doi:10.1016/j.compedu.2006.03.005 ARTICLE IN PRESS Computers & Education xxx (2006) xxx–xxx www.elsevier.com/locate/compedu Typology of teacher perception toward distance education issues – A study of college information department teachers in Taiwan q Yu-Hui Tao a,*, Chu-Chen Rosa Yeh b a Department of Information Management, National University of Kaohsiung, 700 Kaohsiung University Road, Kaohsiung 811, Taiwan, ROC b Institute of Human Resource Management, National Sun Yat-Sen University, Kaohsiung, Taiwan, ROC Received 31 August 2005; received in revised form 21 February 2006; accepted 26 March 2006 Abstract The popularity of distance education has grown rapidly over the last decade in Taiwan’s higher education, yet many fundamental teaching–learning issues are still in debate. While teacher–student interaction is a key success factor in dis- tance education, little work has been done on the teachers. The intent of this research was to clarify teacher’s perceptions on key distance education issues and to develop a discernible typology of different groups of teachers based on their per- ceptions. Because there may be a gulf between teachers and the technology used in distance education, the target of this study was teachers in information related departments in Taiwan’s colleges, who were more familiar with current technol- ogy. Factor analysis and cluster analysis were used to derive the typology. Five higher-level issue constructs emerged from the factor analysis: learning effect, customization, administrative challenges, geographic and resource integration, and instructional design challenges. Four groups of teachers, namely the skeptics, the optimists, the mild-promising group, and the outlier, were identified using cluster analysis of teachers’ perceptions on these five higher-level issue constructs. The profiles of the four groups of teachers were summarized and implications were discussed, which should provide useful insights to the policy makers of higher education on distance education decisions. � 2006 Elsevier Ltd. All rights reserved. Keywords: Distance education; Teacher’s perception; Factor analysis; Cluster analysis 1. Introduction Prompted by the radical changes in telecommunication technology of the last 30 years, distance education has gone through several evolutionary transformations, from text correspondence to programmed instruction with audio/visual aids such as tapes, radio, broadcasting or satellite television, and personal computers, to the 0360-1315/$ - see front matter � 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.compedu.2006.03.005 q A previous version of this paper was presented at the 7th International Conference of Decision Sciences Institute, Shanghai, China, July 4–8, 2003. * Corresponding author. Tel.: +886 7 5919220; fax: +886 7 5919328. E-mail addresses: ytao@nuk.edu.tw (Y.-H. Tao), cc.rosayeh@msa.hinet.net (C.-C. Rosa Yeh). mailto:ytao@nuk.edu.tw mailto:cc.rosayeh@msa.hinet.net 2 Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx ARTICLE IN PRESS flourishing development of e-learning on the Internet (Simonson, Sweeney, & Kemis, 1993). Today, the Inter- net and the World-Wide-Web have become the predominant media for distance education, especially in the well-developed countries that offer degrees at bachelor’s, master’s and doctorate levels. (http://www.degree.- net). Despite the debate over the quality of Web-based education (Institute for Higher Education Policy, 1999), more and more higher level education institutions offer credit and non-credit courses via the internet because of increasing educational costs, lifestyle choices by many adult learners, and strong competitive pres- sures (Arenson, 1998; Mcgorry, 2003). With the gaining popularity of e-learning in distance education, many issues remain for practical implemen- tation. The biggest concern has been the question of whether distance education produces the same or even better learning outcomes than the traditional methods (LaBay & Comm, 2003; Miller, 2001; Russell, 1999). Although some studies did show equivalent performance (Dellana, Collins, & West, 2000; LaBay & Comm, 2003; Mehlenbacher, Miller, Covington, & Larsen, 2000), they also implied that online learning was not for everyone. For instance, Mehlenbacher et al. (2000) pointed out that reflective and global learners performed significantly better online than active and sequential learners. Mixed student satisfaction toward the distance education has also been an issue in addition to class performance (Stewart, Waight, Norwood, & Ezell, 2004; Vamosi, Pierce, & Slotkin, 2004). More critically, Frankola (2000) indicated that between 20% and 50% dis- tance learners dropped out of the online classes due to the following seven reasons: students’ lack of time, lack of management oversight, lack of motivation, problems with the technology, lack of student support, individ- ual learning preferences, poorly designed course, and substandard/inexperienced instructors. The issue of high student-dropout rates was highlighted by Xenosa, Pierrakeas, and Pintelas (2002) and Moody (2004) as a glo- bal concern. Teachers played an important role in the success of distance education (Gibson, Tesone, Hodgetts, & Blackwell, 2001; Lin, Young, Chan, & Chen, 2005; Wiesner, 2000), especially those in higher education (Croy, 1998; Haas & Senjo, 2004). Addressing the question raised by Shoemaker (1998) on the leadership of distance education in higher education, Irlbeck and Pucel (2000) identified five common elements requiring leadership, including quality of education, planning, implementation, resources, and support. Teachers and government policies have significant influences on all these five elements. Berge, Muilenburg, and Haneghan (2002) also suggested that teacher issues were the highest ranking barriers to a successful distance education program. Teachers have been reported to have problems with distance education because of the extra work on class- room material conversion (Lee, 2002), difficulty to gauge student learning (Motiwalla & Tello, 2000), and the lack of teacher–student interaction (Arbaugh, 2005; Ausserhofer, 1999; Gibson et al., 2001; Wiesner, 2000). However, as can be seen in the abundant literature on the effect of distance education, the majority of data were drawn from the learners’ perspective instead of the teachers’ (Carr, 2000; Everetts, 1998; Gibson et al., 2001; Hailey, Keith, & Hult, 2001). Although some teachers’ viewpoints could be found in these liter- atures, since the authors were also teachers, we found very little full-scale empirical research done to collect the teacher’s side of the story. Existing literatures on this respect were limited to small-scale qualitative studies (see Broady-Ortmann, 2002; Haas & Senjo, 2004; Lao & Gonzales, 2005) or studies toward a certain artifact (such as Woods, Baker, & Hopper, 2004). Croy (1998) once pointed out that ‘‘it is faculty who bear primary responsibility for the impact of distance technology in higher education, and there is currently a wide gulf between faculty attitude and this technology’’. Blignaut and Trollip (2003) were aware of this lack of teacher studies and had developed a tax- onomy of faculty participation in synchronous learning environments. Howell, Saba, Lindsay, and Williams (2004) presented seven strategies for university administrators and faculty for deploying their own strategic plan to ensure program success. These strategies included: (1) enabling colleges and departments to accept more responsibility for distance