Metacognition as a Predictor of Conceptual Change

Metacognitive ability­ proficiency in analyzing ones own thought processes ­ is related to the ability to correctly gauge one's mastery of a task (Kruger, 1999; Dunning, 2003). It may also be tied to the ability to make radical conceptual changes ­ learning new information incongruous with prior beliefs. We hypothesize performance on an expanded version of the Cognitive Reflection Test (Frederick, 2005), a battery of questions designed to measure metacognitive ability, would be a predictor of the extent to which undergraduate college students (N=103) improved their understanding of evolution after a semester of college level biology, particularly in the Darwinian principles behind natural selection such as inheritance, variation, and superfecundity. The benefits should be most pronounced in subjects displaying greater metacognitive ability whose prior knowledge incorporated flawed beliefs such as LeMarckianism or needs­based evolution. If metacognitive ability is indeed predictive of learning, it would suggest conceptual change is facilitated by a disposition to think about one's own concepts. It would also suggest that the quality of education in fields such as biology may be improved by fostering and encouraging more reflective thinking. Introduction In most classrooms, there are one or more students who behave qualitatively differently than their peers. Regarded as 'quick on the uptake' or other such terms, much effort has been put into understanding what distinguishes them from their peers and whether similar techniques can be taught to other students in order to improve their performance. This paper focuses on the role of metacognition as a possible factor in the ability to learn; primarily because there are several studies relating learning to metacognition. While research into the specific mechanism by which metacognition plays its role in learning remains inconclusive (Cull, 1994), the two processes are so strongly linked that in a recent literature review on metacognition it has been stated no less explicitly than “In memory research, metacognition was invoked to account for the ability of subjects to strategically control their learning,” (Fleming, et al., 2012). Metacognitive ability­ the ability to reflect on one's own thought processes­ has previously been correlated with the ability to monitor one's own performance accurately; one possible explanation for its role in learning ability. The Dunning­Kruger Effect is a famous example of metacognition research: Dunning and Kruger found that most people consider themselves above average in a variety of fields; for example, Kruger found that participants in the twelfth percentile of various tests on humor, logic, and grammar believed themselves to be of the 62nd percentile, while Dunning later asked psychology students for their self­assessment on their perceived mastery of the material before a test and their projected score afterwords, finding a similar effect; most participants considering themselves to be somewhere in the 60th percentile, while the top percentile was much more accurate in its self­assessment. (Dunning, 2003; Kruger, 1999) Whatever process enables the high­achieving students to accurately gauge their own performance, it is clear the average low­achieving student has less aptitude for it. This, once more, leads to the implication that metacognition is correlated with the ability to learn; for example, it has been noted that metacognition influences learning strategies similarly between both good and poor learners in tasks of metamemory (Cull, 1994). At this point, it becomes necessary to make a distinction between two types of knowledge acquisition: knowledge enrichment and conceptual change. Human cognition is guided by collections of domain­specific knowledge (Carey, 1994). These domains encompass various fields in which humans must reason; such as numeracy. Numeracy constitutes the ability to recognize numbers, and perform operations upon them based off of our understanding that unique numbers have some shared properties in which individual numbers vary. One core principle that is acquired early in the building of numeracy is the principle of succession which postulates any two unique numbers can be compared and an unequivocal conclusion can be reached in regards to which is greater or lesser, often analogized to children via the concept of a 'number line'. Literacy, similarly, consists of acquiring principles such as written syntax, the distinction between verbs, adjectives, and nouns, and the principle of tense as a modifier which can be applied to verbs. A distinction can be drawn between two domains if the core principles upon which they rely are different; for example, the principle of 'succession' cannot be applied to language as it is in mathematics, e.g. the word 'cow' cannot be called either greater or lesser than the word 'chair'. Within these domains, once sufficient knowledge has been gathered with which to construct these core principles, additional knowledge may be acquired which is not a new core principle, but simply a permutation that fits within the existing knowledge structure. For example, learning a new word is an example of enrichment of a previously existing domain­specific knowledge. Even the acquisition of a new language can be classified as knowledge enrichment, as many languages rely on the same core principles such as syntax. As a knowledge domain becomes further enriched, the concepts underlying one's understanding of the domain similarly become further entrenched. On the other hand, conceptual change is invoked when one realizes that an essential core principle of domain­specific knowledge is incorrect. Examples of this change with regards to the field of biology will be discussed further on. The role of metacognition in respect to metamemory has been previously studied, often with tasks such as the ease­of­learning (EOL, the reported difficulty with which participants expect from a task) and the judgment­of­learning (JOL, the self­assessment of whether or not a participant has sufficiently learned a subject). Ease­of­learning and judgement­of­learning are metacognitive tasks, requiring the subject to gauge his or her own capability at a task. In order to judge if a fact is difficult or easy to retain, participants must have some self­awareness of their own learning process; at the same time, in order to judge whether or not they have accurately mastered material, the participants must have some self­awareness regarding what they have and have not learned. Metacognition is linked to knowledge enrichment in metamemory tests; both poor learners and good learners modify their study habits on later memorization tasks according to their EOL judgments. These ease­of­learning judgments are positively correlated with the time spent studying an item, suggesting metacognition plays a role in allowing for optimal resource allocation while learning. The role of metacognition in learning is so taken for granted, in an article that similar finds judgments are made between good and poor learners regarding study time allocation and EOL, the possibility of an alternate hypothesis­ that of metacognition being unrelated to learning­ is expressed, but nearly immediately rejected. (Cull, 1994) The authors instead take their own results with a grain of salt: “[In reference to rejecting metacognition's role in learning:]Such a position is contradicted, however, by a number of other studies indicating that a relationship between metacognition and learning ability does exist. These studies show.that adults make better metacognitive decisions than do children. more successful fifth graders monitor learning difficulty of prose passages better than do less successful fifth graders.high­achieving college students more accurately discriminate what is known and not known than do low­achieving students. college students who perform better on a text comprehension task monitor their comprehension better than students performing less well. even that expert memorizers regulate study more effectively than do novice memorizers(see Intons­Peterson & Smyth, 1987). ” Cull notes an interesting observation: “Studies that have revealed a relationship between cognitive monitoring and learning ability generally have used tasks and materials that are more complex than those used in studies not revealing a relationship. ” A notable feature shared amongst these tasks, however, is that JOL and EOL in specific and metamemory tasks in general measure only knowledge enrichment because they generally involve the participant memorizing words. Thus there is a growing body of knowledge on the interactions between metacognition and knowledge enrichment, but proportionately less research into the role of metacognition in conceptual change. If the observation hinted at by Cull is true ­ that more difficult tasks are the ones in which metacognition plays a greater role ­ then conceptual change, which is a learning task of greater difficulty, should show an even stronger relationship between metacognitive aptitude and learning. Earlier, we drew a distinction between conceptual change and knowledge enrichment with the understanding of later discussion of certain specific conceptual changes in the field of biology. (Shtulman, 2006) Early in life (up until between six and nine years of age) children have a variety of misconceptions on the nature of biology, in which an intuitive explanation is posited for phenomena such as inheritance. When asked about the heritability of certain traits; for argument's sake, the trait of having blue eyes and the trait of being educated. Preschool children are capable of recognizing that children will often take after their parents, but they fail to draw distinction between the former, which is a function of genetics, and the latter, which is a function of exposure to educated parents (Carey