PSY 402 Effects of Metacognitive Regulation on Memory Performance
PSY 402 Effects of Metacognitive Regulation on Memory Performance
Neuropsychology has made enormous progress over the past few decades, but researchers still do not have complete understanding of the functioning of human brain and its memory system. Memory might be described as the capacity to retain information over some period of time, and it underlines the ability to learn (Friedenberg & Silverman, 2006). Cognitive research insists that humans do not have a single type of memory, but rather functionally distinct memory systems interacting with each other (working memory and long-term memory) (Lum & Conti-Ramsden, 2013). Long-term memory has an unlimited capacity to store data, and it is divided on procedural and declarative memories which are the critical elements in the concept of learning. Examining the method of retrieving, developing, or expanding knowledge is considered to be a fundamentally metacognitive process. Therefore, the metacognitive knowledge encompasses awareness of strategies related to learning and problem-solving, along with familiarity of diverse thinking and learning types, including their strengths and weaknesses, both collectively and individually (Veenman, Hout-Wolters, & Afflerbach, 2006). This article explores the relationship of declarative and procedural memories with metacognition, the role of cognitive processes in these types of memory, and the impact of metacognitive monitoring and metacognitive control on problem solving followed by the summary.
Declarative and Procedural Memories
A memory system is understood as the ability to learn, store, and retrieve information by an individual (Lum & Conti-Ramsden, 2013). Literature emphasizes that human memory is not a single faculty, and the experimental and biological research conducted over the last several decades has differentiated memory systems called working memory and long-term memory that been further separated (Squire & Dele, 2015). In general, long-term memory can be divided on declarative memory and procedural memory, and they differ with respect to supporting brain structures as well as cognitive processes underlining learning and memory, but these systems interact and cooperate to support an individual’s learning and cognitive functioning (Lum & Conti-Ramsden, 2013).
Declarative memory enables the individual to rapidly and flexibly learn even from a single exposure and supports storage as well as retrieval of information. In other words, it is memory for facts and events that is demonstrated by speaking, and emerges with conscious recall (Friedenberg & Silverman, 2006). Procedural memory is the unconscious memory of skills informing how to accomplish certain tasks, especially how to use objects or movements of the body. Implicit memory encompasses effects of prior experiences on current behavior without deliberate retrieval, and perhaps without explicitly remembering these previous encounters (Schott et al., 2005). Graf and Masson (2011) stated that procedural memory appears before declarative memory, and it does not deteriorate significantly in its ability during the adult life span. Additionally, it may play a bigger functional role in individuals advancing in age (Graf & Masson, 2011). Implicit memory resides within a perceptual representation system and has a high degree of localization because the base perceptual abilities themselves have relatively well-defined cortical sites. Graf and Masson (2011) also argued that declarative memory is significantly less localized and many different brain structures are critically involved in its functioning, and furthermore, these structures, especially hippocampus, seem particularly sensitive to a verity of potential brain injuries and losing certain abilities of remembering information. Reber (2013) stated that implicit memory is based on the principle of plasticity within neural processing circuits and allows the adaptive reshaping of function to match experience as described by the implicit learning concept.
Metacognition can be divided into two distinct aspects: (a) metacognitive knowledge of cognition, and (b) metacognitive regulation of cognition (Wilkinson, Best, Minshew, & Strauss, 2010). Metacognitive knowledge about cognitive processes allows to realize what an individual knows in reference to cognition including declarative knowledge of factors influencing human cognition and performance. Procedural knowledge involves the awareness of how given skills work and how they should be executed while performing certain tasks. Vrugt and Oort (2008) added also conditional knowledge that relates to the awareness when strategies are needed to tackle a task.
Individuals effectively using their metacognitive skills can monitor as well as direct their learning process by examining deficiencies of the knowledge stored in the long-term memory, developing plans, setting goals, employing problem solving activities, monitoring educational progress to improve memory and expand knowledge. Metacognitive skills allow an individual to be aware of his or her own knowledge stored in the declarative and procedural memories as well as to understand, control, and manipulate his or her own cognitive process in the knowledge acquisition as well as detect and correct errors (Friedenberg & Silverman, 2006). Metacognition allows to be very intentional about adopting appropriate pedagogical and cognitive techniques that maximize the learning effect by effectively encoding the new information and consolidating it with the existing knowledge imbedded in the long-term memory. Individuals should be cognizant that even sleep plays an important role in facilitating cognitive processes. Holz et al. (2012) stated that newly encoded information is evolving in a critical time window after learning while it is still fragile and vulnerable to disruptive stimulus interference; however, sleep occurring at that time can facilitate the process of declarative memory consolidation into long-term representations in a hippocampal-neocortical network.
