2 Psychology of Learning

Setting the Stage

As your first year of teaching draws to a close, you find yourself reflecting on the year. You were hired as one of three agriculture teachers to teach floral design, vet science, and welding. Of the 1,500 students in the school, you begin to think about the students who walked into your class each day. While a majority achieved a passing grade, what did they really learn in your courses? As you consider the makeup of your classes, you realize that one in five students were from underrepresented groups and two out of five students did not have an agricultural background. You question whether you have adequately met the needs of these students especially as they were not the ones who won awards or competed in career development or judging events. It leaves you wondering if they learned what you expected them to learn in your courses. You begin to reflect on several important questions: Are there changes you could make to your instructional approach to better excite all your students, regardless of their background? Is there research about learning to help you design strategies to ensure your teaching results in meaningful learning outcomes for all students?

Introduction

Research on learning should ultimately contribute to improved teaching. While teaching and learning complement one another, good teaching and good learning are not sufficient to ensure one another’s success. Educators play a critical role in creating effective learning environments that assist in completing cognitive activities necessary to develop and demonstrate certain skills and abilities (Schunk, 2012). But your actions may not always result in learning by your participants. Many factors influence whether learning occurs or not, and thus it is important to have a deeper understanding of what learning is and how it happens. So, let’s go a little deeper into a definition of learning to help better understand how learning happens. Does learning involve an increase in knowledge? Does learning involve a change in behavior? Does learning require reflection? Does learning require that you demonstrate some type of activity? Does learning involve a change in beliefs and attitudes? Does learning happen better through social interactions? While researchers, practitioners, and theorists have not reached an agreement on a universal definition of learning (Schuell, 1986), Schunck (2012) defines learning as “an enduring change in behavior, or in the capacity to behave in a given fashion, which results from practice or other forms of experience” (p. 3). Three criteria for learning include: (1) learning involves change, (2) learning endures over time, and (3) learning occurs through experience.

Just as there is no universal definition of learning, there is also debate on how learning occurs (processes) and factors that impact learning. Older theories of learning center on behavioral views, meaning learning is explained through observable behaviors. For instance, if you were an educator who believed learning occurred this way, you would arrange the environment so that individuals would respond to certain features. For example, you give a time-out to learners who need to restore their attention to your class. A cognitive approach situates learning as an internal mental phenomenon that you can infer from what people say and do. An implication for teachers as a result of cognitive theories would mean teachers should make learning meaningful and take into account learners’ perceptions of themselves (their identity) and their environment. The constructivist perspective of learning contends that individuals learn by constructing or forming their knowledge. It focuses more on human factors that explain how learning occurs. Most modern learning theories are based on the tenets of cognitive and constructivist theories so in this chapter, our focus will be on the cognitive and constructivist aspects of learning.

Though many of the learning theories differ in how they distinguish the processes and factors of learning, we know learning is not just about the instructional factors (Pintrich et al., 1986). Of critical importance is what learners do with the information and how they process this information (Schunk, 2012). We also know educators cannot ignore the differences among individual learners including their thoughts, beliefs, attitudes, and values. These factors influence the learning process.

Motivation impacts how individuals learn. In this chapter, we will also explore some theories that offer explanations for what motivates learners. How people approach and construct learning is impacted by their identities (e.g., perceptions, values, goals, beliefs, and attitudes). The identity exploration framework offers a model to consider as we think about how to engage and motivate learners.

