- Email: [email protected]
Exploring the learning process
Teaching and Learning in Nursing (2010) 5, 157–159
www.jtln.org
Exploring the learning process Patricia C. Jenkins EdD, MSN, RN⁎ Roane State Community College, Harriman, TN 37748, USA KEYWORDS: Learning process; Motivation and rewards; Mindsets
1. Introduction Teachers and students come to the classroom possessing distinct temperaments, personalities, talents, weaknesses, and preferred learning styles (Fairhurst & Fairhurst, 1995; Liesveld & Miller, 2005; Mollan-Masters, 1997). Despite the diversity among human beings and their preferences, human beings are learning machines. People do not have to be taught to learn although they can improve their learning strategies. Smilkstein (2003) clearly portrayed that concept with the title of her book, We're Born to Learn. The literature on mindsets (Dweck, 2006), motivation and rewards (Kohn, 1993), and memory and how the brain learns (Kandel, 2006; Medina, 2008; Restak, 2003, 2006; Sousa, 2006; Smilkstein, 2003) facilitates understanding the learning process. The specific questions to be explored in this article are the following: What are fixed and growth mindsets and how do they relate to learning? What is the impact of motivation and rewards on learning? How does the brain learn? What factors impact learning? What is the difference between how a novice solves a problem as compared with an expert?
2. Mindsets Understanding the ways individuals may frame challenges (mindsets) facilitates understanding how different * Corresponding author. E-mail address: [email protected]
types of learners approach the challenge of learning. Dweck (2006) provided insight into the concepts of mindsets, fixed and growth, and the impact of these mindsets or beliefs on individuals. Dweck believed that individuals with a fixed mindset, for example, think that “you can simply measure the fixed ability right now and project it into the future. Just give the test or ask the expert” (p. 27). On the other hand, individuals with a growth mindset think that their abilities or talents can be developed. More specifically, “the fixed mindset makes you concerned with how you'll be judged; the growth mindset makes you concerned with improving” (Dweck, 2006, p. 13). Thus, individuals interpret challenges and failures in markedly different ways depending on their mindsets. In regard to challenges, individuals with a fixed mindset do not believe that it is necessary to invest time and/or effort to accomplish a particular task or assignment. In other words, if you have the ability, accomplishing the task should be easy. This is in stark contrast to individuals with a growth mindset who strive to improve, which requires an investment of both time and effort. Furthermore, for those with a fixed mindset, there is the fear of failure. It is not just the idea that the individual failed at a particular task or assignment. Instead, failure is interpreted to mean that the person is a failure. However, for those with a growth mindset, failure may be a painful experience, but the failure does not define the person (Dweck, 2006). In addition to Dweck's work on mindset, examining motivation and the impact of rewards on behavior will expand our understanding of learning.
1557-3087/$ – see front matter © 2010 National Organization for Associate Degree Nursing. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.teln.2010.03.003
158
P.C. Jenkins
3. Motivation and rewards Motivational theory provides insight into the concept of intrinsic and extrinsic motivators and their impact on learning. “Intrinsic motivation is the expectation that engaging in, or completing, a task will be enjoyable” (McKeachie, Pintrich, Lin, Smith, & Sharma, 1994, p. 107) and is a strong predictor of an individual's success in the workplace or school (Kohn, 1993). This contrasts with the effect of extrinsic motivators (such as grades) on people's response to a learning environment or situation. It is interesting to note that research indicates that external rewards tend to have a negative effect on an individual's intrinsic motivation (Bain, 2004; Kohn, 1993). Kohn (1993) stated, “What rewards and punishments do is induce compliance, and this they do well indeed” (p. 41). However, clearly, he does not believe that rewards facilitate the development of self-motivated (lifelong) learners.
