Reflective Learning ( For Engineering )

Reflective Learning

The Four Stages of Reflective Learning

Reflecting on your experiences, whether they are at work or in the classroom is the best way to ratchet up the learning level of any experience. Reflection strengthens learning and allows you to recognize your areas of growth and areas that need improvement. Reflection is the key part of the 'experiential learning cycle'. Experiential education is defined as "the process of actively engaging students in an authentic experience that will have benefits and consequences. Students make discoveries and experiment with knowledge themselves instead of hearing or reading about the experiences of others. Students also reflect on their experiences, thus developing new skills, new attitudes, and new theories or ways of thinking" (Kraft & Sakofs, 1988). The theoretical learning model below was developed by David Kolb, 1984.

This model can be simplified to:

1. Experiencing – These are activities from which a student may learn (readings, fieldwork, lab work, problem sets, observations, simulations/games).
2. Reflecting – the student thinks about the experience (what was seen, felt, thought about) and integrates the new experience with past experiences. (Keeping a journal or log through your work term will help with this process.)
3. Generalizing – the student develops questions and theories and attaches meaning to the experience.
4. Applying – the student tests out new ideas, attitudes and behaviours and the cycle continues.

Setting Goals and Objectives

While reflecting will facilitate learning after the fact, setting goals and objectives will initiate learning and increase your chances for positive outcomes. We encourage you to set goals for developing new skills and knowledge on your work terms. While the words "goals" and "objectives" are used interchangeably, goals are generally defined as being broad in nature, while objectives are the clearly defined steps needed to achieve your goals. Your goals should be written in terms of the 'learning outcome' of your objectives. For example:

Learning Goal:	To improve oral communications through giving presentations.
Objective:	As part of my work term, I will seek out at least one opportunity to develop and deliver an effective and well organized presentation to my co-workers and supervisor.

Develop your Goals the S M A R T Way

Specific:	Outline in detail what you wish to accomplish. What, why, how?
Measurable:	The goal must be quantifiable; a standard is needed for comparison.
Action-Oriented:	Describe activities needed to accomplish the goal.
Realistic:	The goal must be attainable, practical and do-able.
Timebound:	A time frame is needed; make the commitment.

One way to develop your goals is to think about those transferable skills that employers are looking for and then develop goals and objectives around these:

Transferable Skills:	Example of goal:	Objective:
Communication	Improve technical writing skills	By writing a technical report by end of work term, that analyzes a process, describes a project or demonstrates problem solving to improve operations. Report will be graded as Pass/Fail.
Creativity	Design a robot
Customer Service Orientation	Learn sales techniques
Leadership	Volunteer to organize a fund raising or social event for my work team
Problem Solving	Learn to break down a problem into smaller parts by analyzing a process or operational procedure, generating alternatives and recommending a solution
Project Management	Learn project management software
Self-Directed Learning	Develop goals and objectives for work term
Self-motivation/Initiative	Achieve work term goals and demonstrate them to my supervisor
Team Work	Join a workplace committee
Time Management	Assign timelines to tasks

Another way to think about goals you might set is to identify skills needed on the job:

Skills:	Example of goal:
People:	Improve ability to work with teams and network
Data:	Gain experience conducting research and surveys
Things:	Work in manufacturing to gain hands-on experience
Ideas:	Design a computer program to monitor inventory

Objective:
You can choose to develop goals around either professional experience, personal attributes or technical expertise. You don't have to wait until you are at work to set your goals but you should integrate them with your actual work assignments and discuss them with your supervisor as well as give him/her updates on your progress.

References:

Kraft, D., & Sakofs, M. (Eds.). (1988). The theory of experiential education. Boulder, CO: Association for Experiential Education.
Kolb, D. A. (1984) Experiential Learning, Englewood Cliffs, NJ.: Prentice Hall.

The Experiential Learning Cycle

Experiential learning occurs when a person engages in some activity, looks back at the activity critically, abstracts some useful insight from the analysis, and puts the result to work through a change in behavior. Of course, this process is experienced spontaneously in everyone's ordinary life. People never stop learning; with each new experience, we consciously or unconsciously ask ourselves questions such as, _How did that feel?,_ _What really happened?,_ or _What do I need to remember about that?_ It is an inductive process: proceeding from observation rather than from a priori _truth_ (as in the deductive process).

Learning can be defined as a change in behavior as a result of experience or input, and that is the usual purpose of training. The effectiveness of experiential learning is based on the fact that nothing is more relevant to us than ourselves. One's own reactions to, observations about, and understanding of something are more important than someone else's opinion about it. Research has shown that people learn best by _doing._ One remembers best what one knows better than one remembers what one knows about.

Experiencing

The data-generating part of the experience develops a common base for the discussion that follows. Goals include:

• To Explore_

• To Examine_

• To Study_

• To Identify_

Publishing

The question in this stage is _What happened to me?_ Participants share personal data about what they saw and/or how they felt during the experience.

• Feelings

• Reactions

• Observations

Processing

The question here is _What happened in general?_ Participants systematically examine their commonly shared experience.

• Common themes

• Patterns

• Interactions

• Group dynamics

• Behavioral trends

Generalizing

The question now is _So what?_ From the patterns identified, participants abstract:

• Inferences

• Generalizations

• Learnings

• Principles

• What tends to happen_

These are stated in terms of the _real world_ rather than the learning situation.

Applying

The final question is _Now what?_ Generalizations and learnings are applied to real-life situations, and change is planned. This stage can include:

• Consulting groups

• Goal setting

• Practice sessions

• Contracting for change

The application of learning is a new experience. The cycle begins again_

Conclusion

Learning experiences that utilize the experiential learning model allow participants to confront basic psychological and behavioral issues that they have to deal with in their daily lives. The model gives participants an opportunity to examine their feelings and behaviors related to interactions with other individuals. Examining their feelings and other reactions to situations helps to expand the participants' awareness and understanding of the function their emotions play in their behavior. Not only does this add to the interest and involvement of the participants, it also contributes significantly to the transfer of learning. No other type of learning generates this personal involvement and depth of understanding. The ultimate result is that participants accept responsibility for their own learning and behavior, rather than assigning that responsibility to someone else.

Adapted From:

Pfeiffer, J.W., & Ballew, A.C. (1988). Using structured experiences in human resource development (UATT Series, Vol. 1). San Diego, CA:, University Associates.

Learning Concepts (Part III)

Productions

Production rules are a primary component of many contemporary computer models of cognition (e.g., ACT, GPS, Soar). A production has the form: If THEN When the current state of memory matches the side of the rule, the specified is carried out. The action could be any form of mental processing. Productions can also generate new productions giving rise to new cognitive rules (c.f., creativity).

Flow of control in a production system goes through the set of productions sequentially until a condition is matched. After executing the action, the system continues with the next production or returns to the beginning of the set. This sequence is repeated until a terminal goal condition is satisfied. Thus, production systems require no executive level of control; all control is determined by the productions. Clearly, order of productions in the set is important since it determines which actions are satisfied first.

It is possible to add constraints to productions that alter the strict sequential order and hence introduce some form of higher level control. For example, preference can be given to conditions according to recency or frequency of occurence. Productions can be limited to firing only once for a given condition (rule of refractoriness). Or, goal symbols can be added to the conditions that must be satisfied in order for the production to be satisfied.

Productions map very closely onto the notion of rules found in many cognitive theories and hence are a natural representation to use when building computer models of such theories. They also resemble the S-R associations of behavioral theories, except that production rules do not normally encompass any notion of strength; they are all or none. However, some theorists have allowed individual production rules to have probabilities of executing based upon frequency of use or characteristics of the conditions.

References:

Klahr, D., Langley, P. & Neches, R. (1987). Production System Models of Learning and Development. Cambridge, MA: MIT Press

Feedback/Reinforcement

Feedback and reinforcement are two of the most pivotal concepts in learning. Feedback involves providing learners with information about their responses whereas reinforcement affects the tendency to make a specific response again. Feedback can be positive, negative or neutral; reinforcement is either positive (increases the response) or negative (decreases the response). Feedback is almost always considered external while reinforcement can be external or instrinsic (i.e., generated by the individual).

