More Learning Theory Info: (if that was not enough)
Metacognition
The deliberate conscious control of one’s cognitive activity (Brown, 1980)
Any knowledge or cognitive activity that takes as its object, or regulates, any aspect of any cognitve enterprise... it is called metacognition because its core meaning is "cognition about cognition". Metacognition means to understand what you're thinking about. The teacher might ask you to describe what is going on in your head while you are thinking.

Metacognition is important to know because you need to understand what you're thinking about so you can explain how you got an answer.
Yussen (1985) described metacognition as "thinking about thinking"
Metacognition is a term that spans many sub-areas in psychology and means
different things to different people. A dominant view has been that
metacognition involves the monitoring of performance in order to control
cognition; however, it seems reasonable that much of this control runs
implicitly (i.e., without awareness). Newer still is the field of implicit
memory, and it has different connotations to different sub-groups as well.

I.Metamemory.(or metacognition) involves one's knowledge about and control over their own cognitive processing system. Two fundamental aspects of metacognition are typically identified.

A.KNOWLEDGE relevant to the way in which individuals process information. Three types: 1.PERSON KNOWLEDGE or knowledge about the way in which YOU AND OTHER PEOPLE learn and/or process information, such as: a."I learn best when I study in the morning."
b."People need feedback on the adequacy of their current understanding if they are to learn."
2.TASK KNOWLEDGE or knowledge about various types of learning tasks,
a. It is easier to recognize whether or not something is correct than to recall the same information.
3.STRATEGY KNOWLEDGE or knowledge about the effectiveness of various strategies.
B.EXECUTIVE CONTROL of one's own learning process. Four types of executive
control:
1.PREDICTING such things as how difficult a particular learning task -- e.g., a chapter in the textbook -- the goal toward which one is working, etc.
2.PLANNING what you will do during the learning task, selecting appropriate
strategies, etc.
3.MONITORING the learning process, including:
a.What you currently know about the material being learned,
b.What you don't know but need to know in order to achieve your learning goal,
c.The extent to which you are understanding the material you are studying.
4.EVALUATING the results of the various activities listed above.
II.Criticisms of Metacognitive Theory:
A.Metacognition is a "fuzzy" concept (Brown, 1987) - there is no single agreed upon definition, but most agree that it involves knowledge and control of cognitive processes.
B.It is often difficult to distinguish what is "cognitive" from what is "metacognitive"
EXAMPLE, "asking yourself questions about the chapter might function either to improve your knowledge (a cognitive function) or to monitor it (a metacognitive function)." (Flavell, 1976)
C.Assessment issues (Van Zile-Tamsen, 1996):
1.Behavioral protocols are seldom useful as metacognitive activity occurs in the mind and may not involve overt, observable behavior. Overt behavior represents the product, not the processes involved in generating the product.
2.Self-report inventories have been used to assess metacognitive activity (e.g., Pintrich, Smith, Garcia, & McKeachie, 1991). While such inventories are easy to administer and analyze; they are limited in a number of ways:
a.Students may endorse items they interpret to be desirable, regardless of whether they actually engage in the cognitive activity;
b.Different students may interpret the items in different ways, making it difficult to compare responses;
c.Students may engage in metacognitive activities that are not assessed in the self-reports, thus, our understanding of metacognitive processes is limited to activities represented on the inventory.
3.Interviews and verbal reports (e.g., think-aloud protocols) are more popular methods of assessing metacognitive activity. While such assessment tools overcome the obstacles presented by the self-reports, there is still the concern that participants may not be aware of their mental processing, and/or may not be able to articulate these processes to the researcher. In addition, verbalization may interfere with the processing.
4.At the present time there is no ideal means for assessing metacognition. Many researchers use a combination of the methods described above as a means of triangulation and overcoming the weaknesses of a given methodology.
III.Approaches to Metacognitive Strategy Instruction (Livingston, 1996):
A."Strategies only"-- students are taught about strategies, but not given
conditional information about when/where/why strategy use is appropriate.
B."Direct instruction" -- students receive direct instruction on how to
implement strategies as well as learning conditional knowledge regarding
appropriate strategy use; however, there are limited practice experiences.
C."Self-regulated" approach -- students practice applying the strategies in a variety of settings in addition to receiving direct instruction.

