the influnece of computer and internet access on e-learning technology acceptance

The Influence of Computerand Internet Access onE-learning Technology

AcceptanceDr. Ronda G. Henderson and Dr. Daisy L. Stewart

ABSTRACT

To facilitate the development ofonUr^e and Web-enhanced courses, several institutions have adopted coursemanagement software or e-leaming systems. While many empirical studies have heen conducted concerningfaculty adoption of these technologies, a limited number have addressed the extent to which college studentsaccept these tools. The majority' of these studies failed to consider computer access as a factor regardingstudents' computer technology acceptance. This study investigated whether computer and Internet accessinjluence technology acceptance of e-leaming tools. The E-Leaming Technology Acceptance Instrument wasadministered to 583 business students at two universities in the southeast. Regression analysis revealed thatcomputer and Internet access affected the degree to which students expect Blackboard and the Internet to beeasy to use. Computer and Internet access also affected their attitude towards these technologies. Additionalfindings revealed that sodoeconomic status and race infiuenced computer ownership. Educational implica-tions and recommendations forJurther research are suggested

At the postsecondary level, distance education has grown tremendously. Onlinecourses, which may or may not provide teacher-student interaction, are becomingthe most common form of distance education. According to a study conducted bythe Sloan Consortium, approximately 90% of all public institutions offer onlinecourses (Allen & Seaman, 2004). Research has shown that students who takeonline courses are extremely concerned about teacher-student interaction (Beard& Harper, 2002; Perreault, 2004). Students want to receive continuous feedbackfrom their instructors in an online setting. They also want their instructor to beaccessible when they have a problem or concern (Huang, 2002).

Because many online instructors and students experience interaction and feed-back problems, numerous institutions are choosing the concept of Web-based orhybrid courses to address the various issues surrounding distance learning. InWeb-based courses, many of the techniques such as placing assignments on aWeb site and using chat rooms are incorporated as a supplement to learning. Inthis type of course, students are still physically required to attend class. Students

Dr. Ronda G. Henderson is an Assistant Professor in the Business Communication and Entre-preneurship Department at Middle Tennessee State University. Dr. Henderson may be contactedat [email protected]. Dr. Daisy L. Stewart is an Associate Professor in the School of Educa-tion at Virginia Tech.

Issue XVI Ma)-2007 3

Henderson and Stewart

are expected to attend classes on a periodic basis. In hybrid courses, instructionis not totally online. Periodically, students physically attend class. These akema-tives allow for face-to-face student-teacher interaction while taking advantage oftechnology (Theriot, 2004).

To assist in the delivery of Web-based and online courses, many institutionsand educators have adopted electronic-learning (e-leaming) systems. E-leamingsystems provide educators with an easy method to manage course content andpromote student interaction. These courseware packages can be utilized in a to-tally online setting or as an enhancement to traditional classroom leaming. Whilemany institutions have implemented e-leaming software packages such as WebCTand Blackboard, limited attention has been given to the perceptions of studentsconcerning these systems (Papastergiou, 2006). Although research has shownthat students are receptive to the idea of online leaming, few studies have beenconducted concerning whether students embrace the concept of using e-leamingsystems within a classroom setting.

In addition to the concern of student acceptance of e-leaming systems, tech-nological access and computer use seem to be a major hurdle for students andeducators to overcome (Glenn, 2005). Many students who would like to take ad-vantage of the benefits of e-leaming are unable to do so or find it difficuk becauseof limited technological resources. In many instances, the underlying reason forthis problem involves the socioeconomic status of an individual, contributing tothe digital divide. The digital divide is the gap between those who have accessto computers and the Internet and those who do not (Vail, 2003). Students whohave unlimited access to technology at school and/or at home tend to be moreknowledgeable of computers and have more computer experience than those thatdo not (Zeliff, 2004). In an underprivileged environment, be it school or home, thehardware and software needed to increase computer use is often nonexistent. Ifstudents have limited access to computers, it may impact their frequency of com-puter use. In tum, the frequency of computer use may impact whether a studentaccepts or uses a computer-related technology such as an e-leaming system.

