This is a North Central University course (EDR 8200-8): Develop a Final Literature Review . It is written in APA format, has been graded by an instructor (A), and includes references. Most higher-education assignments are submitted to turnitin, so remember to paraphrase. Let us begin.

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Dr. D’s Cover_Sheet (ensure you use the NCU filename in the header above for your header and
to save your paper).
Name: Orlanda Haynes
Date: 11/19/2017
Please Follow These Procedures: Use this assignment cover sheet as the first page of your paper.
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indicated below. Fill out all highlighted areas.
EDR 8200
Donna Rice, PhD.
Scholarly Literature Review Develop a Final Literature Review
Faculty Use Only
Excellent work on this last assignment, Orlanda! You have a very good start on a draft of your lit
review. I am so impressed! I have enjoyed being your mentor and I wish you very well in your
continued studies. I hope to “see” you again!
Dr. Donna Rice 24.00 (100%)
11/20/17

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Develop a Literature Review Draft
Educational neuroscience is an emerging field with foundations in education research,
neuroscience, cognitive science, developmental psychology, and biology among others (Bruer,
2016; Fischer, Goswami, & Geake, 2010; Rees, Booth, & Jones, 2016; Tommerdahl, 2010;
Zadina, 2015). In fact, most findings support future studies and further development of
educational neuroscience (Daniel, Fischer, Williams, & LaGattuta, 2013; Howard-Jones, 2014;
Rees, Booth, & Jones, 2016; Stubenrauch, Krinzinger, & Konrad, 2014; Tommerdahl, 2010;
Zadina, 2015). The purpose of this literature review is to examine current literature about the
development of adult metacognition from the perspective of cognitive science and neuroscience.
Both fields are not only primary means to understanding how the brain (TB) facilitate
learning but, also, they provide information about how education communities, among others,
can transfer research data from theory to practice (Daniel, Fischer, Williams, & LaGattuta, 2013;
Fischer, Goswami, & Geake, 2010; Zadina, 2015). Although educational neuroscience plays a
major role in the education of how TB support learning, its position is either non-apparent or
distant among issues and topics related to education literature (Fischer, Goswami, & Geake,
2010; West, & Bell-Angus, 2016; Klingberg, 2010; Zadina, 2015). What is more, substantial
results indicate that education neuroscience literature is more about obstacles related to
neuroscience integration rather than about its core benefits (Bowers, 2016; Daniel, Fischer,
Williams, & LaGattuta, 2013; Fischer, Goswami, & Geake, 2010; Howard-Jones, 2014; Rees,
Booth, & Jones, 2016; Schilbach, Wilms, Eickhoff, Romanzetti, Tepest, Bente, ... 2010;
Stubenrauch, Krinzinger, & Konrad, 2014;Tommerdahl, 2010; Zadina, 2015).
These benefits include supporting education practices by improving learning outcomes,
by informing education literature, and by bridging gaps among related disciplines (Cai, Chan,

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Yan, & Peng, 2014; Rees, Booth, & Jones, 2016; Stubenrauch, Krinzinger, & Konrad, 2014;
Tommerdahl, 2010; Zadina, 2015). Likewise, most cognitive science literature discusses
metacognition in terms of aging and metamemory, metacognition knowledge and skillfulness,
metacognition monitoring including problem-solving, and outcomes, and metacognition
strategies and their effectiveness but not how metacognition develops in adults (Dunlosky, &
Jacoby, 2011; Fleming, & Dolan, 2012; Hargis, Yue, Kerr, Ikeda, Murayama, & Castel, 2017;
Piefke, & Glienke, 2017; Saricam, 2015; Semerci, & Elaldi, 2014; Van Der Stel, & Veenman,
2010; Wahlheim, Dunlosky, & Jacoby, 2011 ). More specifically, if there are innate cognitive
processes that facilitate the development of adults’ metacognition skills. The proposed research
topic The Development of Adult Metacognition: Educational Neuroscience would, therefore,
explore the development of adult metacognition from the context of cognitive science and
neuroscience.
The aim is to explore the extent to which the brain’s natural cognitive processes
(TBNCP) such as thinking, remembering, and learning (TRL) correlate with the development of
adults’ metacognition skills. The foundation employs cognitive science and neuroscience
research. Organization of the literature review depicts metacognition and neuroscience themes.
The hypothesis is that TBNCP such as TRL allow adults’ metacognition skills to increase (with
age) naturally. Findings could inform educational practices, bridge gaps between education and
neuroscience, and allow for neuroscience research and education practices to shape the literature
jointly as well as provide frameworks for database sharing policies.
Adult Metacognition and Educational Neuroscience
The field of educational neuroscience has a fundamental link to the fields of cognitive

