-learning research The rest of this study proceeds with a brief review of literature made by previous researchers, a description of the research model and hypotheses for empirical testing, a description of the research methodology, data analyses, a discussion of the results, the implications of the findings for researchers and practitioners, and limitations of the study Literature review 2.1 Definition of e-learning The term e-learning has been widely used in education since the mid-1990s However, the definition of e-learning has not been clearly agreed on Some researchers view e-learning as the delivery of teaching materials via electronic media, such as Internet, Intranets, Extranets, satellite broadcast, audio/video tape, interactive TV, and CD-ROM (Engelbrecht, 2005) Other researchers view e-learning as a webbased learning which utilizes web-based communication, collaboration, knowledge transfer, and training to add values to the individuals and the organizations (Kelly & Bauer, 2004) While it is generally accepted by most researchers that e-learning can be delivered by any electronic media other than web-based media, web technologies have made e-learning more widely accepted by academic institutions as well as business organizations (Alavi & Leidner, 2001; Hiltz & Turoff, 2005) E-learning has become an indispensible part in the competitive educational services market Educational service providers offer online lessons, online tests, and educational consulting to meet the diverse demands of the educational customers Active learning is an instructional method that engages students in the learning process by requiring students to meaningful learning activities (Bonwell & Eison, 1991) Active learning is often contrasted to the traditional lecture where students passively receive information from the instructor The online learner must be active in the process, cognitively complex and motivated for quality e-learning (Alley & Jansak, 2001; Clark, 2002) E-learning provides many opportunities for media-based, student-centered, and interactive learning environments that support active learning (Huffaker & Calvert, 2003; Zhang, Zhao, Zhou, & Nunamaker, 2004) Based on the definitions used in the existing studies, for this research e-learning is defined as web-based learning which utilizes webbased communication, collaboration, multimedia, knowledge transfer, and training to support learners’ active learning without the time and space barriers Even though the potential benefits of e-learning may be significant, there are a number limitations and challenges to e-learning practices E-learning generally requires a high upfront cost, new pedagogical skills, and learners’ self-discipline and motivation (Cantoni et al., 2004) Security issues such as cyber attacks and hacking to e-learning systems are of concern to the learners and service providers (Ramim & Levy, 2006) In administering online tests, authenticating test-takers is one of the major challenges due to the inability to directly monitor the exam takers To enhance the assessment of learning performance, some educational service providers or higher education institutions offer a mixture of online tests and offline tests (Gunasekaran, McNeil, & Shaul, 2002) A number of studies indicated that the degrees of learner satisfaction with e-learning have been widely used to evaluate the effectiveness of e-learning (Zhang et al., 2004; Eom, Wen, & Ashill, 2006; Levy, 2007) The early studies show that technology, technical competency, motivation, instructor characteristics, and student characteristics are factors that affect the effectiveness of e-learning (Dillon & Gunawardena, 1995; Leidner & Jarvenpaa, 1993; Soong, Chan, Chua, & Loh, 2001; Volery & Lord, 2000) Recent studies focused on a wider variety of factors that affect the students’ acceptance of e-learning Pedagogical design and students/facilitator interaction are shown to affect student’s acceptance of e-learning (Martínez, del Bosch, Herrero, & No, 2007) Roca, Chiu, and Martinez (2006) applied the Technology Acceptance Model (TAM) and found that users’ continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usefulness, information quality, confirmation, service quality, system quality, perceived ease of use and cognitive absorption More recently, Levy (2008) investigated issues related to learners’ perceived value by uncovering the critical value factors (CVFs) of online learning activities His study identified five reliable CVFs that contribute to learners’ perceived value: (a) collaborative, social, and passive learning activities; (b) formal communication activities; (c) formal learning activities; (d) logistic activities; and (e) printing activities While the majority of studies focused on the learners’ acceptance of