Cognitive and Learning Strategies - Assignment Example

Cognitive/Learning Strategies

Learning or cognitive strategies are tools that are very useful in helping students to meet their learning needs. The strategies are described as the use of the mind in solving an existing problem or completing a specific task. Cognitive strategies can also be referred to as procedural prompts, scaffolds or procedural facilitators. For effective learning, there is a need for meta-cognition which an art of self-reflection during the learning process. Cognitive strategies offer a structural approach to learning in situations where simple steps cannot be employed to complete a task. The strategies also help the learner in developing internal procedures that allow for the performance of complex tasks. Cognitive strategies have been seen to increase the efficiency of the learners as they approach different tasks of learning. Some of the academic tasks include applying and remembering information obtained from the course content, paragraphs and sentence construction, paraphrasing, editing and classification of information to be learned. Some of the cognitive or learning strategies include self-explanation, reciprocal teaching and KWL. In this paper, more focus will be put on self-explanation as a learning strategy.

Self-explanation

In the multimedia environments, learning is very hard since there is a need for the learners to integrate and comprehend information actively across a variety of modalities and sources. Self-explanation can be described as the process through which one explains a text to self in either a written form or orally (Roy & Chi, 2013). Self-explanation is a strategy for learning that is effective in assisting students or learners in developing a deep understanding of phenomena that are complex and can be applied in supporting multimedia learning. Self-explanation as learning and teaching strategy aims at facilitating in-depth learning. Through this strategy, an individual generates explanation to various tasks by themselves. Self-explanation has been found to lead to immediate improvement in learning transfer and procedural learning.

The learning environment today is flooded with several multimedia activities, and for the learner to benefit from such descriptions, they must have the ability to construct a conceptual representation of knowledge relating and integrating various forms of information from different modalities and sources into a structure that is coherent (McNamara & Magliano, 2012). To achieve this, readers and learners put together information obtained from various media including representative subparts into a universal representation of the whole system. There is a growing need for the learners to integrate the information is as to develop a deep understating of the basic concepts. However, by just exposing the learners to descriptions of multimedia may not necessarily result in automatic in-depth learning and comprehension of the necessary concepts because some of the learners might be probably passive in their processing of multimedia. The information selection, organization, translation, coordination and integration process across several formats and modalities needed for multimedia learning my present the learners with a lot of difficulties. Therefore, the learning process in a multimedia environment can be only effective if the learners are involved in demanding behaviors of construction, integration and knowledge monitoring in a continuous manner.

To overcome some of the challenges that come along with learning in the multimedia environment, the strategy of self-explaining comes in very handy. The strategy allows the learner to overcome the challenges of active construction of knowledge and to monitor the necessary learning processes. Self-explanation is used by students to give the justifications and rules in problem-solving as well as in the study of worked examples. Self-explanation has been proved effective in several instructional domains. In a study conducted by Roy & Chi (2013), students studying physics were examined by the use of verbal protocols. In the study, a correlation was revealed between the number of justifications or explanations generated by students while studying and the problem-solving success. It was observed that most of the students who learned well had employed the use of examples in developing an understanding of the significant issues. Students who apply the strategy of self-explanation have been found to show great gains in learning as compared to the ones who generate fewer explanations. Self-explanation has also been found to be effective when combined with computer-based systems of learning.

Self-explanation is the act of thinking aloud. An individual talks to himself or herself as they work on a specific problem to put in a conscious awareness of the actual process that the mind is going through (Harris, 2014). In self-explain, the individual asks questions to themselves, act on specific answers, attempt various paths of solutions, identify approach changes as well as comment on the shortcomings. The strategy implies the process of explaining to oneself what one is thinking or doing. The technique involves asking questions while putting to improve one’s understanding of what the mind is going through (Wilie, 2011). It is as if the mind of an individual is watching or monitoring their brain. In self-explaining strategy, some of the questions asked include the information needed to be known to solve an existing problem. Where the information needed can be found; has the problem been answered or solved; are the information parts needed preset. What should be done next; any other examples and what sounds right.

Self-explanation brings an individual’s thinking to the surface of their consciousness hence providing them with the ability to examine and watch as they get along with the process of problem-solving. The strategy in an interactive process that pays attention to the back and forth self-talk of question and answer; proposed solutions, answers, and definitions; modification, acceptance or rejection of solutions, answers, and steps (Harris, 2014). The strategy of self-explanation has been found to be very effective and useful since is fosters the integration of fresh knowledge with the already existing one and supports the learner through the process of updating their existing mental model. Self-explain also helps the students to monitor their understanding levels accurately. The strategy encourages the learners to unearth some of the underlying principles in any domain by facilitating the leaner’s ability of information generalization. One of the examples of the domains in which self-explanation has been greatly applying is mathematics . Students are enabled to enhance their mathematics procedural and conceptual knowledge about the principles underlying their mental model.