Information processing theories tend to emphasize the importance of feedback to learning since knowledge of results is necessary to correct mistakes and develop new plans. On the other hand, behavioral theories such as Hull, Guthrie, Thorndike, and Skinner focus on the role of reinforcement in motivating the individual to behave in certain ways. One of the critical variables in both cases is the length of time between the response and the feedback or reinforcement. In general, the more immediate the feedback or reinforcement, the more learning is facilitated.

The nature of the feedback or reinforcement provided was the basis for many early instructional principles, especially in the context of programmed instruction (e.g., Deterline, 1962; Markle, 1964). For example, the use of "prompting" (i.e., providing hints) was recommended in order to "shape" (i.e., selectively reinforce) the correct responses. Other principles concerned the choice of an appropriate "step size" (i.e., how much information to present at once) and how often feedback or reinforcement should be provided.

References:
Deterline, W.A. (1962). An Introduction to Programmed Instruction. New York: Prentice-Hall.
Markle, S.R. (1964). Good Frames and Bad. New York: Wiley.

Schema

Bartlett (1932, 1958) is credited with first proposing the concept of schema (plural: schemata). He arrived at the concept from studies of memory he conducted in which subjects recalled details of stories that were not actually there. He suggested that memory takes the form of schema which provide a mental framework for understanding and remembering information.

Mandler (1984) and Rumelhart (1980) have further developed the schema concept. Schema have received significant empirical support from studies in psycholinguistics. For example, the experiments of Bransford & Franks (1971) involved showing people pictures and asking them questions about what the story depicted; people would remember different details depending upon the nature of the picture. Schema are also considered to be important components of cultural differences in cognition (e.g., Quinn & Holland, 1987). Research on novice versus expert performance (e.g., Chi et al., 1988) suggests that the nature of expertise is largely due to the possession of schemas that guide perception and problem-solving.

Schema-like constructs also form the basis of many theories of cognition including: Schank (scripts), AC  (productions), Soar (episodic memory), Piaget, and Rumelhart & Norman (modes) as well as some instructional theories such as Bruner, Reigeluth, Spiro and Sweller .

References:
Bartlett, F.C. (1932). Remembering: An Experimental and Social Study. Cambridge: Cambridge University Press.
Bartlett, F.C. (1958). Thinking. New York: Basic Books.
Bransford, J.D. & Franks, J.J. (1971). The abstraction of linguistic ideas. Cognitive Psychology, 2, 331-350.
Chi, M., Glaser, R. & Farr, M. (1988). The Nature of Expertise. Hillsdale, NJ: Erlbaum.
Mandler, J. (1984). Stories, Scripts, and Scenes: Aspects of Schema Theory. Hillsdale, NJ: Erlbaum.
Quinn, N. & Holland, D. (1987). Cultural Models of Language and Thought. New York: Cambridge University Press.
Rumelhart, D.E. (1980). Schemata: The building blocks of cognition. In R.J. Spiro, B.Bruce, & W.F. Brewer (eds.), Theoretical Issues in Reading and Comprehension. Hillsdale, NJ: Erlbaum

Sequencing of Instruction

One of the most important issues in the application of learning theory is sequencing of instruction. The order and organization of learning activities affects the way information is processed and retained (Glynn & DiVesta, 1977; Lorch & Lorch, 1985; Van Patten, Chao, & Reigeluth, 1986)

A number of theories (e.g., Bruner, Reigeluth, Scandura) suggest a simple-to-complex sequence. Landa's algo-heuristic theory prescribes a cumulative strategy. According to Gagne's Conditions of Learning theory, sequence is dictated by pre-requisite skills and the level of cognitive processing involved. Criterion Referenced Instruction (Mager) allows the learner the freedom to choose their own learning sequence based upon mastery of pre-requisite lessons. Component Display Theory (Merrill) also proposes that the learner select their own learning sequence based upon the instructional components available.

Theories that emphasize the goal-directed nature of behavior such as Tolman or Newell & Simon would specify that the sequence of instruction be based upon the goals/subgoals to be achieved. Gestalt theories, which emphasize understanding the structure of a subject domain, would prescribe learning activities that result in a broad rather than detailed knowledge for a particular domain.

On the other hand, behavioral (S-R) theories of learning such as connectionism, drive reduction or operant conditioning, would tend to support a linear sequence of instruction. From the behavioral perspective, learning amounts to S-R pairings and mastery of a complex subject matter or task involves the development of a chain or repetoire of such connections. Indeed, a fundamental principle of Skinnerian programmed learning was the "shaping" of such S-R chains.

Theories of adult learning such as adragogy orminimalism emphasize the importance of adapting instruction to the experience or interests of learners. According to these theories , there is no optimal sequence of instruction apart from the learner. A similar position based upon abilities would be espoused by theories of individual differences (e.g., Guilford, Cronbach & Snow, Sternberg) and supported by research on cognitive styles.

References:
Glynn, S.M. & DiVesta, F.J. (1977). Outline and hierarchical organization for study and retrieval. Journal of Educational Psychology, 69(1), 69-95.
Lorch, R.F. Jr., & Lorch, E.P. (1985). Topic structure representation and text recall. Journal of Educational Psychology, 77(2), 137-148.
Van Patten, J., Chao, C.I. & Reigeluth, C.M. (1986). A review of strategies for sequencing and synthesizing instruction. Review of Educational Research, 56(4), 437-471.

Taxonomies

Following the 1948 Convention of the American Psychological Association, Benjamin Bloom took a lead in formulating a classification of "the goals of the educational process". Bloom headed a group of educational psychologists who developed a classification of levels of intellectual behavior important in learning. This became a taxonomy including three overlapping domains; the cognitive, psychomotor, and affective (see Anderson & Krathwohl, 2001; Bloom & Krathwhol, 1956, Gronlund, 1970).

Cognitive learning consisted of 6 levels: knowledge, comprehension, application, analysis, synthesis, and evaluation. For each level, specific learning behaviors were defined as well as appropriate descriptive verbs that could be used for writing instructional objectives. For example:
1.Knowledge: arrange, define, duplicate, label, list, memorize, name, order, recognize, reproduce state.
2.Comprehension: classify, describe, discuss, explain, express, identify, indicate, locate, recognize, report, restate, review, select, translate,
3.Application: apply, choose, demonstrate, dramatize, employ, illustrate, interpret, operate, practice, schedule, sketch, solve, use, write.
4.Analysis: analyze, appraise, calculate, categorize, compare, contrast, criticize, differentiate, discriminate, distinguish, examine, experiment, question, test.
5.Synthesis: arrange, assemble, collect, compose, construct, create, design, develop, formulate, manage, organize, plan, prepare, propose, set up, write.
6.Evaluation: appraise, argue, assess, attach, choose compare, defend estimate, judge, predict, rate, core, select, support, value, evaluate.

The Affective domain (e.g., Krathwhol, Bloom & Masia, 1964) consisted of behaviors corresponding to: attitudes of awareness, interest, attention, concern, and responsibility, ability to listen and respond in interactions with others, and ability to demonstrate those attitudinal characteristics or values which are appropriate to the test situation and the field of study. This domain relates to emotions, attitudes, appreciations, and values, such as enjoying, conserving, respecting, and supporting.

Although not part of the original work by Bloom, others went on to complete the definition of psychomotor taxonomies. For example, Harrow (1972) proposed these six levels: Reflex (objectives not usually written at this "low" level), Fundamental movements - applicable mostly to young children (crawl, run, jump, reach, change direction), Perceptual abilities (catch, write, balance, distinguish, manipulate), Physical abilities (stop, increase, move quickly, change, react), Skilled movements (play, hit, swim, dive, use), and Non-discursive communication (express, create, mime, design, interpret).

The significance of the work of Bloom and others on taxonomies was that it was the first attempt to classify learning behaviors and provide concrete measures for identifying different levels of learning. The development of taxonomies is closed related to the use of instructional objectives and the systematic design of instructional programs (see Gagne, Merrill or Mager ).