e-learning, instructors’ acceptance of e-learning is also of great concern for educational institutions Many educational institutions have provided special training and incentives to the instructors who are willing to incorporate e-learning to their curriculum A number of studies have investigated instructors’ perception on e-learning and success factors (Hu, Clark, & Ma, 2003; Kollias, Mamalougos, Vamvakoussi, Lakkala, & Vosniadou, 2005; Liaw, Huang, & Chen, 2007; Myers, Bennett, Brown, & Henderson, 2004) In the following, we review in detail the Technology Acceptance Model (TAM), service quality, and flow theory in an e-learning context upon which our research model is based 2.2 E-learning Technology Acceptance Model (TAM) TAM was introduced by Davis (1986) to explain computer-usage behavior Since then, TAM has been the most frequently cited and influential model for understanding the acceptance of information technology and has received extensive empirical support 1322 B.-C Lee et al / Computers & Education 53 (2009) 1320–1329 (e.g., Venkatesh, Morris, Davis, & Davis, 2003) The theoretical basis of TAM was Fishbein and Ajzen’s (1975) Theory of Reasoned Action (TRA) TRA is a widely-studied model from social psychology which is concerned with the determinants of consciously intended behaviors According to TRA, a person’s performance of a specified behavior is determined by his or her behavioral intention (BI) to perform the behavior, and BI is jointly determined by the person’s attitude (A) and subjective norm (SN) concerning the behavior in question TAM proposes external variables as the basis for tracing the impact of external factors on two main internal beliefs, perceived usefulness (PU) and perceived ease of use (PEU) According to Davis (1989), perceived ease of use is the degree to which a person believes that using a particular system would be free of effort and perceived usefulness is the degree to which a person believes that using a particular system would enhance his or her job performance These two beliefs both influence users’ attitude toward using information systems (IS) Despite the potential of e-learning as a tool to enhance education and training performance, its value will not be realized if users not accept it as a learning tool Since e-learning utilizes information technology, TAM has been extensively utilized and extended for research in an e-learning context The two TAM constructs (perceived usefulness and ease of use) were applied to assess university students’ acceptance of course websites as an effective learning tool (Selim, 2003) Results revealed that perceived usefulness and ease of use of course website proved to be key determinants of the acceptance and usage of course website as an effective and efficient learning technology To understand an engineer’s acceptance of e-learning, Ong, Lai, and Wang (2004) proposed a construct, perceived credibility, which measures the degree to which a person believes that a particular system would be free of privacy and security threats Their empirical study supports that perceived credibility has a positive effect on engineers’ intention to use e-learning, suggesting learners must be assured that they are free of privacy and security threats Another study investigated the effect of system characteristics on e-learning system use (Pituch & Lee, 2006) After examining a variety of general information systems characteristics, they selected three system characteristics: system functionality, interactivity, and response time System functionality refers to the ability of e-learning systems to provide flexible access to instructional materials via various types of media such as video, audio, and text Interactivity refers to the ability of e-learning systems to facilitate the interactions among students and between faculty and students Tools commonly used in interactive e-learning are e-mail, bulletin boards, and chat room Response time is the degree to which e-learning systems’ response to learners’ inquiries is fast, consistent, and reasonable All these three characteristics are shown to affect the usefulness and intention to use e-learning systems Self-determination theory (SDT) was applied to examine the effects of motivational factors affecting TAM constructs in e-learning in a work setting (Roca & Gagné, 2008) They introduced three motivational factors (perceived autonomy support, perceived competence, and perceived relatedness) based on SDT Perceived autonomy support refers to the e-learning support for the learners’ desire to self-organize their actions Perceived competence refers to the belief that one can successfully perform a distinct set of actions required to utilize effectively e-learning Perceived relatedness refers to the belief that one feels connected and supported by