We will introduce some theoretical and scholarly foundations of learning and the brain, behavioral, cognitive, and constructivist theories of learning and the tenets of motivation related to learning. Specifically, we will explore the following content related to learning:

1. Learning and the brain
2. Overview of learning theories: Behaviorism, cognitivism, and constructivism
3. Selected learning theories: Information processing theory and cognitive load theory
4. Selected motivation theories: Social cognitive theory, outcome expectations and goal setting theory, self-efficacy, and identity exploration framework
5. Synthesis of learning theories and research related to learning

Learning and the Brain

How does understanding the function and structure of the human brain increase our understanding of being an effective educator? Understanding brain development and the location of brain functions helps constrain educational theories and models of behavior (Casey et al., 2000). Human brain development is a complex event occurring across the life cycle. Through the discoveries of cognitive neuroscience, we learned that humans receiving, selecting, storing, transforming, developing, and recovering information are all parts of a continuous development process that happens from birth to early adolescence (Casey et al., 2005). Human brain development in the temporal and frontal areas have been consistently associated with higher cognitive abilities (Casey et al., 2005, 2002; Krawczyk, 2018). Research in neuroscientific brain maturation of cognitive abilities, such as short-term (or working) memory and long-term memory, provides valuable information that can be applied in teaching and learning. Some distinct findings from cognitive neuroscience include: (1) Short-term memory has limited capacity and is associated with the focus of attention (Cowan, 1995); (2) Sensory functions, such as visual, short-term memory capacity declines with increasing task complexity (Alvarez & Cavanagh, 2004); (3) Instead of cramming information in a long and intense learning session, repeating information in multiple short learning sessions has optimized long-term memory and improved information retention (Gluckman et al., 2014); (4) Different kinds of memories rely on different neural correlates and mental processes (Nie et al., 2019), (5) Connecting prior knowledge with new information promotes comprehension and memory coding performance (Maguire et al., 1999), and (6) Various instructional approaches stimulate different parts and functions of the human brain that impact short-term and long-term memory—for example, comparing the repeated practice of solving a mathematics equation to letting learners create a solution stimulates different patterns of brain activity that help learners use more short-term memory (Wirebring et al., 2015).

Although understanding the function and structure of the human brain shines light on how people learn, learning is a far more complicated process than simply understanding neuroscientific brain maturation of cognitive abilities. A more recent and dominant learning perspective in the discipline of learning sciences is the 4E Cognition model. 4E Cognition contends that learning is enacted, embodied, embedded, and extended (Steier et al., 2019). 4E Cognition is a tool for understanding the complicated notion of cognition (or learning). The premise of the 4E Cognition model is that learning involves more than just the brain; our bodies, the situation, and interactions within the environment also contribute to learning. The enacted part of the model implies that thinking involves interaction with others, the immediate context, and various other items like language and culture. Embodied implies that learning is in relation to our actions. Our actions imply learning. The embodied mind cannot function in isolation from the physical, social, and cultural environment because the environment in which the mind exists is part of the mind. Embedded has to do with the environment including physical elements, cultural-historical structures, and social characteristics like interpersonal relationships and interactions. The unique features of an environment provide unique affordances for cognition. For learning to be effective, environmental resources should be taken into account (Pouw et al., 2014). To help you think about the idea of 4E Cognition, consider this example. Think about the context of baseball and specifically an outfielder catching a fly ball. Before the batter steps to the plate, the coach might be able to speculate where the outfielder should stand based on past performance and experience with that particular batter. But, when it comes time for the outfielder to catch the ball, they must react in the moment and adjust according to where the ball is actually hit.

Overview of Learning Theories

Behaviorism, cognitivism, and constructivism play an important role in the development of contemporary educational psychology theories. In the early twentieth century, behaviorism emphasized using instructional reinforcement (both positive and negative) to structure a learning environment, and behaviorists evaluated observable behavior and performance to measure success of learning (Skinner, 1976). Although receiving many criticisms, behaviorism has proven as an effective instructional strategy when a teacher uses memorized educational materials and instructions (Woollard, 2010). For example, when an educator gives immediate and direct feedback to praise learners who correctly answered a pop quiz (factual questions), it is generally recognized as a behaviorist’s teaching strategy. In the 1950s and 1960s, there was a shift from behaviorism to cognitivism, where instructional design was focused more on thought processes and mental activities but less on changing behaviors (Wittrock, 1986).