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science: The brain’s ability to learn (Bruer, 2016; Cai, Chan, Yan, & Peng, 2014; Fleming, &
Dolan, 2012; Howard-Jones, 2014; Kolb, & Gibb, 2011; Rees, Booth, & Jones, 2016; Zadina,
2015). Over lifespans, the brain (TB) reshapes and changes in response to internal and external
factors, which allow for adaptation to different environments (Kolb, & Gibb, 2011; Rees, Booth,
& Jones, 2016). Thinking, remembering, and learning are the brain’s natural learning and
development toolbox.
When a person, for example, accepts a task or project that requires critical thinking,
reasoning skills, and problem-solving abilities, the brain’s nerve cells use chemical synapses
(electrical for faster response or chemical for slower response) to send neurotransmitters, also
known as chemical messages, to other neurons. Depending on the situation (perceived
emergency or otherwise), neurons take shape as electrical or chemical neural impulses. The aim
is to influence or code thoughts, actions, and experiences (Cai, Chan, Yan, & Peng, 2014;
Comeau, McDonald., & Kolb, 2010; Howard-Jones, 2014; Rees, Booth, & Jones, 2016).
In doing so, more information about the task (prior memories and knowledge for
example) becomes available. The entire process is an interplay of cognitive factors combined
with a complex neural network of dendrites (NNOD) and synapses. Knowledge and skills
increase to more advanced levels because NNOD grow in accordance with learners’ activities.
In that, the brain’s construction of NNOD is task specific. They are symbolic of tree twigs; that
is, they grow from roots (neurogenesis).
Stimulation of such plays a key role in how efficient their constructions are. In other
words, the process uses natural chemical or electrical messages to stimulate NNOD to make
connections with other neurons (Kolb, & Gibb, 2011; Neuroplasticity, 2014; Rees, Booth, &
Jones, 2016). Engaging in interactive tasks, for instance, usually triggers these thinking,

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remembering, and learning processes. In healthy people, this action has the potential to occur
naturally as one ages. Learners interested in pursuing new interests, for instance, could begin by
connecting with prior knowledge and skills or by beginning anew (Fleming, & Dolan, 2012;
Fuchs, & Flügge, 2014; Howard-Jones, 2014; Rees, Booth, & Jones, 2016; Neuroplasticity,
2014). However, the ability to use prior learning requires cognition or cognitive abilities (CA)
(Baird, Mrazek, Phillips, & Schooler, 2014; Fleming, & Dolan, 2012).
CA allow people, for example, to ask questions like how to improve academic
performance. Depending on the results, he or she could use the information to implement
change and to monitor the outcome. This aspect of learning is based on cognitive science and
supported by neuroscience (Bailey, Dunlosky, & Hertzog, 2010; Howard-Jones, 2014; Rees,
Booth, & Jones, 2016; Valk, Bernhardt, Böckler, Kanske, & Singer, 2016). Historically,
cognitive psychologists defined metacognition as a form of cognitive control that involves
learning from the context of self-regulation and monitoring (Flavell, 1979).
John Flavell, an American developmental Psychologist, coined the term “metacognition.”
It refers to “cognition about cognition” or “thinking about thinking” (Flavell, 1979, p. 906). He
informed that awareness and knowledge about metacognition facilitate development of
metacognition skills (MK), strategies, and regulation. The process of “thinking” allow one, for
example, to ask questions like how to improve academic performance, what factors are involved,
and how to implement change and monitor outcomes (Flavell, 1979).
Other finding added to the literature by informing that MK were more general than
domain-specific, but distinctively different from general intelligence, and, therefore, could
compensate for lack of prior knowledge in areas such as problem solving (Schraw, 1998). Some
researchers such as Veenman, Wilhelm, and Beishuizen (2004) explored correlations among

