Computer self efficacy, computer anxiety, attitudes towards the ...

1. Concerned aspects of Internet experience, namely participants reportedlength of time in months as an Internet user and reported uses to which theInternet was put.2. The Computer Anxiety Rating Scale (CARS, see Appendix A) was used toassess an individual’s level of computer anxiety. The CARSis a 19 itemself-report inventory, approximately balanced for direction of answer,designed and validated by Heinssen, Glass, and Knight (1987). Items eightand 17 in the CARShad to be changed slightly. Participants responded ona five point Likert type scale (1=strongly disagree; 3=undecided;5=strongly agree). Total score could range from 19, indicating a low levelof computer anxiety, to 95, which would indicate a high degree of computeranxiety.3. The Internet Attitude Scale (IAS, see Appendix B) is a modified version ofthe Computer Attitude Scale, developed and validated by Nickell and Pinto(1986). In order to measure attitudes towards the Internet, the word ‘computer’was replaced with ‘the Internet’ throughout the scale. For example,item 5 ‘Soon our lives will be controlled by computers’ became ‘Soon ourlives will be controlled by the Internet’. The IASconsists of 20 statements,balanced for direction of response, rated on a five point Likert type scale.Scores on the IAS could range from 20, indicating an extremely negativeattitude towards the Internet, to a score of 100, which would imply anextremely positive attitude towards the Internet.4. Torkzadeh and Koufteros’s (1994) Computer Self Efficacy (CSE) Scale,with the following slight modification: it was decided that the three ‘mainframe’statements were not needed, as the move to stand alone machineshad made the concept irrelevant. Two additional statements that were originallyused by Murphy, Coover, and Owen (1989) were included, giving atotal of 29 statements. The items are shown in Appendix C. Each item waspreceded by the phrase ‘I feel confident’. A five point Likert type formatwas employed (1=strongly disagree to 5=strongly agree). All items werepositively worded statements that reflected a variety of computer relatedskills. High scores indicated a high degree of confidence in one’s ability touse computers (see Durndell et al., 2000). Scores could range between 29and 145.All items were translated into Romanian by a completely bilingual Romanianworking in Scotland who spoke English like a native speaker. This translation wasindependently checked by a bilingual Romanian in Romania.2.3. ProcedureA. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535 525The materials were distributed in teaching situations in a Romanian universitytowards the end of the academic year. All participants were volunteers. Completedquestionnaires were sent to the UK, and data analysis was then carried out usingSPSS.

526 A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–5353. ResultsZero order correlations for the whole sample between the CARS, IAS and theCSE Scales and reported time of use of the Internet in months are shown inTable 1. Means and SD’s are also displayed.Zero order correlations for the whole sample between components of the CSEscale: all three correlations between the three components of the total CSE scoreidentified by Torkzadeh and Koufteros (1994) were highly significant (P>0.001).Beginning skills CSE correlated at +0.81 with advanced skills CSE, beginningskills CSE correlated at +0.89 with file and software skills CSE, and advancedskills CSE correlated at +0.86 with file and software skills CSE.Reliability: the reliability of the three main scales was assessed using alpha: for theAIS, the alpha was 0.8977, and if single items were deleted the minimum alphawas 0.8883. For the CSE, the alpha was 0.9696, and if single items were deletedthe minimum alpha was 0.9677. for the CARS, the alpha was 0.9089, and if singleitems were deleted the minimum alpha was 0.9001. The corrected item–total correlationsare shown in Appendices A–C.Gender: the average score by gender for IAS, CARS, CSE and reported time usedthe Internet are all shown in Table 2. For each variable, an ANOVA by gender,academic year and course was carried out, with age as a covariate. (Courses werecategorised into science and non science). In all cases there was a significant differenceby gender, see Table 2. There were no significant interactions.Regression: each of the four dependent variables (IAS, CARS, CSE and reportedtime used the Internet) were in turn regressed on a set of seven predictors, usingthe direct method. In each case three of the seven predictors were the otherthree dependent variables, the remaining four being sex, age, academic year andcourse (science/non science).(a) AIS: the multiple R=0.55, F(7, 109)=6.77, P

A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535 527Table 2Computer anxiety, attitude to the Internet, computer self efficacy and duration of Internet use, meanscores and F ratios, by genderSample group Mean score F ratio(a) Computer anxiety, CARS, by genderMales 37.7 4.60, P