Purpose of the StudyBecause of the technology access disparity that exists, this study was conductedto investigate whether computer access and Internet access have an impact on theacceptance of an e-leaming technology. The research questions used to guide thisstudy were as follows:1. To what extent is e-leaming technology acceptance explained by computer ac-

cess after controlling for the effects of race and socioeconomic status (SES)?2. To what extent is e-leaming technology acceptance explained by Internet ac-

cess after controlling for the effects of race and SES?

4 BUSINESS EDI;CA7ION DIGEST

The Influence of Computer and Internet Access on E-learning Technology Acceptance

Literature Review

Distance EducationDistance education has traditionally been defined as education in which teachersand learners are separated by time and distance. Because of new technologies suchas the PC, the Internet and the World Wide Web, distance education has changedto become more learner centered by providing learners more control over theirlearning (Imel, 1998). Distance education can be delivered through a variety ofmethods from four major categories:

Voice-telephones, audio conferencing, short-wave radio, and one-wayaudiotapes

Video-film, slides, videotapes, and videoconferencing Computer-assisted instruction, computer-managed instruction. Web applica-

tions, internet-based instruction Print-textbooks, study guides, workbooks, and case studies (Willis, 1993).

Of these major instructional tools, Intemet-based learning has become themain way to deliver distance learning curricula due to more powerful personalcomputers, increased bandwidth, and new software packages that are easy tolearn and use (Phipps & Merisotis, 2000).

An abundance of research has been conducted comparing traditional learningand distance learning. A vast majority of studies revealed no significant differ-ence between the two methods of instruction (Glenn, 2005; Smeaton & Keogh,1999). The most influential research resulted in the no significant difference phe-nomenon, reported by Russell in 1999. Russell reviewed 355 studies on distanceeducation that were written from 1928 to 1998.

Despite the large number of comparison studies touting the effectiveness ofdistance learning, many critics continue to have reservations about this mode ofinstruction. One concern with distance learning, as with traditional classroominstruction, is that if a course is not developed effectively, it may not accommodatethe learning style of each learner. Students learn in a variety of ways, which meansthat there should be a variety of methods utilized when transferring knowledgeonline (Bennett, 2001; James & Voigt, 2001). Another issue regarding distancelearning is the lack of student-to-student interaction as well as student-to-teacherinteraction (Ryan, Carlton, & Ali, 1999; Hutchins, 2007). Some courses lack theopportunity for face-to-face interaction, which is a crucial element of learning intraditional settings. Some argue that this limitation could make it difficult for stu-dents to interact and connect with one another on an educational level. Becausemany online instructors and students experience interaction and feedback prob-lems, numerous institutions are choosing the concept of e-leaming to address thevarious issues surrounding distance learning.

Issue XVI May 2007 5


Electronic Learning (E-Learning)Different blends of e-leaming include Web-displayed, hybrid, and online modes ofinstruction. However, Web-enhanced courses have become a mainstay in highereducation. In Web-enhanced courses, classroom instruction is the main deliverymethod; however, it has Web-displayed components that may include online lec-tures and/or interaction, chat or threaded discussions, and online assessments(McArthur, Parker, & Giersch, 2003). Many institutions are opting for this methodbecause it incorporates the use of technology in addition to providing studentswith the traditional benefits of classroom instruction such as face-to-face student-teacher interaction and student-to-student interaction.

