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Cognition

Age and Critical Thinking

Observing mature students in educational settings.

In my introductory post, I addressed an observation of mine from teaching undergraduate critical thinking (CT), which is that students, especially mature students (i.e., aged 23 years and over), think they’re pretty good at CT, even when they’re not … well, not as good as they think they are, anyway! This can be interpreted as meaning that mature students are often overconfident in their ability to think critically. However, there are limitations to this assertion. Although there is a certain bravado associated with mature students and the way that they might engage with the class and speak about their opinions and experiences, this confidence is not necessarily seen when CT disposition is measured. That is, though mature students score slightly higher on CT disposition, there is no significant difference between them and younger, third-level students (i.e., 18- to 22-year-olds). Both score roughly at the mid-range between the lowest and highest possible scores (Dwyer & Walsh, in preparation).

When it comes down to evaluating their motivation and inclinations to think critically, it is possible that mature students are more realistic and honest than other students on self-report measures, despite what is observed in their behaviour. It’s possible that scores are "subdued" as a result of some form of social desirability; that is, perhaps mature students don’t want to appear overconfident in how they approach CT, when pen comes to paper. Conversely, it is also possible that it is younger students who are overconfident, on paper anyway, relative to their behaviour in the classroom. However, these interpretations are just possibilities at best, given that disposition towards thinking (i.e., the extent to which an individual is disposed, inclined, or willing, to perform a given thinking skill [Dwyer et al., 2017; Siegel 1999; Valenzuela et al., 2011]) is generally scored via self-report measures, which have in the past been criticized for a variety of reasons, particularly in assessing components of CT (see Ku, 2009). Also worth noting is that confidence and disposition are not exactly the same thing. Disposition towards thinking is a marker of how much we are inclined or how much we value certain aspects of cognition. It can be argued that the self-report nature of this inclination is itself the test of confidence (i.e., how confident one is that they actually conduct themselves or value something in the way they say they do). However, disposition doesn’t guarantee follow-through. Thus, a better indicator of assessing potential overconfidence in CT is looking at disposition relative to the performance of CT skills.

In a case study that I’m currently preparing with a colleague for publication, the effects of an adult distance learning CT module on CT performance were examined. In the context of the case study, adult distance learning refers to a mode of education in which students are employed adults (N=96) who have returned to part-time, formal education and are completing a Training and Education BA degree through an integration of traditional classroom instruction and e-learning. Performances were compared with a similar cohort of younger students who were also completing a BA and a blended learning CT module (N=42). It was hypothesised that due to the mature students’ age (which increases the likelihood of more metacognitive engagement); and potentially enhanced autonomy (Keegan, 1996; Knowles et al. 2005), student responsibility (Wedemeyer, 1981) and locus of control (Rotter, 1989), that their peformances would be significantly better than those of younger students. As hypothesised, mature students (M = 42.04 years) performed significantly better over time, in terms of CT ability (p = .004, ηp² = .07), than younger students (M = 18.96 years). However, younger students significantly outperformed the mature students prior to any CT training at baseline assessment (p < .001, d = .77).

Though these results are derived from a small-scale case study, the findings will be interesting to consider in future research for a number of reasons. First, as hypothesised, they imply that it is possible for more mature students to gain more from CT instruction than younger students. Second, they imply that, without appropriate CT instruction, younger students are better critical thinkers. Though this result contradicted the intial hypothesis, it is consistent with the perspective that though particular individuals may have more experience (and perhaps more confidence as well) in certain contexts, their higher-order thinking may not correlate due to experience in doing the ‘wrong thing’ or making poor decisions (Kahneman, 2011). A similar perspective is that perhaps maturer individuals may be more ‘set in their ways’ and it may be more difficult for them to adapt their beliefs in light of new information that may falsify their existing knowledge or belief systems (Kahneman, 2011). Third, and perhaps more central to the point of overconfidence, is that though mature students report approximately the same level of disposition towards thinking as younger college students, their ability to apply CT skills, before the intervention of CT training, does not match younger students’ ability.

To some extent, it is fair to say that though mature students think they’re pretty good at CT, often they are not. But, perhaps a more accurate interpretation is that without adequate training in CT, mature students’ perceptions of how they approach CT does not match their actual ability. This is consistent with a large body of research dating back to the 1960s that indicates that we often overestimate our abilities and fall prey to self-serving biases. But, this is the case for a lot of people — why single out more mature students? Simply, as individuals get older, they accrue more experience. There is also a tendency to equate this experience with varying conceptualizations of wisdom. However, experience is very often observed to be unrelated to the decision accuracy of expert judgments and sometimes negatively correlated with decision accuracy (Goldberg, 1990; Hammond, 1996; Kahneman, 2011; Stewart et al., 1992), perhaps as a result of overconfidence (Kahneman, 2011) or, to reiterate, experience in doing the wrong thing (Hammond, 1996). Thus, experience can be misleading.

In conclusion, without adequate training in CT, our perception of how we approach CT does not always match our actual CT ability. What makes this particularly interesting, in more mature populations, is that despite potentially enhanced autonomy, student responsibility and locus of control, it may be that an over-optimistic outlook on the benefits of experience (and its associated heuristic-based, intuitive judgment) takes centre-stage above and beyond actual ability. However, with appropriate training in CT, we see ability significantly improve over time. Thus, if you really care about your decisions and wish to improve how you solve problems and draw conclusions, it is never too late for critical thinking training.

References

Dwyer, C. P., Harney, O., Hogan, M. J., & Kavanagh, C. (2017). Facilitating a student-educator conceptual model of dispositions towards critical thinking through interactive management. Educational Technology & Research Development, 65, 1, 47-73.

Dwyer, C.P. & Walsh, A. (in preparation). A quantitative case study of critical thinking development through adult distance learning.

Goldberg, M. (1990). A quasi-experiment assessing the effectiveness of TV advertising directed to children. Journal of Marketing Research, 27, 445–454.

Hammond, K. R. (1996). Upon reflection. Thinking & Reasoning, 2, 2–3, 239–248.

Kahneman, D. (2011). Thinking fast and slow. UK: Penguin.

Keegan, D. (1996). Foundations of distance education. London: Routledge.

Knowles, M.S.S., Holton, E.F., Swanson, R.A. and Ed.D. (2005). The adult learner: The definitive classic in adult education and human resource development, 6th ed. Amsterdam: Elsevier Butterworth Heinemann.

Ku, K. Y. L. (2009). Assessing students’ critical thinking performance: Urging for measurements using multi-response format. Thinking Skills and Creativity, 4, 1, 70–76.

Rotter, J. B. (1989). Internal versus external control of reinforcement: A case history of a variable. American Psychologist, 45, 489–493.

Siegel, H. (1999). What (good) are thinking dispositions? Educational Theory, 49, 2, 207–221.

Stewart, T. R., Heideman, K. F., Moninger, W. R., & Reagan-Cirincione, P. (1992). Effects of improved information on the components of skill in weather forecasting. Organizational Behavior and Human Decision Processes, 53, 2, 107–134.

Valenzuela, J., Nieto, A. M., & Saiz, C. (2011). Critical thinking motivational scale: A contribution to the study of relationship between critical thinking and motivation. Journal of Research in Educational Psychology, 9, 2, 823–848.

Wedemeyer, C.A. (1981). Learning at the back door: Reflections on non-traditional learning in the lifespan. Madison: University of Wisconsin Press.

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