Cognitive psychologists believe that learning occurs through internal mental processing of information and that learners’ thoughts, beliefs, and attitude play important roles in their learning process (Winne, 1985). Cognitivism stresses that learning is an active and goal-oriented process (Shuell, 1986), and cognitivism utilizes external tools as an instructional strategy to provoke learners’ internal mental activities to learn efficiently. For example, when an educator asks learners to keep an agriscience journal to reflect on what they have learned, this is a cognitive learning strategy that helps learners organize their learning based on how the human brain processes information internally.

On the other hand, constructivism is a learning theory that highlights how learners construct knowledge by developing personal meaning out of experiences rather than passively receiving information. Learning involves the reconstruction of existing knowledge to include the newly encountered experience, and existing knowledge has a contextualized meaning that is aligned with the experience (Haglud et al., 2012; Piaget, 1970). In a classroom, constructivists believe an educator needs to help learners retrieve their existing knowledge and provide opportunities for learners to reconstruct their existing knowledge with external experiences. Additionally, from the social constructivist viewpoints, social interactions play an important role in learning (Vygotsky, 1978). Learners construct their knowledge through conversation, discussion, and interaction with their peers and with educators. For example, instead of asking factual questions, an educator asks “why” questions to elicit learners’ prior knowledge and continually facilitates conversations with learners. The educator attempts to structure a learning environment that allows learners of different backgrounds and experiences to share their thoughts and construct knowledge depending upon their needs. Table 2.1 summarizes the three dominant paradigms of learning theories, behaviorism, cognitivism, and constructivism.

Table 2.1: Summary of behaviorism, cognitivism, and constructivism.

There are many educational psychology theories that are rooted in behaviorism, cognitivism, and constructivism. In this chapter, we go particularly deep into information processing theory (an extension of cognitivism) and some theories that are associated with motivation and learning, such as social cognitive theory and the identity exploration framework.

Selected Learning Theories

Information Processing Theory

Why do learners recall some information but not other information? Information processing theory (IPT) explains how the brain works to learn, store, and use information. The theory attempts to explain the path of how information is encoded into the memory system. Some scholars use an analogy to compare IPT with computer coding and analyzing information. Four factors—stimulation or stimuli, sensory registers, short-term memory, and long-term memory—are involved in the IPT. When we receive environmental stimuli through our senses (sensory input), we try to make meaning of them. In human brains, each sense has its own register to make meaning of the sensory input. Sensory information catches our attention, and the sensory registers progress the information to the short-term memory. However, only the information that is deemed relevant or is familiar to previously stored information will be transferred from sensory registers to short-term memory. The screening process is very selective. In other words, if there are many stimuli, we only respond to certain stimuli that catch our attention. Unless novel information is transferred from short-term memory to long-term memory, learning has not occurred. Our brains need to encode (elaborating processes in transferring) the information before we can store them into long-term memory. During encoding, our brains try to integrate the new information with the knowledge already stored in long-term memory and try to organize the information into a meaningful way. Retrieving existing knowledge and integrating newly encountered information with existing knowledge is critical in helping information transfer from short-term memory to long-term memory. Piaget (1970) provided a different perspective through the lens of educational psychology to explain this process. Piaget suggested two ways individuals use to construct knowledge: accommodation, in which individuals try to develop a new schema (as building blocks of our memories to help us understand how things work) to cope with a new experience, or assimilation, in which individuals try to balance and adapt the existing schema to a new experience. When experiences do not fit into an existing schema, individuals seek equilibration. Individuals take actions, such as asking questions, repeating the new experience, or seeking more information, to find equilibration to make sense of the newly encountered experience (Piaget, 1970).