important people, such as instructors or other learners The perceived autonomy support, competence, and relatedness were shown to influence perceived usefulness, playfulness, and ease of use Other factors such as learner computer anxiety, instructor attitude toward e-learning, e-learning course flexibility, e-learning course quality, and diversity in assessments also seem to affect learners’ satisfaction (Sun, Tsai, Finger, Chen, & Yeh, 2008) Perceived usefulness and self-efficacy were shown to influence behavioral intention to use e-learning (Liaw et al., 2007) 2.3 E-learning service quality While TAM was developed to understand computer-usage behavior, Parasuraman, Zeithaml, and Berry (1985), Parasuraman, Zeithaml, and Berry (1988) developed SERVQUAL, a conceptual model of service quality from their work in the area of retail marketing SERVQUAL is based on the assumption that satisfaction is found in situations where perceptions of service quality meet or exceed consumer expectations Parasuraman, Zeithaml, and Berry (1988) developed the original 22-item five-dimension SERVQUAL based on extensive focus group research (Parasuraman, Zeithaml, & Berry, 1985) The five-dimensions underlying the 22-items include: Tangibles: Physical facilities, equipment and appearance of personnel Reliability: Ability to perform the promised service dependably and accurately Responsiveness: Willingness to help customers and provide prompt service Assurance (including competence, courtesy, credibility and security): Knowledge and courtesy of employees and their ability to inspire trust and confidence Empathy (including access, communication, understanding the customer): Caring, individualized attention the firm provides its customers Recognizing that SERVQUAL is not sufficient for measuring e-business service quality, Kaynama and Black (2000) developed an e-service quality measure comprised of seven dimensions: content, access, navigation, design, response, background, and personalization Aladwani and Palvia (2002) reported on the development of an instrument that captures key characteristics of web site quality from the user’s perspective The 25-item instrument measures four dimensions of web quality: specific content, content quality, appearance and technical adequacy The instrument exhibits psychometric properties and provides an aggregate measure of web quality Given the importance of IS support, DeLone and McLean (2003) recommended that service quality be added as an important dimension of IS success, especially in the e-commerce environment where customer service is crucial Service quality measurement tools have also been developed in the e-learning context In e-learning, the commitment and ability of the instructors are important factors that affect the confidence and trust level of the learners (Dillon & Gunawardena, 1995; Webster & Hackley, 1997) The quality of e-learning teaching materials affects the satisfaction of the learners (Sun et al., 2008) The more confidence and trust the learners have in the quality of teaching materials used for their learning, the more satisfied they are with e-learning environments If teaching materials not meet learners’ expectations, learners tend to be easily distracted and feel uncomfortable and thus overburdened with e-learning High-quality teaching materials motivate learners to continue e-learning by generating more value Therefore, the development of learner-centered teaching materials is critical to the success of e-learning Personalization is important in web-based learning Personalization of web-based learning requires collection of personal data to profile learner preferences, interests, and browsing behaviors in providing personalized services (Chen, Lee, & Chen, 2005) B.-C Lee et al / Computers & Education 53 (2009) 1320–1329 1323 2.4 Flow theory and e-learning Flow theory emphasizes the role of a specific context rather than individual differences in explaining human motivated behaviors Csikszentimihalyi (1975) pioneered Flow Theory, and defined ‘flow’ as ‘‘the holistic sensation that people feel when they act with total involvement” (p 36) Different researchers developed different measurement tools for flow which reflect the unique aspects of analysis For example, Novak, Hoffman, and Yung (2000) measured pleasure which people can experience when they are immersed in certain activities While a number of researchers suggested methodologies and measurement items to measure flow, there has not been a universal measurement tool Playfulness is a concept that is used most widely to measure flow Playfulness is a complex variable which includes individual’s pleasure, psychological stimulation, and interests (Csikszentmihalyi, 1990) Moon and Kim (2001) view playfulness as a situational characteristic of the