Web Resources:
For more about Bloom and his work on taxonomies, see:
http://www.itee.uq.edu.au/~philip/Publications/sigcse-2001-talk/blooms.html
http://www.coe.uga.edu/epltt/bloom.htm
http://en.wikipedia.org/wiki/Benjamin_Bloom

References:

Anderson, L. & Krathwohl, D. (2001). A Taxonomy for Learning, Teaching and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives. New York<: Longman.

Bloom Benjamin S. and David R. Krathwohl, (1956). Taxonomy of Educational Objectives: The Classification of Educational Goals, by a committee of college and university examiners. Handbook I: Cognitive Domain. New York<: Longman, Green.

Gronlund, Norman E. (1970). Stating Behavioral Objectives for Classroom Instruction. New York<: Macmillan.

Harrow, A. (1972). A Taxonomy of the Psychomotor Domain. A guide for Developing Behavioral Objectives. New York<: McKay.

Krathwohl, David R., Benjamin S. Bloom, and Bertram B. Masia. (1964). Taxonomy of Educational Objectives: The Classification of Educational Goals. Handbook II: Affective Domain. New York<: David McKay Co., Inc.

Note: Thanks to Kevin C. Lawrence for his suggestion to include this entry and the links he provided. Thanks to Geoff Issacs for the reference to the SOLO taxonomy.

Learning Concepts (Part II)

Imagery

Imagery is a cognitive phenomena of long-standing, first studied by Wilhelm Wundt at the turn of the century. From a theoretical perspective, imagery is a critical issue in terms of memory structures and processes (e.g., Shepard & Cooper, 1982). Theories that postulate a propositional basis for memory (e.g., ACT ) have difficulty accounting for imagery. A number of imagery researchers have developed their own theories of memory that focus on the visual components of imagery. Paivio has proposed a dual coding theory that suggests that verbal and nonverbal information is processed separately. Kosslyn (1980) has proposed a two-stage model of imagery that involves a surface representation generated in working memory from a deep representation in long-term memory. Piaget & Inhelder (1971) discuss the role of imagery in cognitive development.

From a practical point of view, imagery has been shown to facilitate recall in many studies. It also appears to play a major role in problem-solving and creativity. For example, there are many anecdotes of imagery in scientific discovery (Miller, 1984). Imagery also appears to help sensory-motor skills by allowing mental rehearsal of a task or activity. However, it is clear from theories of intelligence (e.g., Guilford ) that people differ in their ability to create visual images.

References:

Bower, J. (1972). Mental imagery and associative learning. In L.

Gregg (ed.), Cognition in Learning and Memory. New York: Wiley.

Kosslyn, S. (1980). Image and Mind. Cambridge, MA: Harvard University Press.

Miller, A. (1984). Imagery in Scientific Thought. Boston: Birkhauser.

Richardson, A. (1969). Mental Imagery. New York: Springer.

Piaget, J. & Inhelder, B. (1971). Mental Imagery and the Child. New York: Basic Books.

Sheehan, P. (1972). The Function and Nature of Imagery. New York: Academic Press.

Shepard, R. & Cooper, L. (1982). Mental Images and Their Transformations. Cambridge, MA: MIT Press.

Learning Strategies

Learning strategies refer to methods that students use to learn. This ranges from techniques for improved memory to better studying or test-taking strategies. For example, the method of loci is a classic memory improvement technique; it involves making associations between facts to be remembered and particular locations. In order to remember something, you simply visualize places and the associated facts.

Some learning strategies involve changes to the design of instruction. For example, the use of questions before, during or after instruction has been shown to increase the degree of learning (see Ausubel). Methods that attempt to increase the degree of learning that occurs have been called "mathemagenic" (Ropthkopf, 1970).

A typical study skill program is SQ3R which suggests 5 steps: (1) survey the material to be learned, (2) develop questions about the material, (3) read the material, (4) recall the key ideas, and (5) review the material.

Research on metacognition may be relevant to the study of learning strategies in so far as they are both concerned with control processes. A number of learning theories emphasize the importance of learning strategies including: double loop learning ( Argyris ), conversation theory (Pask), and lateral thinking ( DeBono ). Weinstein (1991) discusses learning strategies in the context of social interaction, an important aspect of Situated Learning Theory.

References:
H.F. O'Neil (1978). Learning strategies. New York: Academic Press.
H.F. O'Neil & C. Spielberger (1979). Cognitive and Affective Learning Strategies. New York: Academic Press.
Rothkopf, E. (1970). The concept of mathemagenic behavior. Review of Educational Research, 40, 325-336.
Schmeck, R.R. (1986). Learning Styles and Learning Strategies. NY: Plenum.
Weinstein, C.E., Goetz, E.T., & Alexander, P.A. (1986). Learning and Study Strategies. NY: Academic Press.
Weinstein, C.S. (1991). The classroom as a social context for learning. Annual Review of Psychology, (42), 493-525.

Mastery

A fundamental change in thinking about the nature of instruction was initiated in 1963 when John B. Carroll argued for the idea of mastery learning. Mastery learning suggests that the focus of instruction should be the time required for different students to learn the same material. This contrasts with the classic model (based upon theories of intelligence ) in which all students are given the same amount of time to learn and the focus is on differences in ability. Indeed, Carroll (1989) argues that aptitute is primarily a measure of time required to learn.

The idea of mastery learning amounts to a radical shift in responsibility for teachers; the blame for a student's failure rests with the instruction not a lack of ability on the part of the student. In a mastery learning environment, the challenge becomes providing enough time and employing instructional strategies so that all students can achieve the same level of learning (Levine, 1985; Bloom, 1981).

The key elements in matery learning are: (1) clearly specifying what is to be learned and how it will be evaluated, (2) allowing students to learn at their own pace, (3) assessing student progress and providing appropriate feedback or remediation, and (4) testing that final learning critierion has been achieved.

Mastery learning has been widely applied in schools and training settings, and research shows that it can improve instructional effectiveness (e.g., Block, Efthim & Burns, 1989; Slavin, 1987). On the other hand, there are some theoretical and practical weaknesses including the fact that people do differ in ability and tend to reach different levels of achievement (see Cox & Dunn, 1979). Furthermore, mastery learning programs tend to require considerable amounts of time and effort to implement which most teachers and schools are not prepared to expend.

The mastery learning model is closely aligned with the use of instructional objectives and the systematic design of instructional programs (see Gagne, Merrill). The Criterion Referenced Instruction (CRI) model of Mager is an attempt to implement the mastery learning model. In addition, the theoretical framework of Skinner with its emphasis on individualized learning and the importance of feedback (i .e., reinforcement) is also relevant to mastery learning.

References:
Block, J. H. (1971). Mastery Learning: Theory and Practice. New York: Holt, Rinehart & Winston.
Block, J. H., Efthim, H. E., & Burns, R.B. (1989). Building Effective Mastery Learning Schools. New York: Longman.
Bloom, B.S. (1981). All Our Children Learning. New York: McGraw-Hill.
Carroll, J. B. (1963). A model of school learning. Teachers College Record, 64, 723-733.
Carroll, J.B. (1989). The Carroll model: A 25 year retrospective and prospective view. Educational Researcher, 18(1), 26-31.
Cox, W.F. & Dunn, T. G. (1979). Mastery learning: A psychological trap? Educational Pyschologist, 14, 24-29.
Levine, D. (1985). Improving Student Achievement Through Mastery Learning Programs. San Francisco: Jossey-Bass.
Slavin, R.E. (1987). Mastery learning reconsidered. Review of Educational Research, 57(2), 175-214.

Memory

Memory is one of the most important concepts in learning; if things are not remembered, no learning can take place. Futhermore, memory has served as a battleground for opposing theories and paradigms of learning (e.g., Adams, 1967; Ashcraft, 1989; Bartlett, 1932; Klatzky, 1980; Loftus & Loftus, 1976; Tulving & Donaldson, 1972). Some of the major issues include recall versus recognition, the nature of forgetting (i.e., interference versus decay), the structure of memory, and intentional versus incidental learning.

