Group items tagged

Metacognitive experiences involve the use of metacognitive strategies or metacognitive regulation (Brown, 1987). Metacognitive strategies are sequential processes that one uses to control cognitive activities, and to ensure that a cognitive goal (e.g., understanding a text) has been met. These processes help to regulate and oversee learning, and consist of planning and monitoring cognitive activities, as well as checking the outcomes of those activities.

Self-questioning is a common metacognitive comprehension monitoring strategy. If she finds that she cannot answer her own questions, or that she does not understand the material discussed, she must then determine what needs to be done to ensure that she meets the cognitive goal of understanding the text.

Knowledge is considered to be metacognitive if it is actively used in a strategic manner to ensure that a goal is met. For example, a student may use knowledge in planning how to approach a math exam: "I know that I (person variable) have difficulty with word problems (task variable), so I will answer the computational problems first and save the word problems for last (strategy variable)." Simply possessing knowledge about one's cognitive strengths or weaknesses and the nature of the task without actively utilizing this information to oversee learning is not metacognitive.

Some have reported attrition from eLearning as high as 70 - 80% (Flood 2002, Forrester 2000, in Dagger & Wade, 2004). Parker (1999) argues that “With the growth of distance education has come the problem of exceedingly high attrition rates”. Citing Carter (1996), she suggests that eLearning student attrition in some institutions is exceeds 40%, while others (Frankola, 2001). Diaz (2002), put it at between 20 - 50%,  and Carr (2000), estimate it to be 10% - 20% higher than for traditional on-campus education.

Two concepts and research paradigms are closely related to the problem area of collaborative learning--distributed cognition and shared cognition

Mind tools, (alternatively known as cognitive tools; Kommers, Jonassen, & Mayes, 1991) are intended to engage and facilitate cognitive processing

Concept mapping falls into the large category of Mind tools

This line of research indicated that the multivariate measure of learning represented by the cognitive presence factor could be predicted by the quality of teaching presence and social presence reported by learners in online courses. The relationship between these constructs is illustrated in Fig. 1 below.

The authors (Collins, Brown, & Holum, 1991; Collins, Brown, & Newman,1989) as well as other researchers (Herrington & Oliver, 2000) have refined this model to the belief that useable knowledge is best gained in learning environments featuring the following characteristics:   Authentic context that allows for the natural complexity of the real world Authentic activities Access to expert performances and the modeling of processes Multiple roles and perspectives Collaboration to support the cooperative construction of knowledge Coaching and scaffolding which provides the skills, strategies and links that the students are initially unable to provide to complete the task Reflection to enable abstractions to be formed Articulation to enable tacit knowledge to be made explicit

The goal of learning, therefore, is to engage learners in legitimate peripheral participation in communities of practice (Lave and Wenger 1991). Through community, learners interpret, reflect, and form meaning. Community provides the setting for the social interaction needed to engage in dialogue with others to see various and diverse perspectives on any issue. Community is the joining of practice with analysis and reflection to share the tacit understandings and to create shared knowledge from the experiences among participants in a learning opportunity (Wenger 1998).

The goal of cognitive apprenticeship is to address the problem of inert knowledge and to make the thinking processes of a learning activity visible to both the students and the teacher.  T

Learning-style theory begins with Carl Jung (1927), who noted major differences in the way people perceived (sensation versus intuition), the way they made decisions (logical thinking versus imaginative feelings), and how active or reflective they were while interacting (extroversion versus introversion)

Most learning-style theorists have settled on four basic styles. Our own model, for instance, describes the following four styles: The Mastery style learner absorbs information concretely; processes information sequentially, in a step-by-step manner; and judges the value of learning in terms of its clarity and practicality. The Understanding style learner focuses more on ideas and abstractions; learns through a process of questioning, reasoning, and testing; and evaluates learning by standards of logic and the use of evidence. The Self-Expressive style learner looks for images implied in learning; uses feelings and emotions to construct new ideas and products; and judges the learning process according to its originality, aesthetics, and capacity to surprise or delight. The Interpersonal style learner,1  like the Mastery learner, focuses on concrete, palpable information; prefers to learn socially; and judges learning in terms of its potential use in helping others.

Student Choice: Assessment Products by Intelligence and Style

Miller and Gildea's (1987) work on vocabulary teaching has shown how the assumption that knowing and doing can be separated leads to a teaching method that ignores the way situations structure cognition. Their work has described how children are taught words from dictionary definitions and a few exemplary sentences, and they have compared this method with the way vocabulary is normally learned outside school. People generally learn words in the context of ordinary communication. This process is startlingly fast and successful. Miller and Gildea note that by listening, talking, and reading, the average 17-year-old has learned vocabulary at a rate of 5,000 words per year (13 per day) for over 16 years. By contrast, learning words from abstract definitions and sentences taken out of the context of normal use, the way vocabulary has often been taught, is slow and generally unsuccessful. There is barely enough classroom time to teach more than 100 to 200 words per year. Moreover, much of what is taught turns out to be almost useless in practice. They give the following examples of students' uses of vocabulary acquired this way:

Collins, Brown, and Holum suggested we adopt a model of cognitive apprenticeship as a teaching strategy.  This model encourages teachers and students to verbalize their thinking in order for the student to recognize gaps and to be brought to a more expert level of thinking. 

Modeling – This method requires the teacher to perform a task and to allow the student to observe and to build a mental model of the processes required to complete that task. Coaching – This method requires the student to perform a task while the teacher provides hints, feedback, and reminders to bring their performance closer to an expert performance. Scaffolding – This method requires the teacher to provide supports for the student to perform the task.  As the task is repeated and mastered less supports are provided to the student. Articulation – This method requires the teacher to pull out the student’s problem-solving processes through inquiry or by the student assuming the role of a critic to a set of activities. Reflection – This method requires the student to compare their own problem-solving processes with that of an expert. Exploration – This method requires the teacher to cultivate an environment of problem-solving independent of the expert