Constructivism And Its Implications For Teaching And Learning



Running Head: CLE Project Paper

CLE Project Paper

Mark Beattie

George Mason University

EDIT 732

Dr. Nada Dabbagh

May 7th 2003

Constructivism And Its Implications For Teaching And Learning.

Constructivism is a theory that asserts that learning is an activity that is individual to the learner. This theory hypothesizes that individuals will try to make sense of all information that they perceive, and that each individual will, therefore, “construct” their own meaning from that information. Driscoll (2000) explains that constructivist theory asserts that knowledge can only exist within the human mind, and that it does not have to match any real world reality. Learners will be constantly trying to derive their own personal mental model of the real world from their perceptions of that world. As they perceive each new experience, learners will continually update their own mental models to reflect the new information, and will, therefore, construct their own interpretation of reality.

Constructivism is often compared to objectivism, which is usually quoted as being the counter point or direct opposite of constructivism. Much of objectivist theory is based on the work of behaviorists such as Skinner (1954.) Objectivists believe that information itself is knowable outside the bounds of any human mind, and that any individual interpretation of knowledge can be said to be either correct or incorrect. Objectivists view individual pieces of information as symbols or currency that can be acquired by humans, and can be transferred from human to human should the correct learning conditions exist. (Jonassen, 1991.)

While much of the early work in formal instructional design derived from objectivist theory, modern academic minds have come to accept that learning environments which more closely match the needs of constructivist learning may be more effective. The perceived benefits of constructivist learning may be particularly valuable where the teaching of complex skills, such as problem solving or critical thinking skills are concerned (Tam, 2000.)

If we accept that constructivist theory is the best way to define learning, then it follows that in order to promote student learning it is necessary to create learning environments that directly expose the learner to the material being studied. For only by experiencing the world directly can the learner derive meaning from them. This gives rise to the view that constructivist learning must take place within a suitable constructivist learning environment (CLE). One of the central tenants of all constructivist learning is that it has to be an active process (Tam, 2000); therefore, any CLE must provide the opportunity for active learning.

Tam (2000) lists the following four basic characteristics of CLEs, which must be considered when implementing constructivist instructional strategies:

1) Knowledge will be shared between teachers and students.

2) Teachers and students will share authority.

3) The teacher’s role is one of a facilitator or guide.

4) Learning groups will consist of small numbers of heterogeneous students.

Explicit in these characteristic requirements for CLEs is an understanding that the role of the teacher in any CLE will not be the same as that of a teacher in an objectivist-learning environment (OLE). In a CLE, the teacher must become a guide or facilitator who helps point the student in the direction of the learning materials. Whereas, by contrast in an OLE, the teacher would have been seen as a source of learning materials and as a distributor of learning materials.

The teacher’s role in a CLE must include spending time developing or preparing the CLE for the students to use. This can require detailed preparation to ensure that the students are exposed to relevant authentic tasks. For example, this may encompass preparing collaborative environments to expose students to multiple perspectives. It can also include the design of situated learning cases that match the student’s zone of proximal development, or the design of problems for problem based learning environments where the students have no experience of the subject matter under study. (Oliver, 2000).

While there is no single constructivist theory of instruction (Driscoll, 2000), there are many pedagogical models that are compatible with the ideas of constructivism. These models will all align with some, though not necessarily all of the goals that are associated with CLEs. Honebein (1996) summarizes what he describes as the seven pedagogical goals of CLEs as:

1) To provide experience with the knowledge construction process (students determine how they will learn).

2) To provide experience in and appreciation for multiple perspectives (evaluation of alternative solutions).

3) To embed learning in realistic contexts (authentic tasks).

4) To encourage ownership and a voice in the learning process (student centered learning).

5) To embed learning in social experience (collaboration).

6) To encourage the use of multiple modes of representation, (video, audio text, etc.)

7) To encourage awareness of the knowledge construction process (reflection, metacognition).

Dabbagh & Bannan-Ritland (under contract – In Progress), indicate that the constructivist pedagogical models that meet these goals include:

• Situated learning or anchored instruction,

• Problem based learning (PBL).

• Cognitive Apprenticeships,

• Cognitive Flexible Hypertexts (CFH),

• Communities of Practice or Learning Communities,

• Computer Supported Intentional Learning Environments (CSILES).

• Microworlds Simulations and Virtual Worlds.