Memory, Cognitive Processes, and Implicit Learning
Information processing model that provides description of cognitive processes indicates that human memory is dynamically engaged in the construction of information, and the individual’s prior knowledge has a significant impact on the learning outcome (Gredler, 2009). Memory is a complex system that processes and organizes an individual’s knowledge by actively selecting the sensory data for processing, transforming it into a meaningful information, encoding, and storing it for later use (Gredler, 2009). From sensory input, information comes into one’s memory system, and it needs to be processed and encoded into a form that allows brain to store it. Generally, there are three different modalities of encoding information in the short-term memory and transferring it into the long-term memory: (a) visual, (b) acoustic, and (c) semantic (Friedenberg & Silverman, 2006). Working memory has a very limited storage ability and can only deal with 5 to 9 items at a time, stores information briefly, and the mental representation will disappear without rehearsal or reinforcement (Goldstein, 2011). It involves the process of dynamic maintenance of this restricted capacity; therefore, if the volume of working memory is surpassed, or if the information is not effectively managed by rehearsal, further performance must depend on long-term memory (Squire & Dele, 2015). Long-term memory involves large quantities of information that is stored for long periods of time, and it would be difficult to deny that each normally functioning individual has at the disposal a rich, but not flawless set of long-term memories. According to Goldstein (2011), data is transferred from working memory into long-term memory, and the systems interact or depend on each other.
These cognitive processes are well illustrated by the connectionist network system that resembles the neural networks in the brain in which the memory system is composed of networks interacting with each other, and learning involves the modification of the connection weights among given units in order to develop desirable output patterns (Gredler, 2009). According to Wagner (2016), distributed neocortical networks are responsible for storing memories. These neocortical networks can store episodic memories of particular events along with their contextual details, or semantic memories that are composed of factual knowledge about the surrounding reality, concepts, or rules. They are organized as declarative and procedural knowledge.
Individuals expand their knowledge by explicit learning that is described as conscious, intentional, and declarative process as well as by implicit learning that is unconscious incidental, and procedural (Yang & Li, 2012). According to Deroost at al. (2012), implicit learning is a “default” leaning system providing effortless and quick associative knowledge acquisition from the environmental stimuli without conscious intention, monitoring, or awareness of the learning content. Literature describes the role of implicit learning in the language acquisition where individuals learn unconsciously that certain succession of speech sound takes place more often than others (Lan, Chen, Li, & Grant, 2015). Additionally, implicit learning results in effortless and unintentional learning of prioritizing cognitive events (Deroost et al., 2012).
It can be argued that there is a need for cognitive control of these processes by monitoring and regulating the ongoing actions to flexibly adopt one’s behavior to environmental demands. Many times, cognitive control functions are perceived as the opposite to the automatic and implicit processes that occur fast and unforced. Deroost et al. (2012) hypothesized that implicit processes might actually play a role in achieving cognitive control in the absence of conscious monitoring. To exam this hypothesis, three experimental studies were conducted by testing the activation of “task-relevant information, which in the context of conflict, and support cognitive control” (Deroost et al., 2012, p. 1244). The results suggested that implicit learning is a contributing factor to cognitive control functions.
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PSY 402 Effects of Metacognitive Regulation on Memory Performance
Metacognition and Problem Solving
Metacognition is described as the awareness of the individual’s cognitive activities, learning styles, problem-solving strategies, that can regulate his or her learning processes (Veenman at al., 2006). Jayapraba (2013) stated that all processes involved in examining the techniques and methods individuals use to access, advance or increase information are considered as fundamentally metacognitive. According to Gredler (2009), problem solving is the individual’s engagement with a new and obscure undertaking when the appropriate solution methods are not known. This situation requires the identification of key elements to create a mental map, develop a plan to overcome obstacles, and to execute it. Therefore, metacognition seems to be a logical channel for the problem-solving approaches by individuals performing challenging tasks. In a problem-solving task, metacognition allows to evaluate whether a particular strategy is effective or not and to consider revisions of the current strategy or employ a completely new strategy to solve the problem effectively.
The implication is that school program designers, based on the formal cognitive theories and research, can intentionally insert segments that develop creative thinking and problem solving skills. A deliberate and well planned approach to fostering metacognitive monitoring and metacognitive control on problem solving can result in the development of creativity by advancing self-monitoring, evaluation, and the extraordinary cognitive recombination of encoded associations in the long-term memory (Gredler, 2009). Individuals with well-developed metacognitive skills are able to solve problems by comparing ideas that appear not to be related, and find solutions by making new associations and arrangements based on a given stimulus, and these skills can be taught (Strand, Naden, & Slettebø, 2009).
Summary
Human brain has an amazing capability for processing data, acting upon it, storing information, and reflecting upon this complicated process of acquiring new knowledge or connect an arising challenge with the existing body of knowledge to solve the problem. Individuals develop their knowledge by explicit (conscious) and implicit (unconscious, incidental, and procedural) processes. Implicit learning is a contributing factor to cognitive control functions. Metacognitive skills allow individuals to be aware of their own knowledge stored in the declarative and procedural memories as well as to understand, control, and manipulate their cognitive processes. Additionally, metacognition allows to evaluate effectiveness of particular strategies and consider to go forward, revise, or employ a completely new tactic to solve a problem effectively.
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