Course Management Software (Ct^S)To help facilitate the development of online and Web-enhanced courses, severalinstitutions have adopted course management software or e-leaming systems (Pa-pastergiou, 2006). E-leaming systems are Web-based delivery applications thatassist in managing a course. Typical e-leaming systems, such as Blackboard, We-bCT, and Web Course in a Box, provide various communication and managementtools to facilitate leaming in a Web-based setting. Educators can post announce-ments, assignments, and educational content as well as create and post onlineassessments. They can also track student performance, gauge student interaction,and manage student files. Blackboard is one of the most popular e-leaming sys-tems used by higher education institutions because it provides the framework forcourse delivery (Olsen, 2004; Perreault, 2004). The popularity of this platform isbased mainly on the fact that educators can utilize this system without having anycomputer programming experience (Elorriaga, n.d.; Getty, Burd, Bums, & Piele,2000). The user-friendly graphical user interface, which allows for ease of imple-mentation, is another major benefit of this software (Cartwright, 2000).Technology Acceptance ModelNumerous theories abound regarding the acceptance of an innovation. Davis,Bagozzi, and Warshaw (1989) introduced the Technology Acceptance Model(TAM). TAM is an adaptation of the Theory of Reasoned Action (TRA), a widelyresearched model developed by Fishbein and Ajzen (1975) involving the deter-minants of consciously intended behaviors. Specifically, TAM promotes that twoparticular beliefs, perceived usefulness and perceived ease of use, are of primaryrelevance for computer acceptance behaviors. Perceived usefulness (U) is definedas the user's subjective probability that using a specific application system will in-crease his or her performance. Perceived ease of use (EOU) refers to the degree towhich the user expects the application system to be effortless. TAM proposes thata person's behavioral intention to use computers (BI) is determined by the person'sattitude toward using the application system (A), perceived ease of use (EOU) andperceived usefulness (U) (Davis, Bagozzi, & Warshaw, 1989).

6 BUSINESS EDUCATION DIGEST

The Influence ol Computer and Internet Access on E-learning Technology Acceptance

The Digital DivideWith the dawning of the information age, evidence shows that a disparity existsamong technology usage between different socioeconomic groups (Lewis, 2007).The review of literature involving the digital divide tends to evolve around twocentral themes: computer access and Internet access. Prior research regardingcomputer access revealed inequalities of technology access in relation to variablessuch as race/ethnicity, education, geography, income, age, and disability Studiesfocusing on race/ethnicity revealed that underserved communities including His-panics, African-Americans, and Native Americans were less likely to have homeaccess to a computer and the Internet than their white counterparts (Hoffman& Novak, 1998; National Telecommunications and Information Administration[NTIA], 1999). The National Telecommunication and Information Administration(NTIA) published a study from 1997 data obtained from the US Census Bureau.The data were compiled from 48,000 door-to-door surveys (NTIA, 1999). Theresults revealed that White households were more than twice as likely (40.8%) toown a computer as Black (19.3%) or Hispanic (19.4%) households. When factor-ing income levels. Whites were more likely to have computers (76.3%) than Blacks(64.1%) even at the $75,000 or higher income level. Additionally, Whites (21.2%)were nearly three times as likely to have Internet access compared to Blacks (7.7%)or Hispanics (8.7%).

Using the Spring 1997 CommerceNet/Nielsen Internet Demographic Study(IDS) primary data, Hoffman and Novak (1998) examined racial differences in In-ternet access and use of 5,813 respondents in the United States aged 16 and overThe study concluded that Whites were more likely than African Americans to havea home computer and slightly more likely to have computer access at work. In anadditional study using the IDS data, Hoffman and Novak (1999) focused on thedifferences in Web usage and access among different ethnic and socioeconomicgroups at three different points in time between the spring of 1997 and the springof 1998. The findings confirmed previous studies that revealed disparities in homecomputer access as well as school computer access.

More recent literature regarding computer access reveals more promising statis-tics. According to a study conducted by the National Center for Education Statis-tics (NCES) (2005), great improvements have been made in providing computeraccess to U.S. students in the public classroom. The study used a survey to deter-mine the availability and use of technology in schools. The results revealed 99%of U.S. public schools offered Internet access, up from 3% in 1994. Not only hasthere been a surge in Internet access among schools, the number of instructionalcomputers per child has also improved. The researcher for this study concludedthat in 2003, the ratio of students to computers with Internet access was 4.4 to 1in contrast to a 12 to 1 ratio in 1998.

Although tremendous strides have been made in recent years regarding tech-nology in public schools, differences in the use of computers continue to exist



when students retum home. Home computer access is a major problem for manydisadvantaged students. According to another study conducted by the NCES(2003a), 41% of Blacks and Hispanics use a computer at home compared to 77%of Whites. In addition, families earning less than $20,000 are less likely to usecomputers at home (31%) than those families earning more than $75,000 (89%).These statistics suggest that the digital divide continues to exist and that the rootcause may lie in economic status.