4. The brain and learning Regardless of temperament, personality, or learning preference, human beings are essentially learning machines. Smilkstein (2003) emphasized that human beings are born to learn, think, identify patterns, and process information and that adults and children seem to learn in a similar manner. The human brain is an amazing organ and can perform many processes concurrently; however, the brain is limited in that it is not really able to multitask. In other words, it can only focus on a small number of tasks at any given point in time (Medina, 2008; Restak, 2003, 2006). In fact, doing more than one thing at once or switching back and forth from one task to another involves timeconsuming alterations in brain processing that reduces our effectiveness at accomplishing either one (Restak, 2003, p. 55).
The human brain consists of different sections that have different functions or control different processes. Some of these functions require conscious attention, whereas others are more automatic. For example, the prefrontal and frontal cortex is involved in processes that require conscious attention such as solving problems, paying attention, and controlling our emotions (Medina, 2008, Restak, 2006; Sousa, 2006). On the other hand, the occipital, parietal, and temporal lobes are associated with automatic processes. In addition to the prefrontal and frontal cortex, there are other parts of the brain that also contribute to learning. These include the amygdala and the hippocampus (Sousa, 2006; Medina, 2008). “The amygdala is responsible for both the creation of emotions and the memories they generate” (Medina, 2008, p. 40). The hippocampus is instrumental in changing the working memory (short-term) into long-term (Medina, 2008; Kandel, 2006; Sousa, 2006). Sousa (2006) emphasized that “memories are not stored as a whole in one
place” (p. 51). Instead, a memory is stored in a variety of places and is reassembled upon recall (Medina, 2008; Sousa, 2006). In addition, research indicates that learning produces structural changes in the brain (Kandel, 2006). More specifically, when learning occurs, new synapses are created. “While learning does not increase the number of brain cells, it does increase their size, their branches, and their ability to form more complex networks” (Sousa, 2006, p. 78). Medina (2008) described this as follows: “As neurons learn, they swell, sway and split” (p. 57). This results in the formation of new connections, which requires time to develop. Smilkstein (2003) stated, “Learning takes time because it requires growing new dendrites, synapses, and neural networks” (p. 63).
5. Other factors impacting learning Clearly, learning is a complex cognitive process that requires time and effort. Regardless of the course, students come to the classroom and course with preconceived ideas that impact their ability to learn new content. Learning is, thus, facilitated by building on or challenging students' preconceived ideas (Bain, 2004; National Research Council, 2000) and helping students link new information to previously learned information (Smilkstein, 2003). According to Sousa (2006), “the degree of meaning attributed to new learning will determine the connections that are made between it and other information in longterm storage” (p. 136). Additional factors impact learning. One that seems to promote learning is the desire to answer a question. This is an important concept as there seems to be little motivation to pay attention to information that does not seem to be relevant. Thus, asking questions tends to facilitate learning. Bain (2004) stated, “They [questions] point to holes in our memory structures and are critical for indexing the information that we attain when we develop an answer for that inquiry” (p. 31). Other factors impacting learning include the fact that the brain has a limit to the amount of information it can hold in short-term memory. An interesting finding was that the amount of time it takes to learn something correlates to the amount of material. In other words, learning more material— especially complex material—requires more time. In addition, trying to cover too much content too quickly may negatively impact learning and subsequent transfer of that learning (National Research Council, 2000; Sousa, 2006). The concept of transfer of learning involves the learner being able to apply previous learning to a situation that is, at least, a little different than the original learning environment or situation (McKeachie et al., 1994). The ability to transfer learning is thus impacted by the extent to which the individual understands the material. Sousa (2006) emphasized that “the more connections that students can make
Learning process between past learning and new learning, the more likely they are to determine sense and meaning and thus retain the new learning” (p. 138). It is thus not surprising that learning with understanding requires more time and effort than merely memorizing the material (National Research Council, 2000). Processing and reprocessing information are critical to facilitating the transfer of information to long-term memory (Sousa, 2006). Of note is the fact that “learners store information in long-term memory in an organized fashion related to their existing understanding of the world” (Svinicki, 1994, p. 277). In other words, organizing information into a conceptual framework facilitates both learning and the ability to transfer previously learned material into a new learning situation (National Research Council, 2000).