Cognitive Load Theory

Another widely accepted learning theory based on human brain information processing and storing is cognitive load theory (Sweller et al., 1998). Cognitive load theory contends given that working memory is limited to processing novel information, working memory load is affected by the complexity of the task (intrinsic cognitive load), the relationship between the learning goal and design of instructional materials (extraneous cognitive load), and degree of integration of new information with prior knowledge that is stored in the long-term memory (germane cognitive load) (Schunk, 2012; Sweller, 1994). Therefore, when designing instruction, an educator should remember not to “overload” students with too much new or unfamiliar material, teach in a context with minimized distractions, and break complex learning into smaller chunks to not overwhelm cognitive load.

Motivation and Learning

Motivation is the study of why individuals behave the way they do. Educators are often challenged to figure out how to motivate their learners and interest them in being engaged in their learning and completion of tasks in a learning environment, such as a classroom or laboratory. While there are still many unanswered questions about motivation and little rigorous and systematic research on the interventions of the constructs of motivation, there are some tenets of motivation that are useful to apply in in formal and nonformal learning environments (Graham & Weiner, 2012). Motivation is a driving force that leads to goal-directed behavior to achieve an objective or a certain level of performance. Educators are driven by increasing learners’ motivation and their excitement to learn. What inspires people to learn and achieve the educational goals set for them? How can educators promote learners’ engagement and motivation to learn?

Broadly speaking, there are two types of motivation: intrinsic and extrinsic. Intrinsic motivation refers to when a person is moved to act for their interests, satisfaction, and enjoyment. Extrinsic motivation means a person is moved to act for external rewards, such as money, praise, or to avoid punishments. In this section, we introduce social cognitive theory, outcome expectations and goal setting theory, self-efficacy, and identity exploration framework and provide examples of how these theories could be used to promote learners’ motivation and performance.

Social Cognitive Theory

Social cognitive theory (SCT) is one of the landmark theories developed by psychologist Albert Bandura (1986). The theory stresses dynamic and reciprocal influences of behavior, environment, and individual cognitive factors. Learning through observation, outcome expectations, and self-efficacy are considered as the three individual cognitive factors that are affected by the environment to shape individuals’ behavior. Learning can occur by observing and watching others, which also is known as modeling, imitating, or mirroring (Meltzoff, 1990). Studies have shown observational learning involves both behavioral and neurophysiological reactions (e.g, mirror neuron system) to social environments (Csibra, 2007; Rizzolatti, 2005). Observers take note of others’ behavior, comprehend the meaning of the behavior, and imitate the behavior. For example, children might pick up on their parents being afraid of bugs, and then they also exhibit fear of insects. Specific to a learning environment, apprenticeship is one of the most representative samples of learning through observation. Apprenticeship, where an experienced master-mentor trains the newcomers to acquire skills and knowledge, is a common and effective way that health care, manufacturing, construction, and engineering are used to structure on-the-job training or classroom learning. In education, student teaching and early field observation are common practices of apprenticeship.

Outcome Expectations and Goal Setting Theory

Outcome expectation is one of the critical factors in SCT. Outcome expectation is defined as anticipated consequences (positive or negative) of a person’s behavior (Bandura, 1986). Outcome expectations highly connect with setting a goal and taking actions toward behavior change. Having learners set goals for themselves is one of the most effective ways to stay motivated. Locke and Latham (1990, 2002) proposed five principles of effective goal setting: clarity, challenge, commitment, feedback, and task complexity. Setting up a specific, clear, and challenging goal is better than a general, vague, and easy goal. For example, instead of setting up a goal like “I want to improve my overall course grade,” a specific and clear goal could be “I want to improve my overall course grade from C to B.” In the goal setting process, a learner should also put deliberate effort into achieving this goal. For example, “I want to improve my course grade from C to B. Especially, I want to increase crop and weed science by fifty points. To meet this goal, I will study the textbook for two hours a week.” Receiving immediate feedback is a key component for goal setting. An educator’s role is providing regular feedback throughout the process and helping learners to keep track of their progress. Additionally, if the goal is too complex, an educator could help break down the process into subgoals or give feedback on setting up a realistic timeline. For example, an educator’s feedback could be “I suggest you also put more details about what you will study in the textbook. For example, in week one and week two, you could focus on genetics. Then, in week three and four, you can move onto studying plant breeding and biotechnology.” Goal setting theory is highly associated with self-efficacy.

