EJISDC (2010) 41, 5, 1-17
DEMOGRAPHIC IMPLICATIONS FOR THE USER-PERCEPTIONS OF E-LEARNING
IN HIGHER EDUCATION INSTITUTIONS...
EJISDC (2010) 41, 5, 1-17 2
demographic groupings have been tested on the six research variables through the application
o...
EJISDC (2010) 41, 5, 1-17 3
3. Learning management systems (LMS) for performance management, employee
development plans, f...
EJISDC (2010) 41, 5, 1-17 4
Bataineh & Abdel-Rahman, 2006; Martin & Dunsworth, 2007; Mehra & Mital, 2007).
Several factors...
EJISDC (2010) 41, 5, 1-17 5
2.3 List of Variables
Research Variables
Variables Attributes (32 + 6 demographic Questions) C...
EJISDC (2010) 41, 5, 1-17 6
H1: Teachers score higher than students and administrators.
H2: Non-Computer respondents score...
EJISDC (2010) 41, 5, 1-17 7
3.4 Data Analysis and Validity
SPSS 12.0 has been used to create a database of primary data fo...
EJISDC (2010) 41, 5, 1-17 8
Testing of Hypothesis about the Demographic Impacts (Six Hypotheses about the
impact of Demogr...
EJISDC (2010) 41, 5, 1-17 9
eLearning in their perceptions and attitudes because respondents with computer as a subject
ha...
EJISDC (2010) 41, 5, 1-17 10
Perceptions about the Use Practices -1.725 .085
Perceptions of the Problems of eLearning -3.7...
EJISDC (2010) 41, 5, 1-17 11
Furthermore, the change management aspect of eLearning occurs in a particular
context. The co...
EJISDC (2010) 41, 5, 1-17 12
6. CONCLUSIONS
The research reveals that demographic factors play a moderating role in the re...
EJISDC (2010) 41, 5, 1-17 13
Baumeister, H. (2006) Networked Learning in the Knowledge Economy - A Systemic
Challenge for ...
EJISDC (2010) 41, 5, 1-17 14
Graff, M., Davies, J. & McNorton, M. (2001) Cognitive Style and Cross Cultural
Differences in...
EJISDC (2010) 41, 5, 1-17 15
Memon, G. R. (2007) Education in Pakistan: The Key Issues, Problems and the New
Challenges, J...
EJISDC (2010) 41, 5, 1-17 16
Tinio, V.L. (2002) ICT in Education. Presented By UNDP for the Benefit of
Participants To The...
EJISDC (2010) 41, 5, 1-17 17
Appendix 1 List of Research & Demographic Variables
Research Variables
1. Perceptions about t...
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Demographic implications for the user perceptions of e-learning in higher education institutions of n-w.f.p, pakistan

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Demographic implications for the user perceptions of e-learning in higher education institutions of n-w.f.p, pakistan

  1. 1. EJISDC (2010) 41, 5, 1-17 DEMOGRAPHIC IMPLICATIONS FOR THE USER-PERCEPTIONS OF E-LEARNING IN HIGHER EDUCATION INSTITUTIONS OF N-W.F.P, PAKISTAN Allah Nawaz Dept. of Public Administration Gomal University, Khyber Pakhtunkhwa Pakistan profallahnawaz@yahoo.com Ghulam Muhammad Kundi Dept. of Public Administration Gomal University, Khyber Pakhtunkhwa Pakistan kundi@gu.edu.pk ABSTRACT There are documented differences between the success and failure factors in the developed and developing countries with regard to the development and use of eLearning in Higher Education Institutions (HEIs). These differences are widely attributed to the demographic variations in the context of eLearning development and use. Unless these differences are skillfully identified and accommodated as such into the development and use models, eLearning efforts are reported to be associated with problems in the construction, use and progress of the eLearning environments in the institutions for teaching, learning and administrative purposes. This study is an exploration of the demographic diversities in the HEIs of NWFP, Pakistan to document their impacts on perceptions of the teachers, students and administrators about the nature and roles of eTeaching, eLearning and eEducation. Keywords: Educational Technologies, HEIs, User-Perceptions, eTeaching, eLearning, eEducation, eMaturity, Demographics-impacts 1. INTRODUCTION There is a continuum of perceptions and attitudes of eLearning-users, with those who dislike information and communication technologies (ICTs) on one extreme and those who are their promoters on the other end, while many groups can be located at different points between the two extremes. The research reveals that these differences in attitudes stem from the contextual factors relating to individual, group and organizational characteristics. Mehra & Mital (2007) note that within a university, the context for eLearning consists of human attributes of teachers, students and administrators (age, gender, qualification, perceptions, experience with computers etc.) and organizational characteristics (policies, resources, management, culture and age of the institute). In the context of developing countries, the results are quite similar to developed states in many ways, but different at the broader level. In a study of Jordanian University, it was found that use of computers seems to have little or no effect on teachers' beliefs about their use of technology in their actual teaching