528 A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535(c) CSE: the multiple R=0.73, F(7, 109)=18.15, P

A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535 529and all were highly significant. It is notable that Schumacher and Morahan-Martin(2001) found a zero order correlation of 0.64 between computer comfort/competenceand Internet comfort/competence. The regression analyses emphasised thecomplexity involved when trying to identify the independent effects of these relatedvariables. However, it also illustrated how the computing measures and the Internetmeasures were intertwined. On balance the results tend to support Colley et al.’s(1994) argument that anxiety, attitudes and self efficacy were all in fact aspects ofone construct. Taken overall, it does seems reasonable to argue that the resultssupport Gackenbach’s (1998) contention that research on the Internet may wellmirror research on computing in many ways.The lack of generally agreed measures in this area was remarked on in the Introduction.The reliability data produced in this study was acceptable for the threescales used. The Computer Anxiety Scale showed relatively little variation in itemtotal correlations. The Internet Attitude Scale, which was the newest in that theauthors had replaced the word ‘computer’ with ‘the Internet’ throughout, wasthe least satisfactory. Two of the items, number 7 ‘There are unlimited possibilitiesof Internet applications that have not been thought of yet’, and number 14, ‘TheInternet is a fast and efficient means of gaining information’, had a poor relationshipto the overall score. The authors would not have picked these items out in advanceas potentially being a problem, whilst other items that might have been predicted asnot having a terribly clear relationship to the scale, such as ‘Soon our world will berun by the Internet’ (is it positive or negative towards the Internet to agree withthis?) were not a problem. The Computer Self Efficacy Scale had the highest alpha,slightly higher than that reported by Durndell et al. (2000) on another Romaniansample. The developers of this scale identify different subscales within the overallscale (Torkzadeh & Koufteros, 1994), which normally correlate significantly witheach other. This was found here, with the three subscales correlating between 0.81and 0.89 with each other, somewhat higher than the correlations (0.64 to 0.79) foundwith the same scale in Romania by Durndell et al. (2000).When the data was analysed by gender, the results also supported the predictions.A significant gender variation was found on all the measures, with on averagefemales reporting a smaller time of use of the Internet, less positive attitudes towardsthe internet, greater computer anxiety and lower computer self efficacy than males.The regression analyses were particularly interesting here, as the only independentlysignificant relationship found with gender was with respect to reported use of theInternet. This result clearly supports the views of researchers such as Maurer (1994),who have argued that gender may interact indirectly with computer experience byaffecting computer anxiety and computer-related attitudes. The extension in thepresent study is that the measure of use is of the Internet rather than computing perse, and attitudes to the Internet as well as computer anxiety may be affected. Thiswould again also seem to support Gackenbach’s (1998) contention that research oncomputing and the Internet will be closely linked.A feminist oriented literature exists in this area. Turkle (1995) has produced classicanalyses of the relationship between technology and gender, whilst Grundy(1996) has produced an explicit analysis of gender, power and computing. Such

530 A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535analyses, applied to computers, see computing as part of a masculine dominatedtechnology which pays little heed to human values and is often connected to a militaryor aggressive purpose. It could be argued that the Internet can be viewed as anextension of this as opposed to being a medium encouraging human equality, or asWeiser (2000) puts it, much of the research fails to confirm the Internets ‘GreatEqualizer’ metaphor. The Internet’s use as a source of pornography emphasises thislack of equity. Sussman and Tyson (2000), with reference to computer mediatedinteraction, argued that gendered power differentiation in communicative styletranscends the medium. In other words, if gendered power relations exist in theworld, they are to be expected in computer use and Internet use as well.Thus, the results obtained in the current study appear to indicate that the literatureon Internet use and attitudes is liable to follow the existing equivalent literatureon computing, in particular in tending to produce evidence of a gender effect. Theprecise nature of this effect with regard to the Internet, and how it manifests in differentsituations will no doubt be quite complex, as with the computing literature,but this study does provide some evidence of the direction in which it may go.It was indicated in the Introduction that there was some evidence and historybehind the contention that the countries of ex Communist East Europe may notproduce the gender effects with respect to technology that have been frequentlyidentified in the West (Alting & Brand, 1992). On the other hand, as these countriesleave their past behind, it is possible that a side effect could be that they will begin toproduce the technological gender effects of their western mentors. There has beensome argument as to whether the Soviet system really did produce much genderequality. Buckley (1989), for example, used the phrase ‘womens’ double burden’ forthe situation in the USSR where women had to both be responsible for bringing upchildren and going out to work in order to survive. It also may have been the casethat really high status technology in the military industrial complex was primarily inthe hands of men in the Soviet Union. On the other hand, as Durndell et al. (1998)found, when women engineers in Bulgaria were explicitly asked about the largenumber of women engineers to be found in their country, they tended to give creditto the former system, particularly to its achievements in education. The unificationof Germany was a special and extreme case where two states were turned into one,and where relative gender neutrality for technology in the old East Germany rapidlybecame male dominated in the new unified Western dominated state (Nickel, 1993).It may be doubtful that other states will quite follow this pattern with its specialcircumstances. However, Durndell et al. (1997) and Durndell et al. (2000) producedsome evidence that this may be beginning to happen more slowly elsewhere, and theexistence of the significant gender results found in this study in Romania supportsthat point of view.Finally, the reported uses to which the Internet was put by this sample provides apattern not too dissimilar to that found elsewhere (Miller & Durndell, 2001), perhapsrather surprisingly in the light of the relatively poor technological provision inRomania. Table 4 shows that males were on occasions more likely to report usingthe Internet for particular purposes, but that there was also a certain amount ofsimilarity in the uses that males and females reported for the Internet. Males were