6. Novice versus expert Additional insight into learning comes from research on the difference between a novice and an expert. The work by the National Research Council (2000) discusses how an expert perceives and interprets information as compared with the way a novice perceives the same information. For example, an expert will observe features and identify meaningful patterns that the novice will not. The expert is able to retain a large amount of information in his or her shortterm memory because the expert chunks the information into meaningful patterns or clusters. Experts possess a great deal of knowledge about a subject or their discipline that is organized conceptually around key or core ideas. In addition, experts have a deep understanding of the discipline and are able to easily retrieve the pertinent information to solve a problem. However, being able to easily retrieve the pertinent information or core concepts to understand the problem and recognize the appropriate strategy to solve the problem does not necessarily mean that the expert can perform that task faster than the novice. In other words, speed of task completion is not considered to be a unique feature of an expert (National Research Council, 2000). The work by the National Research Council (2000) identifies several factors affecting the development of both expertise and competent performance. One idea in particular is that “relevant knowledge helps people organize information in ways that support their abilities to remember” (p. 237). Another important factor is that learners do not always relate the knowledge they possess to new tasks, despite its potential relevance. This “disconnect” has important implications for understanding differences between usable knowledge (which is the kind of knowledge that experts have developed) and less organized knowledge, which tends to remain “inert (p. 237).” Third, different domains of knowledge, such as science, mathematics, and history, have different organizing properties. It follows, therefore, that to have an in-depth grasp of an area requires knowledge about both the
159 content of the subject and the broader structural organization of the subject (National Research Council, 2000, pp. 237–238).
In addition, the National Research Council (2000) also noted that capable learners monitor their learning and make adjustments in their strategies as needed. Thus, understanding the development of expertise and how an expert approaches a problem as compared with a novice further contributes to our understanding of the complex process of learning.
7. Conclusion Human beings demonstrate the ability to learn even without being taught how to learn. Clearly, research is providing increasing insight into the complex process of learning, knowledge about the brain, the difference between a novice and an expert, and other factors impacting learning such as mindset, motivation, and reward. Thus, becoming more knowledgeable about the brain, the structural changes that take place in the brain when learning occurs, the learning process, the development of expertise, and the effect of mindsets, motivation, and rewards on learning and the development of lifelong learners has significant implications for the teacher when designing meaningful learning experiences.
References Bain, K. (2004). What the best college teachers do. Cambridge: Harvard University Press. Dweck, C. S. (2006). Mindset. New York: Random House. Fairhurst, A. M., & Fairhurst, L. L. (1995). Effective teaching, effective learning—making the personality connection in your classroom. Palo Alto: Davies-Black Publishing. Kandel, E. R. (2006). In search of memory. New York: W.W. Norton & Company. Kohn, A. (1993). Punished by rewards. Boston: Houghton Mifflin Company. Liesveld, R., & Miller, J. A. (2005). Teach with your strengths. New York: Gallup Press. McKeachie, W. J., Pintrich, P. R., Lin, Y., Smith, D. A. F., & Sharma, R. (1994). A review of the research literature. In K. A. Feldman, & M. B. Paulsen (Eds.), Teaching and learning in the college classroom (pp. 75−114). Needham Heights: Simon & Schuster Custom Publishing. Medina, J. (2008). Brain rules. Seattle: Pear Press. Mollan-Masters, R. (1997). You are smarter than you think, 2nd ed. Ashland: Reality Productions. National Research Council (2000). How people learn. Washington, DC: National Academy Press. Restak, R. (2006). The naked brain. New York: Three Rivers Press. Restak, R. (2003). The new brain. USA: Rodale. Svinicki, M. D. (1994). Practical implications of cognitive theories. In K. A. Feldman, & M. B. Paulsen (Eds.), Teaching and learning in the college classroom (pp. 275−282). Needham Heights: Simon & Schuster Custom Publishing. Smilkstein, R. (2003). We're born to learn. Thousand Oaks: Corwin Press Inc. Sousa, D. A. (2006). How the brain learns, 3rd ed. Thousand Oaks: Corwin Press.