Self-efficacy

Bandura discusses the essential role that self-efficacy plays in social learning theory (Bandura, 1977, 1986). Self-efficacy refers to an individual’s belief in their own capacity to accomplish goals, which influences academic motivation, learning, and achievement (Bandura, 1986). Self-efficacy is task specific, and it is a strong predictor of task performance (Wood & Bandura, 1989). Learners who are more efficacious may have higher expectations for themselves and will set up higher level goals than those learners with less efficacy. Learners who are more efficacious are also more committed to achieving goals and respond more positively to failures (Locke & Latham, 1990). Bandura (1977) suggests four sources to increase self-efficacy: mastery experiences, vicarious experiences, verbal feedback and persuasion, and emotional and physiological states. To help learners master their learning, an educator can create a positive learning environment through reinforcing positive behaviors, using high-energy interactive instruction, and nurturing positive relationships to help learners value what they do. Educators can help learners know that although challenges and failures are inevitable, they have abilities, confidence, and desire to achieve their goals. Educators should also seek out various opportunities for learners to see successful role models. When seeing people with similar backgrounds, knowledge, and skills have successful experiences, learners increase their confidence and belief that they will experience similar success. When educators provide positive feedback to learners, it can lead to higher perceptions of self-efficacy and enhance learner success. Additionally, the emotional and psychological well-being of a person can influence how they feel about their capacities in a particular task.

Identity Exploration Framework

Much of the recent motivational research is focused on awareness and acknowledgment of individual differences and categorization of individuals as being either mastery or performance oriented, intrinsically or extrinsically motivated, and high or low in self-efficacy and self-regulation. In regard to the individuality of learners, educators must recognize that individual attributes of learners are important to how they learn (Graham & Weiner, 2012). Researchers, policy makers, teachers, parents, and learners themselves recognize that developing personal and interpersonal attributes in today’s changing world requires educators to focus on promoting learners’ agency and figuring out who they are and who they will become, the formation of their identities. Identity exploration has been defined as “deliberate internal or external action of seeking and processing information in relation to the self [where the outcome is], the creation of self-relevant meaning with an integrative effect and the facilitation of development” (Flum & Kaplan, 2006, p. 100). It is recommended that an educator’s role in identity exploration “is to organize academic experiences and opportunities that would encourage learners to question their self-aspects and investigate and consider alternative perceptions, values and goals” (Sinai et al., 2012, p. 197). Examples of pedagogical practices educators can engage in to promote identity exploration include posing complex personal problems that encourage learners to think about strengths and limits to alternative solutions, exposing learners to others who are experiencing identity exploration, using writing activities that encourage self-reflection, and creating focused activities around decision-making and critical thinking in the curriculum (Waterman, 1989).

The Identity Exploration Framework (Flum & Kaplan, 2006) is a central mechanism for identity formation associated with intense engagement, positive coping, openness to change, flexible cognition, and meaningful learning. Identity is considered an individual’s perceptions, values, beliefs, attitudes, and goals, is crucial to becoming, and is focused on adaptive motivation for learning the academic material. Some principles that have been identified for promoting adaptive identity exploration within the school curriculum (Kaplan et al., 2014) include:

1. Promoting relevance
2. Triggering exploration
3. Facilitating a sense of safety
4. Scaffolding exploratory actions

Promoting relevance. Promoting relevance involves helping learners connect academic content to self-aspects such as abilities, attributes, goals, values, behaviors, and emotions. It is important to note that perceived relevance is subjective in that it depends on the learner’s current self-constructions, concerns, interests, background, and experiences. One strategy for promoting relevance is to ask the learners to make connections between the academic content and aspects of their lives. For example, as a high school agriculture educator, one place where promoting relevance to learners may be natural is through opportunities like Future Farmers of America (FFA) and participating in Supervised Agricultural Experiences (SAE) events. This is where learners’ individual identities and interests could be illuminated. This strategy can be useful in increasing success of learners by triggering exploration, facilitating a sense of safety, and scaffolding exploratory actions.