education activities; (2) providing faculty more information about the dis- tance education programs and activities; (3) encouraging faculty to incorporate technology into their tradi- tional classrooms; (4) providing strong incentives for faculty to participate in distance education; (5) improving training and instructional support for distance education faculty; (6) building a stronger distance education faculty community; and (7) encouraging more distance education scholarship and research. Unfortunately, these seven strategies were merely general descriptions, and did not offer specific links to applicable groups of teachers with different motivations, perceptions or experiences. There was still a void in the understanding and description of teachers in terms of their overall attitude toward distance education. http://www.degree.net http://www.degree.net Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx 3 ARTICLE IN PRESS We believe this kind of information is important for school leaders in their strategic decision to effectively invest in distance education (Shea, Motiwalla, & Lewis, 2001), to minimize teacher resistance, and to encour- age innovation (Irlbeck & Pucel, 2000). Therefore, the intent of this research was to clarify teacher’s percep- tions on key distance education issues and to develop a discernible typology of different teacher groups based on their perceptions. To reduce possible ‘‘noises’’ caused by unfamiliarity with the technology on the teachers’ part, the target of our study was limited to teachers in information related departments in Taiwan’s higher education institutes. Taiwan’s distance education is briefly introduced below before presenting the research methodology for this study. 2. Distance education in Taiwan Distance education programs could date back to the 19th century. Since then, pioneers in UK and USA have continued to re-invent new generations of distance education (Williams & Nicholas, 2005), and have offered to the world online bachelor’s, master’s and doctorate degrees. These well-developed countries set good examples for developing countries such as Taiwan to follow. To set the stage for this study, the infor- mation and communication technologies (ICT) infrastructure and needs of Taiwan’s distance education were described in this section along with outstanding issues. Taiwan’s government began its own National Information Infrastructure (NII) project in June 1994 after the US government initiated its NII project in 1993 (Chen, 2003). As of February 2005, it was estimated that over 13.8 millions of people go online in Taiwan, which was about 60% of the Taiwan’s 23-million population. In addition, 54% of Taiwan’s households used broadband to access the Internet. In World Economic Forum’s global information technology 2004–2005 report, Taiwan was ranked 15th in the world in terms of network readiness (Schwab, 2005). Because of the high percentage of Internet population, applications such as elec- tronic commerce (EC) and e-government services were popular and common practices in Taiwan (Taiwan Network Information Center, 2005). Taiwan’s e-government was ranked first by Brown University (West, 2005) and 7th by Waseda University (Waseda University of e-Government, 2006). On the EC side, Taiwan’s ability to support and promote digital business and ICT services was ranked 22nd among 65 major economics countries in the 2005 white paper published by Economist Intelligent Unit (2005). These data showed that Taiwan’s ICT infrastructure was very competitive in the world, and should have been more than adequate for distance education. The need for distance education in Taiwan could be seen from its development in three phases. In 1986, National Open University (NOU, http://www.nou.edu.tw), the first higher education institute in Taiwan to offer distance education and continuing education to adults, was established. NOU originally delivered multi- media learning contents via television and radio broadcasting, and started its internet-based classes in 2002. In September 1994, the NII team coordinated the Ministry of Education (MOE) to build an experimental high speed network platform for testing real-time multicast, virtual classroom and curriculum on demand systems in five Taiwan’s national universities. In 1996, real-time multicast distance education was commonly operating in Taiwan’s higher education institutes (Chen, 2003). In 1998, many Taiwan’s universities began to develop Internet-based distance education programs founded on the successful MOE project. Examples of large-scale implementations could be found in National Sun Yat-sen Cyber University (http://cu.nsysu.edu.tw/) and National Taiwan University Online Courses (http://nol.ntu.edu.tw/guest/). In terms of degrees via distance education, NOU has been the only channel offering bachelor degrees and is currently experimenting with the master’s degrees. Since the establishment of NOU, 280 thousand adult stu- dents had participated in NOU programs, however, only 25,000 of them had earned their bachelor degrees. In terms of real-time multicasting, it mainly offered credits for general elective courses across universities. At the same time, online programs provided by individual universities were mainly for non-degree programs or courses-for-credit programs toward a future degree. The MOE in Taiwan had heavily regulated these devel- opments from the start. Taiwan had over 150 higher education institutes to serve the population of 23 mil- lions. The fact that only NOU offered degrees via distance education did not meet the demands of adult learners in Taiwan on distance education. Facing the pressure of the World Trade Organization (WTO) to open Taiwan’s education market, MOE has gradually loosened its tight grip on Taiwan’s higher education in order to achieve global competitiveness. http://www.nou.edu.tw http://cu.nsysu.edu.tw/ http://nol.ntu.edu.tw/guest/ 4 Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx ARTICLE IN PRESS The old regulation by MOE set a limit on the number of credits earned through distance education toward a degree in Taiwan’s higher education institutes; only up to one third of the total graduation requirement were admitted for degree programs (Ministry of Education, 2001). Because of this limitation, many university lead- ers in Taiwan were constrained in their investment and promotion in distance education and thus fell behind their main Asian competitors such as China and South Korea. Recently, MOE has announced a loosening of this regulation from one third of total credits to one half, and to lift the limitation altogether on continuing education programs for K1–K12 teachers, management, and other domains related to Taiwan’s industrial development (Ministry of Education, 2005). This presents a great opportunity as well as challenges for Taiwan’s distance education. Taiwan has a special competitive advantage in language in the greater Chinese-speaking market. Although some well-developed countries such as the US and the UK are expanding their distance education markets to Asia where education value is emphasized traditionally, Taiwan has not seen a great impact thanks to the MOE regulation and the inadequate English proficiency level of local students. The poor English proficiency level had prevented the majority of Taiwanese students from taking imported distance education programs or courses delivered in English. This, however, presents a great opportunity to Taiwan’s distance education pro- viders. They are in the position to fulfill local market demands and potentially the demands of the greater Chinese-speaking communities around the world in distance education. Taiwan’s ICT infrastructure is very competitive in the world, and its ICT services in e-government and EC are prosperous. However, the preparation of higher education institutes for distance education is not quite ready due to a long history of constraining policy by the MOE. With the regulations relaxing, school leaders in higher education institutes are no longer constrained by uncontrollable policy impacts on their leadership (Irlbeck & Pucel, 2000). Consequently, faculty issue becomes the next critical theme in the leadership elements for distance education leaders (Irlbeck & Pucel, 2000). After two decades of lukewarm development and hap- hazard implementation, it is especially important to understand the mindset of these faculties who stand at the front line of the battle to compete on distance education. 