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metacognitive skills (MK), intelligence, and generality vs. domain specific (as far as aging and
MK development). Although their sample size was small and non-random, participants
represented four age groups including college students. Results suggested MK (across the
lifespan) are general, non-domain specific, facilitate learning, and are not entirely dependent on
intelligent. Educational neuroscience is a fundamental means to understanding how the brain
(TB) facilitate learning.
In fact, TB is the only organ in the human body that can shape and reshape itself through
interacting with tangible and intangible factors (Cai, Chan, Yan, & Peng, 2014; Fuchs, & Flügge,
2014; Rees, Booth, & Jones, 2016; Neuroplasticity, 2014). Its natural cognitive processes
include the ability to think, remember, and learn. Neuroscience researchers gather data about
how these factors interact during stages of learning and developing. Findings revealed that the
human brain performs acts of neuroplasticity, which enable the body to respond quickly to
external and internal factors (Fuchs, & Flügge, 2014; Neuroplasticity, 2014; Rees, Booth, &
Jones, 2016).
In 1890, William James was the first to coin the terms “neuroplasticity” (Neuroplasticity,
2014). Other common terms include ‘brain plasticity” and “neural plasticity.” Plasticity refers
to the brain’s ability to make changes initiated by chemical and electrical impulses of the brain’s
nervous system. James noted that nervous tissues, and interconnected organic matter showed
localized plasticity. This finding, unlike common beliefs which, inferenced otherwise, suggested
that the brain’s capacity and functionality were not fix but rather, in some respects, capable of
regrowth, repair, and expansion (Fuchs, & Flügge, 2014; Comeau, McDonald., & Kolb, 2010;
Joghataie, & Shafiei, 2016; Neuroplasticity, 2014). During the 1900s, neuroplasticity research
greatly expanded (Comeau, McDonald., & Kolb, 2010; Seitz, 2011; Zadina, 2015).

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Researchers such as Comeau, McDonald and Kolb (2010) supported prior findings that
the brain’s neural networks can stimulate new dendritic growth. They noted that rats—after
placed in complex housing structures for 14 days—freed themselves. Results suggested the rats’
experience (learning to navigate the housing maze) triggered chemical messages, which in term
stimulated the neural network of dendrites and synapses causing new dendrite growth.
Metacognition Knowledge and Skillfulness
Research showed that metacognition has two primary components: Knowledge about
cognition and monitoring of cognition. What one knows about his/her own cognition, or
cognition awareness in general, refers to metacognition knowledge. An important component of
this concept is “awareness.” It encompasses declarative, procedural, and conditional knowledge
(Baird, Mrazek, Phillips, & Schooler, 2014; Van Der Stel, & Veenman, 2010). knowledge about
oneself including what factors negatively or positively impact performance refers to declarative.
Moreover, metamemory (memorial factors) is highly researched in education science,
cognitive science, and neuroscience (Klingberg, 2010; Piefke, & Glienke, 2017; Smith, Hunt, &
Murray, 2017; Wahlheim, Dunlosky, & Jacoby, 2011). Findings indicate that, unlike children,
most adults have adequate awareness about cognitive factors that could impede or enhance
memory. Likewise, adults with enough metacognition awareness are more prepared to address
metamemory issues than their counterparts. On the other hand, knowing what skills and
resources a task requires refers to procedural knowledge (Van Der Stel, & Veenman, 2010).
From the context of instructional practice, some researchers found that increasing one’s
procedural knowledge improves problem-solving skills (Bailey, Dunlosky, & Hertzog, 2010;
Fleming, & Dolan, 2012; Hargis, Yue, Kerr, Ikeda, Murayama, & Castel, 2017; Hertzog, &
Dunlosky, 2011).

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If an individual, for example, is tasked with deciding when an activity should commence,
why it should be completed within a specific timeframe, and he/she understands and implement
accordingly, then the entire scenario could be declared conditional knowledge. It refers to one
knowing not only when to apply cognitive actions but also why (Van Der Stel, & Veenman,
2010). Other findings showed that metacognition skills (MK) are not domain-specific but
multidimensional (Baird, Mrazek, Phillips, & Schooler, 2014; Van Der Stel, & Veenman, 2010).
These findings are significant because, in some cases, MK skills could compensate for lack
of intelligence. More importantly, metacognition literature suggests the development of
metacognition skills requires the interplay of cognitive factors and the brain’s natural ability to
learn. In addition, some findings such as Hargis, Yue, Kerr, Ikeda, Murayama, and Castel (2017)
indicated that metacognition skills have the potential to increases as one ages.
Metacognition Strategies
Although substantial literature about metacognition strategies exists, most studies are not
current (e.g., 5 years or less). However, some current findings are included. For example, Van
Der Stel and Veenman (2010) noted that monitoring outcomes control desired behaviors and
improve performances, and that implementing strategies require metacognition procedural
knowledge. Veenman also emphasized that some students confuse metacognition skills with
strategies. However, the latter requires concerted efforts including continuous practices and
reviews. Whereas metacognition skills, after the learning curb, become almost automatic.
Moreover, other research indicated that metacognition procedural knowledge as far as
monitoring and implementing strategies could improve learning of metacognition skills more
effectively than traditional learning approaches (Van Der Stel, & Veenman, 2010).