Constructivist pedagogical models are sometimes classified into two separately identifiable groups: 1) Those that are derived from social constructivism, which grew out of the works of the Swiss philosopher and psychologist, Piaget, and therefore emphasize the need for collaboration and social interaction. 2) Those that derive from Cognitive constructivism, which grew out of the work of the Russian psychologist, Vygotsky, and therefore emphasize the importance of authentic meaningful tasks (Tam 2000.)

Learning environments that build on the benefits of collaboration and social negation, such as problem based learning or communities of practice, are sometimes considered to be social constructivist in nature. Those that concentrate on individualist learning, such as microworlds or CFH, are sometimes considered to be based in cognitive constructivism. However, all constructivist pedagogies in general terms have many characteristics in common, and all environments that are derived from the application of these pedagogies can still all be considered to be constructivist-learning environments. (Tam 2000).

As constructivist learning is an individual experience, so too constructivist assessment must be individualized if it is to measure the learning achieved by a particular student. CLEs will, therefore, require new forms of assessment that are integrated within the CLE, and that reflect the achievements of the student. Although CLEs are becoming more widely accepted as a strong basis for learning, constructivist based assessment techniques are sometimes criticized by those who are accustomed to objectivist style certifications, as being inefficient tools for comparing the relative competency levels of students. (Tam, 2000).

As computers make excellent communication tools, constructivist pedagogical models map well into computer environments, and in particular online computer environments. As a result CLEs can be particularly useful as the foundation for both in class as well as distance based educational programs. One good example of a computer supported CLE would be a microworld, (Jonassen, 1996).

Microworlds.

Jonassen (2000), reports that the term “microworld” was first used by Seymour Papert in his 1980 paper, “Mindstorms, Children, Computers, and Powerful Ideas.” Though closely related to simulations and virtual worlds, microworlds can be distinguished from these by the fact that microworlds are designed to enable experimental investigation into a specific subject area. Unlike simulations or virtual worlds, microworlds allow students to set up environmental variables and then check the effect of these settings on a simplified simulation of a real world situation. Additionally, the graphics detail or realism found in a microworld will usually be represented in a simpler way than that presented by a simulation or virtual reality system. Generally speaking, therefore, microworlds are used to investigate constrained problems within specific subject areas that mimic problems that exist in the real world. (Dabbagh & Bannan-Ritland, under contract – In Progress), (Jonassen, 2000.)

Unlike simulations or virtual worlds, microworlds do not specifically have to be computer based. They can include such simple things as a child’s chemistry set or play tea set (Jonassen, 1996, p239). However, computers can provide an ideal platform for the development of microworlds. In large part this is because of the ability of a computer to visually generate graphical representations of real world situations and to apply programmed rules of logic on these environments in a way that will mimic the real world while reflecting parameters input by the learner. Most microworlds are in general considered to be computer supported CLEs. Jonassen (2000), Dabbagh & Bannan-Ritland, (under contract – In Progress.) Due to the use of computer graphics and animation, Jonassen, (2000) considers computer based microworlds to be inherently motivational environments.

Microworlds require that the learner progress from simpler to more complex skills and they, therefore, place great emphasis on the prior abilities of students. Microworlds are generally real world simulations that allow users to experimant and test out hypotheses that will allow them to develop the skills necessary for the solving of real world problems. Most usually, microworlds will allow the learner to investigate problems that would be difficult to experimant with in the real world due to time constraints or physical restrictions. Hooper, Hannifin, Hannifin, Kini & Rober (1996) define a microworld as representing the simplest case of a domain that is still recognizable by an expert in the domain. Though a microworld may become more complex as the learner progresses and becomes more proficient, it will always be the learner that structures the operation of the microworld to suit his or her own learning needs.

Microworlds meet the basic tenant of constructivist environments in that they are experimental, and that learners learn by doing, and as such they must be considered active learning experiences. While the tasks that the learners are involved in are simulated, they can be thought of as authentic as they mimic real world problems. Microworlds do not generally require collaboration or social negotiation, but instead focus on exposing the learner to authentic tasks, and allowing the learner to experiment with their mental models by providing the learner with a way to test the accuracy of their own mental models. Microworlds can, therefore, be described as being based on cognitive constructivism rather than social constructivism.