3. Methodology Because there was no existing typology of teachers in the distance education literature which had presented very diverse views through the development of distance education, this study took an exploratory approach to generate a typology of teachers on various distance education issues. This was done by designing a survey of current distance education issues to collect data from target teachers, and using statistical tools of factor anal- ysis and cluster analysis to categorize responding teachers on a set of issue dimensions derived from the data. The methodology is described in full detail below. An extensive literature review, which included major research papers or reports from 1997 to 2003, was conducted to uncover issues related to distance education. As a result, two basic issue categories emerged from the review. The first was the concerns of the learning effect produced by distance education, such as its ability to facilitate teaching performance and learning outcome, characteristics which enable customization and indi- vidualization of learning, and its ability to integrate learning resources and environment. The second category was the concerns related to the implementation and school administration of distance education, such as its cost to implement, its ability to affect the competitive situation in the higher education market, and its ability to integrate structure within and among schools. From the literature discussed above, a 30-item questionnaire was generated to collect teachers’ perceptions of various distance education issues as shown in Table 1. Only those unique and important issues with at least two references were adopted as questionnaire items. These questions were measured with a seven-point Likert type scale ranging from 1 (extremely disagree) to 7 (extremely agree). Demographic data of teachers such as education background, training, type of affiliation, age, gender were collected through the same questionnaire, as well as their willingness to accept and to use distance education as an instructional alternative. The ques- tionnaire was pre-tested with four teachers, and was modified according to their feedback. The initial Cron- bach’s a was 0.965 for the 30-item perception survey, which demonstrates a high reliability. The final version of the questionnaire takes about fifteen minutes to complete. Table 1 Questionnaire items and references No. Question description References 1 Distance education is important in crossing over the restraint of geography Owston (1997), Gladieux (2000), Raab et al. (2001) 2 Schools are compelled into distance education due to the educational tendency and learners’ needs Harris (1999), Chassie (2002), Pahl (2003) 3 Distance education makes it easier for schools and teachers in providing learners a personalized learning environment Tien (2000), Wallace and Wallace (2001), Tsai and Tseng (2002) 4 Distance education raises the competitive capacity of the school Jain (1997), Jonhendro et al. (2002) 5 Distance education effectively integrates teaching resources Harun (2001), Geueke and Stausberg (2003) 6 Distance education effectively matches the choices between the schools and the learners Hillesheim (1998), Ubell (2000) 7 Distance education increases the flexibility of schools in making teaching strategies Hillesheim (1998), Welle-Strand and Thung (2003) 8 Distance education produces better learning results than traditional teaching Latchman et al. (1999), Louvieris and Lockwood (2002), Welle-Strand and Tjeldvoll (2002) 9 Distance education provides basic teaching as well as the fun of learning Pison (1997), Jonhendro et al. (2002) 10 Distance education boosts learners’ learning interests Jonhendro et al. (2002), Khalifa and Lam (2002) 11 Distance education rapidly delivers knowledge and information to learners Vaupel and Sommer (1997), Chassie (2002) 12 Distance education lowers learning opportunity cost in the learning Pison (1997), Raab et al. (2001), Ubell (2000) 13 The rise of distance education gradually replaces traditional teaching Owston (1997), Hartnett (1999), Carver et al. (1999) 14 Distance education accelerates the imitation between schools Jerman-Blazic (2000), Thiriet et al. (2002), Raab et al. (2001) 15 Distance education changes the current competition terms of education market Hillesheim (1998), Raab et al. (2001), Welle-Strand and Thung (2003) 16 Distance education promotes the school’s service-oriented culture Hillesheim (1998), Boone and Ganeshan (2001) 17 Distance education tailors for the learner and offers the requested content as well as the information Latchman et al. (1999), Unruh (2000) 18 The value of distance education lies in its capability to integrate technology into teachings Starr (1998), Peterson (2001) 19 Distance education develops mutual understanding between teachers and learners Starr (1998), Jonhendro et al. (2002), Liber et al. (2000) 20 Distance education boosts the teacher’s teaching performance Raab et al. (2001), Blignaut and Trollip (2003) 21 Distance education helps to understand learners’ individual preferences Tan and Teo (1998), Kabassi and Virvou (2004) 22 Distance education helps lower regional competition of schools by extending into global market Hailey et al. (2001), Jonhendro et al. (2002), Raab et al. (2001) 23 Distance education promotes information exchange between schools Scollin and Tello (1999), Raab et al. (2001), Thiriet et al. (2002) 24 Distance education fails to protect intellectual property rights of the knowledge Ubell (2000), Kennedy (2002), Syed (2001) 25 Distance education presents a time-consuming issue in preparing teaching material Croy (1998), Peterson (2001), Pahl (2003) 26 Distance education demands flexible learning contents Syed (2001), Kabassi and Virvou (2004) 27 Distance education environment construction is not easy Fosay (1998), Rogers (2000), Konstantopoulos et al. (2001) 28 Distance education is difficult to mimic face-to-face teaching Latchman et al. (1999), Carr (2000), Shapiro et al. (2002) 29 Distance education presents a difficulty in supervising the class condition Odin (1997), Hazari and Schnorr (1999), Syed (2001) 30 Distance education is a long-term investment strategy Ubell (2000), Raab et al. (2001), Carr (2001) Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx 5 ARTICLE IN PRESS 6 Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx ARTICLE IN PRESS Because of the educational infrastructure in Taiwan, college teachers who were affiliated with information related departments had more opportunities to experience learning technologies and possessed a better under- standing