practice (Bataineh & Abdel-Rahman, 2006). In Barbados, there are favorable attitudes toward using ICTs as a supplement and not as a replacement to traditional teaching (Gay et al., 2006). In Malaysia, ICT is more commonly used as a source of information and support learning in the traditional classroom as a tool. It is reported that the use of ICT for communication between students and lecturers, and between lecturers is still not widespread (Mokhtar et al., 2007). For example, “HEIs use computers every day to send e-mail, compose texts with word processing, and search the Web, however, very few use it to enhance their teaching” (Kopyc, 2007). The study under discussion records the impacts of user-characteristics on his/her perceptions and thus attitudes in relation to the educational technologies. The impacts of six The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  2. 2. EJISDC (2010) 41, 5, 1-17 2 demographic groupings have been tested on the six research variables through the application of t-Test procedures to determine the significance of group-mean-differences for recording the impacts of user-attributes on their perceptions and attitudes about the eLearning tools and techniques in HEIs. 2. LITERATURE REVIEW The educational applications of ICTs are multiple; starting from a simple information delivery (for example, accessing an online catalogue of a digital library) and ending with modern uses of cognitive tools (Web 2.0 technologies) and ‘adaptive technologies to support and enhance the learning process (Sirkemaa, 2001). eLearning covers a continuum of educational applications with Word, Excel, Access and PowerPoint as the main gadgets on one end with no or little impact on teaching, learning and administrative practices. On the other extreme are the virtual learning environments with web-based applications and virtual lecture halls having far reaching impacts on teaching, learning and education management (Sife et al., 2007). 2.1 eLearning in HEIs eLearning is widely researched in the perspectives of “higher education as well as corporate training (Tinio, 2002)” and explained as the 'application of electronic technologies’ in supporting, enhancing and delivering teaching and learning (Gray et al., 2003). ICTs represent computers, networks, software, Internet, wireless and mobile technologies to access, analyze, create, distribute, exchange and use facts and figures in a manner that has been unimaginable hitherto (Beebe, 2004). A number of concepts are interchangeably used to represent eLearning: computer-based instruction, computer-assisted instruction, web-based learning, electronic learning, distance education, distance learning, online instruction, multimedia instruction, online courses, networked learning, virtual classrooms, computer mediated communication, Technology supported education/learning and technology uses in education (Tinio, 2002; Abrami et al., 2006; Baumeister, 2006; Manochehr, 2007; Sife et al., 2007; Wikipedia, 2009). HEIs have passed through three stages of evolution and growth: 1. traditional computer-based learning (supplemental use of ICTs); 2. blended (mixed) learning; and 3 virtual learning. These lie on the continuum of two extremes with one extreme of low-tech applications and on the other end are hi-tech environments while in the middle are different forms of blended learning (see for example, Oliver, 2002; Young, 2003; Beebe, 2004; Heinze & Procter, 2006; Manochehr, 2007). HEIs, particularly in developing countries, are voyaging through different levels of blended learning with multiple experimental applications of ICTs in teaching, learning and education management due to the varying availability and accessibility of educational technologies and professionalism of their use. 2.2 User-Perceptions 2.2.1 Educational Technologies Dinevski & Kokol (2005) give a broader classification of educational technologies into: 1. Infrastructure including Computers, Networks; Internet, Intranet and facilities for offline/online access and user interfaces. 2. Content management systems (CMS) for delivery, tracking, management and reporting of online content. The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  3. 3. EJISDC (2010) 41, 5, 1-17 3 3. Learning management systems (LMS) for performance management, employee development plans, financial and activity tracking/reporting, and integration with other systems. 4. Learning technologies for mentoring, chatting, forums, discussions, Web seminars, online meeting and virtual classroom sessions. 