Processing speed (Gs) and working memory (WM) tasks have received considerable interest as correlates of more complex cognitive performance measures. Gs and WM tasks are often repetitive and are often rigidly presented, however. The effects of Gs and WM may, therefore, be confounded with those of motivation and anxiety. In an effort to address this problem, we assessed the concurrent and predictive validity of computer-game-like tests of Gs (Space Code) and WM (Space Matrix) across two experiments. In Experiment 1, within a university sample (N =70), Space Matrix exhibited concurrent validity as a WM measure, whereas Space Code appeared to be a mixed-ability measure. In Experiment 2, Space Matrix exhibited concurrent validity as well as predictive validity (as a predictor of school grades) within a school-aged sample (N=94), but the results for Space Code were less encouraging. Relationships between computer-game-like tests and gender, handedness, and computergame experience are also discussed.
Ackerman, P. L., Beier, M. E., & Boyle, M. O. (2002). Individual differences in working memory within a nomological network of cognitive and perceptual speed abilities. Journal of Experimental Psychology: General, 131, 567–589.
Ackerman, P. L., Beier, M. E., & Boyle, M. O. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin, 131, 30–60.
Aliya, K. S. (2002). The role of computer games in the development of theoretical analysis, flexibility and reflective thinking in children: A longitudinal study. International Journal of Psychophysiology, 45, 149.
Bors, D. A., & Stokes, T. L. (1998). Raven’s Advanced Progressive Matrices: Norms for first-year university students and the development of a short form. Educational & Psychological Measurement, 58, 382–399.
Burns, N. R., & Nettelbeck, T. (2003). Inspection time in the structure of cognitive abilities: Where does IT fit? Intelligence, 31, 237–255.
Carpenter, P. A., Just, M. A., & Shell, P. (1990). What one intelligence test measures: A theoretical account of the processing in the Raven Progressive Matrices Test. Psychological Review, 97, 404–431.
Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge: Cambridge University Press.
Castel, A. D., Pratt, J., & Drummond, E. (2005). The effects of action video game experience on the time course of inhibition of return and the efficiency of visual search. Acta Psychologica, 119, 217–230.
Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245–276.
Colom, R., Abad, F. J., Rebollo, I., & Shih, P. C. (2005). Memory span and general intelligence: A latent-variable approach. Intelligence, 33, 623–642.
Colom, R., & Shih, P. C. (2004). Is working memory fractionated onto different components of intelligence? A reply to Mackintosh and Bennett (2003). Intelligence, 32, 431–444.
Conway, A. R. A., Cowan, N., Bunting, M. F., Therriault, D. J., & Minkoff, S. R. B. (2002). A latent variable analysis of working memory capacity, short-term memory capacity, processing speed, and general fluid intelligence. Intelligence, 30, 163–183.
Danthiir, V., Roberts, R. L., Schulze, R., & Wilhelm, O. (2005). Mental speed: On frameworks, paradigms, and a platform for the future. In O. Wilhelm & R. W. Engle (Eds.), Understanding and measuring intelligence (pp. 24–46). London: Sage.
Deary, I. J. (2001). Human intelligence differences: A recent history. Trends in Cognitive Sciences, 5, 127–130.
Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. A. (1999). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology: General, 128, 309–331.
Enochsson, L., Isaksson, B., Tour, R., Kjellin, A., Hedman, L., Wredmark, T., & Tsai-Felländer, L. (2004). Visuospatial skills and computer game experience influence the performance of virtual endoscopy. Journal of Gastrointestinal Surgery, 8, 876–882.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299.
Floyd, R. G. (2005). Information-processing approaches to interpretation of contemporary intellectual assessment instruments. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assess ment: Theories, tests, and issues (2nd ed., pp. 203–233). New York: Guilford.
Floyd, R. G., Shaver, R. B., & McGrew, K. S. (2003). Interpretation of the Woodcock-Johnson III Tests of Cognitive Abilities: Acting on evidence. In F. A. Schrank & D. P. Flanagan (Eds.), W-J III clinical use and interpretation: Scientist-practitioner perspectives (pp. 1–46). San Diego: Academic Press.