According to the early behaviorist theories (e.g., Thorndike, Guthrie, Hull), remembering was a function of S-R pairings which acquired strength due to contiguity or reinforcement. Stimulus sampling theory explained many memory phenomenon on the basis of statistical outcomes. On the other hand, cognitive theories (e.g., Tolman) insisted that meaning (i.e., semantic factors) played an important role in remembering. In particular, Miller suggested that information was organized into "chunks" according to some commonality. The idea that memory is always an active reconstruction of existing knowledge was championed by Bruner and is found in the theories of Ausubel and Schank.

Some theories of memory have concerned themselves with the nature of the processing. Paivio suggests a dual coding scheme for verbal and visual information. Craik & Lockhart proposed that information can be processed to different levels of understanding. Rumelhart & Norman describe three modes of memory (accretion, structuring and tuning) to account for different kinds of learning.

Other theories have focused on the representation of information in memory. ACT assumes three types of structures: declarative, procedural, and working memory. Merrill proposes two forms: associative and algorithmic. On the other hand, Soar postulates that all information is stored in procedural form. Kintsch (1974) suggests that memory is propositional in nature and it is the relationship among propositions that gives rise to meaning.

Many theories of instruction do not make assumptions about the nature of memory but do specify how information should be organized for optimal learning. For example, Pask outlines the development of entailment structures and Reigeluth discusses elaboration networks.

Individual differences in memory abilities are discussed by Eysenck (1977) and Guilford and represent an important aspect of intelligence.

References:
Adam s, J. (1967). Human Memory. New York: McGraw-Hill.
Ashcraft, M. (1989). Human Memory and Cognition. Glenview, IL: Scott Foresman.
Bartlett, F.C. (1932). Remembering: An Experimental and Social Study. Cambridge: Cambridge University Press.
Eyse nck, M. (1977). Human Memory: Theory, Research and Individual Differences. Oxford: Pergamon Press.
Kintsch, W. (1974). The Representation of Meaning in Memory. Hillsdale, NJ: Erlbaum.
Klatzky, R.L. (1980). Human Memory: Structures and Processes (2 nd Edition). San Francisco: Freeman.
Loftus, G. & Loftus, E. (1976). Human Memory: The Processing of Information. Hillsdale, NJ: Erlbaum.
Tulving,E. & Donaldson, W. (1972). Organization of Memory. New York: Academic Press.

Mental Models

Mental models are representations of reality that people use to understand specific phenomena. Norman (in Gentner & Stevens, 1983) describes them as follows: "In interacting with the environment, with others, and with the artifacts of technology, people form internal, mental models of themselves and of the things with which they are interacting. These models provide predictive and explanatory power for understanding the interaction."

Mental models are consistent with theories that postulate internal representations in thinking processes (e.g., Tolman , GOMS , GPS ). Johnson-Laird (1983) proposes mental models as the basic structure of cognition: "It is now plausible to suppose that mental models play a central and unifying role in representing objects, states of affairs, sequences of events, the way the world is, and the social and psychological actions of daily life." (p397)

Holland et al. (1986) suggest that mental models are the basis for all reasoning processes: "Models are best understood as assemblages of synchronic and diachronic rules organized into default hierarchies and clustered into categories. The rules comprising the model act in accord with the principle of limited parallelism, both competing and supporting one another." (p343) Schumacher & Czerwinski (1992) describe the role of mental models in acquiring expertise in a task domain.

Some of the characteristics of mental models are:

• They are incomplete and constantly evolving
• They are usually not accurate representations of a phenomenon; they typically contain errors and contradictions
• They are parsimonious and provide simplified explanations of complex phenomena
• They often contain measures of uncertainty about their validity that allow them to used even if incorrect
• They can be represented by sets of condition-action rules.

The study of mental models has involved the detailed analysis of small knowledge domains (e.g., motion, ocean navigation, electricity, calculators) and the development of computer representations (see Gentner & Stevens, 1983). For example, DeKleer & Brown (1981) describe how the mental model of a doorbell is formed and how the model is useful in solving problems for mechanical devices. Kieras & Bovair (1984) discuss the role of mental models in understanding electronics. Mental models have been applied extensively in the domain of troubleshooting (e.g., White & Frederiksen, 1985).

One interesting application of mental models to psychology is the Personal Construct Theory of George Kelley (1955). While the primary thrust of Kelly's work was therapy rather than education, it has seen much broader applications (see http://repgrid.com/pcp/) [Thanks to Richard Breen for bringing this to my attention]

For an exploration of the relationship between mental models, systems theory, and cyberspace culture, see "A house of horizions and perspectives" by Heiner Benking and James Rose.

References:

Collins, A., & Gentner, D. (1987). How people construct mental models. In D. Holland & N. Quinn (eds.), Cultural Models in Thought and Language. Cambridge: Cambridge University Press.

deKleer, J. & Brown, J.S. (1981). Mental models of physical mechanisms and their acquisition. In J.R. Anderson (ed.), Cognitive Skills and their Acquistion. Hillsdale, NJ: Erlbaum.

Gentner, D. & Stevens, A.(1983). Mental Models. Hillsdale, NJ: Erlbaum.

Holland, J.H., Holyoak, K.J., Nisbett, R.E., Thagard, P.R. (1986). Induction: Processes of Inference, Learning and Discovery. Cambridge, MA: MIT Press.

Johnson-Laird, P. (1983). Mental Models. Cambridge, MA: Harvard University Press.

Kelly, G. (1995). Principles of Personal Construct Psychology. Norton.

Kieras, D. & Bovair, S. (1984). The role of mental models in learning to operate a device. Cognitive Science, 8, 255-273.

Schumacher, R. & Czerwinski, M. (1992). Mental models and the acquisition of expert knowledge. In R. Hoffman (ed.), The psychology of expertise. New York: Springer-Verlag.

White, B. & Frederiksen, J. (1985). Qualitative models and intelligent learning environments. In R. Lawler & M. Yazdani (Eds.), Artifical Intelligence and Education. Norwood, NJ: Ablex.

Metacognition

Metacognition is the process of thinking about thinking. Flavell (1976) describes it as follows: "Metacognition refers to one's knowledge concerning one's own cognitive processes or anything related to them, e.g., the learning-relevant properties of information or data. For example, I am engaging in metacognition if I notice that I am having more trouble learning A than B; if it strikes me that I should double check C before accepting it as fact." (p 232).

Flavell argued that metacognition explains why children of different ages deal with learning tasks in different ways, i.e., they have developed new strategies for thinking. Research studies (see Duell, 1986) seem to confirm this conclusion; as children get older they demonstrate more awareness of their thinking processes.

Metacognition has to do with the active monitoring and regulation of cognitive processes. It represents the "executive control" system that many cognitive theorists have included in their theories (e.g., Miller, Newell & Simon, Schoenfeld). Metacognitive processes are central to planning, problem-solving, evaluation and many aspects of language learning.

Metacognition is relevant to work on cognitive styles and learning strategies in so far as the individual has some awareness of their thinking or learning processes. The work of Piaget is also relevant to research on metacognition since it deals with the development of cognition in children.

For further discussion of Metacognition, see http://coe.sdsu.edu/eet/Articles/metacognition/start.htm or http://www.gse.buffalo.edu/fas/shuell/cep564/Metacog.htm
References:
Brown, A. (1978). Knowing when, where and how to remember: A problem of metacognition. In R. Glaser (Ed.), Advances in Instructional Psychology. Hillsdale, NJ<: Erlbaum Assoc.
Duell, O.K. (1986). Metacognitive skills. In G. Phye & T. Andre (Eds.), Cognitive Classroom Learning. Orlando, FL<: Academic Press.
Flavell, J. (1976). Metacognitive aspects of problem-solving. In L.
Resnick (Ed.), The Nature of Intelligence. Hillsdale, NJ: Erlbaum Assoc.
Forrest-Pressly, D., MacKinnon, G., & Waller, T. (1985). Metacognition, Cognition, and Human Performance. Orlando: Academic Press.
Garner, R. (1987). Metacognition and Reading Comprehension. Norwood, NJ: Ablex.