5. m(mobile)-learning technologies are enabling learning anywhere and anytime. With the Internet and ICTs available to teachers and students, its integration into education becomes increasingly indispensable (Oh & French, 2004). Internet-based education can contribute to substantial improvements in education (Laffey and Musser, 2006). New communication-tools like e-mail, bulletin boards, etc., provide more reflective and useful interactions among learners, instructors and resources (Arulchelvan & Viswanathan, 2006). Internet tools like Web 2.0, virtual reality applications, videogames and mobile devices are commonly used for communication, entertainment, and learning (Chan & Lee, 2007). Internet provides access to online information along with traditional technologies (Klamma et al., 2007). The multiplicity of perceptions about the nature and role of ICTs in HEIs can be grouped into two broad user-theories or beliefs, which guide most of the eLearning development and use practices around the globe: 1. Instrumental theory: It is the most commonly held belief to view ICTs as a ‘tool’ without any inherent value (neutral) and its value lies in how is it used so a one-size- fits-all policy of universal employment of ICTs (Macleod, 2005; Radosevich & Kahn, 2006). Instrumental education is based on the premise that education serves society so emphasis is placed on the relevance, utility, and contribution of education to the economy. The risk of this approach is that students simply meet some identified need, rather than think critically to achieve personal or communal advancement (Ezer, 2006). 2. Substantive theory: This is a determinist or autonomous approach, which argues that technology is not neutral, rather has positive or negative impacts. Technological determinism suggests that mere presence of technology leads to its standard applications, which in turn bring social change (Macleod, 2005; Radosevich & Kahn, 2006). The substantive theory matches with the ‘liberal theory’ of education (Ezer, 2006), which views learning as an active and interconnected experience and not simply a recollection of facts. 2.2.2 Development and Use Practices The effective integration of ICTs into the educational system is a complex, multifaceted process that involves not just technology but also curriculum and pedagogy, institutional readiness, teacher competencies, and long-term financing, among others (Tinio, 2002). The growth of innovative practices in eLearning has contributed to the development of new skills and competencies and novel ways of using them within project teams (Gray et al., 2003). However, design and development principles need to be aligned with teachers’ understanding of student requirements (Young, 2003; Nyvang, 2006). Given the differences of perceptions about ICTs, eProjects for eLearning become challenging and uphill adventures where developers have to consider a variety of factors (variables) including development approaches and attitudes, project management techniques, user participation, user training, change management and the context within which the development and use of eLearning is about to happen. Research is going on about the factors that affect the user decisions in using computers in teaching, learning and education management (Marcella & Knox, 2004; The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  4. 4. EJISDC (2010) 41, 5, 1-17 4 Bataineh & Abdel-Rahman, 2006; Martin & Dunsworth, 2007; Mehra & Mital, 2007). Several factors have been identified as the determinants of the volume and intensity of using eLearning tools by teachers, students and administrators, for example: 1. Demographic factors (like age, educational background, gender etc); 2. Experience in use of instructional technology, perception about 3. Perceived Usefulness: encouraging interaction, teaching more systematic, creativity in the faculty and the students, intellectual enhancement of the faculty and students (Bataineh & Abdel-Rahman, 2006; Mehra & Mital, 2007) 4. Perceived Ease of use: teaching process less personal, intimidating, highly training intensive, time saved in lecture preparation) (Marcella & Knox, 2004; Mehra & Mital, 2007). 2.2.3 Problems Associated with eLearning “More than half of all information technology projects become runways – overshooting their budgets and timetables while failing to deliver on their goals” (McManus & Wood-Harper, 2004:3). Similarly, “While networked learning is making its appearance in universities, its overall impact is, as yet, rather limited” (Baumeister, 2006). Several researchers have identified problems associated with the development, use and integration of ICTs into teaching, learning and educational management (see for example, Drinkwater et al., 2004; Bondarouk, 2006; Vrana, 2007; Kanuka, 2007; Sife et al., 2007; Wells, 2007) such as: 1. Inertia of behavior of users, like their resistance to changes, etc. 2. Underestimation, lack of awareness and negative attitudes towards ICTs. 3. Lack of systemic approach to implementation and lack of follow-up. 4. High rates of system non-completion and user dissatisfaction with new systems 5. Lack of user-training and lack of administrative and technical end-user support. 6. Mismatches between technologies and the context, culture and work practices. 