interaction between an individual and the situation Three dimensions of perceived playfulness proposed by Moon and Kim (2001) are the extent to which the individual: (1) perceives that his or her attention is focused on the interaction with the web-based system; (b) is curious during the interaction; and (3) finds the interaction intrinsically enjoyable or interesting Since an online consumer is both a buyer and a computer user, one’s experience level (or self-efficacy) and one’s degree of product involvement should influence one’s degree of playfulness in a particular online purchasing context (Koufaris, 2002) Other studies also show that computer experience affect playfulness (Hackbarth, Grover, & Yi, 2003; Webster & Martocchio, 1992) A few e-learning studies address contribution of playfulness to instructors’ and learners’ acceptance of e-learning service Integrating a motivational perspective into the Technology Acceptance Model, Lee, Cheung, and Chen (2005) captured both extrinsic (perceived usefulness and ease of use) and intrinsic (perceived enjoyment) motivators for explaining students’ intention to use e-learning services The results showed that both perceived usefulness and perceived enjoyment significantly and directly impacted their intention to use e-learning services On the other hand, perceived ease of use did not have a significant effect on student attitude or intention to use e-learning services Our literature review reveals that further research is still needed to understand playfulness and the adoption of e-learning The next section discusses our research model and hypotheses Research model and hypotheses 3.1 Research model Based on the literature review, we believe that comprehensive research is needed to assess the intention to use e-learning by the current and future learners The proposed model consists of four independent variables, two belief variables, and one dependent variable The four independent variables are playfulness and three service quality constructs – instructor characteristics, teaching materials, and design of learning contents Instructor characteristics are defined as the extent to which instructors are caring, helpful, and accommodating to students Teaching materials are defined as the extent to which teaching materials are suitable for e-leaning Design of learning contents is defined as the extent to which learning contents are designed and developed to fit students’ needs Two belief variables are perceived usefulness and perceived ease of use Perceived usefulness is the degree to which a person believes that a particular e-learning service would enhance his/her learning performance Perceived ease of use is the degree to which a person believes that using a particular e-learning service would be free of effort The dependent variable is the intention to use e-learning Fig shows our conceptual research model 3.2 Hypotheses Instructor’s attitude and ability affect learners’ attitude toward e-learning, and instructor’s teaching style affects learners’ enthusiasm, participation, and attitude toward e-learning (Dillon & Gunawardena, 1995; Webster & Hackley, 1997) An empirical study on student attitude towards using e-learning reveals that instructor characteristics are the most critical factor in e-learning success, followed by IT infrastructure and university support (Selim, 2007) A recent study suggests that e-learning course quality affect learners’ perceived satisfaction (Sun et al., 2008) Thus, this study hypothesizes the followings: Fig The research model 1324 B.-C Lee et al / Computers & Education 53 (2009) 1320–1329 3.2.1 Hypothesis Instructor characteristics positively affect learners’ perceived usefulness in the e-leaning context 3.2.2 Hypothesis Teaching materials positively affect learners’ perceived usefulness in the e-leaning context Lederer, Maupin, Sena, and Zhuang (2000) demonstrated that ease of understanding and ease of finding various web contents predict ease of use Learners will be more inclined to feel that using the e-learning services is easy if e-learning services are provided with plentiful contents designed to meet their needs In the e-learning context, learner-centered services which provide learners with learning contents accurately and consistently will facilitate perceived ease of e-learning use These lead to the following hypothesis 3.2.3 Hypothesis Design of learning contents positively affects their perceived ease of use in the e-leaning context The fundamental constructs of TAM are perceived usefulness and perceived ease of use Researchers indicate that perceived ease of use affects usage directly and indirectly through perceived usefulness (Venkatesh & Davis, 2000) In the e-learning context, research indicates that ease of use positively affects the system