MethodologyThe population for this study included business students at two AACSB accreditedinstitutions referred to as School A and School B located in North Carolina. Theresearcher collected 583 out of 700 usable surveys from the institutions. To obtaincontact information for the study, all professors in the business schools at bothuniversities who taught introductory business courses were contacted via e-mail.The E-Leaming Technology Acceptance (ETA) instrument was developed usingthe Technology Acceptance Model and the Course Web site Acceptance Model(Davis, Bagozzi, & Warshaw, 1989; Selim, 2003) as guides. The survey was mod-eled after a questionnaire developed by Stoehl and Lee (2003) that was createdto study student Web-based technology experience and its effect on technologyacceptance. The HoUingshead (1975) four-factor index, used to measure socioeco-nomic status (SES), was also included in the ETA.

The ETA measured four technology acceptance constructs: perceived useful-ness, perceived ease of use, attitude, and intention to use. Likert scales rangingfrom strongly disagree (1) to strongly agree (5) were used to measure responses.The instrument was initially pilot tested for validity and reliability using a groupof 20 participants who were excluded from the population. The Cronbach alphalevels for each construct resulted in a reliability of .85 or better. After receiving par-ticipant consent, the survey was administered to college business students duringa class session. The results of the pilot study prompted the researcher to revisesome of the open-ended demographic questions to multiple-choice questions inan effort to obtain complete responses.

A personnel list was used to randomly contact the faculty who taught intro-ductory business courses at both institutions during the Spring 2005 semester torequest permission to visit the classes. Class visits were scheduled to administerthe survey to the students of all business professors who agreed to participate. Theresearcher continued to conduct class visits until the list of professors willing toallow class visits was exhausted. To increase participation, a follow-up e-mail wassent to the professors who chose not to participate. The researcher also phoned theinstructors to encourage participation. These follow-up procedures resulted in thecooperation of two additional professors. The data selected resulted in a responserate of 71 percent.

Hierarchical regression analysis was used to determine the relationship



between the independent variables (race, SES, computer access, and Internetaccess) and the dependent variables (perceived usefulness, perceived ease ofuse, attitude, and intention to use) of this study. Two regression models wereperformed to compute the variance of each set of added variables. The hierar-chical regression used the theoretical framework which suggests variables suchas race and socioeconomic status both influence technology acceptance. Thesetwo independent variables were entered first to control for them. The variable ofinterest, computer access was entered last. Separate regression analysis was con-ducted for each dependent variable. These steps were repeated to test Internetaccess in the regression model.

Findings

Demographic DataA total of 583 business students provided usable responses to the E-leaming Tech-nology Acceptance (ETA) survey. The majority (54%) of the students were lowerclassmen (315 freshmen and sophomores), while 46% of the students were upperclassmen. Fifty-four percent of the students were male and 46% were female. Themajority (59%) of the respondents classified themselves as Black. Thirty-four per-cent of the students classified themselves as White, while 7% reported themselvesas Hispanic, Asian, Pacific Islander, or other.

While 35% of the respondents reported total family income under $35,000,38% of the respondents reported incomes between the ranges of $35,000-$74,999. Nineteen percent of the respondents reported an income over $75,000but less than $100,000; only 9% reported having a family income from $100,000to $200,000 or more. Because of the way the question was asked, the researcherscould not determine whether the reported income was that of the respondent'sfamily of origin or that ofthe individual respondent. Eor the purpose of data analy-sis, the researchers made the assumption that the responses about family incomereferred to the parents' income.

Technology Acceptance FactorsE-leaming technology acceptance was measured using four constructs: perceivedusefulness, perceived ease of use, attitude, and intention to use. The results ofthe hierarchical regression for perceived usefulness revealed that computer ac-cess insignificantly explained only 1.2% of the variance of perceived usefulnessabove and beyond the variance explained by race and socioeconomic status (seeTable 1). Internet access only explained 1.3% of the variance of perceived useful-ness (see Table 2).