2.2.4 Prospects Associated with eLearning in HEIs Education determines, more than anything else, a country's prospects for human development and competitiveness. Fortunately, the information revolution offers some extraordinary opportunities in education (MoST, 2000). The perceptions about the nature and role of ICTs are very positive because several existing opportunities support this optimism (Tinio, 2002). The existing opportunities include the global availability of digital technologies; free and open source systems (FOSS); growing local ICT industry and professionals; local, national and international partnerships; emergence of information societies and digital cultures. For example, universities and even smaller departments within organizations are becoming able to afford sophisticated digital systems (Ezziane, 2007). The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  5. 5. EJISDC (2010) 41, 5, 1-17 5 2.3 List of Variables Research Variables Variables Attributes (32 + 6 demographic Questions) Code 1 Perceptions about Educational Technologies ICTs can solve the problems of teaching, learning and administrative); Reduce digital divide, Enhance academics and can bring social change. 8 Questions PET 2 Perceptions about Development Practices Availability of Hardware & Software; Availability of Networks, Internet, Technical Support and Adequate Training. 7 Questions PDP 3 Perceptions about Use of eLearning Perceived-use –PU; Perceived ease of use – PEU; Types of uses. 6 Questions PUE 4 Perceptions about Problems of eLearning Development and Use problems related to hardware, software, networks, training, technical support and cultural issues. 6 Questions PPE 5 Perceptions about Prospects Expected role of ICTs in teaching, learning and education management. 5 Questions PRS Demographic Variables 1 Respondent Type Teacher, Student, & Administrator RTP 2 Subject Computer & Non-Computer CNC 3 Sector Public & Private PPS 4 Gender Male & Female GDR 5 City Big and Small cities CTY 6 Experience Experience with computer EXP 2.4 Theoretical Framework & Hypotheses Figure 1: Theoretical Framework Note. There are 6 demographics and 5 research variables. Therefore 30 applications of tests of significance are used. H1 is computed by applying relevant test of significance (ANOVA) 5-times (can be considered as having 5 sub-hypotheses). If most of the results out of 5 are substantiated, the hypothesis is accepted. As in case of H1 4 out of 5 tests nullify the null hypothesis of no difference thus, H1 is accepted because 4/5 tests are successful. The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  6. 6. EJISDC (2010) 41, 5, 1-17 6 H1: Teachers score higher than students and administrators. H2: Non-Computer respondents score lower than those with computer as subject. H3: Public sector respondents score lower than those from Private sector. H4: Male respondents score higher than Female. H5: The respondents from Big city score higher than those from Small city. H6: The greater the experience with computers, the greater will be the score. 3. RESEARCH DESIGN 3.1 Survey Approach There is a huge body of studies both in developed and developing countries about the theories and practices of eLearning in HEIs both from qualitative and quantitative perspectives. The quantitative studies, which used survey approach to access the problem situation are many for example, by Irons et al., 2002, Luck & Norton 2005, Marcella & Knox (2004), Abrami et al., 2006, Johnson et al., 2006, Radosevich & Kahn (2006), Bataineh & Abdel-Rahman (2006), Thomas & Allen 2006, Mehra & Mital (2007), Martin & Dunsworth 2007, Garcia & Qin (2007), and DiCerbo (2007) – which are a few from a long list. Likewise, there are qualitative studies based purely on the secondary sources, for example, studies by Sasseville (2004), Valdez et al., (2004), and Davey & Tatnall (2007) are some of the examples. 3.2 Sample and Sampling Procedure The ‘Sample-Population’ for the study included all the HEIs in the cities of Peshawar and Dera Ismail Khan. These two cities were selected as the best representative samples because: 1. Peshawar represents a big city while D I Khan is an example of a small city – with 1.5 million inhabitants in comparison to Peshawar with 4 million inhabitants but with strong educational bases in the province. 2. Both the cities host two of the oldest universities of the province (University of Peshawar – 1950 and Gomal University - 1974). Similarly, they have the oldest as well as new universities in both the public and private sectors. 3. These institutions are populated with students, teachers and administrators from almost all cities and areas of the province. For the development of research project (synopsis), a pilot study was conducted to test the instrument and determine the appropriate sample size using a standard procedure – the researchers used formula (available in several books on social research) given for the purpose. 388 copies of the questionnaire were distributed among the teachers, students and administrators. The response rate was: teachers 137; students 132 and administrators 85 = 354 (92%). 