Based on an extensive review of the metacognitive strategy instruction
literature, the self-regulated approach appears to be the most effective, and the most likely to result in strategy maintenance and transfer. The
self-regulation approach develops both the knowledge and control components that comprise metacognition.

Perhaps the clearest statement on the meaning of metacognition has been provided by John Flavell (1976, 1987). Flavell described metacognition as "ones knowledge concerning one's own cognitive processes and products and anything related to them." He extended this by saying that as well as having a knowledge component, metacognition also refers to "the active monitoring and consequent regulation and orchestration of these processes in relation to the cognitive objects or data on which they bear" (Flavell, 1976, p. 232). Flavell (1987) suggests that metacognition is most likely to develop when learners develop a sense of self as cognitive agents and realise that they are the centre and cause of cognitive activity.

Metacognitive development may be assisted by a number of experiences, one of which may be practice. In other words, when children are immersed in situations where metacognitive strategies are used or encouraged they will get better at metacognition. Flavell (1987) says that involving children in problem solving, in choosing which direction to take, how and where information can be stored and retrieved, where and when decisions have to be made concerning which information to use and how to use it, testing and hypothesising would be the type of experiences that would promote the development of metacognition.

Metacognition is thinking about thinking, knowing "what we know" and "what we don't know." Just as an executive's job is management of an organization, a thinker's job is management of thinking. The basic metacognitive strategies are:
1.Connecting new information to former knowledge.
2.Selecting thinking strategies deliberately.
3.Planning, monitoring, and evaluating thinking processes. (Dirkes, 1985)

Studies show that increases in learning have followed direct instruction in
metacognitive strategies. These results suggest that direct teaching of these thinking strategies may be useful, and that independent use develops gradually (Scruggs, 1985).

Learning how to learn, developing a repertoire of thinking processes which can be applied to solve problems, is a major goal of education. The school library media center, as the hub of the school, is an ideal place to integrate these types of skills into subject areas or students' own areas of interest. When life presents situations that cannot be solved by learned responses, metacognitive behavior is brought into play. Metacognitive skills are needed when habitual responses are not successful. Guidance in recognizing, and practice in applying,
metacognitive strategies, will help students successfully solve problems
throughout their lives. To make an individual that is metacognitively aware, is to ensure that the individual has learned how to learn. The individual behaves in reflective, planful, and where necessary, self-corrective ways. An important feature of executive routines is that they can be taught. (Garner, 1988) As the research literature on metacognition grows, there is more support for the notion that metacognition is important in students' lives. But how do teachers facilitate students' acquisition of metacognitive strategies?

It is important to teach the metacognitive strategies in conjunction with the content that the strategies are to be applied to. This allows students to have concrete experiences with metacognition, and practice the skill. It is then hoped that this skill will be transferred to other areas. However, the skill needs to be mastered in the context of one area first.

Teachers must often teach students how to take responsibility for their own
learning first. Many students believe that it is the teacher's responsibility to make them learn -- the result of more of an adversarial schooling environment than a collegial one. To facilitate this shift to students taking on the responsibility for their own learning, Marzano et al.(1986) suggests these four steps:
•Provide explicit instruction in what the task is, what the objectives are, and how to assess progress or completion.
•Provide opportunities for the class to work cooperatively, in order to mentor each others' learning.
•Provide explicit instruction on how strategies may be transferred, provide
practice in this.
•Help students link newly acquired knowledge to previously learned knowledge.

Other researchers have emphasized the support provided by the teacher.
•Modeling may be the teacher thinking out loud while she solves a problem and checks it.
•Guidance may be as simple as:
•suggesting various strategies for attacking a task
•reminding students of rules previously learned (I before E except after C,
e.g.), •suggesting milestones (you should have x done by 1:00)
•purpose for planning ahead
•how to assess when you have completed the task (your chemicals change to green and fizz).
•Facilitating discussion after the task to allow students to learn:
•the efficacy of various strategies,
•the problems they ran into,
•how they solved the problems,
•and how to avoid those problems in the future.
•Using metacognitive prompts, such as:
•What is the goal of this exercise?
•Have I encountered anything similar?
•What is relevant and irrelevant?
•What strategies will be useful?