Triggering exploration. Triggering exploration involves the questioning and examining of self-aspects that become apparent to learners through relevance. Exploration triggers are subjective experiences that are different from the current identifications or identity commitments (self-perceptions, values, goals, social roles, and relationships) of learners. Because learners differ in their concerns, cultural backgrounds, and openness to identity exploration, the same event may be an exploration trigger for one learner but not for another. Designing experiences that trigger exploration are reliant on the educator’s familiarity with the learners. Exploration triggers may also provoke a sense of conflict and threat including threats to self-worth that lead to struggle and resistance. Educators should be mindful of ensuring a safe learning environment to reduce threats associated with exploration triggers.

Facilitating a sense of safety. Exploration trigger experiences that are perceived as threats, are disappointments to significant others, or are at odds with one’s internalized sense of self can lead to learners feeling anxious and defensive and may require educators to establish a sense of safety in order for learners to engage in exploration. Like the previous two principles, learners may differ in what they perceive as being safe. Educators should engage in strategies that promote belonging, establish norms of mutual respect, and legitimize the perspectives and emotions of learners.

Scaffolding exploratory actions. Once learners perceive relevance of academic content to the self, experience a “relevant different” to trigger their identity exploration, and feel safe to engage in this exploration, they still need to have the knowledge in effective exploration strategies. Examples of scaffolding identity exploration activities include reflective questions for personal and interpersonal consideration, role-playing exercises, reflective writing activities, and peer modeling.

Educators should recognize the unique aspects of learners, especially in regard to the multicultural aspects of learners. Educators should continue to assess the psychological state of learners as they design activities: Are the learners perceiving self-relevance of the content? Are learners experiencing a “relevant difference” from identity aspects? Do learners feel safe? Are learners engaging in adaptive exploration strategies? Reviewing answers to these questions can assist educators in deciding which actions they should take to further learners’ identity exploration in relation to the academic material. Likewise, it is suggested that educators may not be prepared to engage in identity exploration because they do not hold this approach to teaching. Educators may ask themselves the same questions, but with the emphasis being on themselves instead of the learner (Kaplan et al., 2014).

In summary, there are many theories and research on learning that attempt to explain how learning occurs. While many theories exist (for a more comprehensive list, see Schunk, 2012), we have described some of the theories most relevant to agricultural education. The three dominant paradigms of learning theories are behaviorism, cognitivism, and constructivism. Within these paradigms are more specific theories like social cognitive theory. Motivation and self-efficacy are important factors for learning and should be accounted for when designing programs that maximize student learning in your classroom. Finally, the identity exploration framework is a model for educators to use in helping learners with identity exploration since identity and individual attributes of learners has been found to affect learning (Graham & Weiner, 2012).

References 

Alvarez, G. A., & Cavanagh, P. (2004). The capacity of visual short-term memory is set both by visual information load and by number of objects. Psychological Science, 15(2), 106–111. https://doi.org/10.1111/j.0963-7214.2004.01502006.x

Baker, M. A., Robinson, J. S., & Kolb, D. A. (2012). Aligning Kolb’s experiential learning theory with a comprehensive agricultural education model. Journal of Agricultural Education, 53(4), 1–16. https://doi.org/10.5032/jae.2012.04001

Bandura, A. (1977). Social learning theory. General Learning Press.

Bandura, A. (1986). Social foundations of thought and action. Prentice Hall.