3.3 Data Collection Literature survey was conducted to examine the existing research on the topic and extract variables and their mutual relationships from: Books (hard copies) and eBooks (off-line on CDs and online); Free and Open Source Systems (FOSS), i.e., eJournals. The researcher used the ‘Directory of Open Access Journals’ (doaj.org) and Wikipedia.org, Blogs and facebooks; and the websites of United Nations, International universities, Government of Pakistan and websites of the Universities’ in NWFP. For empirical data, a structured questionnaire was constructed based on the extracted variables. The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  7. 7. EJISDC (2010) 41, 5, 1-17 7 3.4 Data Analysis and Validity SPSS 12.0 has been used to create a database of primary data for applying statistical procedures to generate descriptive and inferential statistics and test the hypothesis. t-Tests were used to determine the significance of demographic impacts on the attitudes of different groups of respondents. The overall reliability of Cronbash’s alpha was estimated at 0.9288, with 354 cases and 38 survey items. This value exceeds the required minimum threshold suggested for the overall reliability test, i.e. 0.7 (Koo, 2008). 4. FINDINGS 4.1 Respondents’ Profile Following is the classification of the respondents according to their major demographic characteristics: Table 1: Demographic Data Demographic Groupings 1 Type of Respondents: Students = 132, Teacher = 137, Administrators = 85 2 Subject: Computer = 101, Non-Computer = 253 3 Sector: Public Sector = 180, Private Sector = 174 4 Gender=GDR): Male = 241, Female = 113 5 City (code=CTY): Dera Ismail Khan = 145, Peshawar = 209 6 Experience with Computer (code=EXP): (>=5) = 163, (<5) = 190 4.2 Summary Statistics of the Research Variables Table 2 Descriptive Statistics of Research Variables (n=354) Min Max Mean Std. D Perceptions about the Educational Technologies 3.18 6.55 4.7779 .57637 Views about the development practices 3.00 5.89 4.3082 .52236 Opinion about the use practices 3.10 6.75 4.7961 .58463 Perceptions of the eLearning problems 3.60 6.34 4.8207 .47971 Perceptions about the Prospects of eLearning 2.17 6.12 5.7359 .89704 Chart 1 Mean Scores on Demographic Groupings Average Scores on Demographic Groupings 4.92 5.01 4.63 5.55 4.87 4.81 4.97 4.98 4.69 4.73 4.95 5.05 4.75 4.00 4.20 4.40 4.60 4.80 5.00 5.20 5.40 5.60 5.80 StudentTeacher Adm inistratorC om puter N on-Com puter Public Private M ale Fem ale D IKPeshaw ar >= 5 < 5 Groups Scale The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  8. 8. EJISDC (2010) 41, 5, 1-17 8 Testing of Hypothesis about the Demographic Impacts (Six Hypotheses about the impact of Demographic-Groupings. The impacts of demographics on the user perceptions, theories and attitudes on the development and use of eLearning in higher education are well documented (see for example, Valcke, 2004; Gay et al., 2006; Wims and Lawler, 2007; Moolman and Blignaut, 2008). The developers of eLearning environments are constantly advised by the researchers to address demographic differences regarding the use of ICTs and develop strategies for generating and sustaining positive learner attitudes for effective uses of eLearning environments (Gay et al., 2006). The differences are based on the user- characteristics of gender, age, educational level, computer skills, previous experience with eLearning as well as learning styles, personal goals and attitudes, preferences, cultural background, experience, motivation (Moolman & Blignaut, 2008). Hypothesis # 1 Teachers score higher than students and Administrators. Table 3 Results of ANOVA Applications on Respondent Type (RTP) Sum of Squares df Mean Square F Sig. PET Between Groups 4.748 2 2.374 7.406 .001 Within Groups 112.519 351 .321 PDP Between Groups 16.783 2 8.391 37.032 .000 Within Groups 79.537 351 .227 PUE Between Groups .561 2 .280 .820 .441 Within Groups 120.090 351 .342 PPE Between Groups 10.651 2 5.326 26.485 .000 Within Groups 70.581 351 .201 PRS Between Groups 17.329 2 8.665 11.402 .000 Within Groups 266.725 351 .760 Hypothesis 1 was accepted in the sense that teachers score significantly higher than students and administrators. The ANOVA application gives significant differences of means between the three groups on all the variables except Use practices (F = .82 with p = .441, far more than required significance of .05) where they all hold the same opinion. Hypothesis # 2 Non-Computer respondents score lower than those who study computer. Table 4 T-tests on Computer and Non-Computer (CNC) T Sig. (2-tailed) Perceptions about the Educational Technologies 12.946 .000 Perceptions about the Development Practices 8.504 .000 Perceptions about the Use Practices 14.656 .000 Perceptions of the Problems of eLearning 12.955 .000 Perceptions about the Prospects of eLearning 6.547 .000 IMPACTS 100% Table-value at 0.05 Significance level with 352 df = 1.96 This classification brings out very visible influences on the groups. The p-values on all the tests are .000 which confirms the impact of groupings on the respondents. Thus, respondents with computer background are totally different from the non-computer users of The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  9. 