Teachers can MODEL metacognitive behavior, using techniques such as thinking out loud during problem solving, explaining the process of deciding how to attack a problem or issue, doing some explicit self-monitoring for comprehension, checking the final answer, etc

Self-efficacy
Self-Efficacy is personal belief that one has the capabilities to
produce a wanted behavior. Self efficacy is the belief in one’s capabilities to organize and execute the sources of action required to manage prospective situations - Bandura, 1986. It influences the choices we make, the effort we put forth, how long we persist when we confront obstacles and how we feel.

Belief concerning one’s own capabilities to organize and implement actions
necessary to attain designated performance levels. (Bandura, 1989) - BELIEFABOUT WHAT ONE IS CAPABLE OF DOING. however, beckons of "you can do it" may initially raise self-eff, but ulitmately lower it, if subsequent performance if poor. (Jabbar as a jockey)

(Zimmerman, 1991) - students with high self-efficacy, work harder, persist
longer when difficulties are present and achieve at higher levels. Successes raise and failures lower self-efficacy. Although low self-eff is detrimental, effective self-reg does not require that it be exceptionally high. Salomon (1984) found a slightly lower sense of self-eff led to greater mental effort and better learning than did extremene confidence (Derek vs. Rusty)
Zim model:  Self-Evaluation - Strategic Outcome Monitoring Goal-setting - Implementation

Effective self-reg depends on feeling self-eff for using skills to achieve.
B. describe its impact on student academic activities.
In recent years, self-efficacy has gained popularity in psychological research. Originally coined by Bandura as part of his social cognitive theory (Bandura,1986), self-efficacy has spread as a motivational construct to a large number of other fields, such as developmental psychology (Flammer, 1995), family processes (Schneewind, 1995), and human resource managment (Gist, 1987). This increasing popularity may be attributable to several features of self efficacy that make it
an attractive motivational construct. First, research has suggested that
self-efficacy in some instances can predict future performance better than past
performance (Bandura and Adams, 1977; Bandura, Adames and Beyer, 1977; Bandura,
Adams, Hardy, and Howells, 1980). Second, an individual's self-efficacy is
directly changeable (Bandura, 1986, Eden and Aviram, 1993, Dvir, Eden, and
Banjo, 1995). Finally, self-efficacy judgments arise from assessing a
combination of factors, such as previous experience, outside opinion, and
personal skills (Bandura, 1986).

The self-efficacy literature generally suggests a positive relationship between self-efficacy and task performance. However, much variability across findings exists in the strength of this relationship.

Self-efficacy and task performance It is thus reasonable to hypothesize that overall, a positive relationship will be found between self-efficacy and task performance (Hypothesis 1).

Moderators of Self-Efficacy
Although much of the literature has pointed to the existence of a relationship between self-efficacy and performance, contradictory findings exist. Podsakoff and Farh (1989) found no relationship between self-efficacy and performance in their research of performance feedback and self-efficacy. It has been argued, however, that the lack of findings was due to inconsistent measurement; self-efficacy was measured on an absolute scale, whereas performance was measured and fed back to participants on a relative scale (Quiñones & Mudgett, 1995). This presents a potential source of variance in the magnitude of the relationship found in the literature, and highlights the importance of accurate measurement and appropriate methodology.

Task complexity. In reviewing the self-efficacy literature, it appeared that the type of task performed varied almost as widely as the variables examined. There is evidence that the effects of different factors on performance vary depending in the task being studied (Hill, 1982). One dimension along which a task can vary is complexity (Campbell, 1988).

Research suggests that repeated successes at a task raise self-efficacy
expectations (Gist, 1991), while repeated failures lower them (Hackett, 1990); this is consistent with Bandura's theory that enactive attainment is an influential source of self-efficacy (Bandura, 1986). By definition, the more complex a task, the lower the probability of an individual succeeding at the task. Therefore, to the extent that complexity affects the probability of enactive attainment, it will have an effect on self-efficacy.

Bandura (1990) reported task complexity as a moderator of the relationship
between goal specificity and organizational performance. Their findings also suggested that goal setting mediated the relationship between self-efficacy and performance. Thus, to the extent that self-efficacy and performance are mediated by goal specificity, task complexity acts as a moderator between self-efficacy and performance. It is thus hypothesized that task complexity will moderate the self-efficacy performance relationship, so that the more complex the task, the weaker the relationship will be between self-efficacy and performance
(Hypothesis 2).