A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535 531also more likely to report themselves as being amongst the heaviest users of theInternet, as measured by reported time spent online per week. Other studies, such asSherman et al. (2000) and Odell, Korgen, Schumacher, and Delucchi (2000) indicatea similar picture whilst varying in detail. The big picture seems to be that whilstthere might be a declining, though still existing, difference between males andfemales in overall use of the Internet, there are remaining variations in use betweenthe genders.In conclusion, this study would seem to support the contention that the researchliterature on the use of computers probably will extrapolate to the Internet, and thatthis will include the frequent finding of variations due to gender, in contradiction tothe hopes of some Internet enthusiasts. This study also tends to support the point ofview that the emerging countries of Eastern Europe will not be immune to the genderrelated effects of technology as found in the west. Finally, it would be useful todevelop measures of attitudes, anxiety and self efficacy towards the Internet.Appendix A. Corrected item–total correlations Computer Anxiety Items (CARS)Item1. I feel insecure about my ability to interpret a computer0.44printout2. I look forward to using a computer on my job 0.693. I do not think I would be able to learn a computer0.47programming language4. The challenge of learning about computers is exciting 0.525. I am confident that I can learn computer skills 0.666. Anyone can learn to use a computer if they are patient and 0.53motivated7. Learning to operate computers is like learning any new skill, 0.59the more you practice, the better you become8. I am afraid that if I begin to use computers more I will become 0.40more dependent upon them and lose some of my reasoning skills9. I am sure that with time and practice I will be as comfortable 0.68working with computers as I am in working by hand10. I feel that I will be able to keep up with the advances happening 0.65in the computer field11. I would dislike working with machines that are smarter than 0.43Iam12. I feel apprehensive about using computers 0.7313. I have difficulty in understanding the technical aspects of0.46computers14. It scares me to think that I could cause the computer to destroya large amount of information by hitting the wrong key0.59

532 A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–53515. I hesitate to use a computer for fear of making mistakes that Icannot correct16. You have to be a genius to understand all the special keyscontained on most computer terminals17. If given the opportunity, I would like to learn more about anduse computers more18. I have avoided computers because they are unfamiliar andsomewhat intimidating to me19. I feel computers are necessary tools in both educational andwork settings0.690.620.520.620.57Appendix B. Corrected item–total correlations, Internet Attitude Items (IAS)Item1. The Internet will never replace human life 0.342. The Internet makes me uncomfortable because I don’t0.67understand it3. People are becoming slaves to the Internet 0.614. The Internet is responsible for many of the good things0.69we enjoy5. Soon our lives will be controlled by the Internet 0.646. I feel intimidated by the Internet 0.607. There are unlimited possibilities of Internet applications that 0.10have not been thought of yet8. The overuse of the Internet may be harmful and damaging 0.48to humans9. The Internet is dehumanising to society 0.6510. The Internet can eliminate a lot of tedious work 0.3011. The use of the Internet is enhancing our standard of living 0.6112. The Internet turns people into just another number 0.7413. The Internet is lessening the importance of too many jobs done 0.59now by humans14. The Internet is a fast and efficient means of gaining information 0.1115. The Internet’s complexity intimidates me 0.5416. The Internet will replace the working human 0.4817. The Internet is bringing us into a bright new era 0.5618. Soon our world will be run by the Internet 0.6219. Life will be easier and faster with the Internet 0.6020. The Internet is difficult to understand and frustrating towork with0.32