9. EJISDC (2010) 41, 5, 1-17 9 eLearning in their perceptions and attitudes because respondents with computer as a subject have scored higher than their counterparts on all five research variables, so Null hypothesis stands ineffective. Hypothesis # 3 Public sector respondents score lower than the private. Table 5 T-tests on Public & Private Respondents (PPR) t Sig. (2-tailed) Perceptions about the Educational Technologies -3.938 .000 Perceptions about the Development Practices -2.375 .018 Perceptions about the Use Practices -4.984 .000 Perceptions of the Problems of eLearning -2.740 .006 Perceptions about the Prospects of eLearning -.765 .445 IMPACTS 80% Table-value at 0.05 Significance level with 352 df = 1.96 The difference of being in public or private sector is also significant. 4 out of 5 tests are positive showing changes in the responses except on ‘Perceptions about the prospects of eLearning’. Null hypothesis is therefore rejected because private sector respondents score higher than the public sector on all the variables. It also indicates that private sector respondents are more involved in eLearning than the public sector subjects. The alternative hypothesis is thus substantiated. Hypothesis # 4 Males score higher than female respondents. Table 6 T-tests on Males and Females (GDR) t Sig. (2-tailed) Perceptions about the Educational Technologies 5.156 .000 Perceptions about the Development Practices 1.885 .060 Perceptions about the Use Practices 6.933 .000 Perceptions of the Problems of eLearning 4.730 .000 Perceptions about the Prospects of eLearning 1.998 .046 IMPACTS 80% Table-value at 0.05 Significance level with 352 df = 1.96 Gender effects have very widely been identified by the researchers from developed and developing countries with positive results showing that gender is a good predictor of using eLearning tools in HEIs round the globe (Graff et al., 2001; Irons et al., 2002; Thomas & Allen, 2006; Abrami et al., 2006; Cagiltay et al., 2006; Tubaishat et al., 2006). In this research, Male and Female respondents have significant difference of perceptions about four of the research variables except ‘Views about the Development Practices’. Therefore, Null hypothesis is rejected. Hypothesis # 5 Respondents from big city score higher than those from small city. Table 7 T-tests on Big and Small City Respondents (CTY) T Sig. (2-tailed) Perceptions about the Educational Technologies -3.546 .000 Perceptions about the Development Practices -.695 .488 The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  10. 10. EJISDC (2010) 41, 5, 1-17 10 Perceptions about the Use Practices -1.725 .085 Perceptions of the Problems of eLearning -3.761 .000 Perceptions about the Prospects of eLearning -2.637 .009 IMPACTS 60% Table-value at 0.05 Significance level with 352 df = 1.96 The respondents from both the cities have no difference of opinion about the ‘development and use practices’ (two variables) indicating that the same type of development and use practices is prevalent irrespective of big and small cities. However, the respondents have significantly different views on three of the research variables: Perceptions about educational technologies, problems and prospects showing the difference of eLearning facilities and environment or greater eMaturity of big city (Moolman & Blignaut, 2008). Thus, we reject the Null hypothesis. Hypothesis # 6 Greater the experience with computers, greater will be the score. Table 8 T-tests on Experience of User (EXP) T Sig. (2-tailed) Perceptions about the Educational Technologies 6.758 .000 Perceptions about the Development Practices 6.360 .000 Perceptions about the Use Practices 4.354 .000 Perceptions of the Problems of eLearning 5.369 .000 Perceptions about the Prospects of eLearning 3.477 .001 IMPACTS 100% Table-value at 0.05 Significance level with 352 df = 1.96 Experience with computers have positive impacts on the user perceptions about educational technologies and adopting eLearning in the sense that greater the experience, more positive is the attitude of users (Blázquez & Díaz, 2006; Manochehr, 2007; Bondarouk, 2006; Mehra & Mital, 2007; Ezziane, 2007; Moolman & Blignaut, 2008). In the current study, the experience with computers has significant impact on all the variables because experienced users have higher perceptions and understanding of the eLearning issues than their counterparts. Given the significance of the impacts, alternative hypothesis is accepted. 