Our classrooms are filled with a variety of learning styles and abilities. Some students grasp concepts easily, while others struggle to keep up with a fast paced environment filled with detailed curriculum outcomes. To help develop our students into expert learners, we must understand the integration between metacognitive knowledge, regulator control processes, and reflective thinking. This paper will outline and observe metacognition, self-regulation, behaviorism, constructivism, and reflect how these theories are utilized in my educational program.
The methodologies that were once followed to develop our students have drastically changed. The ways in which education is viewed today and the approaches taken have evolved from an instructor centered idea to one of collaboration, cognition, and reflection. Helping students to plan, evaluate, and reflect on ones learning has proven to be beneficial to the overall development and achievement of students today. Metacognition is a term used to describe the ability to self evaluate your own levels of cognition.
As described by Pennequin, Sorel, Nanty, & Fontaine (2010), “metacognition”, or “thinking about thinking”, refers to different capacities that enable one to think about one’s own cognition processes” (p. 198). Pennequin et al, (2010) argue that there are two central components: metacognitive knowledge, and metacognitive skills. Metacognitive knowledge is based on declarative knowledge involving learning strategies about oneself as a problem solver, while metacognitive skills involve the awareness of one’s own cognitive system.
It is understood that children can achieve at a higher level if they participate in metacognitive training. “Metacognitive processes allow people to select and invent strategies explicitly, by thinking about their understanding of the task demand, their available cognitive resources, and their own experience in solving similar problems” (Pennequin et al. pg. 201) Students begin to develop their own strategies based on the successes and failures of previous experience. According to Schraw’s (1998) training model, he proposed and instructional aid known as the Strategy Evaluation Matrix (SEM).
This model contains information on strategy selection and when and how to use specific strategies. Much of the focus comes back to planning, monitoring, and evaluating. Schraw and Moshman (1995) describe knowledge of cognition as having three levels of metacognitive awareness: declarative, procedural, and conditional. “Declarative knowledge refers to knowing “about” things. Procedural knowledge refers to knowing “how” to do things. Conditional knowledge refers to knowing the “why” and “when” aspects of cognition” (Schraw & Moshman, 1995, pg. 352).
People that can self-evaluate their own abilities will become better learners by applying the necessary strategies to do so. Self-Regulation is the process of developing an ability to learn on your own while recognizing the needs for strategies to overcome challenges. Zimmerman (2002) states that “self-regulation is not a mental ability or an academic performance skill; rather it is the self-directive process by which learners transform their mental abilities into academic skills” (p. 65). Students become aware of their learning and develop goals internally to progress ones development.
As cited by Matthews, Morrison and Ponitz (2009), “strong behavioral regulation early in the school trajectory sets the stage for academic success by predicting increased school engagement and motivation and children’s adoption of positive learning strategies” (Fredricks, Blumenfeld, & Paris, 2004; Zimmerman & Schunk, 2001). These learner types are proactive in their efforts because they are aware of their limitations and therefore develop strategies to overcome these challenges. Learners whom become self-regulated become lifelong learners; a very sought after skill.
Having the capability to fully control ones learning requires a great deal of reflection and self discipline. As described by Zimmerman, “self-regulation of learning involves more than detailed knowledge of a skill; it involves the self-awareness, self-motivation, and behavioral skill to implement that knowledge appropriately” (pg. 66). These learner types have the ability to recognize when they are not learning and apply skills and strategies to overcome this. These skills are not inherited and can be taught at an early age and have proven to produce positive results in child learning. Helping children develop self-regulation early in their school lives will increase the likelihood of equal opportunity to learn and positive outcomes for all” (Matthews et al. 2009, pg. 701) Clearly, there are major differences between the thought processes of expert learners and novice learners. A skill attained by expert learners is their ability to recognize when learning is not taking place. Novice learners seldom reflect on their learning and do not self evaluate or make adjustments to correct unsuccessful attempts at learning.