A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535 533Appendix C. Corrected item–total correlations, Computer Self Efficacy Items (CSE)ItemI feel confident:1. working on a personal computer (microcomputer) 0.802. getting software up and running 0.763. using the users guide when help is needed 0.504. entering and saving data (numbers or words) into a file 0.785. escaping (exiting) from the programme (software) 0.706. calling up a data file to view on the monitor screen 0.707. understanding terms/words relating to computer hardware 0.768. uerstanding terms/words relating to computer software 0.799. handling a floppy disc correctly 0.7810. learning to use a variety of programmes (software) 0.7611. learning advanced skills within a specific programme (software) 0.7712. making selections from an onscreen menu 0.7413. using the computer to analyse number data 0.6914. using a printer to make a ’hard copy’ of my work 0.7515. copying a disc 0.7916. copying an individual file 0.8317. adding and deleting information from a data file 0.7618. moving the cursor around the monitor screen 0.5219. writing simple programmes for the computer 0.6120. using the computer to write a letter or essay 0.5821. describing the function of computer hardware (e.g. keyboard, 0.66monitor, disc drives, computer processing unit)22. understanding the 3 stages of data processing: input, processing, 0.68output23. getting help for problems in the computer system 0.5024. storing software correctly 0.8425. explaining why a programme (software) will or will not run on a 0.69given computer26. using the computer to organise information 0.7327. getting rid of files when they are no longer needed 0.7228. organising and managing files 0.8029. troubleshooting computer problems 0.67ReferencesAlting, A., & Brand, M. (Eds.). (1992). East and west European conference: ten years GASAT activity in achanging Europe. Eindhoven, Holland: GASAT/Eindhoven Technical University.Balka, E., & Smith, R. (Eds.). (2000). Women work and computerization. Boston: Kluwer.

534 A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535Bandura, A. (1997). The exercise of control. New York: W. H. Freeman.Beckers, J., & Schmidt, H. (2001). The structure of computer anxiety: a six factor model. Computers inHuman Behavior, 17(1), 35–49.Brosnan, M. (1998). Technophobia. London: Routledge.Brosnan, M., & Lee, W. (1998). A cross cultural comparison of gender differences in computer attitudesand anxiety: the UK and Hong Kong. Computers in Human Behavior, 14(4), 559–577.Buckley, M. (1989). Women and ideology in the Soviet Union. Hemel Hempstead, England: HarvesterWheatsheaf.Chua, S., Chen, D., & Wong, P. (1999). Computer anxiety and its correlates: a meta analysis. Computersin Human Behavior, 15(5), 609–623.Coffin, R., & Mackintyre, P. (2000). Cognitive, motivation and affective processes associated with computerrelated performance: a path analysis. Computers in Human Behavior, 16(2), 199–222.Colley, A., Gale, M., & Harris, T. (1994). Effects of gender role identity and experience on computerattitude components. Journal of Educational Computing Research, 10(2), 129–137.Durndell, A. (1991). Paradox and practice: gender in computing and engineering in eastern Europe. InG. Lovegrove, & B. Segal (Eds.), Women into computing: selected papers 1988–1990 (pp. 392–400).London: Springer Verlag.Durndell, A., Cameron, C., Knox, A., Stocks, R., & Haag, Z. (1997). Gender and computing: west andeast Europe. Computers in Human Behavior, 13(2), 269–280.Durndell, A., Haag, Z., & Laithwaite, H. (2000). Computer self efficacy and gender: a cross cultural studyof Scotland and Romania. Personality and Individual Differences, 28, 1037–1044.Durndell, A., & Thomson, K. (1997). Gender and computing: a decade of change? Computers and Education,28(1), 1–9.Durndell, A., Uzunova, F., Asenova, D., Asenov, A., & Thomson, K. (1998). Gender neutral engineering:an impossible dream?—the case of east Europe. International Journal of Science Education, 20(7), 783–793.Farenga, S., & Joyce, B. (1999). Intentions of young students to enrol in science courses in the future: anexamination of gender differences. Science Education, 83(1), 55–75.Gackenbach, J. (Ed.). (1998). Psychology and the Internet: intrapersonal, interpersonal and transpersonalimplications. New York: Academic Press.Griffiths, M. (1999). Internet addiction. The Psychologist, 12(5), 246–250.Grundy, F. (1996). Women and computers. Exeter, England: Intellect Books.Heinssen, R. K., Glass, C. R., & Knight, L. A. (1987). Assessing computer anxiety: development andvalidation of the computer anxiety rating scale. Computers in Human Behavior, 3, 49–59.HESA (Higher Education Statistics Agency) (2000). Higher education statistics for the UK, 1998/9. London:HESA.Holdstock, L. (1989). The ratio of male to female undergraduates. In J. Radford (Ed.), Gender and choicein education and occupation (pp. 59–83). London: Routledge.Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukopadhyay, T., & Scherlis, W. (1989). Internetparadox: a social technology that reduces social involvement and psychological well-being? AmericanPsychologist, 53(9), 1017–1031.Levine, T., & Donitsa-Schmidt, S. (1998). Computer use, confidence, attitudes and knowledge: a causalanalysis. Computers in Human Behavior, 14(1), 125–146.Maurer, M. (1994). Computer anxiety correlates and what they tell us: a literature review. Computers inHuman Behavior, 10(3), 369–376.McIlroy, D., Bunting, B., Tierney, K., & Gordon, M. (2001). The relation of gender and backgroundexperience to self reported computing anxiety and cognitions. Computers in Human Behavior, 17(1),21–33.Miller, J., & Durndell, A. (2001). Internet use, computer anxiety and attitudes towards the Internet: acomparison of the USA and Scotland. Proceedings of the British Psychological Society, 9(2), 108.Morahan-Martin, J. (1998). Males, females and the Internet. In J. Gackenbach (Ed.), Psychology and theInternet: intrapersonal, interpersonal and transpersonal implications (pp. 169–184). New York: AcademicPress.