Casey, B. J., Giedd, J. N., & Thomas, K. M. (2000). Structural and functional brain development and its relationship to cognitive development. Biological Psychology, 54, 241–257. https://doi.org/10.1016/s0301-0511(00)00058-2

Casey, B. J., Tottenham, N., Liston, C., & Durston, S. (2005). Imaging the developing brain: What have we learned about cognitive development? The Trends in Cognitive Sciences, 9(3), 104–110. https://doi.org/10.1016/j.tics.2005.01.011

Casey, B. J., Tottenham, N., & Fossella, J. (2002). Clinical, imaging, lesion, and genetic approaches toward a model of cognitive control. Developmental Psychobiology, 40(3), 237–254. https://doi.org/10.1002/dev.10030

Cowan, N. (1995). Attention and memory: An integrated framework. Oxford University Press.

Csibra, G. (2007). Action mirroring and action understanding: An alternative account. In P. Haggard, Y. Rossetti, & M. Kawato (Eds.), Sensorimotor foundations of higher cognition: Attention and performance XXII (pp. 435–480). Oxford University Press.

Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(1), 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153

Delazer, M., Ischebefk, A., Domahs, F., Zamarian, L., Koppelstaetter, F., Siedentopf, C. M., & Felber, S. (2005). Learning by strategies and learning by drill: Evidence from an fMRI study. Neuroimage, 25(3), 838–849. https://doi.org/10.1016/j.neuroimage.2004.12.009

Flum, H. & Kaplan, A. (2006) Exploratory Orientation as an Educational Goal, Educational Psychologist, 41:2, 99-110, DOI: 10.1207/s15326985ep4102_3

Gluckman, M., Vlach, H. A., & Sandhofer, C. M. (2014). Spacing simultaneously promotes multiple forms of learning in children’s science curriculum. Applied Cognitive Psychology, 28(2), 266–273. https://doi.org/10.1016/j.neuroimage.2004.12.009.

Graham, S., & Weiner, B. (2012). Motivation: Past, present, and future. In K. R. Harris, S. Graham, T. Urdan, C. B. McCormick, G. M. Sinatra, & J. Sweller (Eds.), APA educational psychology handbook, Vol. 1. Theories, constructs, and critical issues (pp. 367–397). American Psychological Association. https://doi.org/10.1037/13273-013

Haglund, J., Jeppson, F., & Andersson, J. (2012). Young children’s analogical reasoning in science domains. Science Education, 96(4), 725–756. https://doi.org/10.1002/sce.21009

Kaplan, A., Sinai, M., & Flum, H. (2014). Design-based interventions for promoting students’ identity exploration within the school curriculum. Advances in Motivation and Achievement, 18, 243–291. https://doi.org/10.1108/S0749-742320140000018007

Krawczyk, D. C. (2018). Reasoning origins: Human development during childhood. In D. C. Krawczyk (Ed.), Reasoning: The Neuroscience of how we think (pp. 101–129). Elsevier Inc. https://doi.org/10.1016/C2015-0-05936-6

Lee, J. K., & Kwon, Y. (2011). Why traditional expository teaching-learning approaches may founder? An experimental examination of neural network in biology learning. Journal of Biological Education, 45(2), 83–92. https://doi.org/ 10.1080/00219266.2010.548874

Locke E. A., & Latham G. P. (1990). A theory of goal setting and task performance. Prentice Hall.

Locke E. A., & Latham G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57, 705–717. https://doi.org/10.1037/0003-066X.57.9.705

Maguire, E. A., Frith, C. D., & Morris, R. G. M. (1999). The functional neuroanatomy of comprehension and memory: The importance of prior knowledge. Brain, 122, 1839–1850. https://doi.org/10.1093/brain/122.10.1839

Meltzoff, A. N. (1990). Foundations for developing a concept of self: The role of imitation in relating self to other and the value of social mirroring, social modeling, and self practice in infancy. In D. Cicchetti & M. Beeghly (Eds.), The self in transition: Infancy to childhood (pp. 139–164). University of Chicago Press.

