Restricted accessResearch articleFirst published online 1999-06
The Designing of the Computer Anxiety and Learning Measure (Calm): Validation of Scores on a Multidimensional Measure of Anxiety and Cognitions Relating to Adult Learning of Computing Skills using Structural Equation Modeling
This article discusses the process through which a powerful multidimensional measure of affect and cognition in relation to adult learning of computing skills, the Computer Anxiety and Learning Measure (CALM), was derived from its early theoretical stages to validation of its scores using structural equation modeling. The discussion emphasizes the importance of ensuring a strong substantive basis from which to develop reliable items for a measure as well as the usefulness of gathering qualitative data in both the factor and item design stages. The final instrument comprises 11 first-order factors and 1 negative item factor. These can be more parsimoniously represented as 5 factors, 2 of which are second order, and a measurement-method effect. Although tests of factorial invariance across different faculties provide considerable support for the stability and generalizabilty of the model, future research would need to examine whether the CALM model is invariant across different adult populations in similar computer learning/training environments.
Get full access to this article
View all access options for this article.
References
1.
Bagozzi, R. P. (1993). An examination of the psychometric properties of measures of negative affect in the PANAS-X Scales. Journal of Personality and Social Psychology, 65, 836-851.
2.
Bandalos, D. , & Benson, J. (1990). Testing the factor structure invariance of a computer attitude scale over two grouping conditions. Educational and Psychological Measurement, 50, 49-60.
3.
Bandura, A. (1988). Self-efficacy conception of anxiety. Anxiety Research, 1, 77-98.
4.
Bandura, A (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28, 117-148.
5.
Bandura, A. (1997). Self-efficacy. New York: Freeman.
6.
Barlow, D. H. (1988). Anxiety and its disorders. New York: Guilford.
7.
Beck, A. T. , & Emery, G. (1985). Anxiety disorders and phobias. New York: Basic Books.
8.
Benson, J. , & Hocevar, D. (1985). The impact of item phrasing on the validity of attitude scales for elementary school children. Journal of Educational Measurement, 22, 231-240.
9.
Bouma, G. D. (1996). The research process. Oxford, UK: Oxford University Press.
10.
Carver, C. S. (1989). How should multifaceted personality constructs be tested? Issues illustrated by self-monitoring, attributional style, and hardiness. Journal of Personality and Social Psychology, 56, 577-585.
11.
Cohen, L. , & Manion, L. (1994). Research methods in education (4th ed.). London: Routledge.
12.
Covington, M. V. (1984). The motive for self-worth. In R. Ames & C. Ames (Eds.), Research on motivation in education (Vol. 1, pp. 77-113). New York: Academic Press.
13.
Covington, M. V. (1992). Making the grade. New York: Cambridge University Press.
14.
Heckhausen, H. (1991). Motivation and action. Heidelberg, Germany: Springer-Verlag.
15.
Heinssen, R. K. , Glass, C. R., & Knight, L. A. (1987). Assessing computer anxiety: Development and validation of the Computer Anxiety Scale. Computers in Human Behavior, 3, 49-59.
16.
Hoyle, R. H. , & Panter, A. T. (1995). Writing about structural equation models. In R. H. Hoyle (Ed.), Structural equation modeling (pp. 76-99). Thousand Oaks, CA: Sage.
17.
Hu, L. , & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation modeling (pp. 76-99). Thousand Oaks, CA: Sage.
18.
Jöreskog, K. G. , & Sörbom, D. (1989). LISREL 7: A guide to the program and applications. Chicago: SPSS, Inc.
19.
Krueger, R. A. (1988). Focus groups: A practical guide for applied research. Newbury Park, CA: Sage.
20.
Lance, C. E. , Teachout, M. S., & Donnelly, T. M. (1992). Specification of the criterion construct space: An application of hierarchical confirmatory factor analysis. Journal of Applied Psychology, 77, 437-452.
21.
Loyd, B. H. , & Gressard, C. (1984). Reliability and factorial validity of computer attitude scales. Educational and Psychological Measurement, 44, 501-505.
22.
Marsh, H. W. (1986). Negative item bias in rating scales for preadolescent children: A cognitive-developmental phenomena. Developmental Psychology, 22, 129-149.
23.
Marsh, H. W. (1987). The hierarchical structure of self-concept and the application of hierarchical confirmatory factor analysis. Journal of Educational Measurement, 24, 17-39.
24.
Marsh, H. W. (1993). The multidimensional structure of physical fitness: Invariance over gender and age. Research Quarterly for Exercise and Sport, 64, 256-273.
25.
Marsh, H. W. (1994). Confirmatory factor analysis models of factorial invariance: A multifaceted approach. Structural Equation Modeling, 1, 5-34.
26.
Marsh, H. W. , Balla, J. R., & Hau, K. T. (1996). An evaluation of incremental fit indices: A clarification of mathematical and empirical processes. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling techniques (Vol. 4, pp. 59-98). Hillsdale, NJ: Lawrence Erlbaum.
27.
Marsh, H. W. , & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of self-concept: First- and higher-order factor models and their invariance across groups. Psychological Bulletin, 97, 562-582.
28.