5. DISCUSSION Contextual and demographic impacts on user perceptions and attitudes have widely been investigated and reported as critical points for the decision makers to consider when planning and implementing eLearning solutions in the HEIs. Researchers are constantly identifying the incompatibility of eLearning models with contextual requirements of specific countries, particularly in the developing world. The impacts of demographics on the user perceptions and attitudes about the development and use of eLearning tools in higher education are well reported (Valcke, 2004; Gay et al., 2006; Wims & Lawler, 2007; Mehra & Mital, 2007). The developers of eLearning environments are frequently insisted by the researchers to consider demographic diversities while developing strategies for generating and sustaining positive learner attitudes for eLearning environments (Buzhardt & Heitzman-Powell, 2005; Gay et al., 2006). These differences emerge from user-characteristics such as gender, age, educational level, computer skills, previous experience with eLearning as well as learning styles, personal goals and attitudes, preferences, cultural background, experience, motivation (Luck & Norton, 2005; Moolman & Blignaut, 2008). The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  11. 11. EJISDC (2010) 41, 5, 1-17 11 Furthermore, the change management aspect of eLearning occurs in a particular context. The contextual factors influence the eLearning theories and practices, which has to be understood and handled by both the developers and users of eLearning environments. The context is multifaceted and includes community, culture and technology and becomes very important when understanding implementation of the ICTs in education (Nyvang, 2003). The context of an organization like university is made of internal and external contextual elements (Loing, 2005). Internal contextual factors are the human characteristics and the organizational attributes while, external context is made of government ICT-policies and the broader social environment. The role of context in eLearning is consistently identified by almost every research study concerning the integration of educational technologies (Tinio, 2002; Oliver, 2002; Nyvang, 2003; Aaron et al., 2004; Loing, 2005; Cawson, 2005; Macleod, 2005; Ehlers, 2005; Baumeister, 2006; Stephenson, 2006; Hameed, 2007). In traditional computer-enhanced learning, the computer was used as a tool to complete a task or get something done so there was not need to address the broader environmental context of the individual (Young, 2003). Even today, Ezer (2006), in a study of Indian universities, found that “most IT education is ineffective because it is too technical and not at all concerned with local contexts and real world problems.” Similarly, another research reveals that despite the best of intentions, efforts and resources, many of the eLearning projects end in failure primarily because they are not undertaken in the perspectives of existing and changing social and political context (Wells, 2007). Thus, much more research is needed regarding teaching orientations, personal traits and the construction of online learning environments (Phillips et al., 2008). To cut short, context is either a support or a barrier for eLearning project management (Nyvang, 2003; Sasseville, 2004). System developers need to design an eLearning model within the context of the existing support and resource infrastructures (Tran et al., 2005). There is no universal eLearning-model to fit every context rather learning has to be conducted within the culturally familiar contextual frameworks (Stephenson, 2006). Baumeister (2006) asserts that eLearning is a multi-dimensional phenomenon which needs to be understood in terms of its relationship with the societal environment within which it is applied, meaning that a successful eLearning model in Atlanta, USA may be “ineffective or inappropriate” for students in Kuala Lumpur (Stephenson, 2006). Research indicates that failure to establish effective communication environment during ISD process usually ends up into a kind of IS failure (Nawaz et al., 2007). In this study, all hypotheses (alternative) have been substantiated thereby confirming different degrees of impacts of all six demographic attributes on the responses of the respondents. Table 5.1 gives the summary of results and decisions about the acceptance and rejection of hypotheses. Table 9 Results and Decisions about Hypothesis on Demographic Impacts Hypotheses Results Accepted Impact %age 1 Student/Teacher/Administrator 4/5 80 H1 2 Computer/Non-Computer 5/5 100 H2 3 Public/Private 4/5 80 H3 4 Male/Female 4/5 80 H4 5 Big/Small Cities 3/5 60 H5 6 Experience with Computers 5/5 100 H6 The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