Motivation

Motivation is a piviotal concept in most theories of learning. It is closely related to arousal, attention, anxiety, and feedback/reinforcement. For example, a person needs to be motivated enough to pay attention while learning; anxiety can decrease our motivation to learn. Receiving a reward or feedback for an action usually increases the likelihood that the action will be repreated. Weiner (1990) points out that behavioral theories tended to focus on extrinsic motivation (i.e., rewards) while cognitive theories deal with intrinsic motivation (i.e., goals) .

In most forms of behaviorial theory, motivation was strictly a function of primary drives such as hunger, sex, sleep, or comfort. According to Hull's drive reduction theory, learning reduces drives and therefore motivation is essential to learning. The degree of the learning achieved can be manipulated by the strength of the drive and its underlying motivation. In Tolman's theory of purposive behaviorism, primary drives create internal states (i.e., wants or needs) that serve as secondary drives and represent instrinsic motivation.

In cognitive theory, motivation serves to create intentions and goal-seeking acts (see Ames & Ames<, 1989). One well-developed area of research highly relevant to learning is achievement motivation (e.g., Atkinson & Raynor, 1974; Weiner). Motivation to achieve is a function of the individual's desire for success, the expectancy of success, and the incentives provided. Studies show that in general people prefer tasks of intermediate difficulty. In addition, students with a high need to achieve, obtain better grades in courses which they perceive as highly relevant to their career goals. On the other hand, according to Rogers, all individuals have a drive to self-actualize and this motivates learning.

Malone (1981) presented a theoretical framework for instrinsic motivation in the context of designing computer games for instruction. Malone argues that instrinsic motivation is created by three qualities: challenge, fantasy, and curosity. Challenge depends upon activities that involve uncertain outcomes due to variable levels, hidden information or randomness. Fantasy should depend upon skills required for the instruction. Curiosity can be aroused when learners believe their knowledge structures are incomplete, inconsistent, or unparsimonious. According to Malone, instrinsically motivating activities provide learners with a broad range of challenge, concrete feedback, and clear-cut criteria for performance.

Keller (1983) presents an instructional design model for motivation that is based upon a number of other theories. His model suggests a design strategy that encompasses four components of motivation: arousing interest, creating relevance, developing an expectancy of success, and producing satisfaction through intrinsic/extrinsic rewards.

The Choice Theory of William Glasser is also relevant to the motivation aspects of learning (see http://www.funderstanding.com/choice-theory/choice-theory#more-1056 )
For descriptions of other theories of motivation, see http://changingminds.org/explanations/theories/a_motivation.htm
For suggestions about how to apply motivation to teaching, see http://www.vanderbilt.edu/cft/resources/teaching_resources/interactions/motivating.htm
References:
Ames<, C. & Ames, R. (1989). Research in Motivation in Education, Vol 3. San Diego<: Academic Press.
Atkinson, J. & Raynor, O. (1974). Motivation and Achievement. Washington<: Winston.
Keller, J. (1983). Motivational design of instruction. In C. Riegeluth (ed.), Instructional Design Theories and Models. Hillsdale, NJ<: Erlbaum.
Malone, T. (1981). Towards a theory of instrinsically motivating instruction. Cognitive Science, 4, 333-369.
McClelland, D. (1985). Human Motivation. Glenview, IL<: Scott, Foresman.
Weiner, B. (1990). History of motivational research in education. Journal of Educational Psychology, 82(4), 616-622.

Learning Concepts (Part I)

Anxiety

Anxiety can be an inhibiting factor in learning and therefore has received considerable attention. It is closely related to arousal, attention and motivation as well as the entire topic of emotions (Clark & Fiske, 1982; Mandler, 1984). Anxiety is usually triggered by a situation that involves a decision or judgement; tests and exams are common precursors of anxiety in educational settings.

A distinction is made between state anxiety, increased arousal due to environmental factors, and trait anxiety, an individual's characteristic way of reacting to arousal. The level of anxiety displayed by a person is a mutual function of both types of anxiety. Trait anxiety is an aspect of personality and social behavior; for example, it correlates with self-esteem and defensiveness.

Anxiety has been shown to impair performance in a wide range of cognitive functions including attention, memory, concept formation and problem solving (e.g., Sieber et al., 1977; Spielberger, 1966). There is an interaction with task difficulty; anxiety results in poorer performance in complex tasks but may improve performance on very simple tasks. This result can be explained by Hull's drive reduction theory in so far as arousal increases the strength of responding but competing responses are activated in complex tasks. Because of its influence on performance, anxiety is highly relevant to Aptitude x Treatment Interaction (ATI) research .

Anxiety can be reduced in an instructional context by:

1) instructions that minimize stress and prepare individual

2) increased use of positive feedback during a task

3) reduced opportunities for failure in a task

References:

Clark, M.S. & Fiske, S.T. (1982). Affect and Cognition. Hillsdale, NJ: Erlbaum.

Mandler, G. (1984). Mind and Body. New York: Norton.

Sieber, J., O'Neil, H.F., & Tobias. S. (1977). Anxiety, Learning and Instruction. Hillsdale, NJ: Erlbaum.

Spielberger, C. (1966). Anxiety and Behavior. New York: Academic Press. 

Arousal

The concept of arousal has been a major aspect of many learning theories and is closely related to other important concepts such as anxiety, attention, and motivation.

One of the most important findings with respect to arousal is the so-called Yerkes-Dodson law which predicts a U-shaped function between arousal (motivation) and performance. Across a broad range of experimental settings, it has been shown that both low and high levels of arousal produce minimum performance whereas a moderate level of arousal results in maximum performance in a task. This suggests that too little or too much stimulation tends to be ignored by individuals.

Berlyne (1960) attempted to explain the relationship between arousal and curiosity based upon Hull's drive reduction theory . According to Berlyne, there is an optimal level of arousal for an individual at a given time. If the level of arousal drops below the optimal level, the organism will seek stimulation (i.e., exploratory behavior). Berlyne argued that curiosity was a consequence of "conceptual conflict" that could be caused by: doubt, perplexity, contradiction, incongruity, or irrelevance.

Eysenck (1982) examines the relationship between attention and arousal. He concludes that there are two types of arousal: a passive and general system that can raise or lower the overall level of attention, and a specific, compensatory system that allows attention to be focused on certain task or environmental stimuli. Mandler (1984) argues that arousal is the key element in triggering emotional behavior.

References:

Berlyne, D. (1960). Conflict, Arousal, and Curiosity. New York: McGraw-Hill.

Eysenck, M. (1982). Attention and Arousal. NY: Springer-Verlag.

Mandler, G. (1984). Mind and Body. NY: Norton. 

Attention

Attention is a major topic of study in psychology and is closely related to the subject of consciousness which was the principal focus of the early psychologists such as Wilhelm Wundt and William James.

In 1958, Broadbent proposed his filter theory which specified that we could only attend to one input at a time. The theory suggested that stimuli can be filtered based upon physical attributes, prior to full processing by the perceptual system. Filter theory proposed that attention was a limited capacity channel that determined the serial processing of the perceptual system.

Filter theory did not allow for the influence of long-term memory or meaning of the stimulus. However, studies showed that semantic characteristics of the stimulus did affect attention. Theories proposed by Deutsch & Deutsch (1963) and Norman (1968) suggested that all inputs are analyzed but only pertinent stimuli were attended to. Neisser (1967) outlined a two-process theory that made attention (and hence consciousness) a matter of degree. According to Neisser's theory, both properties of the stimuli as well as semantic factors, play a role in attention. Neisser argues for a constructive view of cognition in which perception is shaped by existing knowledge and hence attention is influenced by experience.

Kahneman (1973) introduced a model of attention that introduces the idea of deliberate allocation. The model suggests that in addition to unconscious processes, attention can be consciously focused (such as when someone mentions our name). The model also introduces the idea of attention as a skill that can be improved (i.e., as a learning strategy). In his Conditions of Learning theory , Gagne suggests that gaining the attention of the student is the first step in successful instruction.