Table 1. Results o/thc Hierarchical Regression ojthe Perceived Usefulness Variable in Regard toComputer Access

Model 1SES, RaceModel 2computer access

R SOUARED CHANGE

.033

.012

F-CHANGE

7.22

1.32

SIGNIFICANCE

.001

.262

Table 2. Results ofthe Hierarchical Regression ofthe Perceived Usefulness Variable in Regard toInternet Access

Model 1SES, RaceModel 2Internet access

R SOUARED CHANGE

.034

.013

F-CHANGE

739

1.89

SIGNIFICANCE

.001

.131

Regression analysis of the ease of use variable concluded that computer accesssignificantly explained 6.4% of the variance of ease of use above and beyond thevariance explained by race and socioeconomic status. Internet access significantlyexplained 3.8% ofthe variance of ease of use. See Table 3 and Table 4 respectivelyfor detailed statistics.

Table 3. Resu/is ofthe Hierarchical Regression of the Ease of Use Variable in Regard to Computer Access


RSQUARED CHANGE

.007

.064

F-CHANGE

1.42

7.17

SIGNIFICANCE

.243

The Influence ot Computer and Internet Access on E-learning Technology Acceptance

plained 4.9% of the variance of the attitude variable. These results are displayed inTable 5 and Table 6 respectively.

Table 5. Results ofthe Hierarchical Regression ofthe Attitude Variable in Regard to Computer Access


R SQUARED CHANGE

.012

.074

F-CHANGE

2.60

8.47

SIGNIFICANCE

.075


Conclusions and Discussion of Findings

Digital DivideWhile the findings from this study did not clearly reveal whether a digital divideregarding computer use existed among the respondents based on their socio-economic status, several conclusions can be made about this issue. Overall, asmall percentage of the respondents of this study reported a lack of computerownership and Internet access. However, the students from the predominatelyWhite institution (School B) had a higher level of computer ownership than thestudents from the predominately Black institution (School A). In addition, thestudents from School B had higher family incomes than those from School A.These findings suggest that socioeconomic status (SES) and race may be indica-tors of computer access.

Ease of Use Perceptions about Blackboard and the InternetBased on the results of this study, another conclusion that can be drawn is that thedegree of computer and Internet access of these business students impacts theirperceptions about how easy it is to use e-leaming tools such as the Intemet andcourse management systems, specifically Blackboard. Whether students perceivedBlackboard and the Intemet to be easy to use was also influenced by the frequencyof computer and Intemet use. As might be expected, this suggests that perceivedease of use of Blackboard and the Intemet may increase as students spend moretime using the computer and the Intemet. Levine and Donitsa-Schmidt (1998)concluded that more computer use has a positive effect on perceived computerself-confidence. In addition, Reznich (1996) revealed that increased computer usedecreased anxiety in word processing courses. Therefore, when teaching e-leam-ing courses, instructors should consider the level of computer access and Intemetaccess students have. Upon assessing students' level of technology access, alteringthe strategies and assignments used when delivering the course may be needed.For example, providing self-paced activities would alleviate the anxiety that somestudents face when taking e-leaming courses. Group assignments and projectsmay also improve self-confidence.

Attitudes about Blackboard and the InternetStudents' attitudes toward using Blackboard or the Intemet are impacted bytheir level of computer and Intemet access. Students' feelings about using thesetechnological tools may be influenced by whether they own a computer or theamount of computer and Internet access they have on their campus. The findingsof this study are supported by prior research that indicates a positive attitudetoward computers is a crucial factor in helping students to learn computer tech-nologies (Anderson & Reed, 1998; Zhang & Espinoza, 1998; Carey, Chisholm,& Irwin, 2002). Thus, initiating strategies to increase computer and Intemet ac-cess may improve student attitudes, which may in tum impact students' ability


the Influence of Computer and Internet Access on E-learning Technology Acceptance

to leam using e-leaming technologies. Educators must incorporate technologyin the teaching and leaming process as often possible to increase exposure andimprove computer literacy.

Beyond the Digital DivideWhile the results of the hierarchical regression model revealed statistically insig-nificant findings about whether computer access influences student perceptionsof Blackboard and Intemet usefulness in improving class performance, the resultsdid indicate that SES and race significantly impacted students' perceptions of theusefulness of these tools. In addition to this finding, the results of this study re-vealed that computer access does not influence students' intention to use e-leam-ing technology.