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Conclusion
Educational neuroscience is an emerging field with foundations in, among others,
education research, neuroscience, cognitive science, developmental psychology, and biology.
The fundamental link is the brain ability to learn. (Booth, & Jones, 2016; Bruer, 2016; Daniel,
Fischer, Williams, & LaGattuta, 2013; Fischer, Goswami, & Geake, 2010; Rees, Tommerdahl,
2010; Zadina, 2015). Over lifespans, it reshapes and changes in response to internal and external
factors, which allow for adaptation to different environments (Fuchs, & Flügge, 2014; Howard-
Jones, 2014; Kolb, & Gibb, 2011). Thinking, remembering, and learning are the brain’s natural
learning and development toolbox.
Findings suggest neuroscience and cognitive science are primary means to understanding
how it facilitates learning as well as how education communities, among others, can transfer
such knowledge from theories to practices (Cai, Chan, & Peng, 2014; Comeau, McDonald, &
Kolb, 2010; Daniel, Fischer, Williams, & LaGattuta, 2013; Dunlosky, & Jacoby, 2011; Fischer,
Goswami, & Geake, 2010; Fuchs, & Flügge, 2014; Howard-Jones, 2014; Joghataie, & Shafiei
Dizaji, 2016; Zadina, 2015). This literature review (draft) is a framework for my proposed
research The Development of Adult Metacognition: Educational Neuroscience. It includes five
themes of which “Adult Metacognition and Educational Neuroscience” discusses principles and
concepts of adult metacognition from the context of educational neuroscience.” Metacognition
Aging and Metamemory provide findings and results regarding ageing factors as they relate to
metamemory, and “Metacognition Monitoring” addresses problem-solving and outcomes.
The theoretical framework employs research from both cognitive science and
neuroscience. Because the brain facilitates learning naturally through thinking, remembering,
and neuroplasticity (Fuchs, & Flügge, 2014; Joghataie, & Shafiei, 2016; Neuroplasticity, 2014),

10. HaynesOEDR8200-8 10
the hypothesis is that these cognitive and neurological processes, combined with aging, allow
adults’ metacognition skills to increase naturally. However, most cognitive science literature
discusses metacognition in terms of aging and metamemory, metacognition knowledge and
skillfulness, metacognition monitoring including problem-solving and outcomes, and
metacognition strategies and their effectiveness, but not how metacognition develops in adults
(Dunlosky, & Jacoby, 2011; Fleming, & Dolan, 2012; Hargis, Yue, Kerr, Ikeda, Murayama, &
Castel, 2017; Piefke, & Glienke, 2017; Saricam, 2015; Semerci, & Elaldi, 2014; Van Der Stel, &
Veenman, 2010; Wahlheim, Dunlosky, & Jacoby, 2011 ).
Likewise, research suggests (current) education neuroscience literature is more about
obstacles related to neuroscience integration rather than about core benefits (Bowers, 2016;
Daniel, Fischer, Williams, & LaGattuta, 2013; Fischer, Goswami, & Geake, 2010; Howard-
Jones, 2014; Rees, Booth, & Jones, 2016; Schilbach, Wilms, Eickhoff, Romanzetti, Tepest,
Bente, ... 2010; Stubenrauch, Krinzinger, & Konrad, 2014;Tommerdahl, 2010; Zadina, 2015).
Some of which include supporting education practices by improving learning outcomes, by
informing education literature, and by bridging gaps among related disciplines (Cai, Chan, Yan,
& Peng, 2014; Rees, Booth, & Jones, 2016; Stubenrauch, Krinzinger, & Konrad, 2014;
Tommerdahl, 2010; Zadina, 2015). Therefore, the purpose of the proposed research is to
discover to what extent the brain’s innate cognitive processes facilitate development of adult
metacognition skills. Findings would inform educational practices, bridge gaps among education
and neuroscience disciplines, and provide foundations for database sharing policies (Daniel,
Fischer, Williams, & LaGattuta, 2013; Fischer, Goswami, & Geake, 2010; Rees, Booth, &
Jones, 2016).

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Baird, B., Mrazek, M. D., Phillips, D. T., & Schooler, J. W. (2014). Domain-specific
enhancement

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