Studies have found that the use of self-explaining in studying allows the learners to explain the problems to them thereby proving justification for their actions of the sequences of solution (Johnson, 2006). Self-explanation also leads to the improvement of the outcomes of learning in various domains like arithmetic, interest calculations, geometry, argumentation, conversations of Piaget number, comprehension of biology texts as well as problem beam balancing. The effects of the strategy have been observed across a large pool of cohorts include children and adults. The strategy also enhances transfer in several domains despite the participants receiving no feedback on their explanation’s quality.

Problem Solving

Most of the education institutions agree that problem solving is one of the most significant and meaningful components of thinking and learning. The process of problem solving may not always start with clear statements of the problem. Instead, the majority of the problems should first be identified or picked up from the environment then they are defined and mentally described (Dunbar, 2011). The problem-solving process should then put the focus on the recognition of the problem, the definition of the problem and representation of the problem. According to Dunbar (2011), one of the main components of the problem, solving is the act of searching in the problem space. A problem space has several aspects including the initial, goal and operational states. A set of operators assists the problem solver in moving from one state to the other.

Well-Defined Problem versus ill-Defined Problem

There are two main classes of problems namely well-defined problems and ill-defined problems. Well-defined problems are the problems which have clear goals, solution paths and defined solution obstacles with basis on the information provided (Janssen, 2007). A well-defined problem has a convergent solution that makes use of application of a certain limited number of principles and rules within the parameters that are well defined. An example of a well-defined problem in a school subject is solving algebra in mathematics. Such an example is a well-defined problem because it has one single convergent and correct answer that leads to satisfaction in the final solution. The problem needs relatively small amounts of constrained knowledge or information based on the textbook chapter or material provided (Hong, 2011). The well-defined problem contains all the components of the problem such as an initial state that is well defined, a goal state that is known, sets of logical state and parameters that are a constraint.

Most of the problems in mathematics are considered well-defined problems because they require the application concrete number of solutions, concepts, principles and rules studied as constraint problems. The skills used in solving algebra in mathematical problems can only be transferred or applied to problems of a similar type. The process of solving well-defined problems include the use of certain search techniques like analogical problems recall, analysis of means-end, simplifying and decomposing, sub-goal finding and tests. The process of solving such problems is already defined and agreed upon and may only have slight variations depending on the experts or specific problem domains.

An ill-defined problem is characterized by the inadequacy of a clear solution path. Such a problem has multiple solutions, several paths to the solution, limited parameters that are also difficult to manipulate and has several uncertainties about the rules, concepts, and principles needed for the solution process (Jonassen, 2007). An ill-defined problem does not have a clearly defined problem statement thus making it very challenging to define the problem or give the problem representation. Ill-defined problems are being routinely encountered each day throughout the human experience. An example of an ill-defined problem is a school subject is trying to find a cure to cancer in biology. Such a problem is considered because despite the fact that the problem situation is in specific contexts, the description of the problem itself is out-rightly vague and the necessary information for the solution process is not given in the problem statement.

The goals of the problem are also vaguely defined even though they must be considered during the process of problem-solving. The information needed for the process of decision-making is also inaccurate, incomplete or ambiguous. In such a problem, there is a lot of uncertainty surrounding the rules, principles, and concepts to be put in place. The relationship between the rules, concepts, and principles is very inconsistent, and the case elements vary with various contexts with basis on the individual context interactive elements. An ill-defined problem like trying to find a cure to cancer in biology books is also very wide in scope and may require a lot of research, which often go beyond the course work. To solve such a problem, the learner is exposed to a mountain of challenges most of which may not be overcome in a relatively long period.

IDEAL Problem-Solving Model and Problem-Solving Framework of PISA

In an ideal problem-solving model, the first two steps include the identification of the problem and definition of the problem (Deno, 2010). In the first step, the problem that needs to be solved is identified. This step is because, without the identification of the problem, it may be very hard to outline the goals, principles, and concepts to be applied in the solution process. After the identification of the problem, there is the need to define the problem. In this step, a diagnosis of the situation is conducted, and focus is laid on the problem. There are several techniques used in this step including the use of flow charts in identifying the specific steps and diagrams of cause-and-effect that defines and analyses the root causes. The process of defining the problem includes a review and documentation of the way the processes working currently. At this stage, several aspects are described including who does what, necessary information, tools, communication between individuals and groups and the period and format to be used. The second component of problem definition is the evaluation of the probable effect or impact of the revised policies and new tools applied in developing the new model.