Fry, A. F., & Hale, S. (1996). Processing speed, working memory, and fluid intelligence: Evidence for a developmental cascade. Psychological Science, 7, 237–241.
Fry, A. F., & Hale, S. (2000). Relationships among processing speed, working memory, and fluid intelligence in children. Biological Psychology, 54, 1–34.
Gathercole, S. E., & Pickering, S. J. (2000). Working memory deficits in children with low achievements in the national curriculum at 7 years of age. British Journal of Educational Psychology, 70, 177–194.
Gentile, D. A., & Walsh, D. A. (2002). A normative study of family media habits. Journal of Applied Developmental Psychology, 23, 157–178.
Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational & Psychological Measurement, 66, 393–416.
Hitch, G. J., Towse, J. N., & Hutton, U. (2001). What limits children’s working memory span? Theoretical accounts and applications for scholastic development. Journal of Experimental Psychology: General, 130, 184–198.
Horn, J. L., & Blankson, N. (2005). Foundations for better understanding of cognitive abilities. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (2nd ed., pp. 41–68). New York: Guilford.
Horn, J. L., & Noll, J. (1997). Human cognitive capabilities: Gf-Gc theory. In D. P. Flanagan, J. L. Genshaft, & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests and issues (pp. 53–91). New York: Guilford.
Howell, D. C. (2007). Statistical methods for psychology (6th ed.). Belmont, CA: Thomson Wadsworth.
Jensen, A. R. (1982). Reaction time and psychometric G. In H. J. Eysenck (Ed.), A model for intelligence (pp. 93–132). New York: Springer.
Jensen, A. R. (1998). The g factor: The science of mental ability. New York: Praeger.
Just, M. A., & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122–149.
Kane, M. J., Hambrick, D. Z., & Conway, A. R. A. (2005). Working memory capacity and fluid intelligence are strongly related constructs: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131, 66–71.
Kyllonen, P. C., & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity?! Intelligence, 14, 389–433.
Law, D. J., Morrin, K. A., & Pellegrino, J. W. (1995). Training effects and working memory contributions to skill acquisition in a complex coordination task. Learning & Individual Differences, 7, 207–234.
Lengenfelder, J., Bryant, D., Diamond, B. J., Kalmar, J. H., Moore, N. B., & DeLuca, J. (2006). Processing speed interacts with working memory efficiency in multiple sclerosis. Archives of Clinical Neuropsychology, 21, 229–238.
Luo, D., Thompson, L. A., & Detterman, D. K. (2006). The criterion validity of tasks of basic cognitive processes. Intelligence, 34, 79–120.
Lynn, R., Allik, J., & Irwing, P. (2004). Sex differences on three factors identified in Raven’s Standard Progressive Matrices. Intelligence, 32, 411–424.
McGrew, K. (2005). The Cattell-Horn-Carroll theory of cognitive abilities. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (2nd ed., pp. 136–180). New York: Guilford.
McGrew, K., & Flanagan, D. P. (1998). The intelligence test desk reference (ITDR): Gf-Gc cross-battery assessment. Boston: Allyn & Bacon.
McPherson, J., & Burns, N. R. (2005). A speeded coding task using a computer-based mouse response. Behavior Research Methods, 37, 538–544.
McPherson, J., & Burns, N. R. (2007). Gs Invaders: Assessing a computer game-like test of processing speed. Behavior Research Methods, 39, 876–883.
Miller, L. M., Schweingruber, H., & Brandenburg, C. L. (2001). Middle school students’ technology practices and preferences. Journal of Educational Multimedia & Hypermedia, 10, 125–140.
Mitchell, A., & Savill-Smith, C. (2004). The use of computer and video games for learning: A review of the literature. London: Learning and Skills Development Agency.
Miyake, A. (2001). Individual differences in working memory: Introduction to the special section. Journal of Experimental Psychology: General, 130, 163–168.
Miyake, A., Friedman, N. P., Rettinger, D. A., Shah, P., & Hegarty, M. (2001). How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis. Journal of Experimental Psychology: General, 130, 621–640.
Montanelli, R. G., & Humphreys, L. G. (1976). Latent roots of random data correlation matrices with squared multiple correlations on the diagonal: A Monte Carlo study. Psychometrika, 41, 341–348.