Ertmer and Newby (1996) argue that when an expert learner faces cognitive failure, this is detected and learning strategies are applied to correct the problem. Expert learners have the ability to diagnose and dissect a task to determine how to approach the task while depending on previous knowledge throughout. “It is the monitoring and self-regulatory skills that enable experts to know not only what is important (declarative knowledge) but also how (procedural knowledge), when, where and why (conditional knowledge) to apply the right knowledge actions (Ertmer & Newby, 1996, p. ) . Poorer learners do not detect the cognitive failure and therefore make no adjustments to correct it. As part of the process of self-regulation, expert learners apply skills early on in the learning task. “They access their knowledge warehouse to recall past experiences with similar tasks and select and approach with matching task requirements and personal resources in such a way that the desired results can be obtained” (Ertmer & Newby, 1996, p. 10. They develop a plan and outline what is needed to achieve their goal. During the execution of the task, they are continually reflecting and re-evaluating to determine if alterations are needed. Finally, upon completion of the task, they self evaluate to determine if the goal was achieved. This is a cycle of plan, monitor, and evaluate that is continual until successful completion and the task has been learned. The works of Zimmerman (2002) closely resemble that of Ertmer and Newby in reference to component skills.
These skills include: (a) setting specific proximal goals for oneself, (b) adopting powerful strategies for attaining the goals, (c) monitoring ones performance electively for signs of progress, (d) restructuring one’s physical and social context to make it compatible with one’s goals, (e) managing one’s time use efficiently, (f) self-evaluating one’s methods, (g) attributing causation to results, and (h) adapting future methods. When considering the level of learning, the above skills can be monitored to determine their presence or absence and can the closely tied to the level of the learner.
The above mentioned skills would be characteristic of an expert learner. Expert learners would recognize the absence of a skill if learning has not taken place and adjust accordingly. During the delivery and facilitation of problem solving in my math program, I can closely relate to the skills outlined by Ertmer and Newby and those of Zimmerman as well. I spend a great deal of time with my students teaching them how to problem solve. Essentially, I help the students develop strategies to assist them with every portion of the problem solving model.
We work together collectively starting with the planning stages. When approaching a problem in our math program we follow a prescribed procedure for each and every problem with the hope of developing a positive habitual method to solving problems. We start by reading the problem three times together. Each time we stop and discuss what the important information is and what information is not needed to move forward. We then discuss if we have ever seen or worked on a problem that is similar to the one presented before us.
If so, we share that problem with each other and discuss how it was handled and what the similarities are as well as the differences. Following this, we record only the pertinent information and discard the rest. Again, we reflect and re-evaluate to make sure that we are in agreement before we move on. We then create diagrams, sketches, graphs, or any other visual that can assist with the solving of the problem. When we feel we are comfortable with our representations, we share with others and further plan for the next step. At this point, we work to solve the problem (do the math) and determine the solution.
Upon finding and answer, we reflect on the problem to determine if the answer is plausible. If not, the cycle begins again to determine where we went wrong. If the answer is realistic, we move to the next step to form a conclusion. This entire process could be seen as strategic but in referencing the models necessary to become expert learners, this process is very closely aligned. I teach in a small school with a unique situation of being the only middle school math teacher. Therefore, I teach the same students for three years following them from grade 7 to 9.
Upon completion of grade nine, the problem solving strategy is no longer in need of reinforcement; the students do it with each and every problem routinely and continue to do so when they move into high school. This is a skill that I recognize to be of high importance and work to ensure it becomes part of each student’s mastery before leaving junior high. While recognizing the importance of self-regulation and metacognition, one cannot ignore the need to for practice. “Drill and Kill” is a popular phrase to describe this type of learning.
It was once considered to be “boring, repetitive, and mind numbing” (Zimmerman, 2002) but according to interviews with experts, (Ericsson & Charness, 1994) claim to have conflicting views. Upon interviewing experts, it was learned that “experts spend approximately four hours each day in study and practice and find these activities highly motivating” (Zimmerman, 2002) Experts need to spend time perfecting their skills and find it stimulating to do so. They become motivated to take their skills to a higher level and recognize the need for repetition to get there.
This type of practice is not beneficial when conducted by itself, but it does compliment other learning strategies when performed together with the above mentioned skills. When reflecting on the lessons I deliver and facilitate in my math program, I often rely on time spent practicing. Students need to have an opportunity to absorb new skills and have difficulty with retention if not practiced. They start to get a feel for what they are doing and begin to internalize the skill so it can be utilized in similar problems in the future.
For example, if a student learns the skill of long division with a two digit dividend and a single digit divisor and has been granted to opportunity to practice this skill, they will get a feel for how it works. When this skill has become part of their mastery, they can extend this skill into three, four, five digit dividends with multiple digit divisors. However, without the opportunity to drill this concept, the feel for how they are done and confidence gained is not present and therefore, extending the skill can be much more daunting. When students spend time doing these drills it can act as a motivational tool.