The problem-solving framework by PISA has four major steps, namely, exploration and understanding; representation and formulation; planning and execution; and monitoring and reflection. In the problem-solving framework of PISA (2012), there are three main futures namely the nature of the problem situation the problem-solving process and the problem context. The first future, which is the nature of the problem situation, all the necessary information for the process of problem solving, is disclosed at the beginning. However, not all the information needed is disclosed because some of the information coming up during the process in which the problem situation is explored. In another side all, the information may be disclosed at the outset of the process.

In the second phase of the PISA problem-solving framework, which is the actual problem, solving process, there are several cognitive processes involved in the specific tasks. First is the understanding and exploration of the information given concerning the problem. Secondly, there is representation and formulation of tabular, graphical, verbal or symbolic representations of the situation and the hypothesis of their relationships. Thirdly, there is the establishment of a plan through the goal and sub-goal setting and the execution of the subsequent steps for the plan. Finally, there is the monitoring of the progress, reaction to the feedback and reflection on the outlined solution, problem information, and the adopted strategy. The list aspect or future of the PISA problem-solving model is the identification of the problem context, which focuses on the everyday scenario within which the problem is embedded.

The ideal problem-solving model and the PISA problem-solving framework are all aimed at the final goal of solving an existing problem. However, the two are different in the approaches. The ideal model is simple and gives a Cleary defined process and systematic approach to the problem-solving process. The PISA framework is a bit more complex in that is focus much in detail of the problem, the context of the problem, the various aspects of the problem and the impact of the process being used to solve the problem. However, despite the few disparities in the structure and concept, the two models all offer a systematic approach to the process of problem-solving.

In teaching, the best model to be applied is the PISA problem-solving framework. However much complex it might appear, the model is very clear and gives a lot of detail towards the process of problem-solving as compared to the ideal model. In the class setting, there is need first to explore and understand the existing problem. This enables the teacher and the learner to have a clear understanding of the problem for the onset so that no confusion arises in the process. Secondly, there is a need for representation of the problem with diagrams, flowcharts, and graphics to give the learner and visual representation of the whole picture. This aspect allows for easy grasping of the concepts and establishment of clearly defined relationships. The teacher also needs to plan the process of problem-solving by having lesson plans, teaching aids and execution the plan as necessary. Finally, for the teacher to evaluate the outcome of the whole process, there is a need for monitoring and the reflecting on the established plan. The PISA framework is easy to apply and give of detail to the process.

To overcome some of the challenges that come along with learning in the multimedia environment, the strategy of self-explaining comes in very handy. The strategy allows the learner to overcome the challenges of active construction of knowledge and to monitor the necessary learning processes. Self-explanation is used by students to give the justifications and rules in problem-solving as well as in the study of worked examples. Self-explanation has been proved effective in several instructional domains. In a study conducted by Roy & Chi (2013), students studying physics were examined by the use of verbal protocols. In the study, a correlation was revealed between the number of justifications or explanations generated by students while studying and the problem-solving success. It was observed that most of the students who learned well had employed the use of examples in developing an understanding of the significant issues. Students who apply the strategy of self-explanation have been found to show great gains in learning as compared to the ones who generate fewer explanations. Self-explanation has also been found to be effective when combined with computer-based systems of learning.

Self-explanation is the act of thinking aloud. An individual talks to himself or herself as they work on a specific problem to put in a conscious awareness of the actual process that the mind is going through (Harris, 2014). In self-explain, the individual asks questions to themselves, act on specific answers, attempt various paths of solutions, identify approach changes as well as comment on the shortcomings. The strategy implies the process of explaining to oneself what one is thinking or doing. The technique involves asking questions while putting to improve one’s understanding of what the mind is going through (Wilie, 2011). It is as if the mind of an individual is watching or monitoring their brain. In self-explaining strategy, some of the questions asked include the information needed to be known to solve an existing problem. Where the information needed can be found; has the problem been answered or solved; are the information parts needed preset. What should be done next; any other examples and what sounds right.

Self-explanation brings an individual’s thinking to the surface of their consciousness hence providing them with the ability to examine and watch as they get along with the process of problem-solving. The strategy in an interactive process that pays attention to the back and forth self-talk of question and answer; proposed solutions, answers, and definitions; modification, acceptance or rejection of solutions, answers, and steps (Harris, 2014). The strategy of self-explanation has been found to be very effective and useful since is fosters the integration of fresh knowledge with the already existing one and supports the learner through the process of updating their existing mental model. Self-explain also helps the students to monitor their understanding levels accurately. The strategy encourages the learners to unearth some of the underlying principles in any domain by facilitating the leaner’s ability of information generalization. One of the examples of the domains in which self-explanation has been greatly applying is mathematics . Read More