Cognitive science, critical thinking, and higher education

Research into various tools to support critical thinking has reaped mixed findings. Some rankings of student-developed concept maps (as opposed to teacher-developed maps) indicate more sophisticated thinking from learners (Daley, Shaw, Balistrieri, Glasenapp, and Piacentine 1999). A meta-analysis of eighteen published reports (divided into nineteen individual studies—fourteen of which included student-developed maps) examining the use of concept mapping in classrooms demonstrated a positive impact on student achievement and attitudes (Horton, Mcconney, Gallo, Woods, Senn, and Hamelin 1993). However, the generalizability of concept maps to applied tasks is not clear. Horton et al. (1993) reported that the subject area and the study location both had an impact on the level of improvement. For example, when used in a clinical reasoning task in the place of traditional tools, concept maps did not result in any significant improvements across a range of critical thinking indicators (Wheeler and Collins 2003).

Some studies of cognition have also indicated that the way that feedback and reinforcement are provided may influence skill development in learners. Dweck and colleagues (Dweck 1975; Dweck and Reppucci 1973) identified different groups of child learners. They found that some children are incremental theorists who believe that their intellectual competence consists of a set of skills that may be enhanced through effort. The outcome of effortful behavior is increased intelligence. These children seek out tasks that allow for learning opportunities. Dweck and colleagues identified a separate and opposing group they called entity theorists. These children attribute performance outcomes to ability. They see intelligence as a global and stable trait that cannot be increased through effort. Because they equate the need to expel effort with lower intelligence, they do not seek out challenging tasks but instead seek opportunities that guarantee success and minimize the chance of making an error. Without taking into account these different approaches students will take, it is difficult to apply a single feedback or reinforcement strategy based on the experimental evidence. What these studies suggest is that the path from cognitive science to the classroom is far from smooth. Laboratory-based research is difficult to translate to real-life teaching situations and therein lies the challenge for the application of cognitive science to the teaching of critical thinking.

The above discussion traces several ways in which the findings from cognitive science and particularly research on heuristics and biases can be used to create better learning for critical thinking through concept mapping, metacognition, and so on. While there is potential in applying laboratory-based research in this way, caution must be taken when attempting to apply cognitive science or neuroscience to classroom practice (see also Bruer 1997). While cognitive science can indeed shed light on the underlying thought processes, it is also important to take into account the specific contextual features of the institution, the students concerned, and the discipline, which gives some weight to the context-specific view of critical thinking. The journey from the laboratory to the classroom is long and fraught with difficulty. In particular, it is difficult to control all the factors in a classroom to provide any level of certainty about any specific intervention. The combination of these issues has meant that the application of the sciences of learning, including cognitive science, to any level of education is a multistep process that involves an ongoing conversation between researchers and practitioners (Lodge and Bosanquet, 2014). It would appear that this conversation is still at an early stage.

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