Typically, when they start to get correct answers, they want to do more, and the sense of achievement is present. However, if they have not yet mastered this skill, it is impossible to extend the skill as most lessons in math are cumulative. Meaning that without a solid foundation, you cannot extend your learning until the initial skill is understood. Behaviorist theories are applied in the classroom in a variety of ways. For example, some programs utilize self paced learning modules that provide frequent feedback with materials, presented in small sections and then assessed rather than a long unit assessment and end of unit test.
Behaviorist methods are also used in classroom management practices as teachers attempt to shape classroom behaviors. Behaviorist theories are implemented in a classroom by having the teachers identify desired behaviors and set and apply a reinforcement schedule to promote desired responses. In other words, a teacher would develop a system to reinforce positive outcomes rather than punish for an undesired behavior. However, there has been research conducted that supports the notion that the behaviorist theory does not always produce the desired outcome. Empirically, behaviourism led to predictions which were not supported by the data. For example, behaviourism states that rewarding an activity leads to a greater occurrence of that activity” (Human Learning and Motivation, 2006). This was not always the case as was provided the example of the art students that produced beautiful work with no reward and did so for their love of art. Then, when rewarded for their accomplishments, the quality of their work declined. Within our own school board, we utilize a rewards program called PEBS (Positive Effective Behaviour Supports) that is designed to reinforce positive behavior.
The goal is to provide our students with academic and social-behavioral skills they need in order to be successful in life. Much of the program deals with school-wide discipline that includes proactive strategies for defining, teaching, and supporting appropriate student behaviors. As cited on the Cape Breton Victoria Regional School Board website: Positive behavior support is an application of a behaviorally -based systems approach to enhance the capacity of schools, families, and communities to design effective environments that improve the link between research-validated practices and the environments in which teaching and learning occurs.
Attention is focused on creating and sustaining primary (school-wide), secondary (classroom), and tertiary (individual) systems of support that improve lifestyle results (personal, health, social, family, work, recreation) for all children and youth by making problem behavior less effective, efficient, and relevant, and desired behavior more functional (PBIS. org). The purpose of the program is to create a positive environment where good behavior is continually reinforced working to develop it into become the norm.
Positive behavior in schools will lead to a higher level of learning with more focus on achievement and less focus on correcting inappropriate behaviors. “Modeled behaviors are more likely to be performed if they have previously led to rewarding outcomes than if they have resulted in punishment, regardless of whether individuals have experience the consequences directly or vicariously” (Schunk, 1987, pg. 150). Constructivist theories enforce the changing of one’s customary ways of thinking. These heories are based on the principle that the learner actively develops knowledge and understanding as opposed to passively receiving information in response to external forces, such as rewards. Constructivists consider that learning is an active construct as prior knowledge is routinely accessed. From a constructivist viewpoint, the emphasis is taken away from the instructor and focussed on the learner. Jerome Bruner, Jean Piaget, and Lev Vygotsky were three major contributors to the ideas of constructivism.
Bruner believed that people have an understanding of the world in terms of similarities and differences and rely on a coding system where specific knowledge derives from higher levels of categories. As cited by Palincsar (1998), it has been argued by Bruner (1990) that the cognitive revolution was meant to do more than simply be an improvement on behaviorism; it was also meant to promote a psychology that focused on “meaning making”. Cognitive structures including schemata and heuristics were introduced by cognitive psychologists as the images of knowledge in memory.
Problem solving and transfer ability are the result of the motivation created by these cognitive structures. Another influential theorist in the Constructivist movement was Jean Piaget. Research conducted by Piaget included the study of how knowledge grows. He believed that the child learns very differently than adults and that direct instruction practices do not allow for the child to incorporate individual perspective. This could lead to a void of the child’s own perspective and discovery learning.
Allowing children to discover for themselves requires guidance and facilitation rather than instruction. One could argue that this can be a very time consuming method of learning that could possibly inhibit a program from advancing through curriculum. While following our Nova Scotia curriculum, it is suggested that at the beginning of each math lesson, our current program should open with a discovery activity. These activities can be very beneficial to the overall understanding of topics but they usually come with a cost involving a great deal of time.
We can ill afford the time to complete all of these discovery lessons and are therefore forced to select the ones found to be the most valuable. Having taught the program for 6 years has enabled me to determine the value of each and makes selections easy. The discovery lessons are designed in such a manner that the students work though an assignment, typically in a group setting, answering a series of questions. Each question extends the previous question therefore extending the knowledge. As the students progress, they begin to make connections and begin to recognize patterns.