Measurement of self-efficacy. There are various ways of obtaining self-efficacy ratings, and the method used may have an impact on the results. According to Bandura (1986, 1995), self- efficacy has three dimensions: magnitude, strength, and generality. Magnitude refers to the degree of task difficulty an individual believes he or she can handle. Strength refers to the confidence of the magnitude judgment. Generality refers to the variety of situations to which the self-efficacy judgment can apply. Self-efficacy is then measured by obtaining ratings of strength and magnitude, and aggregating them.

Although Bandura was specific about the way self-efficacy should be measured, not all researchers take this approach. Lee & Bobko (1994) compared the validities of five different methods of computing self-efficacy measures. The
first measure, self-efficacy magnitude, is simply the sum of positive responses. Another method is self-efficacy strength, which is calculated by adding the ratings across all performance levels. The third method uses a combination of the first two; z scores the self-efficacy strength items are only added across those performance levels to which participants answered "yes." The fourth method is the same as the third, except that raw scores instead of z scores are used. Finally, one can measure self-efficacy by simply asking participants to rate their confidence level on a given task.

Lee and Bobko (1994) found that the single item measure had the lowest
convergent validity with the other measures and showed the lowest correlation with self-efficacy antecedents and consequents. They also found that the composite methods showed higher validities than either the magnitude or strength methods alone. This suggests that the way in which self-efficacy is measured can have a significant impact on the results of a study, and be a potential source of error. It is thus hypothesized that the type of self-efficacy measure used will moderate the relationship between self-efficacy and performance. The relationship between self-efficacy and task performance will be strongest when measured with a strength/magnitude combination than with other measures (Hypothesis 3).

