Validating Measurements of Perceived Ease Comprehension and Ease of Navigation of an Online Learning Technology: Improving Web Based Learning Tool Adoption and Use
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Validating Measurements of Perceived Ease Comprehension and Ease of Navigation of an Online Learning Technology: Improving Web Based Learning Tool Adoption and Use

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Many universities are realizing that the implementation and use of online learning tool become a competitive advantage to address the actual learning needs. The purpose of this study is to determine ...

Many universities are realizing that the implementation and use of online learning tool become a competitive advantage to address the actual learning needs. The purpose of this study is to determine the factors that influence users’ perceived ease of use of Webct an online learning tool. We administrated a questionnaire to undergraduate students from an university in Quebec, Canada. The results tend to corroborate that ease of comprehension and ease of navigation are the key factors which influence the perceived ease of use of WebCT. More specifically, the terms used in educational web applications must be as simple and relevant as possible. Jargon and technical terms in the wording of text used for links should be carefully avoided. This research is extending the finding of IT adoption studies by specifying what make an online tool easy to use.

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Validating Measurements of Perceived Ease Comprehension and Ease of Navigation of an Online Learning Technology: Improving Web Based Learning Tool Adoption and Use Validating Measurements of Perceived Ease Comprehension and Ease of Navigation of an Online Learning Technology: Improving Web Based Learning Tool Adoption and Use Document Transcript

  • 2011 International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies.International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies http://www.TuEngr.com, http://go.to/Research Validating Measurements of Perceived Ease Comprehension and Ease of Navigation of an Online Learning Technology: Improving Web Based Learning Tool Adoption and Use a* Bangaly KABA a Schools of Business, International Relations and Economic Policy (BIREP), International University of Grand-Bassam, IVORY COAST ARTICLEINFO A B S T RA C T Article history: Many universities are realizing that the implementation Received 21 March 2011 Received in revised form and use of online learning tool become a competitive advantage to 27 May 2011 address the actual learning needs. The purpose of this study is to Accepted 31 May 2011 determine the factors that influence users’ perceived ease of use of Available online 01 June 2011 Webct an online learning tool. We administrated a questionnaire Keywords: to undergraduate students from an university in Quebec, Canada. Technology; The results tend to corroborate that ease of comprehension and Acceptance; ease of navigation are the key factors which influence the Model; perceived ease of use of WebCT. More specifically, the terms used WebCT (Web course tools); Measurement; in educational web applications must be as simple and relevant as E-learning. possible. Jargon and technical terms in the wording of text used for links should be carefully avoided. This research is extending the finding of IT adoption studies by specifying what make an online tool easy to use. 2011 International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Some Rights Reserved. 1. Introduction  Recently, following the example of other organizations, a large number of universities have been giving primary importance to the use of information and communication technologies (ICTs), allocating substantial resources to their acquisition. ICTs are used on a *Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses: kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 287 eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf
  • daily basis in universities to build students and employees’ databases, to carry out statisticalanalyses, to conduct refined bibliographical research, to send e-mails, to permit multimediaanimation in classrooms, etc. (Bradley et al., 2006; Mbarika et al., 2003a, 2003b). In addition tothese uses, ICTs have become the preferred media for distance learning services (Mbarika,2004), thus considerably reducing temporal and spatial constraints (geographical disparities).The current trend is for distance learning to become an option for a great number of instructorsto respond to the new needs of students. The investments made in order to acquire, implement and use ICT for educational purposesshould be expected to result in positive impacts for the quality of instruction. More specifically,these investments should materialize in the form of increased productivity, a reduction