Eysenck (1982) examines the relationship between attention and arousal. He concludes that there are two types of arousal: a passive and general system that can raise or lower the overall level of attention, and a specific, compensatory system that allows attention to be focused on certain task or environmental stimuli.

References:

Broadbent, D. (1958). Perception and Communication. London: Pergamon Press.

Deutsch, J. & Deutsch, D. (1963). Attention: Some theoretical considerations. Psychological Review, 70, 80-90.

Eysenck, M. (1982). Attention and Arousal. NY: Springer-Verlag.

Kahneman, D. (1973). Attention and Effort. Englewood Cliffs, NJ: Prentice-Hall.

Neisser, U. (1967). Cognitive Psychology. New York: Appleton-Century-Croft.

Norman, D. (1967). Memory and Attention. New York: Wiley.

Trabasso, T. & Bower, G. (1968). Attention in Learning. New York: Wiley 

Attitudes

Attitudes are usually defined as a disposition or tendency to respond positively or negatively towards a certain thing (idea, object, person, situation). They encompass, or are closely related to, our opinions and beliefs and are based upon our experiences. Since attitudes often relate in some way to interaction with others, they represent an important link between cognitive and social psychology. As far as instruction is concerned, a great deal of learning involves acquiring or changing attitudes. Attitude change is especially relevant to management and sales training .

Hovland, Janis, & Kelly (1953) provided one of the first major theories of attitude change, developed in the framework of Hull's learning theory , and oriented towards the effects of persuasive communication. According to the Hovland et al theory, changes in opinions can result in attitude change depending upon the presence or absence of rewards. The learning of new attitudes is no different in nature than any other verbal or motor skill, except that opinions relate to a single proposition whereas other skills involve a series of propositions. The acceptance of a new opinion (and hence attitude formation) is dependent upon the incentives that are offered in the communication.

Heider (1958) developed a balance theory of attitude change that was influenced by Gestalt principles . In Heider's theory, when beliefs are unbalanced, stress is created and there is pressure to change attitudes. The two main factors affecting balance are the sentiment (e.g., liking, approving, admiring) and unity (e.g., similarity, proximity, membership) qualities of beliefs. Balance exists if the sentiment or unity between beliefs about events or people are equally positive or negative; imbalance occurs when they are dissimilar in nature.

Abelson (1968) and others developed theories of cognitive consistency. Cognitive consistency suggests that people will try and maintain consistency among their beliefs and make changes (i.e., accept or reject ideas) when this doesn't occur. For example, if a college student who wants to live in a coed dormitory and also wants to get good grades is presented with the fact that students who live in coed dorms get poor grades, the student will either reject this proposition or change his attitudes about coed dorms or good grades.

Festinger's theory of cognitive dissonance is one of the best known and most researched frameworks pertaining to attitude change. According to this theory, attitude change is caused by conflict among beliefs. A number of factors determine the strength of the dissonance and hence how much effort is required to change attitudes. By manipulating these factors, attitude change can be facilitated or inhibited.

Attitudes are one of the five major categories of learning outcomes in Gagne's theoretical framework.

References:

Abelson, R. (1968). Theories of Cognitive Consistency Theory. Chicago: Rand McNally.

Heider, F. (1959). The Psychology of Interpersonal Relations. New York: Wiley.

Hovland, C., Janis, I., & Kelley, H. (1953). Communication and Persuasion. New Haven, CT: Yale University Press.

Triandis, H. (1971). Attitude and Attitude Change. New York: Wiley.

Cognitive/Learning Styles

Cognitive styles refer to the preferred way an individual processes information. Unlike individual differences in abilities (e.g., Gardner, Guilford, Sternberg) which describe peak performance, styles describe a person's typical mode of thinking, remembering or problem solving. Furthermore, styles are usually considered to be bipolar dimensions whereas abilities are unipolar (ranging from zero to a maximum value). Having more of an ability is usually considered beneficial while having a particular cognitive style simply denotes a tendency to behave in a certain manner. Cognitive style is a usually described as a personality dimension which influences attitudes, values, and social interaction.

A number of cognitive styles have been identified and studied over the years. Field independence versus field dependence is probably the most well known style. It refers to a tendency to approach the environment in an analytical, as opposed to global, fashion. At a perceptual level, field independent personalities are able to distinguish figures as discrete from their backgrounds compared to field dependent individuals who experience events in an undifferentiated way. In addition, field dependent individuals have a greater social orientation relative to field independent personalities. Studies have identified a number connections between this cognitive style and learning (see Messick, 1978). For example, field independent individuals are likely to learn more effectively under conditions of instrinstic motivation (e.g., self-study) and are influenced less by social reinforcement.

Other cognitive styles that have been identified include:

scanning - differences in the extent and intensity of attention resulting in variations in the vividness of experience and the span of awareness

leveling versus sharpening - individual variations in remembering that pertain to the distinctiveness of memories and the tendency to merge similar events

reflection versus impulsivity - individual consistencies in the speed and adequacy with which alternative hypotheses are formed and responses made

conceptual differentiation - differences in the tendency to categorize perceived similarities among stimuli in terms of separate concepts or dimensions

Learning styles specifically deal with characteristic styles of learning. Kolb (1984) proposes a theory of experiential learning that involves four principal stages: concrete experiences (CE), reflective observation (RO), abstract conceptualization (AC), and active experimentation (AE). The CE/AC and AE/RO dimensions are polar opposities as far as learning styles are concerned and Kolb postulates four types of learners (divergers, assimilators, convergers, and accommodators) depending upon their position on these two dimensions. For example, an accommodater prefers concrete experiences and active experimentation (AE, CE).

Pask has described a learning style called serialist versus holist. Serialists prefer to learn in a sequential fashion, whereas holists prefer to learn in a hierarchial manner (i.e., top-down).

Theoretically, cognitive and learning styles could be used to predict what kind of instructional strategies or methods would be most effective for a given individual and learning task. Research to date on this problem has not identified many robust relationships (see Cronbach & Snow). However, the 4MAT framework based on the work of Bernice McCarthy which suggests 4 learning modes (Analytic, Imaginative, Common Sense, and Dynamic) has been widely applied in education (see http://www.aboutlearning.com). And the learning styles framework developed by Dunn & Dunn (1999) seems to be useful in terms of creating teacher awareness of individual differences in learning. 

For more about Learning Styles, see http://www.oswego.edu/~shindler/lstyle.htm.  Application of learning styles to engineering is discussed at http://www2.ncsu.edu/unity/lockers/users/f/felder/public/Learning_Styles.html . Discussion about the relationship between learning styles and the Multiple Intelligences theory of Gardner< can be found at http://www.ldpride.net/learningstyles.MI.htm  and http://falcon.jmu.edu/~ramseyil/learningstyles.htm .

References:

Dunn, R. & Dunn, K. (1999). The Complete Guide to the Learning Strategies Inservice System. Boston: Allyn & Bacon.

Kolb, D.A. (1984). Experiential Learning. Englewood< Cliffs, NJ: Prentice-Hall.

Messick, S. (1976). Individuality in Learning. San Francisco: Jossey-Bass.

Sternberg, Robert (1997). Thinking Styles. Boston: Cambridge University Press.

Witkin, H.A. & Goodenough, D.R. (1981). Cognitive Styles: Essence and Origins. NY: International Universities Press. 

Creativity

There have been many different approaches to the study of creativity. The relationship between creativity and intelligence has been always been a central concern of psychology (Guilford<, 1950). Much effort has been devoted towards the measurement of creative potential (e.g. Guilford<, 1989; Torrance<, 1979). There have also been many attempts to increase creative behaviors (e.g., Osborn, 1953; Parnes, 1967). Taylor & Williams (1966) provides a survey of the relationship between creativity and instruction.