Self-regulation:
One of the greatest difficulties facing designers of
constructivist learning environments is the question of evaluating the learning that takes place. Under the constructivist paradigm, the learner determines his or her own learning goals. Given that the designers may not know the goals of the learner, how can they evaluate whether the goals have been met? The simplest answer seems to be to ask the learner. How does the learner know whether they have met their own goals? If the learner is self-regulating, that is, if they are constantly, and consciously, monitoring their comprehension and correcting comprehension failures, they will know if they have met their goals. How then can the designer know whether the learner is self-regulating? This aspect typically requires additional measures. Because it is a complex
cognitive event, which involves numerous activities for the learner, researchers have a difficult time measuring a self-regulation learner (Howard-Rose & Winne, 1993). Three scales which have attempted to quantify self-regulated learning (SRL) are the SRL Rating scale (Corno, & Collins 1983); The Learning and Study Strategies Inventory (LASSI) (Westerman, 1995); and The Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich & Garcia, 1993). The results show that the revised MSLQ metacognitive self-regulation scale seems to be a reliable and valid measure of self-regulated learning when given in a web based learning
environment. Self-regulated learning is a dualistic construct with properties of an aptitude (Snow & Lohman, 1984) and an event (Winne, 1997; Winne & Hadwin, 1997). Self-regulated learners are students whose academic learning abilities and self-discipline make learning easier so motivation is maintained. Albert Bandura (1977) studied observational learning (recall the modeling in the Bobo doll study) and self-regulation. Bandura defined self-regulation as the ability
to control our own behavior and it is the workhorse of human personality.
Bandura suggests three steps: (1) Self-observation, we look at ourselves, our behavior, and keep tabs on it; (2) Judgment, we compare what we see with a standard; (3) Self-response, if we did well in comparison with our standard, we give ourselves rewarding self-responses. If we did poorly, we give ourselves punishing self-responses.
According to Bandura's social cognitive theory, individuals possess a self-system that enables them to exercise a measure of control over their thoughts, feelings, motivation, and actions. This self-system encompasses one's cognitive and affective structures and provides reference mechanisms and a set of subfunctions for perceiving, regulating, and evaluating behavior, which results from the interplay between the system and environmental sources of influence. As such, it serves a self-regulatory function by providing individuals with the capability to influence their own cognitive processes and actions and thus alter their environments. Individuals engage in self-referent thought that mediates between knowledge and action. Through self-reflection, individuals evaluate their own experiences and thought processes. Bandura
(1986) argued that self-reflection is the most uniquely human characteristic. Self-reflective judgments include perceptions of self-efficacy, beliefs in one's capability to organize and execute the courses of action required to manage prospective situations. The higher the sense of efficacy, the greater the effort, persistence, and resilience.
Bandura (1986) wrote that, through the process of self-reflection, individuals are able to evaluate their experiences and thought processes. According to this view, what people know, the skills they possess, or what they have previously accomplished are not always good predictors of subsequent attainments because the beliefs they hold about their capabilities powerfully influence the ways in which they will behave. However, self-perceptions of capabilities help determine what individuals do with the knowledge and skills they currently possess. More importantly, self-beliefs are critical determinants of how well
knowledge is acquired initially.
In another study, Yang (1993) has found that with respect to self-regulatory learners: 1) high regulatory students tend to learn better under learner control than program control; 2) high self regulatory students are able to monitor, evaluate, or manage their learning effectively during learner controlled instruction with embedded questions; 3) learner control reduces instructional time required to complete the lesson; and 4) high self-regulatory students
manage their learning and time efficiently. One procedure for supporting
self-regulated learning is to instruct learners to engage in self-explaining, a behavior associated with enhanced learning, that ordinarily follows from spontaneous self-monitoring (Chi et al., 1994). Learning in informal settings is an ideal environment where activities create opportunities for students to practice scientific inquiry, and to do so in a self-directed fashion where learners take responsibility of their own learning (Gunstone, 1991). Successful learners tend to assess their own understandings and monitor their own progress in ways that seem to facilitate learning (Chi & Bassok, 1989). In other words, one must know what they do not know in order to ask the questions that promote learning (Miyake & Norman, 1979). This suggests the importance of prior knowledge before a concept is introduced or attending an informal learning environment in order to determine the quantity and quality of information which the learner has not already incorporated in their personal schema of knowledge.
In addition, Hagen and Weinstein (1995) believe that master and performance goals can dramatically include college students’ self-regulated learning. These independent but complementary types of goals are shaped in important ways by how faculty organize and structure their classrooms for learning. Involvement in self-regulatory learning is tied closely to student efficacy beliefs (Pintrich & DeGroot, 1990). In presenting a model of self-efficacy as a temporally preceding of self-regulated learning (defined as behavioral constellation of monitoring, elaboration, and effort management strategies), Garcia and Pintrich
(1991) determined that a participant’s belief in their capabilities was more likely to lead to higher levels of self-regulated learning. They developed the Motivated Strategies for Learning Questionnaire, which indicated that intrinsic motivation and self-efficacy had substantial effects on self-regulated learning. In another study, Garcia and Pintrich (1992) have shown that metacognitive self-regulatory strategies were consistently positively related to critical thinking across domains. The study supports the positive relationship between motivation, deep strategy use, and critical thinking. Pintrich (1995) has found that self-regulated learning is an important component of learning for college students. Students must have greater awareness of their own behavior, motivation, cognition and their positive motivational beliefs, and must practice
self-regulated learning strategies. Corno and Mandinach (1983) define
self-regulatory learning as an effort to deepen and manipulate the associative network in a particular area and to monitor and improve that deepening process. It refers to the deliberate planning and monitoring of the cognitive and affective processes that are involved in the successful completion of academic tasks. They also suggest that for some learners these metacognitive processes of planning and monitoring may be so well developed that at times they appear to occur automatically. Five components are viewed by Corno and Mandinach (1983) as necessary and sufficient to define self-regulated learning. The fivecomponents are organized into two categories: the information acquisition processes that include alertness (receiving and tracking information), and monitoring; and the transformational processes of selectivity, connectivity, and
planning. They continue to state that self-regulated learning, which represents the highest form of cognitive engagement, is epitomized by the task appropriate use of information acquisition and transformation skills. Corno (1994) investigated the development of students' orientations to engage in self-regulatory effort and to value or even enjoy this experience. The conclusion is that self-regulated learning comes about from the continuing interchange between students and the educating elements of their extended environments (such as in informal settings), adults and knowledgeable peers, various enacting curricula, and affording activities. Winne (1997) suggests that learners experiment, bootstrapping newer forms of self-regulated learning from prior forms and enabling the learner to step back and review or reflect on
their acquisition.
Self-conscious reflection is a perspective of self-regulation that involves evaluation and modification of the goal or objective, as well as design of the path or procedures used to get there. Learning requires self-conscious reflection. Functionally, this is the best approach. This type of learning requires evaluating and choosing between two or more viable alternative paths.
Zimmerman (1989) defines self-regulated learning strategies as actions and processes directed at acquiring information or skill that involve agency, purpose, and instrumentality perceptions by learners. Strategies include self evaluation, organizing and transforming, goal-setting and planning, seeking information, keeping records and monitoring, environmental structuring, self consequating, rehearsing and memorizing, seeking social assistance, and reviewing records. Subskills required to organize a course of action are themselves governed by broader self-regulatory skills such as knowing how to diagnose task demands or constructing and evaluating alternative strategies. Self-regulated learning is not a mental ability, such as intelligence, or an
academic skill, such as reading proficiency; rather, it is the self-directive process through which learners transform their mental abilities into academic skills (Schunk & Zimmerman, 1998). Possessing these self-regulatory skills can permit students to improve their performances across varied academic activities. He has also developed a cyclic model, which represents the behaviors of a self-regulated learner