A. Durndell, Z. Haag / Computers in Human Behavior 18 (2002) 521–535 535Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological Internet useamongst college students. Computers in Human Behavior, 16(1), 13–29.Murphy, C., Coover, D., & Owen, S. (1989). Development and validation of the computer self-efficacyscale. Educational and Psychological Measurement, 49, 893–899.Nickel, H. (1993). Women in the GDR and in the new Federal states. In N. Funk, & M. Mueller (Eds.),Gender politics and post communism (pp. 138–150). London: Routledge.Nickell, G. S., & Pinto, J. N. (1986). The Computer Attitude Scale. Computers in Human Behavior, 2, 301–306.Odell, P., Korgen, K., Schumacher, P., & Delucchi, M. (2000). Internet use among female and male collegestudents. CyberPsychology and Behavior, 3(5), 855–862.Pohl, M. (1997). The Internet: a feminine technology? In R. Lander, & A. Adam (Eds.), Women in Computing(pp. 190–197). Exeter, England: Intellect Books.Reinen, I., & Plomp, T. (1997). Information technology and gender equality: a contradiction in terminis?Computers and Education, 28(2), 65–78.Roger, A., & Duffield, J. (2000). Factors underlying persistent gendered option choices in school scienceand technology in Scotland. Gender and Education, 12(3), 367–384.Schumacher, P., & Morahan-Martin, J. (2001). Gender, Internet and computer attitudes and experiences.Computers in Human Behavior, 17(1), 95–110.Sherman, R., End, C., Kraan, E., Cole, A., Campbell, J., Birchmeier, Z., & Klausner, J. (2000). TheInternet gender gap among college students: forgotten but not gone? Cyberpsychology and Behavior,3(5), 885–894.Sussman, N., & Tyson, D. (2000). Sex and power: gender differences in computer mediated interactions.Computers in Human Behavior, 16(4), 381–394.Todman, J. (2000). Gender differences in computer anxiety among university entrants since 1992. Computersand Education, 34, 27–35.Torkzadeh, G., & Koufteros, X. (1994). Factoral validity of a computer self efficacy scale and the impactof computer training. Educational and Psychological Measurement, 54(3), 813–921.Turkle, S. (1995). Life on the screen: identity in the age of the Internet. New York: Simon & Schuster.Weiser, E. (2000). Gender differences in Internet use patterns and Internet application preferences: a twosample comparison. CyberPsychology and Behavior, 3(2), 167–178.Whitely, B. (1997). Gender differences in computer related attitudes and behaviour: a meta analysis.Computers in Human Behavior, 13(1), 1–22.Wright, R. (1997). Women in computing: a cross national analysis. In R. Lander, & A. Adam (Eds.),Women in computing (pp. 72–83). Exeter, England: Intellect Books.