intransaction costs, and therefore; in improved performance (Goodhue et al. 2000; Mathieson,1991). Many models have allowed researchers to determine and measure the factors involved inthe adoption of a technological innovation (Goodhue et al., 2000; Mathieson, 1991; Taylor andTodd, 1995). Among these, Davis (1989)’s technology acceptance model (TAM) figures as aclassic in the field of the adoption of technological innovations. TAM is generally referred to asthe most influential and commonly employed theoretical model in information systemsresearch (Lee et al. 2003). This theory is of particular interest in explaining user behavior withregard to IT. TAM has been consistently validated by a number of empirical studies (Davis etal., 1989; Kwon and Chidambaram, 2000; Mathieson, 1991; Taylor and Todd, 1995; Venkateshet al., 2003). However, since most of these studies aim to test the model, opportunities for theinformation systems and information technology (IS/IT) community to contribute becomemore and more restricted if serious theoretical modifications are not made to the fundamentalmodel. At least two possible criticisms of TAM can be made. First, TAM is a generalizedtheory which does not always seem to take into account particular types of technologicalinnovations. In fact, the process of acceptance depends upon the nature of the IT (Igbaria, 1994;Mahler and Rogers 2000; Markus, 1997). Secondly, TAM fails to provide useful explanationswhich could help those who design or manufacture IT to increase the level of acceptance oftheir products by end users (Venkatesh and Davis, 2000, Benbasat and Barki, 2007). 288 Bangaly KABA
  • This situation considerably limits the practical application of TAM (Benbasat and Barki,2007). In light of this finding, we intend in this study to validate new scales of measurement ofthe ease of use of WebCT, which is a course management system for online learning. This study based on technology acceptance model (TAM) is initiated to validate themeasurement of the factor that influence users’ perceived ease of use of WebcT in order toenhance our understanding of online learning tools use. TAM stated that easier is to use asystem or a technology high is the probability of its adoption and use. Unfortunately, the modeldoes not indicate what make practically a technology easy to use. Our main research questionis: what are the practical factors or measures which could be considered as alternative of users’perceived ease of use? We consider that perceived ease of comprehension and perceived ease ofnavigation as good alternatives which could serve as measurements of the ease of use ofWebCT even other online learning tools. Before outlining the conceptual framework of thisstudy, we consider it is useful to present the characteristics and the attractions of WebCT whichmay be unfamiliar to the general public.2. Overview of WebCT  Among internet and Web-based applications for online courseware, WebCT emerges as aleader (Clark, 2002). This application was designed by the information systems department ofthe University of British Columbia about a decade ago. Since then, the functionality of WebCThas constantly improved, and it is now used by more than 2,200 institutions in more than 70countries (WebCT, 2005). WebCT is a powerful tool for the creation of a distance learningenvironment. It provides a complete set of tools for the delivery of an online course (Palloffand Pratt, 2001 ; Mioduser et al. 2000). Once instructors and students become familiar with thesoftware, it can be used for e-learning. WebCT offers the possibility of synchronous andasynchronous communication, sending e-mails, file sharing, student evaluations, access tocourse materials, and access to outside resources dedicated to learning.3. Theoretical Framework  Chris et al. (2004) emphasize the importance of the online knowledge management tool’suser interface as a critical factor for its adoption and for online learning. Indeed, as a link*Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses:kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering,Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 289eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf
  • between the user and the system, the user interface allows a reduction of effort by making thenavigation among the different components of the system easier. The success of an online application also relies upon the terminology used. Theterminology of a system refers to all words, phrases, and abbreviations it uses (Lindgaard,1994). For example, a frequent problem with online courseware systems has to do with thetechnical jargon used. This jargon includes technical or professional vocabularies with whichgeneral users are often unfamiliar. In such cases, great effort must be made by end users in orderto utilize the system to its full potential. A clear and comprehensible terminology can thusreduce the effort necessary to master the system and to make users more productive.Consequently, it may be concluded that clarity of terminology is a good measurement ofperceived ease of use. Davis et al. (1989) states that a technology or a system designed in such a way as to allowits potential user to expend little time or energy (avoiding the constant need to refer to the user’smanual or to contact the provider for help, etc.) will encounter few obstacles to its adoption.These authors predict that the more a technology is perceived to be easy to use, the greater thelikelihood of its adoption. According to Davis et al. (1989), ease of use corresponds to thedegree to which a person believes that using a new IT will be easy. It is measured by thefollowing three indicators using Likert scales: the technology is easy to master, the technologyis user-friendly, the technology, in general, is easy to use. These measurements are for generalpurposes and do not always appear to take into account the specific characteristics of a giventype of technology. This lack of specificity is susceptible to make the task of IS designers morearduous when it comes time to determine the specific aspects of the system which couldinfluence users’ perceptions. The previous shortcoming has led Moore and Benbasat (1991) to argue that one of theproblems facing the theories related to the adoption of technological innovations is the lack ofvalid, trustworthy instruments to measure users’ perceptions in the context of adoption of theseinnovations. Our intent in the current study is to identify and validate measurements of theperception of ease of use which takes into account the features of a specific technologicalinnovation, which is WebCT. The concept of ease of use is generally used in the literature on user acceptance of 290 Bangaly KABA
  • technology and on user behavior. As previously mentioned, Davis et al. (1989) identify ease ofuse as one of the important determinants of the use of ICTs. Davis (1989) suggests that theperceived ease of use can in fact determine the perceived usefulness. Mathieson (1991) andSzajna (1996) report that ease of use accounts in large part for variations in perceivedusefulness. Therefore, in light of the aforementioned contributions, we can assert that a bettercomprehension of the measurements of ease of use of WebCT constitutes a worthwhile domainto investigate, because it could have a beneficial effect on the other determinants of ICTsuccess. Inspired by the study of Lederer et al. (2000), we propose in the current research, the easeof comprehension and the ease of navigation as alternative measurements of WebCT’s ease ofuse. However, unlike Lederer et al. (2000), we consider that these two variables are rathermeasurements of perceived ease of use, not the antecedents. After having pinpointed the various theoretical contributions that are relevant to ouranalysis, the next section focuses on the methodology adopted in this research.4. Methodology 4.1 Questionnaire Development  The data for this study was collected through a questionnaire survey that was divided intodifferent sections. Each section was devoted to each variable of the research model: Taskcharacteristics, group characteristics, facilitating conditions, social influence, and the intentionof the users. A seven-point Likert scale, where 1 indicates “strongly disagree” and 7 “stronglyagree” (see questionnaire in appendix) was used to measure the latent variables used in thestudy, with the exception of socio-demographic factors. These latent variables included:perceived ease of use, perceived ease of comprehension, perceived ease of navigation,perceived competency, computer anxiety, technical support and user help, and experience usingthe internet. Variables measurements were inspired by Lederer et al. (2000) and Davis et al.(1989), and adapted to the context of this study. Each variable’s was measured using multipleitems. Aside from demographic factors, the present analysis is only concerned with twovariables, “perceived ease of use” and “ease of navigation”. In the following section wepresent the results obtained by our analysis.*Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses:kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering,Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 291eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf
  • A pre-test of the questionnaire was performed in order to assure its content validity beforeits final distribution to the respondents. First, we designed a preliminary version of thequestionnaire. This version was given to researchers in the field of IT and information systems(IS), and to experts in the industry familiar with the African context. Each individual providedsome comments on the formulation, the syntax, and the number of items included in thequestionnaire. Taking into account the various comments, we made minor changes to thequestionnaire. The various comments also permitted us to eliminate biases which could exist inthe questionnaire. .4.2 Data Collection  Data in this study were collected using a questionnaire survey. Orlikowski and Baroudi(1991) maintain that the questionnaire survey is the method of data collection mostly used in ITresearch. This method is often indicated for gathering data, describing and explaining people’sperceptions, attitudes, or behaviors. Questionnaires have the advantage of being structured andassuring standardization in the formulation of questions and in their sequence. We administereda survey to undergraduate students at a French-speaking university in Canada that use WebCTin their course of studies. It should be noted that in this university, WebCT served as aninstructional supportive tool. In order to be assured of a high response rate, we administered the survey by direct contact.This mode of communication is very demanding in terms of investment, both in the time it takesand in the amount of travel required. However, it seems to be the richest data collectiontechnique (Emory, 1980). With the instructors’ assistance, we solicited students’ directparticipation in their classrooms. The questionnaires were filled out on a voluntary basis beforethe beginning of courses. We obtained 172 usable responses out of 230 questionnairesadministered, yielding a 75% response rate.4.3 Data Analysis    The statistical analysis for this study employed the SPSS statistical software. Theassessment of the collected data’s descriptive statistics, construct validity and the testing of theindicators’ reliabilities were conducted in SPSS. The factor analysis of principal componentwas mainly applied to validate the measurement of easy of comprehension and easy ofnavigation. 292 Bangaly KABA
  • 5. Results  Details of the socio-demographic variables chosen for this study are given in Table 1. Table 1: Socio-demographic profiles. Absolute Percentage Variables Characteristics Frequencies Gender Male 57 33.1% Female 115 66.9% Age 16 - 21 years 67 39% 22 - 27 years 87 50.6% 28 - 33 years 10 5.8% 34 - 39 years 6 3.6% 40 or older 2 1.2% Years of Less than 1 year 1 0.6% experience using 1 year 1 0.6% the internet 1 to 2 years 7 4.1% 2 to 3 years 15 8.7% 3 to 4 years 27 15.7% 4 to 5 years 33 19.2% 5 or more years 88 51.2% Different uses of Information seeking 6.32 1.04 the internet Downloading 5.10 1.84 Sending email 6.61 0.93 Chat 3.29 2.16 Forum 2.92 1.87 The socio-demographic variables examined in this study are concerned with gender, age,years of experience using the internet, and the uses made of the internet. Only a third of the 172respondents were men. The predominance of women in university programs is a reality whichcannot be ignored. The respondents were relatively young, since 154 of the respondents(89.6%) are less than 30 years old. According to Paré (2002), the new generation of students hasan unprecedented level of mastery of ICTs (computers and the Internet). It is interesting, but notsurprising in the North American context, that the vast majority of respondents seem to befamiliar with the use of the internet. Indeed, 70.4% of respondents possess more than fouryears’ experience using the internet, which could favor their acceptance of WebCT which is aweb-based application. However, the respondents show a very weak score in terms of their use of the online chatand of discussion forum. This low score is a bad sign of WebCT usage as these functionalitiesare nonetheless among the essential components of the application, since they permit bothsynchronous and asynchronous communication among learners as well as with the instructor.*Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses:kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering,Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 293eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf
  • 5.1 Validation of the scales of measurement used  Variables measurements were validated through convergent and discriminant validitytesting. A principal components factorial analysis (PCA) was performed on each variablesmeasurement items in order to verify both types of validity. Additionally, the reliability ofeach variable measurement was established by calculating Cronbach’s Alpha coefficient. Thetests of convergent and discriminant validity and of reliability are three measures necessary forthe validation of a scale of measurement. In the following section, the results of these three testsare presented.5.1.1.  