www.jtln.org
Exploring the learning process Patricia C. Jenkins EdD, MSN, RN⁎ Roane State Community College, Harriman, TN 37748, USA KEYWORDS: Learning process; Motivation and rewards; Mindsets
1. Introduction Teachers and students come to the classroom possessing distinct temperaments, personalities, talents, weaknesses, and preferred learning styles (Fairhurst & Fairhurst, 1995; Liesveld & Miller, 2005; Mollan-Masters, 1997). Despite the diversity among human beings and their preferences, human beings are learning machines. People do not have to be taught to learn although they can improve their learning strategies. Smilkstein (2003) clearly portrayed that concept with the title of her book, We're Born to Learn. The literature on mindsets (Dweck, 2006), motivation and rewards (Kohn, 1993), and memory and how the brain learns (Kandel, 2006; Medina, 2008; Restak, 2003, 2006; Sousa, 2006; Smilkstein, 2003) facilitates understanding the learning process. The specific questions to be explored in this article are the following: What are fixed and growth mindsets and how do they relate to learning? What is the impact of motivation and rewards on learning? How does the brain learn? What factors impact learning? What is the difference between how a novice solves a problem as compared with an expert?
2. Mindsets Understanding the ways individuals may frame challenges (mindsets) facilitates understanding how different * Corresponding author. E-mail address: [email protected]
types of learners approach the challenge of learning. Dweck (2006) provided insight into the concepts of mindsets, fixed and growth, and the impact of these mindsets or beliefs on individuals. Dweck believed that individuals with a fixed mindset, for example, think that “you can simply measure the fixed ability right now and project it into the future. Just give the test or ask the expert” (p. 27). On the other hand, individuals with a growth mindset think that their abilities or talents can be developed. More specifically, “the fixed mindset makes you concerned with how you'll be judged; the growth mindset makes you concerned with improving” (Dweck, 2006, p. 13). Thus, individuals interpret challenges and failures in markedly different ways depending on their mindsets. In regard to challenges, individuals with a fixed mindset do not believe that it is necessary to invest time and/or effort to accomplish a particular task or assignment. In other words, if you have the ability, accomplishing the task should be easy. This is in stark contrast to individuals with a growth mindset who strive to improve, which requires an investment of both time and effort. Furthermore, for those with a fixed mindset, there is the fear of failure. It is not just the idea that the individual failed at a particular task or assignment. Instead, failure is interpreted to mean that the person is a failure. However, for those with a growth mindset, failure may be a painful experience, but the failure does not define the person (Dweck, 2006). In addition to Dweck's work on mindset, examining motivation and the impact of rewards on behavior will expand our understanding of learning.
1557-3087/$ – see front matter © 2010 National Organization for Associate Degree Nursing. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.teln.2010.03.003
158
P.C. Jenkins
3. Motivation and rewards Motivational theory provides insight into the concept of intrinsic and extrinsic motivators and their impact on learning. “Intrinsic motivation is the expectation that engaging in, or completing, a task will be enjoyable” (McKeachie, Pintrich, Lin, Smith, & Sharma, 1994, p. 107) and is a strong predictor of an individual's success in the workplace or school (Kohn, 1993). This contrasts with the effect of extrinsic motivators (such as grades) on people's response to a learning environment or situation. It is interesting to note that research indicates that external rewards tend to have a negative effect on an individual's intrinsic motivation (Bain, 2004; Kohn, 1993). Kohn (1993) stated, “What rewards and punishments do is induce compliance, and this they do well indeed” (p. 41). However, clearly, he does not believe that rewards facilitate the development of self-motivated (lifelong) learners.
4. The brain and learning Regardless of temperament, personality, or learning preference, human beings are essentially learning machines. Smilkstein (2003) emphasized that human beings are born to learn, think, identify patterns, and process information and that adults and children seem to learn in a similar manner. The human brain is an amazing organ and can perform many processes concurrently; however, the brain is limited in that it is not really able to multitask. In other words, it can only focus on a small number of tasks at any given point in time (Medina, 2008; Restak, 2003, 2006). In fact, doing more than one thing at once or switching back and forth from one task to another involves timeconsuming alterations in brain processing that reduces our effectiveness at accomplishing either one (Restak, 2003, p. 55).
