Encouraging Students to Learn How to Learn
Simon Brassell, Department of Geological Sciences, Indiana University Bloomington
Metacognition encompasses learner-centered processes that monitor progress and adapt strategies for acquiring knowledge through self-awareness of actions necessary to achieve learning objectives. It often occurs spontaneously in expert learners, whereas novices typically require instructional scaffolding that encourages reflection, aids recognition of the scope of understanding, and provides directed guidance to enhance comprehension, overcome bottlenecks, or redress misconceptions.
In teaching introductory classes in the geosciences I endeavor to prompt students to be cognizant of their learning styles and depth of understanding through a variety of in-class and on-line activities. Completion of self-test exercises coupled with learning prompts that identify key concepts for each theme provides individual measures of comprehension, reexamined by comparison of answers in student pairs, then substantiated or corrected by class discussions. Persistent repetition of this activity in every lecture session inculcates students' recognition that their learning benefits from reflection and corroboration. Complementary on-line assignments further reinforce this process, and provide clear evidence (via bonus questions linked to attendance) that students who have been engaged in the reflective class activity possess a deeper understanding of targeted topics. These assignments also provide student feedback identifying which parts of each exercise were challenging or difficult to understand, and those that were beneficial to their learning. The more insightful comments tend to derive from the more accomplished students, which provides supporting evidence of the benefits of metacognitive activities. A similar pattern exists in the responses in assignments that require students to propose and answer both multiple-choice and short-answer questions for a forthcoming exam. Their compositions vary greatly in complexity and difficulty; some are shallow focused on simple memorization of facts, whereas the best are thoughtful constructions deeply rooted in reflective learning of key concepts.
The geosciences represent a fertile discipline for development of metacognitive skills because it requires students to comprehend discrete sets of information and interconnect them to build their understanding of fundamental concepts. For example, a critical challenge in studies of the evolution of the Earth is the integration of knowledge derived from diverse sources, such as the ability to identify a rock specimen from its mineralogy and texture, advanced conceptually by the capacity to place it within a spatial and temporal framework using varied clues from paleontology, stratigraphy, and structure, and then to combine all these elements to reconstruct its history. This challenging and complex task demands that students seek answers from lines of evidence presented by the specimen. It involves an investigative process that is readily adaptable to a metacognitive approach through focusing on the acquisition of reasoning skills involving self-assessment of the basis of each component of knowledge.
In my experience the greatest challenge in efforts to encourage metacognition among students is the inherent divergence in their learning styles that lessens the viability of generalized recommendations to encourage reflective study. It appears that varied resources – oral and visual explanations, use of analogies, instructional aids, and stepwise guides – differ markedly in terms of their effectiveness in advancing learning outcomes for individual students. A major challenge in efforts to create scaffolding to encourage use of metacognitive processes is identifying approaches that can cater for distinctive student learning styles. An on-line exercise could potentially achieve that goal through design of a matrix of questions structured around pathways that include specific modules tailored to identify and subsequently center on developing particular learning attributes.