Test of convergent validity  An analysis of the correlations among the items measuring each variable was first carriedout, followed by a principal components analysis (PCA) with Varimax rotation when more thanone factorial axis was found. The use of this method must satisfy three criteria. The first one is the criterion relative tothe eigenvalue which aids in identifying the number of components (factors) to retain. In thisstudy, we refer to Kaiser (1958)’s rule according to which only the axes whose eigenvalue ishigher than 1 are retained. The second criteria is related to the factorial contributions (loadings)which aims at identifying relevant items or indicators that better explain a factor. According tothis criterion, only items with factorial contributions greater than 0.3 are accepted (Blau et al.,1993). The last criterion deals with the communalities of items and it indicates the proportion ofexplained variance in the combination of each factor. This criterion allows the assessment ofthe level of representation of each item in the principal components. In this study, an itemwhose communality was inferior to 0.4 was dropped from the analysis, in compliance with thesuggestions of Evrard et al. (2003).5.1.1.  Measurement of Perceived Ease of Comprehension  Table 2 includes items measuring the ease of comprehension. Results in Table 3 showthat the correlations among the items of measuring the ease of comprehension are positive and 294 Bangaly KABA
  • significant, which might be a manifestation of the uniqueness of this measurement. The PCAyields a factor which explains 68.36% of the total variance, with important positive factorialcontributions (loadings) and a good quality of representation for each item (>0.4) (see Table 4).Based on the above results, we can state that the unidimensionality of this measurement hasbeen proven. Table 2: Presentation of items measuring the ease of comprehension. Variable Codification Items description Ease of 3.1 WebCT uses relevant comprehension terms 3.2 WebCT uses simple terms 3.3 WebCT includes links that give detailed information 3.4 WebCT has a pleasant design 3.5 WebCT posts pages that are easy to read Table 3: Correlations matrix of ease of comprehension. Items 3.1 3.2 3.3 3.4 3.5 3.1 1 3.2 0.753** 1 3.3 0.646** 0.555** 1 3.4 0.486** 0.490** 0.573** 1 3.5 0.587** 0.589** 0.608** 0.750** 1 *** p< 0.01; ** p<0.05; *p<0.1 ns: not significant Table 4: Factorial solution of ease of comprehension. Variables (Ease of Quality of Items comprehension) representation 3.1 0.842 0.709 3.2 0.820 0.673 3.3 0.818 0.668 3.4 0.795 0.633 3.5 0.857 0.734 Eigenvalue 3.418 Explained variation 68.3565.1.1 Measurement of perceived ease of navigation  Table 5 shows items measuring the ease of navigation. The correlations among the itemsof the perceived ease of navigation variable are all positive and significant (Table 6) and*Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses:kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering,Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 295eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf
  • demonstrate the uniqueness of measurement of this variable. The PCA results in Table 7 show aunique factor explaining 79.65% of the variance. All the items have a very good quality ofrepresentation (>0.4). Table 5: Presentation Items measuring the ease of navigation Variable Codification Items description Ease of 4.1 WebCT allows me to easily return Navigation to previously-viewed pages 4.2 I can always tell where I am when navigating WebCT 4.3 WebCT is an easy site to navigate Table 6: Correlations matrix of ease of navigation Items 4.1 4.2 4.3 4.1 1 4.2 0.715** 1 4.3 0.647** 0.721** 1 *** p< 0,01; ** p<0,05; *p<0,1 ns: not significant Table 7: Factorial solution of ease of navigation Variables (Perceived ease of navigation) Quality of representation Items 4.1 0.881 0.776 4..2 0.912 0.832 4.3 0.884 0.781 Eigenvalue 2.389 Explained variation 79.649%5.1.2 Discriminant Validity  The objective of this test is to verify the independence of the variables. Like for the test ofconvergent validity, a principal components analysis was carried out on the items measuringeach variable. Three items were dropped from the analyses because each of them had a loadinggreater than 0.3 on the two selected factors. These items are: Item 3.3 (WebCT includes linksthat give detailed information) and item 3.4 (WebCT has a pleasant and agreeable design) forthe variable ease of comprehension; and item 4.3 (WebCT is an easy site to navigate) for ease ofnavigation. According to the results discussed above and shown in table 8, we can assume theindependence of the two variables of the research. 296 Bangaly KABA