The human brain consists of different sections that have different functions or control different processes. Some of these functions require conscious attention, whereas others are more automatic. For example, the prefrontal and frontal cortex is involved in processes that require conscious attention such as solving problems, paying attention, and controlling our emotions (Medina, 2008, Restak, 2006; Sousa, 2006). On the other hand, the occipital, parietal, and temporal lobes are associated with automatic processes. In addition to the prefrontal and frontal cortex, there are other parts of the brain that also contribute to learning. These include the amygdala and the hippocampus (Sousa, 2006; Medina, 2008). “The amygdala is responsible for both the creation of emotions and the memories they generate” (Medina, 2008, p. 40). The hippocampus is instrumental in changing the working memory (short-term) into long-term (Medina, 2008; Kandel, 2006; Sousa, 2006). Sousa (2006) emphasized that “memories are not stored as a whole in one
place” (p. 51). Instead, a memory is stored in a variety of places and is reassembled upon recall (Medina, 2008; Sousa, 2006). In addition, research indicates that learning produces structural changes in the brain (Kandel, 2006). More specifically, when learning occurs, new synapses are created. “While learning does not increase the number of brain cells, it does increase their size, their branches, and their ability to form more complex networks” (Sousa, 2006, p. 78). Medina (2008) described this as follows: “As neurons learn, they swell, sway and split” (p. 57). This results in the formation of new connections, which requires time to develop. Smilkstein (2003) stated, “Learning takes time because it requires growing new dendrites, synapses, and neural networks” (p. 63).
5. Other factors impacting learning Clearly, learning is a complex cognitive process that requires time and effort. Regardless of the course, students come to the classroom and course with preconceived ideas that impact their ability to learn new content. Learning is, thus, facilitated by building on or challenging students' preconceived ideas (Bain, 2004; National Research Council, 2000) and helping students link new information to previously learned information (Smilkstein, 2003). According to Sousa (2006), “the degree of meaning attributed to new learning will determine the connections that are made between it and other information in longterm storage” (p. 136). Additional factors impact learning. One that seems to promote learning is the desire to answer a question. This is an important concept as there seems to be little motivation to pay attention to information that does not seem to be relevant. Thus, asking questions tends to facilitate learning. Bain (2004) stated, “They [questions] point to holes in our memory structures and are critical for indexing the information that we attain when we develop an answer for that inquiry” (p. 31). Other factors impacting learning include the fact that the brain has a limit to the amount of information it can hold in short-term memory. An interesting finding was that the amount of time it takes to learn something correlates to the amount of material. In other words, learning more material— especially complex material—requires more time. In addition, trying to cover too much content too quickly may negatively impact learning and subsequent transfer of that learning (National Research Council, 2000; Sousa, 2006). The concept of transfer of learning involves the learner being able to apply previous learning to a situation that is, at least, a little different than the original learning environment or situation (McKeachie et al., 1994). The ability to transfer learning is thus impacted by the extent to which the individual understands the material. Sousa (2006) emphasized that “the more connections that students can make
Learning process between past learning and new learning, the more likely they are to determine sense and meaning and thus retain the new learning” (p. 138). It is thus not surprising that learning with understanding requires more time and effort than merely memorizing the material (National Research Council, 2000). Processing and reprocessing information are critical to facilitating the transfer of information to long-term memory (Sousa, 2006). Of note is the fact that “learners store information in long-term memory in an organized fashion related to their existing understanding of the world” (Svinicki, 1994, p. 277). In other words, organizing information into a conceptual framework facilitates both learning and the ability to transfer previously learned material into a new learning situation (National Research Council, 2000).