of the impacts of technology on the learning environment. They were also most likely to lead or par- ticipate in distance education projects in their schools. We had selected them as the target population of this investigation. The questionnaires were sent to a random sample of 400 teachers in the information manage- ment or information technology department of 150 universities, institutes of technology and junior colleges listed in the MOE in Taiwan. Segmentation of teachers’ perception of distance education issues was achieved through factor analysis and cluster analysis (Hair, Anderson, Tatham, & Black, 1998). Factor analysis was used to dissect teachers’ overall perception into a few revealing dimensions by extracting the underlying factors from the question items. These dimensions (factors) represented a higher-level construct of teachers’ perception on distance education issues. Factor analysis produced a factor score for each case on each dimension. These standardized scores now rep- resented teachers’ perceptions on the higher-level constructs. Cluster analysis was then performed using these factor scores as clustering variables. Segmentation was then determined using the most appropriate clustering results. 4. Findings The findings are briefly described in the order of teacher profile, factor analysis, and cluster analysis below. 4.1. Teacher profile A total of 80 teachers responded to the survey. After discarding 3 incomplete ones, 77 questionnaires were entered into our analysis, yielding a final response rate of 19.25%. Technically speaking, the case to variable ratio of 3.57:1 (77 cases versus 30 variables) in our study fell below the recommended general rule of thumb of at least 5:1 for an adequate factor analysis as suggested in Hair et al. (1998). However, 3.57:1 was higher than the 2:1 ratio suggested by Cattell (1988), and the 1:1 ratio suggested by Baggaley (1982). Roberts, Gibson, Rainer, and Fields (2001) also supported Cattell’s and Baggaley’s claims with evidences of existing references such as Abdul-Gader and Kozar (1995) and Essex et al. (1998). The descriptive statistics of teacher profile were summarized in Table 2. Briefly speaking, the majority of responding teachers were male, between the age of 31 and 45, and holding a Ph.D. degree. Over 62% of them were trained in information related fields but without formal training in educational methods. More than 75% of teachers served in private universities or colleges while nearly 25% served in public universities or colleges. Eighty percent of respondents said that they accepted the notion of using distance education, while a little more than 85% said that they were willing to try distance education as an alternative teaching method. In gen- eral, characteristics of respondents in terms of gender, age, education level, educational method training, and school affiliation met the overall image of the target teachers in Taiwan with a higher percentage of Ph.D. holding males in their 30s and 40s. From both the technical and analytical view, the representativeness of the respondents was considered ade- quate. However, caution is advised in generalizing the results of this study to all teachers in higher education institutes because the sample was limited to information-related faculty. 4.2. Factor analysis Kaiser–Meyer–Olkin (KMO) test for sampling adequacy and Bartlett’s test for sphericity were used to first examine the suitability of selected variables for the factor analysis (Bryman, 1989). As seen in Table 3, KMO test resulted in a 0.873 value that was greater than the suggested minimum value of 0.5 for adequacy, and Bart- lett’s test also demonstrated a very good sphericity (v2 = 1637.91, df = 437, p < 0.000). These tests indicated that the 30 variables were suitable for the following factor analysis. Factor analysis was used to extract the principal components of teachers’ perception on the 30 distance education issues. Only those extracted factors with eigenvalues bigger than one were selected. In the end, a total of five factors emerged which together explained 69.78% of the total variance. Varimax with Kaiser Table 3 KMO and Bartlett’s test for factor analysis Kaiser–Meyer–Olkin measure of sampling adequacy 0.873a Bartlett’s test of sphericity Approx. v2 1637.91 df 437 p-Value 0.000b a >0.5 minimum suggested value. b Level of significance. Table 2 Teacher’s profile Gender: (n = 77) Male 56 (72.7%) Female 21 (27.3%) Age: (n = 77) 625 2 (2.6%) 26–30 12 (15.6%) 31–35 16 (20.8%) 36–40 23 (29.9%) 41–45 18 (23.4%) >45 5 (7.7%) Course training in education: (n = 75) Normal college or university 8 (10.7%) Credits from education courses 5 (6.7%) None 62 (82.6%) Willing to try distance education: (n = 77) Yes 66 (85.7%) No 11 (14.3%) Degree: (n = 77) Ph.D. 53 (68.8%) Master 23 (29.9%) College 1 (1.3%) Major: (n = 77) Information 48 (62.3%) Information related 21 (27.3%) Non-information 8 (10.4%) School affiliation: (n = 77) Private 58 (75.3%) Public 19 (24.7%) Accept the concept of distance education: (n = 77) Yes 62 (80.5%) No 15 (19.5%) Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx 7 ARTICLE IN PRESS Normalization was applied to ensure the extracted factors were distinct from each other. Question items 2, 4, 6, 12, 14, and 18 were dropped from the analysis due to their low factor loadings on every extracted factor. Table 4 shows the result of the factor analysis. Each factor was named to reflect a common higher level con- struct of those questions that loaded on the same factor. Factor one included 9 question items with regard to issues of learning effect, which resulted in a high Cronbach’s alpha of 0.9359. Four question items in relation to the customization issues made up the second factor, with a Cronbach’s alpha of 0.8177. The third factor included 5 question items concerning administrative challenges of distance education, with a Cronbach’s alpha of 0.7762. Three questions with respect to the ability of geographic and resource integration constituted the Table 4 Factor analysis results Factor Question number Cronbach’s alpha 1 Learning effect 13, 9, 20, 19, 16, 8, 10, 11, 21 0.9359 2 Customization 26, 27, 17, 22 0.8177 3 Administrative challenges 25, 24, 29, 15, 30 0.7762 4 Geographic and resource integration 1, 3, 5 0.7783 5 Instructional design challenges 28, 23, 7 0.7269 Overall 0.9467 8 Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx ARTICLE IN PRESS fourth factor, with a Cronbach’s alpha of 0.7783. The fifth factor had a Cronbach’s alpha of 0.7269 and was composed of three question items regarding instructional design challenges. Cronbach’s alpha of the overall 24-item questionnaire remained high at 0.9467. 4.3. Cluster analysis K-mean cluster algorithm was then applied to obtain four distinct segments for teachers, which were fur- ther named according to the final cluster center position on each of the five factors identified earlier (see Table 5). As seen in Fig. 1, the four segments for teachers were: (1) cluster one: the skeptics, (2) cluster two: the opti- mists, (3) cluster three: the mild-promising group, and (4) cluster four: the outlier. (1) The skeptics: Teachers in this cluster were not convinced of the learning effect of distance education. Although they did not swing one way or the other on the issues of customization and administrative challenges, they did appear to be a little unsure about the ability of using distance education to integrate Table 5 Final cluster centers Cluster 1 2 3 4 Learning effect �1.34699 0.55038 0.49910 �1.26603 Customization �0.05939 �1.20376 0.08656 2.79220 Administrative challenges 0.06095 �1.97469 0.20506 �1.80373 Geographic and resource integration �0.21837 1.16464 �0.05957 1.58256 Instructional design challenges 0.31234 �0.06815 �0.02309 �4.72857 -6 -5 -4 -3 -2 -1 0 1 2 3 4 Le ar ni ng ef fe ct Cu sto m iz at io n A dm in . c ha lle ng es In te gr at io n D es ig n ch al le ng es Cluster variables F in al c lu st er c en te rs Skeptics Optimists Mild-promising Outlier Fig. 1. Segmentation of teachers’ perception on distance education issues. Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx 9 ARTICLE IN PRESS learning resources or to break geographic boundaries. They were also aware of the instructional design challenges brought forward by using distance education. Twenty teachers or 26% of total respondents belonged to this segment. They evenly spread across all age groups and between public and private schools. Among them, 80% were male, 50% held a Ph.D. degree and 80% majored in information. How- ever, a great majority (90%) of them had not received any course training in education at all. Although 70% of teachers in this group were willing to try distance education, only 55% of them accepted the concept. (2) The optimists: Though a smaller group, these teachers were stronger believers and supporters of distance education. They disagreed with customization and administration challenges issues, and were impressed with the geographic and resource integration ability of distance education. They were positive on dis- tance education’s learning effect, and did not think much about the instructional design challenges. Five teachers were in this group representing 6% of total respondents. They belonged to the higher age groups of above 36–40, and were affiliated with private schools. Among them, 60% were male. Interestingly, only 20% of them held a Ph.D. degree, and 50% of them had obtained course training in education. In terms of their major, 40% of them were in information and another 40% in information related fields. All teachers in this group accepted the concept and were willing to try distance education. (3) The mild-promising group: This group reflected the majority perception. They mildly agreed with the learning effect of distance education, but did not hold strong opinions on all the other issue dimensions. There were 51 teachers in the segment, representing 66% of the respondents. They fell between the age groups of 31–45, and were affiliated with private schools. Among them, 71% were male, 78% held Ph.D. degrees, but 82% had had no course training in education. Only 10% of teachers in this group did not major in information or related fields. A high 88% of teachers accepted the concept of distance education and a higher 90% were willing to try it. (4) The outlier: There was one teacher who held extremely strong opinions on all issue dimensions and could not be grouped with any other teachers. So this respondent was classified as an outlier. 5. Discussions and implications Three themes worthy of further discussion emerged from our analysis of teachers’ perceptions on distance education issues in Taiwan. The first is a lack of competitive awareness on the teachers’ part regarding the distance education environment. Second, the data showed a high percentage of teachers holding promising views on the development of distance education in Taiwan. Finally, the study revealed a substantial percentage of skeptic teachers whom should not be ignored in the decision and implementation of successful distance edu- cation programs. Discussions and implications were provided below for each theme. 5.1. A lack of competitive awareness The result of the factor analysis produced five higher-level constructs of distance education issues similar to our initial conceptualization from the literature review. The foremost concerns that teachers had in their mind were the ability of distance education to influence learning and teaching outcomes, since that was the most important part of a teacher’s role. Though separated from the learning effect factor, issues of customization and instructional design challenges ultimately led to the quality of distance education, and were indeed two very distinct constructs compared to traditional education. Other factors such as administrative challenges and geographic and resource integration were within our conceptual expectation on the implementation and school administration side. The only surprise was the issues regarding distance education’s ability to affect the competitive situation in the higher education market, which did not converge under the data structure of the responses from this sample. It was possible that teachers just did not care enough about these competitive issues since they were not at the position to make school competitive decisions. This surprise might have been the result of the previous experience of a constrained distance education development under the MOE regulations which had impeded school leaders in Taiwan to clearly see its future and to effectively implement strategies. Under the regulations, many of the investments or actions by school 10 Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx ARTICLE IN PRESS leaders were regarded as unrealistic and were resented by many teachers. With the recent MOE deregulation, school leaders can now better envision the role of distance education in their institutes for adoption decisions and implementation strategies. Very soon, schools will be forced to build appropriate ability of distance edu- cation to promote their competitive position in higher education market, and to consider proper evaluation of the returns or the critical success factors of distance education. We believe that teachers’ lack of awareness on the competitive issues will improve in the near future. 5.2. A high percentage of promising teachers Except for a small group of optimists, it appeared that most teachers were wary of the major issues regard- ing distance education and were unsure how these issues might play out in the future. The largest segment of teachers took a neutral position on all issue dimensions except for the learning effect dimension to which they expressed mild support. Teachers in this group would be the easiest to convert to proponents of distance edu- cation since they had not formed strong opinions one way or the other. The combined percentage of the promising group and the optimists group reached 72% of total respon- dents, which implied that the school leaders had a good chance to rally enough support from teachers once implementation and promotion of distance education started. We believe that the high percentage of promis- ing group was the result of a positive influence from previous experiences of distance education pioneers in countries such as the US and the UK. For these groups who believed in learning effect, we suggest school lead- ers to consider the following strategies offered by Howell et al. (2004) to further enhance their support for dis- tance education: (1) enabling colleges and departments to accept more responsibility for distance education activities, (2) encouraging faculty to incorporate technology into their traditional classrooms, (3) building a stronger distance education faculty community, and (4) encouraging more distance education scholarship and research. 