Muro, M., & Jeffrey, P. (2008). A critical review of the theory and application of social learning in participatory natural resource management processes. Journal of environmental planning and management, 51(3), 325–344. https://doi.org/10.1080/09640560801977190

Nie, J., Zhang, Z., Wang, B., Li, H., Xu, J., Wu, S., Zhu, C., Yang, X., Liu, B., Wu, Y., Tan, S., Wen, Z., Zheng, J., Shu, S., & Ma, L. (2019). Different memory patterns of digits: a functional MRI study. Journal of Biomedical Science, 26(22). https://doi.org/10.1186/s12929-019-0516-y

Piaget, J. (1936). Origins of intelligence in the child. Routledge & Kegan Paul.

Piaget, J. (1970). Genetic epistemology. Columbia University Press.

Pintrich, P. R., Cross, D. R., Kozma, R. B., & McKeachie, W. J. (1986). Instructional psychology. Annual Review of Psychology, 37, 611–651. https://doi.org/10.1146/annurev.ps.37.020186.003143

Pouw, W.T.J.L., van Gog, T. & Paas, F. (2014). An Embedded and Embodied Cognition Review of Instructional Manipulatives. Educational Psychology Review, 26(1), 51–72. https://doi.org/10.1007/s10648-014-9255-5

Rizzolatti, G. (2005). The mirror neuron system and its function in humans. Anatomy and Embryology, 210, 419–421. DOI 10.1007/s00429-005-0039-z

Schunk, D. H. (2012). Learning theories: An educational perspective (6th ed.). Pearson.

Shuell, T. J. (1986). Cognitive conception of learning. Review of Educational Research, 56(4), 411–436. https://doi.org/10.3102/00346543056004411

Sinai, M., Kaplan, A., & Flum, H. (2012). Promoting identity exploration within the school curriculum: A design-based study in a junior high literature lesson in Israel. Contemporary Educational Psychology, 37(3), 195–205. https://doi.org/10.1016/j.cedpsych.2012.01.006

Skinner, B. F. (1976). About Behaviorism. Vintage Books.

Steier, R., Shapiro, B., Christidou, D., Pierroux, P., Davidsen, J., & Hall, R. (2019). Tools and Methods for ‘4E Analysis’: New lenses for analyzing interaction in CSCL.

Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312. https://doi.org/10.1016/0959-4752(94)90003-5

Sweller, J., van Merriënboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. https://doi.org/10.1023/A:1022193728205

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

Waterman, A. S. (1989). Curricula interventions for identity change: Substantive and ethical considerations. Journal of Adolescence, 12(4), 389–400. https://doi.org/10.1016/0140-1971(89)90062-6

Winne, P. H. (1985). Cognitive processing in the classroom. In T. Husen & T. N. Postlethwaite (Eds.), The International Encyclopedia of Education (Vol. 2, pp. 795–808). Pergamon.

Wirebring, L. K., Lithner, J., Jonsson, B., Liljekvist, Y., Norqvist, M., & Nyberg, L. (2015). Learning mathematics without a suggested solution method: Durable effects on performance and brain activity. Trends in Neuroscience and Education, 4(1), 6–14. https://doi.org/10.1016/j.tine.2015.03.002

Wittrock, 1986: Please replace Wittrock, 1986 to Brophy, J., & Good, T. L. (1986). Teacher behavior and student achievement. In M. C. Wittrock (Ed.), Handbook of research on teaching (3rd ed., pp. 328-375). New York: Macmillan.

Wood, R., & Bandura, A. (1989). Social cognitive theory of organizational management. Academy of Management Review, 14(3), 361–384. https://doi.org/10.2307/258173

Woollard, J. (2010). Psychology for the classroom: Behaviourism. Routledge.