These findings suggest that computer access is not enough to close the digi-tal divide. Research has shown that simply providing students with technologydoes not guarantee that the students will use it (Blau, 2002). Thus, the morerealistic issue that needs to be addressed is digital inclusion. To assist in themovement toward digital inclusion, career and technical educators must con-tinue to provide students with the technical skills needed to use the technology.In addition, educators must design courses that encourage the use of technologyin and out of the classroom.

Recommendations for Further ResearchAge was not considered a variable of interest in this study. However, the respon-dents from the predominately black institution (School A) were generally youngerthan those fi-om the predominately white institution (School B). Numerous studieshave been conducted investigating the relationship between generational age andtechnology. According to Karuppan (2001), younger students are more likely touse the Intemet than older students. However, investigating how race impacts thisrelationship would be interesting.

After analyzing the responses of the participants in this study, the data revealedthat many of the respondents opposed the use of Blackboard as an effective learn-ing tool. Considering that Blackboard is one of several commercially marketedcourse management systems, investigations into whether another system wouldreveal more positive levels of agreement in regard to technology acceptance mightbe needed. For example, an innovative alternative called "open source" coursemanagement software is now available (Olsen, 2003). Open source course man-agement software is free to users and is developed through partnerships betweencommercial companies and academic educators from leading technical institu-tions. If open source course management software is the future trend, determiningthe level of acceptance of this type of software among both students and facultymay be helpful.



ReferencesAllen, I., & Seaman, J. (2004). Entering the mainstream: The quality and extent

of online education in the United States, 2003 and 2004. Retrieved April 15,2005 from http://sloan-c.org/resources/entering_mainstream.pdf

Anderson, D. K., & Reed, W. M. (1998). The effects of Intemet instruction, priorcomputer experience and learning style on teachers' Intemet attitudes andknowledge. Journal of Educational Computing Research, 190), 227-246.

Beard, L., & Harper, C. (2002). Student perceptions of online versus on campusinstruction. Education, 122(4), 658-664.

Bennett, G. (2001). Student learning in the online environment: No significantdifference? Quest, 53(1), 13.

Blau, A. (2002). Access isn't enough. American Libraries, 33(6), 50-52.Carey, J., Chisholm, 1. & Irwin, H. (2002). The impact of access on perceptions

and attitudes towards computers: An international study. Education Media In-ternational, 39(3-4), 223-235.

Cartwright, A. (2000). Blackboard experience of a chemistry teacher. Journal ofChemical Education, 77(6), 699.

Davis, R, Bagozzi, R., & Warshaw, R (1989). User acceptance of computer tech-nology: A comparison of two theoretical models. Management Science, 35(8),982-1003.

Elorriaga, M. (n.d.). Blackboard 5. elxam Magazine. Retrieved October 21, 2004from the World Wide Web: http://www.eleammag.org/subpage/sub_page.cfm?section=6&list_item=2&page=l

Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduc-tion to Theory and Research. Reading, MA: Addison-Wesley.

Getty, N., Burd, B., Bums, S & Piele, L. (2000). Using courseware to deliver li-brary instruction via the web: Four examples. Reference Services Review, 28(4),349-359.

Glenn, J. (2005). Achieving tech equity: Three gaps, three sets of solutions. Busi-ness Education Eorum, 59(4), 8-14.

Hoffman, D. L., & Novak, T. R (1998). Bridging the Racial Divide on the Intemet.Science. 280, 390-391.

Hoffman, D., & Novak, T. (1999). The growing digital divide: Implications for anopen research agenda. Retrieved July 20, 2005, from http://search.markle.org/cgi-bin/ts.pl



HoUingshead, A. B. (1975). Eour factor index of social status. Unpublished manu-script, Yale University, New Haven, CT.

Huang, H. (2002). Student perceptions in an online mediated environment. Inter-national Journal of Instructional Media, 29(4), 405-420.

Hutchins, H. (2007). Minimizing "distance" in online courses: strategies to sup-port leamer interaction in marketing education courses. Business Education Eo-rum, 61(3), 54-58.

Imel, S. (1998). Myths and realities. (Report No. BBB16032). Columbus, OH. ERICClearinghouse on Adult, Career, and Vocational Education.