6. Novice versus expert Additional insight into learning comes from research on the difference between a novice and an expert. The work by the National Research Council (2000) discusses how an expert perceives and interprets information as compared with the way a novice perceives the same information. For example, an expert will observe features and identify meaningful patterns that the novice will not. The expert is able to retain a large amount of information in his or her shortterm memory because the expert chunks the information into meaningful patterns or clusters. Experts possess a great deal of knowledge about a subject or their discipline that is organized conceptually around key or core ideas. In addition, experts have a deep understanding of the discipline and are able to easily retrieve the pertinent information to solve a problem. However, being able to easily retrieve the pertinent information or core concepts to understand the problem and recognize the appropriate strategy to solve the problem does not necessarily mean that the expert can perform that task faster than the novice. In other words, speed of task completion is not considered to be a unique feature of an expert (National Research Council, 2000). The work by the National Research Council (2000) identifies several factors affecting the development of both expertise and competent performance. One idea in particular is that “relevant knowledge helps people organize information in ways that support their abilities to remember” (p. 237). Another important factor is that learners do not always relate the knowledge they possess to new tasks, despite its potential relevance. This “disconnect” has important implications for understanding differences between usable knowledge (which is the kind of knowledge that experts have developed) and less organized knowledge, which tends to remain “inert (p. 237).” Third, different domains of knowledge, such as science, mathematics, and history, have different organizing properties. It follows, therefore, that to have an in-depth grasp of an area requires knowledge about both the
159 content of the subject and the broader structural organization of the subject (National Research Council, 2000, pp. 237–238).
In addition, the National Research Council (2000) also noted that capable learners monitor their learning and make adjustments in their strategies as needed. Thus, understanding the development of expertise and how an expert approaches a problem as compared with a novice further contributes to our understanding of the complex process of learning.
7. Conclusion Human beings demonstrate the ability to learn even without being taught how to learn. Clearly, research is providing increasing insight into the complex process of learning, knowledge about the brain, the difference between a novice and an expert, and other factors impacting learning such as mindset, motivation, and reward. Thus, becoming more knowledgeable about the brain, the structural changes that take place in the brain when learning occurs, the learning process, the development of expertise, and the effect of mindsets, motivation, and rewards on learning and the development of lifelong learners has significant implications for the teacher when designing meaningful learning experiences.
References Bain, K. (2004). What the best college teachers do. Cambridge: Harvard University Press. Dweck, C. S. (2006). Mindset. New York: Random House. Fairhurst, A. M., & Fairhurst, L. L. (1995). Effective teaching, effective learning—making the personality connection in your classroom. Palo Alto: Davies-Black Publishing. Kandel, E. R. (2006). In search of memory. New York: W.W. Norton & Company. Kohn, A. (1993). Punished by rewards. Boston: Houghton Mifflin Company. Liesveld, R., & Miller, J. A. (2005). Teach with your strengths. New York: Gallup Press. McKeachie, W. J., Pintrich, P. R., Lin, Y., Smith, D. A. F., & Sharma, R. (1994). A review of the research literature. In K. A. Feldman, & M. B. Paulsen (Eds.), Teaching and learning in the college classroom (pp. 75−114). Needham Heights: Simon & Schuster Custom Publishing. Medina, J. (2008). Brain rules. Seattle: Pear Press. Mollan-Masters, R. (1997). You are smarter than you think, 2nd ed. Ashland: Reality Productions. National Research Council (2000). How people learn. Washington, DC: National Academy Press. Restak, R. (2006). The naked brain. New York: Three Rivers Press. Restak, R. (2003). The new brain. USA: Rodale. Svinicki, M. D. (1994). Practical implications of cognitive theories. In K. A. Feldman, & M. B. Paulsen (Eds.), Teaching and learning in the college classroom (pp. 275−282). Needham Heights: Simon & Schuster Custom Publishing. Smilkstein, R. (2003). We're born to learn. Thousand Oaks: Corwin Press Inc. Sousa, D. A. (2006). How the brain learns, 3rd ed. Thousand Oaks: Corwin Press.