5.3. A substantial percentage of skeptic teachers The fact that more than a quarter of the respondents were skeptics was alarming. These teachers were not sure of the customization and administration challenges brought forth by implementing distance education, nor did they care much about distance education’s ability to integrate resources. Moreover, they questioned distance education’s ability to produce quality education and learning outcomes. School policy makers should be aware that it might take a lot of effort to motivate the skeptics of distance education. More conclusive and positive evidence of the learning effect from distance education was required to win this group over. It was also possible that this group of teachers lacked appropriate training in the design and use of distance education, or that they simply did not acquire any positive experience from participating in a distance education project. Two possible remedies for the skeptics are offered below. 5.3.1. Increasing the percentage of teachers with course training in education Comparing teacher profile items, ‘‘course training in education’’ seemed to mark the most significant dif- ferences between the skeptics, the mild-promising, and the optimists. In our sample, there were only 10% of the skeptics and less than 20% of the mild-promising teachers who had acquired course training in education, while over 50% of the teachers in the optimists group had done so. Unlike K1–K12 teachers in Taiwan, teach- ers in higher education institutes were allowed to teach without basic training in education-related subjects. We believe enhancing teachers’ knowledge and experience in educational theories and practices could be an effective way to influence their attitude toward distance education. Accordingly, increasing the percentage of teachers with course training in education by offering more distance education related courses to teachers and encouraging teachers to take courses in teaching and education might be a direction for school adminis- tration to focus on. 5.3.2. Building dedicated support for teachers lacking experience or knowledge in distance education Teaching resources centers were established in many of Taiwan’s higher education institutes, and were especially emphasized by schools with successful distance education programs. Teaching resources centers Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx 11 ARTICLE IN PRESS in many schools played important roles in providing training courses or activities to promote distance edu- cation. As a solution for the skeptics, schools might also dedicate teaching resources centers to the support for teachers lacking distance education experience or related resources. This could be done by providing individual consultation to teachers and encouraging participation in new distance education projects. Howell et al. (2004) offered similar strategies which were applicable in converting the skeptics. These included (1) providing faculty more information about the distance education programs and activities, (2) pro- viding strong incentives for faculty to participate in distance education, and (3) improving training and instructional support for distance education faculty. The taxonomy of faculty participation in synchronous learning environments developed by Blignaut and Trollip (2003) can also be a useful resource for school policy makers. We had little to learn from the one teacher in the outlier group, except that there is bound to be outliers in every issue. The implication of this outlier group is that policy makers better prepare themselves for noises in the process of all decision-making. 6. Conclusion The above discussion and implications should be referenced in light of some limitations of this study. The first research limitation was the case-to-variables ratio of 3.57:1, which was lower than the 5:1 general rule of thumb, although we had found evidences that claimed lower ratios to be acceptable (see Baggaley, 1982; Cat- tell, 1988; Roberts et al., 2001). The second limitation was the generalizability of this study which was limited to Information-related teachers. Because Information-related teachers had historically been one of the key driving forces behind distance education in Taiwan, the results might have represented a more favored view toward distance education among all teachers. In other words, it may take school leaders of higher education institutes additional efforts and time than what the results of this study might have indicated to successfully bring all the teachers on board on the issues of distance education. Due to the recent de-regulation by Taiwan’s MOE, Taiwan’s higher education institutes are facing a new challenge on distance education strategies. A clear understanding of the composition of teachers in these per- ception groups is important for schools’ policy makers to form better directions and decisions when imple- menting distance education. Researchers and developers of distance education technology should also be aware of these different groupings of users. Additional studies are recommended to extend the research on teachers’ perceptions to their overall attitude (e.g., willingness to use distance education), their need for edu- cational technology, technical assistance and training support, and a comparison with students’ perceptions on these issues. Acknowledgements The authors thank the anonymous referees for their valuable suggestions in completing this paper, and Mr. Chung-Cher Wu for his assistance in collecting the data. This research project was partially sponsored by National Science Council of the Republic of China with Grant No. NSC 89-2416-H-214-011. References Abdul-Gader, A. H., & Kozar, K. A. (1995). The impact of computer alienation on information technology investment decisions: an exploratory cross-national analysis. Management Information Systems Quarterly, 1(4), 535–559. Arbaugh, J. B. (2005). Is there an optimal design for on-line MBA courses?. Academy of Management Learning and Education 4(2), 135–149. Arenson, K. (1998). Virtual classroom vs. physical classroom: an exploratory study of class discussion patterns and student learning in an asynchronous internet-based MBA course. Journal of Management Education, 24(2), 213–223. Ausserhofer, A. (1999). Web-based teaching and learning: a panacea? IEEE Communications Magazine(March), 92–96. Baggaley, A. R. (1982). Deciding on the ratio of the number of subjects to the number of variables in factor analysis. Multivariate Experimental Clinical Research, 6(2), 81–85. Berge, Z. L., Muilenburg, L. Y., & Haneghan, J. V. (2002). Barriers to distance education and training: survey results. The Quarterly Review of Distance Education, 3(4), 409–418. 