24.2 Theories and Perspectives in Science Education. An excerpt from The Sourcebook for Teaching Science
Numerous theories and perspectives concerning the teaching and learning of science are addressed in this book, a few of the more prominent ones of which are referenced here.
24.2.1 – Active Learning: Learn by Doing
Active learning[i] is a set of strategies that posits the responsibility for learning with the student. Discovery learning[ii], problem-based learning (22.3), experiential learning, and inquiry-based instruction (22.1) are examples of active learning. Discussion, debate (22.4), student questioning (5.1, 22.1, 23.1), think-pair-share (25.7), quick-writes (25.7), polling, role playing, cooperative learning (22.3, 22.5), group projects (13.1-8, 22.5), and student presentations (22.4) are a few of the many activities that are learner driven. It should be noted, however, that even lecture can be an active learning event if students processes and filter information as it is provided. Cornell notes (3.1) and diagramming (16.2) are a couple of activities that can make lectures active learning events.
24.2.2 – Teaching to multiple learning modalities
We can learn through any of our five senses, but the three most valuable are vision, hearing, and touch. Theorists and practitioners claim that learners have a preference for one learning style over another. Visual learners learn best by watching, while auditory learners learn best by verbal instruction, and kinesthetic learners learn best by manipulation. Because of the demands of the profession, teachers often resort to the instructional style that requires the least time and preparation, namely lecture and discussion. Although these may be valuable approaches to teaching and learning, they fail to take advantage of other learning modalities, and disenfranchise students whose primary modality is visual or kinesthetic. Throughout this book we emphasize the use of all three modalities in teaching and learning.
24.2.3 – Teaching to multiple intelligences
Intelligence is a property of the mind that includes many related abilities such as the capacities to reason, plan, solve problems, comprehend language and ideas, learn new concepts, and think abstractly. Historically, psychometricians have measured intelligence with a single score (intelligence quotient, IQ) on a standardized test, finding that such scores are predictive of later intellectual achievement. Howard Gardner[iii] and others assert that there are multiple intelligences, and that no single score can accurately reflect a person’s intelligence. More importantly, the theory of multiple intelligences implies that people learn better through certain modalities than others, and that the science teacher should design curriculum to address as many modalities as possible. Gardner identifies seven intelligences, which are listed below. The numbers in parentheses indicate sections in this book that address each intelligence.
24.2.4 – Metacognition: Teaching students to think about their thinking
John Flavel[vi] argues that learning is maximized when students learn to think about their thinking and consciously employ strategies to maximize their reasoning and problem solving capabilities. A metacognitive thinker knows when and how he learns best, and employs strategies to overcome barriers to learning. As students learn to regulate and monitor their thought processes and understanding, they learn to adapt to new learning challenges. Expert problem solvers first seek to develop an understanding of problems by thinking in terms of core concepts and major principles (6.1-4, 7.1-7, 11.1-4). By contrast, novice problem solvers have not learned this metacognitive strategy, and are more likely to approach problems simply by trying to find the right formulas into which they can insert the right numbers. A major goal of education is to prepare students to be flexible for new problems and settings. The ability to transfer concepts from school to the work or home environment is a hallmark of a metacognitive thinker (6.4).
24.2.5 –Developing higher order reasoning
Perhaps the most widely used classification of human thought is Bloom’s Taxonomy[vii]. Benjamin Bloom and his team of researchers wrote extensively on the subject, particularly on the six basic levels of cognitive outcomes they identified – knowledge, comprehension, application, analysis, synthesis, and evaluation. Bloom’s taxonomy (6.1) is hierarchical, with knowledge, comprehension and application as fundamental levels, and analysis, synthesis and evaluation as advanced (6.1-6.4). When educators refer to “higher level reasoning,” they are generally referring to analysis, synthesis and/or evaluation. One of the major themes of this book is to develop higher order thinking skills through the teaching of science.
24.2.6 –Constructivism: Helping students build their understanding of science
Constructivism[viii] is a major learning theory, and is particularly applicable to the teaching and learning of science. Piaget[ix] suggested that through accommodation and assimilation, individuals construct new knowledge from their experiences. Constructivism views learning as a process in which students actively construct or build new ideas and concepts based upon prior knowledge and new information. The constructivist teacher is a facilitator who encourages students to discover principles and construct knowledge within a given framework or structure. Throughout this book we emphasize the importance of helping students connect with prior knowledge and experiences as new information is presented, so they can dispense with their misconceptions (7.4-7) and build a correct understanding. Seymour Papert,[x] a student of Piaget, asserted that learning occurs particularly well when people are engaged in constructing a product. Papert’s approach, known as constructionism, is facilitated by model building (12.5), robotics, video editing (16.5), and similar construction projects.
24.2.7 – Pedagogical content knowledge (PCK) in science
An expert scientist is not necessarily an effective teacher. An expert science teacher, however, knows the difficulties students face and the misconceptions they develop, and knows how to tap prior knowledge while presenting new ideas so students can build new, correct understandings. Schulman[xi] refers to such expertise as pedagogical content knowledge (PCK), and says that excellent teachers have both expert content knowledge, and expert PCK. In How People Learn, Bransford, Brown and Cocking state: “Expert teachers have a firm understanding of their respective disciplines, knowledge of the conceptual barriers that students face in learning about the discipline, and knowledge of effective strategies for working with students. Teachers' knowledge of their disciplines provides a cognitive roadmap to guide their assignments to students, to gauge student progress, and to support the questions students ask.”[xii] Expert teachers are aware of common misconceptions and help students resolve them. This book is dedicated to improving science teacher pedagogical content knowledge.
[i] Bonwell, C. & Eison, J. (1991). Active Learning: Creating Excitement in the Classroom AEHE-ERIC Higher Education Report No.1. Washington, D.C.: Jossey-Bass.
[ii] Bruner, J. S. (1961). The act of discovery. Harvard Educational Review 31(1): 21–32.
[iii] Gardner, H. (1993). Frames of Mind: The theory of multiple intelligences. New York: Basic Books.
[iv] Herr, N. and Cunningham, J. (1999). Hands-On Chemistry Activities with Real-Life Applications. San Francisco: Jossey Bass (John Wiley).
[v] Cunningham, J. and Herr, N. (1994). Hands-On Physics Activities with Real-Life Applications. San Francisco: Jossey Bass (John Wiley).
[vi] Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of
cognitive-developmental inquiry. American Psychologist, 34, 906-911.
[vii] B. S. Bloom (Ed.) (1956). Taxonomy of Educational Objectives: The Classification of Educational Goals. New York: David McKay Company, Inc.
[viii] Bodner, G. (1986). Constructivism: A theory of knowledge. Journal of Chemical Education, 63(10), 873-877.
[ix] Piaget, Jean. (1950). The Psychology of Intelligence. New York: Routledge.
[x] Papert, S. (1993). Mindstorms: Children, Computers, and Powerful Ideas. New York: Basic Books.
[xi] Schulman, L.S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher 15(2), 4-14.
[xii] Bransford, D., Brown, E., and Cocking, R. (eds.) (1999). How People Learn: Brain, Mind, Experience, and School. Committee on Developments in the Science of Learning, National Research Council. Washington, D.C.: National Academy Press.