While there are many views about the nature of creativity (see Sternberg, 1988; Finke, Ward & Smith, 1992), there is some agreement that the creative process involves the application of past experiences or ideas in novel ways. The Creative Problem Solving (CPS) Model, based upon the work of Osborn and Parnes, suggests that the creative process involves five major steps: fact-finding, problem-finding, idea- finding, solution-finding, and acceptance-finding (VanGundy, 1987). Certain cognitive skills seem to underlie creative behavior such as: fluency, flexibility, visualization, imagination, expressiveness, and openess (resistance to closure). These skills may be personality characteristics, they may be learned, or they may be situational. There is also general acknowledgement that social processes play a major role in the recognition of creativity (Amabile, 1983).

Langley et al. (1987) have argued that creativity in the context of scientific discovery is a form of problem-solving. Specifically, they propose that finding problems and formulating them involves the same underlying cognitive processes of heuristic search and subgoal generation as any other kind of problem-solving behavior.

Other work closely related to creativity includes: originality (see Maltzman ), productive thinking (Wertheimer ), and lateral thinking (DeBono). Creativity plays a central role in management training) .

References:

Amabile, T. (1983). The Social Psychology of Creativity. New York: Springer-Verlag.

Guilford, J. P. (1950). Creativi ty. American Psychologist, 5, 444-454.

Guilford, J.P. (1986). Creative Talents: Their Nature, Uses and Development. Buffalo, NY: Bearly Ltd.

Finke, R.A., Ward, T.B., & Smith, S.M. (1992). Creative Cognition. Cambridge, MA: Bradford/MIT Press.

Langley, P., Simon, H., Bradshaw, G., & Zytkow, J. (1987). Scientific Discovery: Computational Explorations of the Creative Processes. Cambridge, MA: MIT Press.

Marks-Tarlow, T. (1995). Creativity inside out: Learning through multiple intelligences. Reading, MA: Addison-Wesley.

MODEL PEMBELAJARAN TEMATIK DAN IMPLEMENTASI

Pendahuluan

Pemerintah pada beberapa tahun lalu telah mengeluarkan kebijakan tentang otonomi daerah. Kebijakan ini antara lain memberi ruang gerak yang luas kepada lembaga pendidikan khususnya sekolah dasar dalam mengelola sumber daya yang ada, dengan cara mengalokasikan seluruh potensi dan prioritas sehingga mampu melakukan terobosan-terobosan sistem pembelajaran yang lebih inovatif dan kreatif.

 Salah satu upaya kreatif dalam melaksanakan pembelajaran yang   menggunakan kurikulum berbasis kompetensi di sekolah dasar adalah melakukan pembelajaran tematik. Pembelajaran model ini akan lebih menarik dan bermakna bagi anak karena model pembelajaran ini menyajikan tema-tema pembelajaran yang lebih aktual dan kontekstual dalam kehidupan sehari-hari. Namun demikian masih banyak pihak yang belum memahami dan mampu menerapkan model ini secara baik. Melalui tulisan ini akan diuraikan secara singkat tentang pembelajaran tematik secara konseptual dan implementasinya dalam kegiatan pembelajaran.

Arti dan Prinsip Dasar Pembelajaran Tematik

Pembelajaran tematik dapat diartikan suatu kegiatan pembelajaran dengan mengintegrasikan materi beberapa mata pelajaran dalam satu tema/topik pembahasan. Sutirjo dan Sri Istuti Mamik (2004: 6) menyatakan bahwa pembelajaran tematik merupakan satu usaha untuk mengintegrasikan pengetahuan, keterampilan, nilai, atau sikap pembelajaran, serta pemikiran yang kreatif dengan menggunakan tema. Dari pernyataan tersebut dapat ditegaskan bahwa pembelajaran tematik dilakukan dengan maksud sebagai upaya untuk memperbaiki dan meningkatkan kualitas pendidikan, terutama untuk mengimbangi padatnya materi kurikulum. Disamping itu pembelajaran tematik akan memberi peluang pembelajaran terpadu yang lebih menekankan pada partisipasi/keterlibatan siswa dalam belajar. Keterpaduan dalam pembelajaran ini dapat dilihat dari aspek proses atau waktu, aspek kurikulum, dan aspek belajar mengajar.

Dalam menerapkan dan melaksanakan pembelajaran tematik, ada beberapa prinsip dasar  yang perlu diperhatikan yaitu 1) bersifat terintegrasi dengan lingkungan, 2) bentuk belajar dirancang agar siswa menemukan tema, dan 3) efisiensi. Agar diperoleh gambaran yang lebih jelas berikut ini akan diurakan ketiga prinsip tersebut,  berikut ini.

1.      Bersifat kontekstual atau terintegrasi dengan lingkungan.

Pembelajaran yang dilakukan perlu dikemas dalam suatu format keterkaitan, maksudnya pembahasan suatu topik dikaitkan dengan kondisi yang dihadapi siswa atau ketika siswa menemukan masalah dan memecahkan masalah yang nyata dihadapi siswa dalam kehidupan sehari-hari dikaitkan dengan topik yang  dibahas.

2.      Bentuk belajar harus dirancang agar siswa bekerja secara sungguh-sungguh untuk menemukan tema pembelajaran yang riil sekaligus mengaplikasikannya. Dalam melakukan pembelajaran tematik siswa didorong untuk mampu menemukan tema-tema yang benar-benar sesuai dengan kondisi siswa, bahkan dialami siswa.

3.      Efisiensi

Pembelajaran tematik memiliki nilai efisiensi antara lain dalam segi waktu, beban materi, metode, penggunaan sumber belajar yang otentik sehingga dapat mencapai ketuntasan kompetensi secara tepat.

Ciri-ciri Pembelajaran Tematik

Pembelajaran tematik memiliki ciri-ciri atau karakteristik Sebagai berikut 1) berpusat pada siswa, 2) Memberikan pengalaman langsung kepada siswa, 3)  Pemisahan mata  pelajaran tidak begitu jelas, 4) Menyajikan konsep dari berbagai mata pelajaran dalam suatu proses pembelajaran., 5) Bersifat fleksibel, 6) Hasil pembelajaran dapat berkembang sesuai dengan minat, dan kebutuhan siswa. Agar diperoleh gambaran yang lebih jelas tentang karakteristik tersebut dapat diuraikan sebagai berikut:

1.      Berpusat pada siswa

Proses pembelajaran yang dilakukan harus menempatkan siswa sebagai pusat aktivitas dan harus mampu memperkaya pengalaman belajar. Pengalaman belajar tersebut dituangkan dalam kegiatan belajar yang menggali dan mengembangkan fenomena alam di sekitar siswa.

2.      Memberikan pengalaman langsung kepada siswa

Agar pembelajaran lebih bermakna maka siswa perlu belajar secara langsung dan mengalami sendiri. Atas dasar ini maka guru perlu menciptakan kondisi yang kondusif dan memfasilitasi tumbuhnya pengalaman yang bermakna.

3.      Pemisahan mata  pelajaran tidak begitu jelas

Mengingat  tema dikaji dari berbagai mata pelajaran dan saling keterkaitan maka  batas mata pelajaran menjadi tidak begitu jelas.

4.      Menyajikan konsep dari berbagai mata pelajaran dalam suatu proses pembelajaran.

5.      Bersifat fleksibel

Pelaksanaan pembelajaran tematik tidak  terjadwal secara ketat antar mata pelajaran.

6.      Hasil pembelajaran dapat berkembang sesuai dengan minat, dan kebutuhan siswa.

karakteristik pembelajaran terpadu/tematik sebagai berikut: 1) pembelajaran berpusat pada anak, 2) menekankan pembentukan pemahaman dan kebermaknaan, 3) belajar melalui pengalaman langsung, 4) lebih memperhatikan proses daripada hasil semata, 5) sarat dengan muatan keterkaitan.