1. Self-evaluation and monitoring occur when students judge their personal
effectiveness, often from observations and recordings of prior performances and outcomes.
2. Goal setting and strategic planning occur when students analyze the learning task, set specific learning goals, and plan or refine the strategy to attain the goal.
3. Strategy-implementation monitoring occurs when students try to execute a
strategy in structured contexts to monitor their accuracy in implementing it.
4. Strategic-outcome monitoring occurs when students focus their attention on links between learning outcomes and strategic process to determine
effectiveness. The model is cyclical because self-monitoring on each learning trial provides information that can change subsequent goals, strategies or performance efforts. An important part of this model is initial self-evaluation, because this typically initiates the learner’s attitude toward belief in his or her own competence, or self-efficacy.
Zimmerman and his associates have been instrumental in tracing the
relationships among self-efficacy perceptions, self-efficacy for
self-regulation, academic self-regulatory processes, and academic achievement. This line of inquiry has successfully demonstrated that self-regulatory efficacy contributes to academic efficacy. Self-efficacy is a critical component of self-regulated learning theory. Self-efficacy is a person's sense of being able to deal effectively with a particular task; a belief about personal competence in a particular situation. If an individual student believes they are capable of learning the concept or regulating their own acquisition of the knowledge, then their ability to learn will increase. Schunk and Zimmerman (1998) indicate that this factor provides a bridge between the cognitive and the contextual
forces, such as informal settings, by way of increasing self-regulatory
learning. Zimmerman, Bandura, and Martinez-Pons (1992) used path analysis to demonstrate that academic self-efficacy mediated the influence of self-efficacy for self-regulated learning on academic achievement. Academic self-efficacy influenced achievement directly as well as indirectly by raising students' grade goals. Results of these investigations demonstrate that acquisition of cognitive skills, modeling effects, attributional feedback, and goal setting influence the development of self-efficacy beliefs and that these beliefs, in turn, influence academic performances.
Schunk’s (1990) definition of self-regulated learning includes the beliefs that learners hold with respect to their capabilities for learning (self-efficacy). It is Schunk’s view that self-efficacy, as a predictor of motivation and skill acquisition, can help explain students’ self-regulated learning efforts (Schunk, 1988). Students who attribute successes to their abilities and efforts are likely to feel efficacious about learning and engage in self-regulatory behaviors that further increase their skills (Schunk, 1990). As far as tools for assisting self-regulated learning, there are several characteristics of computer technology that make it a desirable vehicle for examining the concept. Computers make it possible to independently store data collected via interaction with the student, thus providing the possibility for improved efficiency in data collection process. Computers also have the capability of monitoring and recording user interaction and/or progress
providing immediate feedback to the learner. This capability has both research and instructional benefits: first, profiles of the step-by-step process of learner interaction with ideas or concepts can be stored and retrieved for later analysis; second, the immediate feedback that the learner receives allows a greater degree of learner control by providing individualized opportunities for review of the material. Mandinach (1984, 1987) has used the computer as a vehicle for studying the concept of self-regulated learning in the strategic planning knowledge of self-regulation in intellectual computer games. Mandinach concluded that the high and low ability students displayed different patterns of cognitive engagement and the those who utilized self-regulated learning, task focus, and resource management forms of engagement were more successful in completing the game.