12 Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx ARTICLE IN PRESS Blignaut, S., & Trollip, S. R. (2003). Developing a taxonomy of faculty participation in synchronous learning environments – an exploratory investigation. Computers and Composition, 41, 149–172. Boone, T., & Ganeshan, R. (2001). The effect of information technology on learning in professional service organizations. Journal of Operations Management, 19, 485–495. Broady-Ortmann, C. (2002). Teachers’ perceptions of a professional development distance learning course: a qualitative case study. Journal of Research on Technology in Education, 35(1), 107–116. Bryman, A. (1989). Research methods and organizational studies. London: Unwin Hyman. Carr, S. (2000). Online psychology instruction is effective, but not satisfying, study finds. Chronicle of Higher Education(February 11), A48. Carr, S. (2001). Is anyone making money on distance education? Chronicle of Higher Education(February 6), A41. Carver, C. A., Jr., Howard, R. A., & Lane, W. D. (1999). Enhancing student learning through hypermedia courseware and incorporation of student learning styles. IEEE Transactions on Education, 42(1), 33–38. Cattell, R. B. (1988). The meaning and strategic use of factor analysis. In J. R. Nesselroade & R. B. Cattell (Eds.), Handbook of multivariate experimental psychology. Chicago: Rand McNally. Chassie, K. (2002). The lure of e-learning. IEEE Potentials(August/September), 33–35. Chen, C. H. (2003). The historic analysis on the development of the distance education after 1990 – the rethinking of the social learning and the educated revolution. Journal of Educational Media and Library Science, 40(4), 513–524. Croy, M. J. (1998). Distance education, individualization, and the demise of the university. Technology in Society, 20, 317–326. Dellana, S. A., Collins, W. H., & West, D. (2000). Online education in a management science course-effectiveness and performance factors. Journal of Education for Business, 76(1), 43–47. Economist Intelligent Unit. (2005). The 2005 e-readiness ranking. Available from . Essex, P., Magel, S. R., & Mosteller, D. E. (1998). Determinants of information center success. Journal of Management Information Systems, 15(2), 95–117. Everetts, R. B. (1998). Experience in distance learning from a student’s perspective. In International symposium on technology and society, Indiana University, Indiana, USA, June 12–13. Fosay, W. R. (1998). Education technology in schools and in business: a personal experience. Educational Horizons, 66(4), 154–157. Frankola, K. (2000). Why online learners drop out. Workforce(October 21), 52–60. Geueke, M., & Stausberg, J. (2003). A meta-data-based learning resource server for medicine. Computer Methods and Programs in Biomedicine, 72(3), 197–208. Gibson, J. W., Tesone, D. V., Hodgetts, R. M. & Blackwell, C. W. (2001). The human dimension of online education: cyberstudents speak out. In IEEE international conference on communication dimensions (pp. 367–378), Sante Fe, USA, October 24–27. Gladieux, L. E. (2000). Global on-line learning: hope or hype? International Higher Education, 18(Winter), 3–4. Available from . Haas, S. M., & Senjo, S. R. (2004). Perceptions of effectiveness and the actual use of technology-based methods of instruction: a study of California criminal justice and crime-related faculty. Journal of Criminal Justice Education, 15(2), 263–285. Hailey, D. E., Keith, G.-D., Jr., & Hult, C. A. (2001). Online education horror stories worthy of Halloween: a short list of problems and solutions in online instruction. Computers and Composition, 18, 387–397. Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. G. (1998). Multivariate data analysis (5th ed.). London, UK: Prentice-Hall. Harris, D. A. (1999). Online distance education in the United States. IEEE Communication Magazine(March), 87–91. Hartnett, J. (1999). Interacting with interactions. Inside Technology Training, July/August. Available from . Harun, M. H. (2001). Integrating e-learning into the workplace. The Internet and Higher Education, 4, 301–310. Hazari, S., & Schnorr, D. (1999). Leveraging student feedback to improve teaching in web-based courses. The Journal, 11(June). Available from. Hillesheim, G. (1998). Distance learning: barriers and strategies for students and faculty. The Internet and Higher Education, 1(1), 31–44. Howell, S. L., Saba, F., Lindsay, N. K., & Williams, P. B. (2004). Seven strategies for enabling faculty success in distance education. The Internet and Higher Education, 7, 33–49. Institute for Higher Education Policy (1999). What’s the difference? A review of contemporary research on the effectiveness of distance learning in higher education. Washington, DC: Institute for Higher Education Policy. Irlbeck, S. A. & Pucel, D. J. (2000). Dimensions of leadership in higher education distance education. In Proceedings of international workshop on advanced learning technology (pp. 63–64), Palmerston, North New Zealand. Jain, R. (1997). A revolution in education. IEEE Multimedia, 4(1), 1–5. Jerman-Blazic, B. (2000). The usability aspects of a universal brokerage and delivery system for the pan-European higher education. In International workshop on advanced learning technologies (pp. 184–185), Palmerston, North New Zealand, December 4–6. Jonhendro Ching, G. B., Wahab, R., Leng, W. M., Aun, J. T. L., Yeoh, E., Hock, O., et al. (2002). KDU e-community network. The Internet and Higher Education, 4, 317–328. Kabassi, K., & Virvou, M. (2004). Personalized adult e-training on computer use based on multiple attribute decision making. Interacting with Computers, 16(1), 115–132. Kennedy, G. (2002). E-learning. Computer Law and Security Report, 18(2), 91–98. Khalifa, M., & Lam, R. (2002). Web-based learning: effects on learning process and outcome. IEEE Transactions on Education, 45(4), 350–356. http://www.eiu.com/site_info.asp?info_name=eiu_2005_e_readiness_rankings http://www.eiu.com/site_info.asp?info_name=eiu_2005_e_readiness_rankings http://www.bc.edu/bc_org/avp/soe/cihe/newsletter/News18/text2.html http://www.bc.edu/bc_org/avp/soe/cihe/newsletter/News18/text2.html http://www.ittrain.com/learning-online/7-8-99-learning-nuts-bolts.htm http://www.ittrain.com/learning-online/7-8-99-learning-nuts-bolts.htm http://www.thejournal.com/magazine/vault/A2089.cfm Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx 13 ARTICLE IN PRESS Konstantopoulos, M., Spyrou, T., & Darzentas, J. (2001). The need for an academic middleware for advanced learning services. Computers Network, 37, 773–781. LaBay, D. G., & Comm, C. L. (2003). A case study using gap analysis to assess distance learning versus traditional course delivery. The International Journal of Educational Management, 17(6/7), 312–317. Lao, T., & Gonzales, C. (2005). Understanding online learning through a qualitative description of professors and students’ experiences. Journal of Technology and Teacher Education, 13(3), 459–474. Latchman, H. A., Salzmann, C., Gillet, D., & Bouzekri, H. (1999). Information technology enhanced learning in distance and conventional education. IEEE Transactions on Education, 42(4), 247–254. Lee, J. (2002). Faculty and administrator perceptions of instructional support for distance education. International Journal of Instructional Media, 29(1), 27–45. Liber, O., Oliver, B., & Britain, S. (2000). The TOOMOL project: supporting a personalized and conversational approach to learning. Computers and Education, 34, 327–333. Lin, C.-B., Young, S. S.-C., Chan, T.-W., & Chen, Y.-H. (2005). Teacher-oriented adaptive Web-based environment for supporting practical teaching models: a case study of ‘‘school for all’’. Computers and Education, 44, 155–172. Louvieris, P., & Lockwood, A. (2002). IT induced business transformation in higher education: an analysis of the UniCafe’ experience and its implications. Computers and Education, 38, 103–115. Mcgorry, S. Y. (2003). Measuring quality in online programs. The Internet and Higher Education, 6, 159–177. Mehlenbacher, B., Miller, C. R., Covington, D., & Larsen, J. S. (2000). Active and interactive learning online: a comparison of Web-based and conventional writing classes. IEEE Transactions on Professional Communication, 43(2), 166–184. Miller, S. (2001). How near and yet how far? Theorizing distance teaching. Computers and Composition, 18, 321–328. Ministry of Education, ROC. (2001). Procedural rules governing distance learning at the junior college and higher levels issued on 2001.6.29. Available from http://www.edu.tw/EDU_WEB/EDU_MGT/MOECC/EDU1849001/ii7205/dp/wto_edulaw/wto-c18.htm. Ministry of Education, ROC. (2005). 