 

Peran dan Pemilihan Tema dalam Pembelajaran Tematik

Tema dalam pembelajaran tematik memiliki peran antara lain:

1.      Siswa lebih mudah memusatkan perhatian pada satu tema atau topik tertentu.

2.      Siswa dapat mempelajari pengetahuan dan mengembangkan berbagai kompetensi mata pelajaran dalam tema yang sama.

3.      Pemahaman terhadap  materi pelajaran lebih mendalam dan berkesan

4.      Kompetensi berbahasa bisa dikembangkan lebih baik dengan mengaitkan mata pelajaran lain dan pengalaman pribadi siswa.

5.      Siswa lebih merasakan manfaat dan makna belajar karena materi disajikan dalam konteks tema yang jelas.

6.      Siswa lebih bergairah belajar karena mereka bisa berkomunikasi dalam situasi yang nyata.

7.      Guru dapat menghemat waktu karena mata pelajaran yang disajikan secara terpadu dapat dipersiapkan sekaligus dan diberikan dalam 2 atau 3 kali.

Pemilihan tema dalam pembelajaran tematik dapat berasal dari guru dan siswa. Pada umumnya guru memilih tema dasar dan siswa menentukan unit temanya.  Tema juga dapat dipilih berdasarkan pertimbangan konsensus antar siswa.

Hal-hal yang perlu diperhatikan dalam pembelajaran tematik

Ada beberapa hal yang perlu dipertimbangkan dalam pembelajaran tematik, yaitu:

1.      Pembelajaran tematik dimaksudkan agar pelaksanaan kegiatan pembelajaran lebih bermakna dan utuh.

2.      Dalam pelaksanaan pembelajaran tematik  perlu mempertimbangkan alokasi waktu untuk setiap topik, banyak sedikitnya bahan yang tersedia di lingkungan.

3.      Pilihlah tema yang terdekat dengan siswa.

4.      Lebih mengutamakan kompetensi dasar yang akan dicapai dari pada tema.

Keunggulan dan kekurangan Pembelajaran Tematik

Pelaksanaan pembelajaran tematik memiliki beberapa keuntungan dan juga kelemahan yang diperolehnya. Keuntungan yang dimaksud yaitu:

1.      Menyenangkan karena bertolak dari minat dan kebutuhan siswa

2.      Pengalaman dan kegiatan belajar relevan dengan tingkat perkembangan dan kebutuhan siswa.

3.      Hasil belajar akan bertahan lebih lama karena lebih berkesan dan bermakna.

4.      Menumbuhkan keterampilan sosial, seperti bekerja sama, toleransi, komunikasi, dan tanggap terhadap gagasan orang lain.

Pembelajaran tematik di samping memiliki beberapa keuntungan sebagaimana dipaparkan di atas, juga terdapat beberapa kekurangan yang diperolehnya. Kekurangan yang ditimbulkannya yaitu:

1.      Guru dituntut memiliki keterampilan yang tinggi 

2.      Tidak setiap guru mampu mengintegrasikan kurikulum dengan konsep-konsep yang ada dalam mata pelajaran secara tepat.

Implementasi Pembelajaran Tematik di Sekolah Dasar

Pembelajaran tematik di sekolah dasar (SD) merupakan suatu hal yang relatif baru,  sehingga dalam  implementasinya belum sebagaimana yang diharapkan. Masih banyak guru yang merasa sulit dalam melaksanakan pembelajaran tematik ini. Hal ini terjadi antara lain karena guru belum mendapat pelatihan secara intensif  tentang pembelajaran tematik ini. Disamping itu juga guru masih sulit meninggalkan  kebiasan kegiatan pembelajaran yang penyajiannya berdasarkan mata pelajaran/bidang studi.

Pelaksanaan pembelajaran tematik di sekolah dasar pada saat ini  difokuskan pada kelas-kelas bawah (kelas 1 dan 2) atau kelas yang anak-anaknya masih tergolong pada anak usia dini, walaupun sebenarnya pendekatan pembelajaran tematik ini bisa dilakukan di semua kelas sekolah dasar.

Pembelajaran tematik dilakukan dengan beberapa tahapan-tahapan seperti penyusunan perencanaan, penerapan, dan evaluasi/refleksi. tahap-tahap ini secara singkat dapat diuraikan sebagai berikut:

1.      Perencanaan

Mengingat perencanaan sangat menentukan keberhasilan suatu pembelajaran tematik, maka perencanaan yang dibuat dalam rangka pelaksanaan pembelajaran tematik harus sebaik mungkin Oleh karena itu ada beberapa langkah yang perlu dilakukan dalam merancang pembelajan tematik ini yaitu: 1) Pelajari kompetensi dasar pada kelas dan semester yang sama dari setiap mata pelajaran, 2) Pilihlah tema yang dapat mempersatukan kompetensi-kompetensi  untuk setiap kelas dan semester, 3) Buatlah ”matriks hubungan kompetensi dasar dengan tema”, 4) Buatlah pemetaan pembelajaran tematik. Pemetaan ini dapat dapat dibuat dalam bentuk matriks atau jareingan topik, 5) Susunlah silabus dan rencana pembelajaran berdasarkan matriks/jaringan topik pembelajaran tematik

2.      Penerapan pembelajaran tematik

Pada tahap ini intinya guru melaksanakan rencana pembelajaran yang telah disusun sebelumnya. Pembelajaran tematik ini akan dapat diterapkan dan dilaksanakan dengan baik perlu didukung laboratorium yang memadai. Laboratorium yang memadai  tentunya berisi berbagai sumber belajar yang dibutuhkan bagi pembelajaran di sekolah dasar. Dengan tersedianya laboratorium yang memadai tersebut maka guru ketika menyelenggarakan pembelajaran tematik akan dengan mudah memanfaatkan sumber belajar yang ada di laboratorium tersebut, baik dengan cara membawa sumber belajar ke dalam kelas maupun mengajak siswa ke ruang laboratorium yang  terpisah dari ruang kelasnya.

3.   Evaluasi Pembelajaran Tematik

 Evaluasi pembelajaran tematik difokuskan pada evaluasi proses dan hasil. Evaluasi proses diarahkan pada tingkat keterlibatan, minat dan semangat siswa dalam proses pembelajaran, sedangkan evaluasi hasil lebih diarahkan pada tingkat pemahaman dan penyikapan siswa terhadap substansi materi dan manfaatnya bagi kehidupan siswa sehari-hari. Disamping itu evaluasi juga dapat berupa kumpulan karya siswa selama kegiatan pembelajaran yang bisa ditampilkan dalam suatu paparan/pameran karya siswa.

 Instrumen yang dapat digunakan untuk mengungkap pemahaman siswa terhadap materi pelajaran dapat digunakan tes hasil belajar. dan untuk mengetahui tingkat kemampuan siswa melakukan suatu tugas dapat berupa tes perbuatan atau keterampilan dan untuk mengungkap sikap siswa terhadap materi pelajaran dapat berupa wawancara, atau dialog secara informal.

Disamping itu instrumen yang dikembangkan dalam pembelajaran tematik dapat berupa: kuis, pertanyaan lisan, ulangan harian, ulangan blok, dan tugas individu atau kelompok, dan lembar observasi.

Kesimpulan 

Berdasarkan uraian di atas dapat ditegaskan bahwa pembelajaran tematik   dimaksudkan agar pembelajaran lebih bermakna dan utuh. Pembelajaran tematik ini  memiliki peran yang sangat penting dalam meningkatkan perhatian, aktivitas belajar, dan   pemahaman siswa terhadap materi yang dipelajarinya, karena pembelajarannya lebih berpusat pada siswa, memberikan pengalaman langsung kepada siswa,   pemisahan mata  pelajaran tidak begitu jelas, menyajikan konsep dari berbagai mata pelajaran dalam suatu proses pembelajaran., bersifat fleksibel, hasil pembelajaran dapat berkembang sesuai dengan minat, dan kebutuhan siswa.

Pembelajaran tematik agar berhasil dengan baik perlu dilakukan  dengan menempuh tahapan perencanaan, penerapan dan evaluasi.

Daftar Pustaka

Sutirjo dan Sri Istuti Mamik.  (2005). Tematik: Pembelajaran Efektif dalam Kurikulum 2004. Malang: Bayumedia Publishing.