use and perceived usefulness (Pituch & Lee, 2006) Thus, this study hypothesized the following 3.2.4 Hypothesis Learners’ perceived ease of use positively affects their perceived usefulness Previous research suggests that the success of e-learning depend on continued usage (Chiu, Hsu, Sun, Lin, & Sun, 2005) Studies indicated perceived usefulness contribute to the learners’ behavioral intention to use the e-learning system (Liaw, 2008) Perceived ease of use is shown to affect behavioral intention (Ong et al., 2004) However, contrary to previous studies, perceived ease of use was the sole determinant of intention to use, while perceived usefulness did not have significant effect on intention to use (Yuen & Ma, 2008) Thus, this study hypothesized the followings 3.2.5 Hypothesis Learners’ perceived usefulness positively affects their intention to use e-learning 3.2.6 Hypothesis Learners’ perceived ease of use positively affects their intention to use e-learning services Venkatesh and Brown (2001) indicate that hedonic outcomes such as pleasure, enjoyment, playfulness, happiness are intrinsic motivators of system adoption Intrinsic motivation is considered to be a reward Playfulness is a factor that reflects the user’s intrinsic belief in WWW acceptance (Moon & Kim, 2001) Another study also shows that perceived playfulness contributed significantly to the users’ intent to use a web site (Lin, Wu, & Tsai, 2005) Thus, this study hypothesized the following 3.2.7 Hypothesis E-learning’s playfulness positively affects their intention to use e-learning Research methodology 4.1 Instrument construction A questionnaire instrument was developed for this study Individual scale items are listed in Appendix A These scale items were developed based on the existing literature discussed in the previous sections Our research model consists of seven variables: instructor characteristics, teaching materials, design of learning contents, playfulness, perceived usefulness, perceived ease of use, and intention to use elearning We developed multi-item Likert scales which have been widely used in the questionnaire-based perception studies All variables are subjectively measured using the five-point Likert Scale, with being ‘‘Strongly Agree” and being ‘‘Strongly Disagree.” Table shows the above-mentioned operational definition of each variable 4.2 Data collection The survey was conducted in a comprehensive university in South Korea during October of 2007 250 undergraduate students who had attended at least one e-learning class participated in this study through an anonymous survey instrument All of the survey participants Table Variables and operational definitions Variable Operational definition Instructor characteristics Teaching materials Design of learning contents Playfulness Perceived usefulness Perceived ease of use Intention to use e-learning The The The The The The The extent extent extent extent extent extent extent to to to to to to to which which which which which which which instructors are caring, helpful, and accommodating to students teaching materials are suitable for e-leaning learning contents are designed for the consistent and accurate delivery students enjoy e-learning students believe that e-learning will enhance learning outcomes students believe that e-learning will be easy to use students intend to participate in e-learning 1325 B.-C Lee et al / Computers & Education 53 (2009) 1320–1329 majored in one of the five disciplines (accounting, business management, management information systems, taxation, and tourism) offered by the College of Business Administration The courses selected for the study combined both e-learning and traditional face-to-face learning methods The traditional face-to-face learning methods include required attendance, regular textbook, and presence of instructor during the scheduled class time and office hours Both synchronous and asynchronous web-based technologies were used for the e-learning support The asynchronous e-learning support includes online lecture notes, online quizzes, online announcements, online assignments, electronic student–student and student–instructor communication, audio and video streaming, and threaded discussions The synchronous e-learning support includes chat and video conferencing 98% of the survey participants are in the age range of 17–30 years 18% of the survey participants are freshmen, 36% sophomores, 31% juniors, and 15% seniors Of the 250 distributed questionnaires, 22 were not completed validly, and 14 were not returned, resulting in 214 valid responses (a response rate of 85.6%) Table summarizes the demographic profile of the survey participants who returned the valid responses Data analysis 5.1 Model validation SPSS version 12.0 was used to analyze the collected data Given the