Upon completion of the task, if done successfully, the students have self-discovered a new concept with the support of their peers and their teacher facilitating the lesson. It is a very interesting concept and works well with some lessons. Vygotsky’s contribution to constructivism includes his ideas of socio-cultural theories and his beliefs regarding zone of proximal development ZPD. According to Palinscar (1998), Vygotsky believed that to increase the understanding in the relationship between development and learning we must distinguish between two developmental levels: “the actual and the potential levels of development” (p. 52). The actual level refers to what the child can perform independently while the potential level refers to what can be accomplished with the aid of an assistant. Support systems should be provided for students to carry out activities that they cannot complete independently, but are able to complete through social interactions with others. Therefore, the zone of proximal development defines functions that a student has not mastered but is in the process of doing so.
An example of a learning activity that would be closely aligned with the ideas of Vygotsky would include the utilization of clusters. This process involves a series of different group projects with the students working in collaboration with a management plan that is student centered. We often perform tasks similar to this in my math program that involve students relying on prior knowledge, working with the assistance of others, in the development of new skills. Not all concepts can be delivered in the manner but there are opportunities to do so in our curriculum.
Geometry is a unit in math that is conducive to clusters. The students work with a variety of manipulatives together in groups to discover and extend learning. This design has proven to be successful in the development of knowledge in geometry. Also, the students seem to enjoy the change in delivery and style of learning. These type projects are challenging to set up with much of the work on the front end. Once the groups are established with all materials organized and outcomes clearly understood, the projects seem to flow efficiently.
In conclusion, many forms and theories of learning styles and types of learning have been observed. Metacognition, self-regulation, behaviorism, and constructivism are all theories that have contributed to a better understanding of how people learn. Recognizing that we are all different and learn at different rates, levels, and through different means, supports the notion that in some ways all theories should be incorporated into our lessons. Through the examples provided involving my math lessons, different lessons closely resemble different strategies outlined in each of the theories. This study has helped me to understand the complexities of the mind and the demand for differentiated instruction. Developing students to think cognitively about their learning will greatly assist them to become lifelong learners. This should be a goal of all educational programs.
Ackerman, R. & Goldsmith, M. (2011). Metacognitive Regulation of Text Learning: On Screen Versus on Paper. Journal of Experimental Psychology: Applied, 17, 18-32. doi: 10. 1037/a0022086 Cape Breton Victoria Regional School Board, (n. d. ). PEBS. Retrieved from http://www. bv. ns. ca/pebs/ Education 6600: Human Learning and Motivation. Memorial University of Newfoundland, 2006, Retrieved from http://online. mun. ca/d2l/lms/content/viewer/main_frame. d2l? ou=114857&tId=1071550 Ertmer, P. & Newby, T. (1996). The expert learner: Strategic, self-regulated, and reflective. Instructional Science, 24, 1-24. doi: 10. 1007/BF00156001 Matthews J. S. , Ponitz C. C. , and Morrison F. J. (2009). Early Gender Differences in Self-Regulation and Academic Achievement. Journal of Educational Psychology, 101, 689-704. doi: 10. 1037/a0014240
Palinscar, A. (1998). Social constructivist perspectives on teaching and learning. Annual Review of Psychology, 49, 345-375. doi: 10. 1146/annurev. psych. 49. 1. 345 Palinscar, A. & Brown, A. (1987). Enhancing instructional time through attention to metacognition. Journal of Learning Disabilities, 20, 66-75. doi: 10. 1177/002221948702000201 Pennequin V. ,Sorel O. , Nanty I. , and Fontaine R. (2010). Metacognition and low achievement in mathematics: The effect of training in the use of metacognitive skills to solve mathematical word problems.
Thinking and Reasoning, 16, 198-220. doi: 10. 1080/13546783. 2010. 509052 Schraw, G. & Moshman, D. (1995). Metacognitive theories. Educational Psychology Review, 7, 351-371. doi: 10. 1007/BF02212307 Schunk, D. (1987). Peer models and children’s behavioral change. Review of Educational Research, 57, 149-174. Retrieved from http://www. jstor. org/stable/1170234 Zimmerman, B. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 42, 64-70. Retrieved from http://www. jstor. org/stable/1477457