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

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