Nyborg, H. (2003). The scientific study of general intelligence: A tribute to Arthur R. Jensen. Amsterdam: Pergamon.
Oberauer, K., Schulze, R., Wilhelm, O., & Süß, H.-M. (2005). Working memory and intelligence—their correlation and their relation: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131, 61–65.
O’Connor, B. P. (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, & Computers, 32, 396–402.
O’Connor, B. P. (2001). Extension: SAS, SPSS, and MATLAB programs for extension analysis. Applied Psychological Measurement, 25, 88.
Porter, D. B. (1995). Computer games: Paradigms of opportunity. Behavior Research Methods, Instruments, & Computers, 27, 229–234.
Prokosch, M. D., Yeo, R. A., & Miller, G. F. (2005). Intelligence tests with higher g-loadings show higher correlations with body symmetry: Evidence for a general fitness factor mediated by developmental stability. Intelligence, 33, 203–213.
Quaiser-Pohl, C., Geiser, C., & Lehmann, W. (2006). The relationship between computer-game preference, gender, and mental-rotation ability. Personality & Individual Differences, 40, 609–619.
Raven, J. C., Raven, J. E., & Court, J. H. (1998). Progressive matrices. Oxford: Oxford Psychologists Press.
Rushton, J. P., Skuy, M., & Fridjhon, P. (2003). Performance on Raven’s Advanced Progressive Matrices by African, East Indian, and White engineering students in South Africa. Intelligence, 31, 123–137.
Schmid, J., & Leiman, J. N. (1957). The development of hierarchical factor solutions. Psychometrika, 22, 53–61.
Schweizer, K. (2005). An overview of research into the cognitive basis of intelligence. Journal of Individual Differences, 26, 43–51.
Schweizer, K., & Moosbrugger, H. (2004). Attention and working memory as predictors of intelligence. Intelligence, 32, 329–347.
Stankov, L. (2000). Complexity, metacognition, and fluid intelligence. Intelligence, 28, 121–143.
Stankov, L., & Roberts, R. D. (1997). Mental speed is not the “basic” process of intelligence. Personality & Individual Differences, 22, 69–84.
Süß, H.-M., Oberauer, K., Wittmann, W. W., Wilhelm, O., & Schulze, R. (2002). Working-memory capacity explains reasoning ability—and a little bit more. Intelligence, 30, 261–288.
Swanson, L., & Kim, K. (2007). Working memory, short-term memory, and naming speed as predictors of children’s mathematical performance. Intelligence, 35, 151–168.
Unsworth, N., & Engle, R. W. (2005). Working memory capacity and fluid abilities: Examining the correlation between Operation Span and Raven. Intelligence, 33, 67–81.
Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41, 321–327.
Washburn, D. A. (2003). The games psychologists play (and the data they provide). Behavior Research Methods, Instruments, & Computers, 35, 185–193.
Wickelgren, I. (1997). Working memory linked to intelligence. Science, 275, 1581–1582.
Wolff, H.-G., & Preising, K. (2005). Exploring item and higher order factor structure with the Schmid-Leiman solution: Syntax codes for SPSS and SAS. Behavior Research Methods, 37, 48–58.
Wood, R. T. A., Griffiths, M. D., Chappell, D., & Davies, M. N. O. (2004). The structural characteristics of video games: A psycho-structural analysis. Cyberpsychology & Behavior, 7, 1–10.
Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). The Woodcock-Johnson Test of Cognitive Abilities. Itasca, IL: Riverside.
Yelland, N., & Lloyd, M. (2001). Virtual kids of the 21st century: Understanding the children in schools today. Information Technology in Childhood Education Annual, 13, 175–192.
Zajac, I. T., & Burns, N. R. (2007). Measuring auditory inspection time in primary school children. Journal of Individual Differences, 28, 45–53.
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McPherson, J., Burns, N.R. Assessing the validity of computer-game-like tests of processing speed and working memory. Behavior Research Methods 40, 969–981 (2008). https://doi.org/10.3758/BRM.40.4.969
- Work Memory Task
- Digit Symbol
- Fluid Intelligence
- Play Computer Game
- Space Matrix