2005.8.15 announcement of revision for procedural rules governing distance learning at the junior college and higher levels. Available from FILEID=138231and open. Moody, J. (2004). Distance education: why are the attrition rates so high? Quarterly Review of Distance Education, 5(3), 205–210. Motiwalla, L., & Tello, S. (2000). Distance learning on the Internet: an exploratory study. The Internet and Higher Education, 2(4), 253–264. Odin, J. L. (1997). ALN: pedagogical assumptions, instructional strategies, and software solutions. Honolulu, HI: University of Hawaii at Manoa. Available fromhttp://www.hawaii.edu/aln/aln_tex.htm. Owston, R. D. (1997). The World Wide Web: A technology to enhance teaching and learning? Educational Researcher, 26(2), 27–33. Pahl, C. (2003). Managing evolution and change in web-based teaching and learning environments. Computers and Education, 40, 99–114. Peterson, P. W. (2001). The debate about online learning: key issues for writing teachers. Computers and Composition, 18, 359–370. Pison, T. (1997). Distance learning is an opportunity. Cricuits and Devices(March), 41–43. Raab, R. T., Ellis, W. W., & Abdon, B. R. (2001). Multisectoral partnerships in e-learning: a potential force for improved human capital development in the Asia Pacific. The Internet and Higher Education, 4, 219–227. Roberts, T. L., Jr., Gibson, M. L., Jr., Rainer, R. K., Jr., & Fields, K. T. (2001). Response to comments on factors that impact the implementation of a systems development methodology. IEEE Transactions on Software Engineering, 27(3), 282–286. Rogers, A. (2000). The failure and promise of technology in education, Global SchoolNet Foundation. Available from . Russell, T. (1999). The ‘‘no significant difference phenomena’’ website. Available from . Schwab, K. (2005). Global Information Technology Report, World Economic Forum. Available from . Scollin, P. A., & Tello, S. F. (1999). Implementing distance learning: frameworks for change. The Internet and Higher Education, 2, 11–20. Shapiro, D., Furst, S. A., Spreitzer, G., & Von Glinow, M. A. (2002). Transnational teams in the electronic age: are team identity and high-performance at risk? Journal of Organizational Behavior, 23, 455–468. Shoemaker, J. (1998). Leadership in continuing and distance education in higher education. Boston, MA: Allyn and Bacon. Shea, T., Motiwalla, L., & Lewis, D. (2001). Internet-based distance education – the administrator’s perspective. Journal of Education for Business, 77(2), 112–116. Simonson, M., Sweeney, J., & Kemis, M. (1993). Doing distance education: what works? Instructional Innovator, 38(1), 25–28. Starr, D. R. (1998). Virtual education: current practices and future directions. The Internet and Higher Education, 1, 157–165. Stewart, B. L., Waight, C. L., Norwood, M. M., & Ezell, S. D. (2004). Formative and summative evaluation of online courses. Quarterly Review of Distance Education, 5(2), 101–109. Syed, M. R. (2001). Diminishing the distance in distance education. IEEE Multimedia(July–September), 18–20. Taiwan Network Information Center. (2005). Survey of 2005 Taiwan broadband network usage. Available from . Tan, A. H., & Teo, C. (1998). Learning user profile for personal information dissemination. In IEEE international conference on computational intelligence (pp. 183–188), Anchorage, USA, May 4–9. Thiriet, J.-M., Robert, M., Lappalainen, P., Hoffmann, M. H. W., Martins, M. J. M., & Seoane, A. (2002). Toward a pan-European virtual university in electrical and information engineering. IEEE Transactions on Education, 45(2), 152–160. http://www.edu.tw/EDU_WEB/EDU_MGT/MOECC/EDU1849001/ii7205/dp/wto_edulaw/wto-c18.htm http://www.edu.tw/EDU_WEB/EDU_MGT/HIGH/EDU6136001/distancelearning.htm? http://www.edu.tw/EDU_WEB/EDU_MGT/HIGH/EDU6136001/distancelearning.htm? http://www.hawaii.edu/aln/aln_tex.htm http://www.gsm.org/techarticle/promise.html http://www.gsm.org/techarticle/promise.html http://cuda.teleeducation.nb.ca/nosifnificantdifference http://cuda.teleeducation.nb.ca/nosifnificantdifference http://www.weforum.org/site/homepublic.nsf/Content/Global+Competitiveness+Programme%5CGlobal+Competitiveness+Report http://www.weforum.org/site/homepublic.nsf/Content/Global+Competitiveness+Programme%5CGlobal+Competitiveness+Report http://www.twnic.net.tw/download/200307/0502a.ppt http://www.twnic.net.tw/download/200307/0502a.ppt 14 Y.-H. Tao, C.-C. Rosa Yeh / Computers & Education xxx (2006) xxx–xxx ARTICLE IN PRESS Tien, J. M. (2000). Individual-centered education: an any one, any time, any where approach to engineering education. IEEE Transactions on Systems, Man, and Cybernetics – Part C: Applications and Reviews, 30(2), 213–218. Tsai, C.-J., & Tseng, S. S. (2002). Building a CAL expert system based upon two-phase knowledge acquisition. Expert Systems with Applications, 22, 235–248. Ubell, R. (2000). Engineers turn to e-learning. IEEE Spectrum(October), 60–63. Unruh, D. L. (2000). Desktop videoconferencing: the promise and problems of delivery of web-based training. The Internet and Higher Education, 3, 183–199. Vamosi, A. R., Pierce, B. G., & Slotkin, M. H. (2004). Distance learning in an accounting principles course-student satisfaction and perception of efficacy. Journal of Education for Business, 79(6), 360–366. Vaupel, J., & Sommer, M. (1997). Multimdeia education, distance learning and electronic commerce applications. In International conference on virtual systems and multimedia (pp. 174–175), September 10–12. Wallace, F. L., & Wallace, S. R. (2001). Electronic office hours: a component of distance learning. Computers and Education, 37, 195–209. Waseda University of e-Government. (2006). World e-government ranking. Available from . Welle-Strand, A., & Thung, T. (2003). E-learning polices, practices and challenges in two Norwegian organizations. Evaluation and Program Planning, 26, 185–192. Welle-Strand, A., & Tjeldvoll, A. (2002). Learning and value creation—strategies missing? Sandvika: Norwegian School of Management BI, Research Report No. 6-2002. West, D. (2005). Global e-government 2005, Brown University, Available from . Wiesner, P. (2000). Distance education: rebottling or a new brew? Proceedings of the IEEE, 88(7), 1124–1130. Williams, P., & Nicholas, D. (2005). E-learning: what the literature tells us about distance education. Aslib Proceedings: New Information Perspectives, 57(2), 109–122. Woods, R., Baker, J. D., & Hopper, D. (2004). Hybrid structures: faculty use and perception of web-based courseware as a supplement to face-to-face instruction. Internet and Higher Education, 7, 281–297. Xenosa, M., Pierrakeas, C., & Pintelas, P. (2002). A survey on student dropout rates and dropout causes concerning the students in the course of informatics of the Hellenic Open University. Computers and Education, 39, 361–377. http://www.digitaldivide.net/news/view.php?HeadlineID=955 http://www.digitaldivide.net/news/view.php?HeadlineID=955 http://www.insidepolitics.org/egovt05int.pdf Typology of teacher perception toward distance education issues - A study of college information department teachers in Taiwan Introduction Distance education in Taiwan Methodology Findings Teacher profile Factor analysis Cluster analysis Discussions and implications A lack of competitive awareness A high percentage of promising teachers A substantial percentage of skeptic teachers Increasing the percentage of teachers with course training in education Building dedicated support for teachers lacking experience or knowledge in distance education Conclusion Acknowledgements References