Maurer, M. , & Simonson, M. (1984, January). Development and validation of a measure of computer anxiety. Paper presented at the Annual Meeting of the Association for Educational Communications and Technology, Dallas, Texas. (ERIC Document Reproduction Service No. ED 243 411)
29.
McDonald, R. P. , & Marsh, H. W. (1990). Choosing a multivariate model: Noncentrality and goodness-of-fit. Psychological Bulletin, 107, 247-255.
30.
Meier, S. (1988). Predicting individual differences in performance on computer-administered tests and tasks: Development of the computer aversion scale. Computers in Human Behavior, 4, 175-187.
31.
Michelson, L. , & Ascher, L. M. (1987). Anxiety and stress disorders. New York: Guilford.
32.
Miles, M. B. , & Huberman, A. M. (1994). Qualitative data analysis. Thousand Oaks, CA: Sage.
33.
Morgan, D. L. (1988). Focus groups as qualitative research. Newbury Park, CA: Sage.
34.
Pekrun, R. (1992). The impact of emotions on learning and achievement: Towards a theory of cognitive/motivational mediators. Applied Psychology: An International Review, 41, 359-376.
35.
Rosen, L. D. , & Maguire, P. D. (1990). Myths and realities of computerphobia: A meta-analysis. Anxiety Research, 3, 175-191.
36.
Rosen, L. D. , Sears, D. C., & Weil, M. M. (1987a). Computerphobia. Behavior Research Methods, Instrumentation, & Computers, 19, 167-179.
37.
Rosen, L. D. , Sears, D. C., & Weil, M. M. (1987b). Computerphobia measurement. A manual for the administration and scoring of three instruments: Computer Anxiety Rating Scale (CARS), Attitudes Toward Computers Scale (ATCS) and Computer Thoughts Survey (CTS). Dominguez Hills, CA: California State University.
38.
Rosen, L. D. , Sears, D. C., & Weil, M. M. (1993). Treating technophobia: A longitudinal evaluation of the Computerphobia Reduction Program. Computers in Human Behavior, 9, 27-50.
39.
Rosen, L. D. , & Weil, M. M. (1995a). Computer anxiety: A cross-cultural comparison of university students in ten countries. Computers in Human Behavior, 11, 45-64.
40.
Rosen, L. D. , & Weil, M. M. (1995b). Computer availability, computer experience and technophobia among public school teachers. Computers in Human Behavior, 11, 9-31.
41.
Sarason, I. G. (1972). Experimental approaches to test anxiety: Attention and the uses of information. In C. D. Spielberger (Ed.), Anxiety: Current trends in theory and research (Vol. 2, pp. 383-403). New York: Academic Press.
42.
Sarason, I. G. (1984). Stress, anxiety, and cognitive interference: Reaction to tests. Journal of Personality and Social Psychology, 46, 929-938.
43.
Sarason, I. G. (1991). Anxiety, self-preoccupation and attention. In R. Schwarzer & R. A. Wicklund (Eds.), Anxiety and self-focussed attention (pp. 9-13). Chur, Switzerland: Harwood Academic Publishers.
44.
Sarason, I. G. , & Sarason, B. R. (1987). Cognitive interference as a component of anxiety: Measurement of its state and trait aspects. In R. Schwarzer, H. M. van der Ploeg, & C. D. Spielberger (Eds.), Advances in test anxiety research (Vol. 5, pp. 3-14). Lisse, the Netherlands: Swets & Zeitlinger.
45.
Schwarzer, R. (1996). Thought control of action: Interfering self-doubts. In I. G. Sarason, G. R. Pierce, B. R. Sarason (Eds.), Cognitive interference: Theories, methods, and findings (pp. 99-115). Upper Saddle River, NJ: Lawrence Erlbaum.
46.
Shek, D. T. (1993). Factor structure of the Chinese version of The General Health Questionnaire (GHQ-30): A confirmatory factor analysis. Journal of Clinical Psychology, 49, 678-683.
47.
Spielberger, C. D. (1972a). Anxiety as an emotional state. In C. D. Spielberger (Ed.), Anxiety: Current trends in theory and research (Vol. 1, pp. 23-49). New York: Academic Press.
48.
Spielberger, C. D. (1972b). Conceptual and methodological issues in research on anxiety. In C. D. Spielberger (Ed.), Anxiety: Current trends in theory and research (Vol. 2, pp. 481-493). New York: Academic Press.
49.
Spielberger, C. D. (1975). Anxiety: State-trait process. In C. D. Spielberger & I. G. Sarason (Eds.), Stress and anxiety (Vol. 1, pp. 115-143). Washington, DC: Hemisphere/Wiley.
50.
Spielberger, C. D. , Pollans, C. H., & Worden, T. V. (1984). Anxiety disorders. In S. M. Turner & M. Hersen (Eds.), Adult psychopathology and diagnosis (pp. 263-303). New York: John Wiley.
51.
Tucker, L. R. , & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, 1-10.
52.
Wiersma, W. (1991). Research methods in education: An introduction. Boston: Allyn & Bacon.
53.
Wine, J. (1971). Test anxiety and direction of attention. Psychological Bulletin, 76, 92-104.