theory-driven approach to scale development, scale validation was done using exploratory factor analysis and confirmatory factor analysis The factor analysis utilized the principal component extraction method and Varimax rotation It required that factor loadings exceed 0.40 One item (IC5) from Instructor Characteristics, one item (TM3) from Teaching Materials, and two items (LC2, LC3) from Design of Learning Contents were deleted due to a low factor loading While four items were removed from the three factors in the independent variables, no items were deleted from the two belief variables and the dependent variable The high reliability of these variables can be attributed to the fact that numerous previous studies validated the factor items Table summarizes factor loadings, Cronbach’s alpha, Eigenvalues, and variances explained of all indicator variables The results indicated the presence of seven factors with Eigenvalues greater than one This questionnaire used the Cronbach’s a coefficient to test the internal consistency among items of the same construct According to Cuieford (1965), a Cronbach’s a value that is greater than 0.7 indicates high reliability and a Cronbach’s a value that is less than 0.35 represents unacceptable reliability A Cronbach’s a value between 0.35 and 0.7 has fair but acceptable reliability Researchers suggest Cronbach alpha of 0.70 for confirmatory research and 0.60 for exploratory research as acceptable (Fornell & Larcker, 1981; Hair, Anderson, Tatham, & Black, 1998) Thus, all constructs can be considered reliable The reliability values of the constructs are in the range of 0.634–0.903 suggesting acceptable reliability Cumulative variance explained for all the variables are measured to be acceptable: for the independent variables, 60.34%; for the belief variables, 81.65%; and for the dependent variable, 65.56% The factor loading values of all indicator variables are over 0.494, far exceeding 0.30, which, as a rule of thumb, is considered the minimum loading for interpretability (Tabachnick & Fidell, 1996) Table Demographic profile and descriptive statistics of surveyed students Item Frequency % Gender Male Female 129 85 60 40 Age 17–19 20–22 23–25 26–29 30+ 121 58 23 57 27 11 Year in college Freshman Sophomore Junior Senior 39 76 67 32 18 36 31 15 Table Factor analysis and reliability Category Independent variables Factor PL Item Factor loading Eigen value Total variance explained (%) Cumm variance explained (%) Cronbach’s alpha PL1 PL2 PL3 PL4 2.814 20.097 20.097 0.817 Belief variables IC 0.717 0.854 0.693 0.816 IC1 IC2 IC3 IC4 2.159 15.422 35.519 0.675 LC 0.810 0.677 0.648 0.494 LC1 LC4 LC5 LC6 1.973 14.095 49.614 0.661 TM 0.521 0.611 0.662 0.767 TM2 TM3 1.502 10.729 60.342 0.634 PU 0.751 0.847 PU1 PU2 PU3 2.524 50.470 50.470 0.903 Dependent variables PE 0.888 0.892 0.924 PE1 PE2 1.559 31.177 81.647 0.697 IU 0.803 0.907 IU1 IU2 IU3 IU4 2.622 65.562 65.562 0.821 0.770 0.866 0.728 0.866 PL = Playfulness; IC = Instructor characteristics; LC = Design of learning contents; TM = Teaching materials; PU = Perceived usefulness; PE: Perceived ease of use; IU = Intention to use e-learning 1326 B.-C Lee et al / Computers & Education 53 (2009) 1320–1329 Table Test results Relationship between variables Instructor characteristics Teaching materials Design of learning Contents perceived ease of use Perceived usefulness Perceived ease of use Playfulness ? ? ? ? ? ? ? Perceived usefulness Perceived usefulness Perceived ease of use Perceived usefulness Intention to use e-learning Intention to use e-learning Intention to use e-learning B b t-Value P-value 0.704 0.329 0.313 0.519 0.598 0.137 0.569 0.433 0.235 0.287 0.389 0.679 0.117 0.586 7.107 3.858 4.369 6.155 13.366 2.304 10.520 0.000 0.000 0.000 0.000 0.000 0.022 0.000 p < 0.05 p < 0.001 5.2 Hypotheses testing Although structural equation modeling (SEM) has advantages over traditional statistical techniques such as regression, it is recommended that for a model with two to four factors, an investigator plan on collecting at least 100 cases, with 200 being better (Loehlin, 1992) Another rule of thumb, based on Stevens (1996), is to have at least 15 cases per measured variable or indicator Due to the smaller sample size than recommended for SEM, a regression model is used for testing the hypotheses Table summarizes the test results All predictors are significant in explaining the relationships Instructor characteristics (b = 0.433, p < 0.001), teaching materials (b = 0.235, p < 0.001), and perceived ease of use (b = 0.389, p < 0.001) are positively related to perceived usefulness as hypothesized Thus, hypotheses and are supported Design of learning contents (b = 0.287, p < 0.001) is positively related to the perceived ease of use, thus confirming hypothesis Perceived ease