  12. 12. EJISDC (2010) 41, 5, 1-17 12 6. CONCLUSIONS The research reveals that demographic factors play a moderating role in the relationships between the research variables. Extreme cases in demographic diversities disturb the normal relationships between different factors of a topic therefore, measurement and assessment of demographic variations is indispensable for getting the real picture of the phenomena in practice. For example, every demographic feature tested in this research comes up with one or another degree of impact. Computer/non-computer and experience are leading attributes of the respondent which are obviously changing their responses to extent of opposition. Thus, the eLearning solutions must be compatible with the human and contextual factors of any country. Furthermore, domestic digital models need to be developed through domestic research because the policy of ‘one-for-all’ paradigm is proving problematic in several countries. This research confirms the need for local research by unearthing the ‘existing-diversities’ among the eLearning users of HEIs, who differ in their perceptions about various aspects of educational technologies and their applications in education. There is need to develop domesticated and customized models of eLearning for every single but different group of users. It means that different groups need differing eLearning facilities and training to reach the same levels of eMaturity in the institute. For example, female respondents who score low on all research variables need more resources and attention their male counterparts for ‘equal-digital-growth’. Addressing these diverse groups of users, there are several opportunities available to the authorities, which can help in serving each different group through multiple digital devices and services. For example, Web 2.0 technologies are interactive and come in a variety of interactions and interfaces between the user-groups and the new technologies or work environments. The problems from demographic dimensions are universal however; their intensity is more implicative in the developing and poor countries than the advanced states with high levels of education, economic equalities and availability of government services for the masses. In developing states such as Pakistan, the situation is not so promising in terms of demographic groupings. Here the groups are not only highly dissimilar but also the number of groups is greater. Thus, knowledge about the impacts of user-characteristics in the development and use of eLearning environments in HEIs of a developing country is the prerequisite to introduce successful educational DOI in higher education. 7. REFERENCES Aaron, M., Dicks, D., Ives, C. & Montgomery, B. (2004) Planning for Integrating Teaching Technologies, Canadian Journal of Learning and Technology, 30, 2 http://www.cjlt.ca/index.php/cjlt/article/viewArticle/124/118. Abrami, P.C., Bernard, R.M., Wade, A., Schmid, R.F., Borokhovski, E., Tamim, R., Surkes, M.A., Lowerison, G., Zhang, D., Nicolaidou, I., Newman, S., Wozney, I., and Peretiatkowicz, A. (2006) A Review of e-Learning in Canada: A Rough Sketch of the Evidence, Gaps and Promising Directions, 56 pages. http://www.ccl- cca.ca/pdfs/StateOfField/SFRElearningConcordiaApr06.pdf Arulchelvan, S. and Viswanathan, D. (2006) Pattern of Usage of Various Electronic Media by Higher Education Students, International Journal of Education and Development Using ICT, 2(4), 100-118. Bataineh, R.F. & Abdel-Rahman, A.A. (2006) Jordanian EFL Students' Perceptions of their Computer Literacy: An Exploratory Case Study. International Journal of Education and Development using ICT, 2, 2 http://ijedict.dec.uwi.edu/viewarticle.php?id=169&layout=html. The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org
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  17. 17. EJISDC (2010) 41, 5, 1-17 17 Appendix 1 List of Research & Demographic Variables Research Variables 1. Perceptions about the Educational Technologies: Questions were asked about the availability and accessibility of hardware/software, network; and Internet (code=PET). 2. Views about the Development Practices: Questions were raised about ICT Policies, User Needs; User Participation, Training and Satisfaction; Implementation; Maintenance; Evaluation (code=PDP) 3. Views about the Use Practices: Questions included perceived ease of use, perceived usefulness, types of use; experience with computers, and user-developer- communication (code=PUP) 4. Perceptions about the eLearning Problems: The questions were asked about the problems related to the development, use and user-satisfaction (code=PRB) 5. Perceptions about the Prospects of eLearning: The respondents were inquired about what prospects they foresee for eLearning in the Prospects of eLearning based on the existing opportunities in HEIs of NWFP (code=PRS) Demographic Variables 1. Respondent-Type: Teachers and Students (code=RTP) 2. Sector: Public and Private (code=PPR) 3. Gender: Male/Female (code=GDR) 4. Subject: Computer/Non-Computer (code=CNC) 5. City Peshawar/Dera Ismail Khan CTY 6. Experience with Computers: (code=EXP) The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org

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