  • The reliability test will conclude this validation of scales. The results appear in thefollowing table: Table 8: Results of the test of discriminant validity Variables Ease of Ease of Items comprehension navigation 3.1 0.887 3.2 0.872 3.5 0.809 4.1 0.924 4.2 0.884 Eigenvalue 2.894 1.139 Explained variation 57.888% 22.783%5.1.3 Analysis of the Reliability of the Measurement    In order to ascertain the degree to which the measurement instrument (the questionnaire)used in this study evaluates the perceptions of respondents in a consistent manner, weperformed a reliability analysis by calculating Cronbach’s Alpha coefficient. The results for thetwo constructs of the study appear in the Table 9. Table 9: Results of the reliability test. Variables of the study Variables Items Cronbach’s Alpha Wording Ease of comprehension 3.1.; 3.2; 3.5 0.8367 Ease of navigation 4.1; 4.2 0.8315 Throughout these results, we notice that the value of Cronbach’s Alpha for all the variablesis superior to 0.7, which shows the reliability of the adopted measurement instrument (Evrard etal., 2003 ; Teo et al., 1999).6. Conclusion, Limits, and Directions for Future Research  The goal of the present study was to determine and validate measurements of theperception of ease of use which takes into account the features of an online tool, which is*Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses:kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering,Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 297eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf
  • WebCT. According to the analysis carried out in this work, perceived ease of comprehensionand perceived ease of navigation emerge as good alternatives which could serve asmeasurements of the ease of use of WebCT, and indeed of other online interaction and learningtools. The implications of these results, for the designers of Web-based educational applicationsin general and for those of WebCT in particular, are to continue to work toward making theirproduct as user-friendly as possible. More specifically, the terms used in educational webapplications must be as simple and relevant as possible. Jargon and technical terms in thewording of text used for links should be carefully avoided. These recommendations are equallyvalid for the academic content on WebCT. The results of this study can also be of benefit tothose individuals responsible for selecting online applications, in that they would know inadvance the relevant factors to take into account in order to increase the likelihood of success ofthe chosen technologies. Nevertheless, this research has its limits. For a better assessment of the face validity or thecontent validity of the measurement used, it would have been helpful to recruit experts toexamine them. Increasing the survey sample size would also have been quite useful to ensurethat the study’s findings could be generalized. In the future, this study could be extended toinclude other departments or universities where the level of ICT use is heterogeneous in orderto evaluate and understand possible differences in results. Further, the extension of the researchto other countries where the level of students’ access to e-learning tools is limited or at least isstill at an embryonic stage would constitute a relevant basis for comparison of the externalvalidity of the measurement instrument validated by this study. In such a study, it would bebeneficial to proceed with a confirmatory factor analysis. 298 Bangaly KABA
  • 7. Acknowledgment  A very special thank you is due to Associate Professor Dr. Boonsap Witchayangkoon forinsightful comments, helping clarify and improve the manuscript.8. References Blau, G., A. Paul and N. St. John. (1993). “On developing a general index of work commitment,” Journal of vocational behavior, Vol. 42, no. 3, pp. 298-314.Benbasat, I. and Barki, H. 2007. Quo vadis, TAM? Journal for the Association of Information Systems, Vol. 8, no.4, pp. 211-218Bradley, R., Sankar, C., Clayton, H., Raju, PK, and Mbarika, V. (2006). “An Empirical Investigation of the Impact of GPA on Perceived Improvement of Higher-Order Cognitive Skills,” Decision Sciences Journal of Innovative Education.Chris, Evans A, Nicola J. G. B., Kavita S. B, Darren K. G. (2004). “Virtual learning in the biological sciences: pitfalls of simply ‘‘putting notes on the web”,” Computers & education, Vol. 43, pp. 49–61.Clark, J. (2002). “A product review of WebCT,” Internet and Higher education, Vol. 5, p. 79–82Davis, F. D. (1989). “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS quarterly, Vol.13, no. 3, pp.318-343.Davis, F. D., R. Bagozzi P. and P. R. Warshaw. (1989). “User acceptance of computer technology: a comparaison of two theoretical models,” Management science, Vol. 35, no. 8, pp. 982-1003.Emory, C. W. (1980). Business research methods. Revised edition, Homewood Irwin Inc.Evrard, Y., B. Pras and E. Roux. (2003). Market: études et recherches en marketing. 3rd edition, Paris, Dunod.Goodhue, D. L., B. D., Klein and S. T., March. (2000). “User evaluation of IS as surrogates for objective performance,” Information & management, Vol. 38, pp. 87-101.Igbaria, M. (1994). “An examination of the factors contributing to microcomputer technology acceptance,” Accounting, management and information technology, Vol. 4, no.4, pp. 205-224.Kaiser, H.F (1958). “The varimax criterion for analytic rotation in factor analysis,” Psychometrika, Vol. 23, p. 187-200.http://www.itcortex.com/Stat_Failure_Cause.htm (visited 20 December 2003)*Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses:kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering,Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 299eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf
  • Lindgaard, G. (1994). Usability testing and system evaluation: A guide for designing useful computer systems, Chapman & Hall, London.Lederer, D.; Maupin, D.; Sena, M. and Zhuang, Y. (2000). “The technology acceptance model and world wide web,” Decision support systems, Vol. 29, no. 3, p. 269-282.Lee, Y., Kozar, K.A., Larsen, K.R.T. (2003). The Technology Acceptance model: Past, Present, and future. CAIS, Vol. 12, pp. 752-780.Legris, P. , J., Ingham and P. Collerette. (2003). “Why do people use information technology? A Critical review of the technology acceptance model,” Information & management, Vol. 40, pp. 191-204.Mahler, A. and Rogers M. Everett. (2000). “The diffusion of interactive communication innovations and the critical mass : the adoption of telecommunication services by German banks,”.Telecommunication policy, Vol. 23, pp. 719-740Markus, M. L. (1987). “Toward a critical mass theory of interactive media: universal access, interdependence and diffusion,” Communication research, Vol. 14, pp. 491-511.Mathieson, K. (1991). “Predicting user intentions: comparing the Technology Acceptance Model with the Theory of Planned Behavior,” Information systems research, Vol. 2, no. 3, pp.173-191.Mbarika, V., Sankar, C.S., Raju, P.K. (2003a). “Role of Multimedia Instructional Materials on Multicriteria Technology and Engineering Decisions,” Decision Sciences Journal of Innovative Education, Vol. 1, #2.Mbarika, V., Sankar, C.S., Raju, P.K. (2003b). ”Identification of Factors that Lead to Perceived Learning Improvements for Female Students,” IEEE Transactions on Education, Vol. 46, # 1, pp. 26-36.Mbarika, V. (2004). “TeleEducation in Sub-Saharan Africa: A Breakout Approach to Sub-Saharan Africa’s Education Dilemma,” IEEE Technology and Society,Vol. 22, #4, pp. 20-26.Mioduser, D.; Nachmis, R.; Lahave, O.; Oren, A. (2000). “Web-based learning environments: current pedagogical and technological state,” Journal of research on computing in education, Vol. 33, no. 1, pp. 55-76.Moore, G. C. and Benbasat, I. (1991). “Development of an instrument to measure the perception of adopting an information technology innovation,” Information systems research, Vol.2 no.3, pp. 37-46.Mustonen-Ollila, E. and K. Lyytien. (2003). “Why organizations adopt information system process innovations: a longitudinal study using diffusion of innovation theory,” Information systems journal, Vol. 13, p. 275-297.Orlikowski, W.J. and J. J. Baroudi, (1991). “Studying information technology in organizations: 300 Bangaly KABA
  • research approaches and assumptions,” Information systems research, Vol. 2, no. 2, pp. 1-28.Palloff, R., and Lamaster, K. (2001). “Lessons from the cyberspace classroom,” The realities of online teaching, Sans Francisco: Jossey-Bass.Paré, G. (2002). “La génération Internet : un nouveau profile d’employé,” Gestion, Vol. 27, no. 2, pp.47-57.Szajna, B. (1996). “Empirical evaluation of the revised technology acceptance model,” Management science, Vol. 42, no. 1, pp. 85-92.Taylor, S and Todd, P.A. (1995). “Understanding information technology usage: a test of competing models,” Information systems research, Vol. 6, no. 2, p. 91-108.Teo, T.; Lim, V. and Lai, R. (1999). “Intrinsic and extrinsic motivation in Internet usage,” Omega, International Journal of Management Science, Vol. 27, no. 1, pp. 25-37.Venkatesh, V. and F. D. Davis (2000). “A theoretical extension of the technology acceptance model: four longitudinal field studies,” Management science, Vol. 46, no. 2, p. 186-204.WebCT (2005). http://WebCT.com/entrypage, visited September 2007 Dr. Bangaly Kaba earned his PhD degree in Information Systems from a joint PhD program administered by the four largest universities in Montreal (UQAM, HEC, Concordia University and McGill University). He is a visiting professor at International university of Grand-Bassam. His research interests include the adoption and implementation of information and communication technologies (ICT), especially mobile technologies, the impact of ICT on organizations, cultural issues in ICT adoption and use, tele-education, multimedia learning case study, quantitative methods, and management of international projects.Peer Review: This article has been internationally peer-reviewed and accepted for publication according to the guidelines given at the journal’s website.*Corresponding author (Bangaly KABA). Tel/Fax: +225 21 30 34 57 Ext. 111 E-mail addresses:kbangaly@hotmail.com. 2011. International Transaction Journal of Engineering,Management, & Applied Sciences & Technologies. Volume 2 No.3. ISSN 2228-9860. 301eISSN 1906-9642. Online Available at http://TuEngr.com/V02/287-301.pdf