of use (b = 0.389, p < 0.001) is positively related to perceived usefulness as hypothesized Thus, hypothesis is supported Perceived usefulness (b = 0.679, p < 0.001) is shown to have positive effect on intention to use e-learning, thus confirming hypothesis Perceived ease of use (b = 0.117, p < 0.05) is related to intention to use e-learning at a significance level of 0.05, offering support for hypothesis However, hypothesis is statistically the weakest among the seven hypotheses Finally, playfulness is shown to have positive effect on intention to use e-learning (b = 0.586, p < 0.001), thus confirming hypothesis Discussions In this empirical study, we analyzed learners’ acceptance of e-learning services from student perspectives in South Korea First, we analyzed the relationships between the three service quality constructs (instructor characteristics, teaching materials, and design of learning contents) and the two belief constructs (perceived usefulness and perceived ease of use) Second, we analyzed the relationships between the belief constructs (perceived usefulness and perceived ease of use) and intention to use e-learning Third, we analyzed flow construct (playfulness) and intention to use e-learning Instructor characteristics and teaching materials are positively related to perceived usefulness Design of learning contents is positively related to the perceived ease of use These results indicate that as the service quality of e-learning improves, the learners tend to be more positive towards e-learning Compared to traditional offline education, the growth opportunities of e-learning abound As web technologies advance, e-learning providers can enhance e-learning services without additional costs by taking advantage of the declining cost of technologies, thus resulting in greater adoption by learners Among the variables under study, perceived usefulness is the greatest predictor of intention to use e-learning The result shows that the easier to use the students feel e-learning is, the more useful they feel e-learning is Perceived usefulness in turn has a positive effect on the intention to use e-learning For learners to continue to use e-learning, e-learning should be designed and developed to deliver value to them The usefulness can be enhanced by providing enhanced e-learning services without increasing the complexity of the e-learning process Finally, playfulness positively affects the intention to use e-learning One of the recent trends in educational services is to improve the educational outcomes by incorporating amusement For example, edutainment typically seeks to instruct its participants by embedding entertainment into lessons Incorporation of playfulness into teaching materials presents the greatest challenge to instructors who not have sufficient computer skills Educational institutions need to provide adequate resources to instructors and need to train them to use a variety of educational tools innovatively A variety of entertainment tools are easily available in the online game industry Periodic survey and assessment of new entertainment tools for educational use seem worth conducting Most of our findings support recent studies in the TAM domain conducted in various countries As indicated by our findings, perceived ease of use was found to be a significant antecedent of perceived usefulness (Imamoglu, 2007; Ong et al., 2004) Perceived usefulness positively affects the intention to use e-learning (Liaw, 2008; Roca & Gagné, 2008; Sánchez-Franco et al., 2009) Design of learning contents was found to affect perceived ease of use (Pituch & Lee, 2006) Teaching materials affect the e-learning effectiveness (Littlejohn, Falconer, & Mcgill, 2008; Zhang et al., 2004) E-learning’s playfulness positively affects learners’ intention to use e-learning (Roca et al., 2006) However, it is noted that the enjoyment of e-learning does not affect the intention to use e-learning among Mediterranean educators, while the enjoyment of e-learning affects the intention to use e-learning among Nordic educators (Sánchez-Franco et al., 2009) Nordic educators live in individualistic and weak uncertainty avoidance societies and Mediterranean educators live in collectivistic and high uncertainty avoidance societies Results of this study indicate that there may be a relationship between learners’ culture and intentions to use e-learning While learner characteristics such as learner computer anxiety and self-efficacy have been investigated in other studies, our study focuses on e-learning service quality constructs to make our model parsimonious We believe that the selected constructs are considered to be critical for the successful development of e-learning Recently, Pituch and Lee (2006) found there is no significant relationship between self-efficacy and usefulness and intention to use e-learning Future research is needed to fully understand the relationships between student characteristics and service quality constructs that improve or undermine learners’ intention to use e-learning B.