In their article “Computers as Mindtools for Engaging Learners in Critical Thinking” Jonassen, Carr & Yueh (1998) describe computer based microworlds as being dynamic modeling tools that can act as “exploratory learning environments” or what they term “discovery spaces.” Perhaps the most important feature of Microworlds is that they involve active learning. Learners learn by doing when they input parameters to the microworld, come up a with a hypothesis on the effect of the parameter values they have set, and then test their hypothesis using the programmed logic of the microworld to simulate reality. (Jonassen, 2000).

Hooper, Hannifin, Hannifin, Rieber & Kini (1996) describe computer based microworlds that utilized the turtle graphics based programming language Logo. They indicate that while research has found no clear link between the use of microworlds and improvements in students critical thinking skills, this may be purely as a result of difficulties in measuring the holistic effects of any constructivist-learning environment. However, Jonassen (2000) reports that work by Thompson and Wang in 1998 found that skills learned in microworlds did indeed transfer effectively to the real world.

Jonassen (2000) emphasizes the usefulness of the hypothesis-testing feature of microworlds in the development of critical thinking in learners. Jonassen agrees that many of the problem solving tasks being investigated will be specific to an individual microworld. However, he indicates a firm belief that that improvements in a learner’s problem solving abilities in the constrained problem area investigated in a microworld may well transfer to more general critical thinking skills that can be applied in other areas.

Dabbagh & Bannan-Ritland, (Under contract – In Progress.) list the instructional characteristics of microworlds as including:

• The promotion of exploratory or experiential learning.

• They allow a hypothesis to be tested.

• They model parts or features of the real world.

• They compress time and space to aid speedy hypothesis testing.

• The model is considered by experts to accurately reflect the real world.

• They are aimed at learners with specific prior knowledge.

• They support the incremental acquisition of complex skills.

• Learners can directly control social or environmental parameters.

• Include both deductive and inductive reasoning.

• Allow users to learn form errors.

• Encourage incidental learning.

• Promote hypothesis testing and higher order thinking.

• Provide a learning path from known to unknown.

• Provide simple ideas that are visually grounded in reality.

• Provide informative feedback.

While microworlds do not necessarily incorporate the social constructivist characteristics of collaboration and social negotiation, this is because they are derived more directly from the ideas of cognitive constructivism. As described above, clearly the characteristics of microworlds align sufficiently well with those of constructivism for microworlds to be considered constructivist learning environments.

References

Dabbagh, N. & Bannan-Ritland, B. (under contract - in progress). Chapter 5: Pedagogical models for online learning. Online learning: Concepts, strategies, and application. Upper Saddle River, NJ: Merrill Education, Prentice Hall.

Driscoll, Marcy. (2000).  Psychology of Learning for Instruction.  Boston: Allyn & Bacon.

Hannafin, M.J., Hannafin, K.M., Hooper, S.R., Rieber, L.P., & Kini, A.S. (1996). Research on and research with emerging technologies. In D.H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 378-402). New York, NY: Simon & Shchuster Macmillan.

Honebein, P.C. (1996). Seven goals for the design of constructivist learning environments. in Constructivist Learning Environments: Case Studies in Instructional Design. Brent G. Wilson (Ed.). Englewood Cliffs: Educational Technology Publications: 11-24.

Jonassen, D. (1991). Objectivism vs constructivism: Do we need a new philosophical paradigm?, Educational Technology, Research and Development, 39(3), 5-13.

Jonassen, D. H. (1994). Toward a Constructivist Design Model. Educational Technology, April, 34-37.

Jonassen, D.H. (1996). Computers in the classroom: Mindtools for critical thinking. Columbus, OH: Merrill/Prentice-Hall..

Jonassen, D.H. (2000). “Microworld learning environments: immersion in action”, In Computers in the classroom –mindtools for critical thinking, Englewood Cliffs, NJ, Merrill, Prentice Hall. (237-253).

Jonassen, D.H., Carr, C., & Yueh, H.P. (1998, March). Computers as Mindtools for engaging learners in critical thinking. Tech Trends, 43 (2), 24-32.

Oliver, K.M. (2000), Methods for developing constructivism learning on the web,” Educational Technology, 40 (6)

Skinner, B.F., (1953), Science and human behavior, New York: The Macmillan Company.

Tam, M. (2000). Constructivism, Instructional Design, and Technology: Implications for Transforming Distance Learning. Educational Technology and Society, 3 (2).

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