James, M., & Voigt, M. (2001). Tips from the trenches: Delivering online courseseffectively. Business Education Eorum, 55(3), 56-57.

Karuppan, C. (2001). Web-based teaching materials: A user's profile. Intemet Re-search: Electronic Networking Applications and Policy, 11(2), 138-148.

Levine, T. and Donitsa-Schmidt, S. (1998). Computer use, confidence, atti-tudes, and knowledge: A causal analysis. Computers in Human Behavior, 14(1),125-146.

Lev^ds, A. (2007). Digital divides the poor. Education Digest, 72(5), 71-72.McArthur, D., Parker, A., & Giersch, S. (2003). Why plan for e-leaming? Planning

Higher Education, 31(4), 20-28.National Center for Education Statistics (2005). Intemet access in U.S. public schools

and classrooms: 1994-2003. Washington, DC: Department of Education. Re-trieved April 28, 2005 from http://nces.ed.gov/pubs2005/2005015.pdf

National Telecommunications and Information Administration (NTIA) (1999).Falling through the net: Defining the distal divide. A report on the telecommunica-tions and information technology gap in America. Washington, DC: Department ofCommerce. Retrieved July 20, 2005 from http://www.ntia.doc.gov/ntiahome/net2/falling.html

Olsen, F. (2003). Sharing the code. The Chronicle of Higher Education, 49(47),A31-A32.

Olsen, F. (2004). Course management: Colleges push for an open approach. TheChronicle of Higher Education, 50(21), BIO, B12.

Papastergiou, M. (2006). Course management systems as tools for the creation ofonline leaming environments: evaluation from a social constructivist perspec-tive and implications for their design. Intemational Joumal on E-Leaming, 5(4),593-623.

Perreault, H. (2004). Online course development for business education. In D.Christopher & S. Jaderstrom (Eds.), NBEA 2004 Yearbook, 42, 1-12,

Issue XV/May 2007 15


Phipps, R., & Merisotis, J. (2000). Quality on the line: Benchmarks for success in In-temet-based distance education. Institute for Higher Education Policy. RetrievedMarch 10, 2003 from http://www.ihep.com/quality.pdf.

Reznich, C. (1996). Applying minimalist design particles to the problem of com-puter anxiety. Computers in Human Behavior, 12, 2, 245-61.

Russell, T. L. (1999). The no significant difference phenomenon. Raleigh: North Caro-lina State University, Office of Instructional Telecommunications.

Ryan, M., Carlton, K., & Ali, N. (1999). Evaluation of traditional classroom teach-ing medthods versus course delivery via the world wide web. Joumal of NursingEducation, 38(6), 272-77.

Selim, H. (2003). An empirical investigation of student acceptance of course web-sites. Computers & Education, 40(4), 343-60.

Smeaton, A., & Keogh, G. (1999). An analysis of the use of virtual delivery of un-dergraduate lectures. Computers & Education, 32, 83-94.

Stoehl, L., & Lee, K. (2003). Modeling the effect of experience on student accep-tance of Web-based courseware. Intemet Research: Electronic Networking Applica-tions and Policy, 13(5), 364-374.

Theriot, P. (2004). Student values and ethics in an e-leaming environment. In D.Christopher & S. Jaderstrom (Eds.), NBEA 2004 Yearbook, 42,13-25.

Vail, K. (2003). Next generation divide. American School Board Joumal, J90(l),14-17.

Willis, B. (1993). Distance education: A practical guide. Englewood Cliffs, NJ: Educa-tional Technology Publications, 17.

Zeliff, N. (2004). Pedagogical and technological challenges of the Intemet. In D.Christopher & S. Jaderstrom (Eds.), NBEA 2004 Yearbook, 42, 67-88.

Zhang, Y., & Espinoza, S. (1998). Relationships among computer self-efficacy, at-titudes toward computers, and desirability of leaming computing skills. Joumalof Research on Computingin Education, 30(4), 421-436.


the influnece of computer and internet access on e-learning technology acceptance

Documents

computer access

business students

takeonline courses

distance learning

webenhanced courses

based orhybrid courses

inwebbased courses

leaming tools