-C Lee et al / Computers & Education 53 (2009) 1320–1329 1327 Conclusions Because of the time and space barriers, learners in the traditional offline education are required to receive education at a certain time and location On the contrary, the Internet-based e-learning is less restricted in terms of time and space In addition, e-learning is known to save educational costs and facilitate dissemination of knowledge in a timely fashion As e-learning is increasingly adopted by educational institutions and corporations, e-learning success factors need to be evaluated and taken into consideration in the development of the elearning systems to deliver the most effective services South Korea’s dense student population and high educational standards make investments in e-learning very cost-effective Despite the fact that South Korea is one of the fastest growing countries in e-learning, e-learning literature from South Korean perspectives are relatively small In the globalized educational environment, understanding and investigating the country specific e-learning phenomena are of great importance By investigating critical factors on e-learning adoption in South Korea, our study attempts to fill a gap in the individual country-level e-learning research Our survey results confirm the seven hypotheses Our findings indicate that instructor characteristics and teaching materials are the predictors of the perceived usefulness of e-learning, and perceived usefulness and playfulness are the predictors of the intention to use e-learning While statistically significant, perceived ease of use was shown to have the weakest effect on the intention to use e-learning among the three predictors All these results are very consistent with the previous studies conducted in other countries, proving the universal nature of the learners’ perceptions and behavior towards e-learning As is typical in many empirical studies, this study is not without limitations First, while we limited e-learning service quality to three factors (instructor characteristics, teaching materials, and design of learning contents), additional service factors such as systems quality, security, and responsiveness exist These additional service factors may influence the belief and dependent variables Therefore, future research needs to include such factors to build a comprehensive model while maintaining the conciseness of the model Second, this study focused on the higher education institutions and did not reflect on the perceptions of employees on the e-learning in business settings Future research needs to address the perceptions of students and corporate employees and analyze perception differences between them Lastly, as the world gets more globalized, understanding cross-cultural issues in e-learning will draw more attention from researchers, education institutions, and business organizations While our study is limited to e-learning in South Korea, cross-cultural e-learning studies may shed valuable new insights into this ever-growing area Appendix A Instrument: All items were measured on a five-point Likert scale Constructs Items Measures Instructor characteristics IC1 IC2 IC3 IC4 IC5a TM1 TM2 TM3a LC1 LC2a LC3a LC4 LC5 LC6 P1 P2 P3 P4 PU1 PU2 PU3 PE1 PE2 IU1 IU2 IU3 IU4 The instructor provides high-quality instruction The instructor provides information on learning progress The instructor delivers instructions clearly The instructor’s measurement of student performance is fair The instructor motivates me to use e-learning E-learning provides me with sufficient teaching materials E-learning provides me with teaching materials that fit with the learning objectives E-learning provides me with teaching materials that are easy to use The level of difficulty of the learning contents is appropriate The content of assignments is easy to understand The amount of learning contents is appropriate The delivery schedule of learning contents is flexible E-learning provides individualized learning management E-learning provides a variety of learning methods I feel e-learning helps me improve my creativity I feel e-learning helps me improve my imagination by obtaining information I feel I can have a variety of experiences without any interference I feel e-learning is fun regardless of usage purposes E-learning improves my learning outcomes E-learning is very useful to me E-learning helps me accomplish my learning effectively E-learning study methods are easy to understand E-learning is easy to use I 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