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Intelligence and the development of methodological skills in higher education: The case of information literacy

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Version 2 2015-03-05, 11:38
Version 1 2015-01-12, 09:21
poster
posted on 2015-03-05, 11:38 authored by Tom RosmanTom Rosman

Abstract

Despite a large body of research on the significance of intelligence in lifelong learning and in the development of academic skills (Kuncel, Hezlett, & Ones, 2004) little is known on its relationship with scholarly information literacy. Nevertheless, both information searching and the development of information search skills require many abilities commonly measured by intelligence tests, such as analytical (Lenox & Walker, 1993) and problem-solving abilities (Brand-Gruwel, Wopereis, & Vermetten, 2005), as well as a certain amount of cognitive flexibility (Stern & Neubauer, 2013). We thus hypothesize that verbal and fluid intelligence play a major role both in information-searching skills (Hypothesis 1) and in the development of the respective skills (Hypothesis 2).

A two-wave field study was carried out with 126 psychology freshmen from a large German university. Participants were 81 % female and 19 % male, and were aged 20.39 years (SD = 2.43) in the first wave. The first wave took part at the beginning of the first semester. Fluid intelligence was measured with Raven’s Advanced Progressive Matrices (APM; Raven, Raven, & Court, 1998); verbal intelligence was measured by 20 verbal analogies from the IST-2000R intelligence test (Liepmann, Beauducel, Brocke, & Amthauer, 2007). Information literacy was assessed with the Procedural Information-seeking Knowledge Test (PIKE; Rosman & Birke, in press). In the second wave at the beginning of the second semester (six months later), the PIKE was administered a second time.

At the first measurement point, information literacy correlated significantly and positively with verbal intelligence (r = .20; p < .05), but missed statistical significance for fluid intelligence (r = .10; n. s.). This indicates that students with a high verbal intelligence have higher information search skills (Hypothesis 1). To test the second hypothesis, a residualized gain score (Cronbach & Furby, 1970) was calculated by regressing information literacy levels of the second measurement on information literacy levels of the first measurement point. Positive correlations between the gain score and both verbal (r = .24; p < .01) and fluid intelligence (r = .16; p < .05) indicate that during the first semester, increase in information literacy is indeed higher for more intelligent students.

Our results show that intelligence not only plays an important role in “traditional” academic domains (e. g., mathematical ability), but is also involved in the development of methodological skills like information literacy. Particularly students with a low intelligence are likely to be overtaxed by the complexity of today’s academic information retrieval systems and the massive amounts of scholarly information available worldwide. This, in turn, might impair information searching and the development of adequate search skills. Our results suggest that verbal intelligence plays a slightly more important role, which is likely due to information literacy exhibiting a strong verbal component (e. g., defining the search problem, generation of search keywords or synonyms, etc.).

 

References

Brand-Gruwel, S., Wopereis, I., & Vermetten, Y. (2005). Information problem solving by experts and novices: Analysis of a complex cognitive skill. Computers in Human Behavior, 21 (3), 487-508.

Cronbach, L. J., & Furby, L. (1970). How we should measure "change" – Or should we? Psychological Bulletin, 74 (1), 68-80.

Kuncel, N. R., Hezlett, S. A., & Ones, D. S. (2004). Academic performance, career potential, creativity, and job performance: Can one construct predict them all? Journal of Personality and Social Psychology, 86 (1), 148-161.

Lenox, M. F., & Walker, M. L. (1993). Information literacy in the educational process. The Educational Forum, 57 (3), 312-324.

Liepmann, D., Beauducel, A., Brocke, B., & Amthauer, R. (2007). Intelligenz-Struktur-Test 2000 R. Göttingen, Germany: Hogrefe.

Mayer, R. E. (2011). Intelligence and achievement. In R. J. Sternberg & S. B. Kaufman (Eds.), The Cambridge handbook of intelligence (pp. 738-747). New York, NJ: Cambridge University Press.

Raven, J., Raven, J. C., & Court, J. H. (1998). Raven manual section 4: Advanced Progressive Matrices. Oxford: Oxford Psychologists Press.

Rosman, T., & Birke, P. (in press). Fachspezifische Erfassung von Recherchekompetenz durch prozedurale Wissenstests: Psychologie vs. Informatik [Discipline-specific assessment of information-seeking ability with procedural knowledge tests: Psychology vs. computer science]. In Mayer, A.-K. (Ed.), Informationskompetenz im Hochschulkontext – Interdisziplinäre Forschungsperspektiven. Lengerich, Germany: Pabst Science Publishers.

Stern, E., & Neubauer, A. (2013). Intelligenz – Große Unterschiede und ihre Folgen. München: DVA.

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