Materials and Technology: References

Materials and Technology: References

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Borg, W. R., & Gall, M. D. (1989). Educational research. New York: Longman.

Brophy, J. (Ed.). (1991). Advances in research on teaching (Vol. 2). Greenwich, CT: JAI Press.

Callister, T. A, Jr., & Dunne, F. (1992). The computer as doorstop: Technology as disempowerment. Phi Delta Kappan, 74(4), 324-326.

Clark, R. E. (1992). Six definitions of media in search of theory. In D. P. Ely & B. B. Minor (Eds.), Educational media and technology yearbook (Vol. 18, pp. 65-76). Englewood, CO: Libraries Unlimited.

Cuban, L. (1986). Teachers and machines: The classroom use of technology since 1920. New York: Teachers College Press.

Flagg, B. (1990). Formative evaluation for educational technologies. Hillsdale, NJ: Lawrence Erlbaum.

Hativa, N. (1988). Computer-based drill and practice in arithmetic: Widening the gap between high- and low-achieving students. American Educational Research Journal, 25(3), 366-397.

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Ralph, J., & Dwyer, M. C. (1988). Making the case: Evidence of program effectiveness in schools and classrooms. Washington, D.C.: U.S. Department of Education, Office of Educational Research and Improvement and RMC Research.

Thorkildsen, R., & Lowry, W. (1990). The effects of a videodisk program on mathematics self-concept: Research report. Logan, UT: Utah State University, Center for Persons with Disabilities.

Woodward, J. (1994). Effects of curriculum discourse style on eighth graders' recall and problem solving in earth science. Elementary School Journal, 94(3), 299-314.

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Copyright © 1998 by American Association for the Advancement of Science

http://www.project2061.org/publications/bfr/online/material/refer.htm

According to Seels and Richey (1994), theory consists of the concepts, constructs, principles, and propositions that contribute to the body of knowledge. The power of a theory derives from its organized structure of related propositions that describe, explain, predict and control the observed phenomena (Gall, Borg, & Gall, 1996).

It is human nature to make sense out of the world. Through observations of the world by senses, people tend to impose orders by finding out what is going on. Theory is developed to describe what is observed, and explain why and how the observed phenomenon occurs. The intention of the theory development sometimes is beyond its descriptive and explanatory functions. The ultimate purposes of theory-building sometimes lie in the predication and the control of the phenomenon. This tendency of theory building is described very clearly by Babbie (1998):

" Observing and tryng to interpret what we observe is a native human activity. It's the foundation of our survival. In everyday life, however, we are often casual and semiconscious in both our observations and our interpretations, so that we make mistakes in both. Scientists make observation and interpretation conscious, deliberate acts." (p. 3)

It is the conscious and deliberate observations and intepretations that set up the foundations of the theory. Theory, thus, is a systematic explanation for the observations, which includes a set of constructs that are linked with other with a certain relationship (Gall, Borg, & Borg, 1996).. The constructs are the made-up concepts representing ideas or entities targeted to be explained, e.g. personality, intelligence, or achievement.

There are two approaches for theory development:

1. Grounded theory approach: it derives constructs and laws directly from the immediate data that one has collected.
2. Hypothesis Testing: this is to start by formulating a hypothesis based on a thoery, and then submit it to a test by collecting empirical data. Three major steps:

• The formulation of a hypothesis: a proposition about the relationship between two or more theoretical constructs
• The deduction of observable consequences of the hypothesis: it guides the research method design determining what variables to be controlled, how to control variables, and what to observe, e.g.samples and measurements of variables
• The testing of hypothesis by making observation, i.e. collecting and analyzing research data

A knowledge building process cannot be complete without embracing both approches. The establishment of theories requires both our sensory percetpion and rational reflection. Creation and verification of theories both contribute to the process of knowledge building of a field.

How do instructional-design theories differ from learning theories?
It is the major function that a theory is proposed to serve that Reigeluth (1999) used to distinguish learning theory and instructional-design theory. Learning theories, concerning more with describing and explaining how learning occurs, highlight the descriptive and explanatory function of a theory, i.e. what it is and how it is. On the other hand, instructional-design theories, focusing on prescribing how to better facilitate learning, emphasize the prescriptive and controlling characteristics of a theory, i.e. what it should be and how it should be.

Based on the description of several literature mentioned in Reigeluth's (1999) article on what is instructional-design theories, a comparison between instructional-design theories and learning theories is listed as follows:

Instructional-design theories	Learning theories
Science of Artificial: a systematic contrivance imposed to control learning	Natuarl Science: a scientific inquiry to understanding of learning
Prescriptive: a means to increase chances of attaining the instructional goals	Descriptive: a means to describe and to explain why learning occurs
To provide guidance to practitioners about what methods to use to attain different instructional goals	To proivde deeper understanding of the effects of a certainmethod by knowing why it works

References:

Gall, M. D., Borg, W. R., & Gall, J. P. (1996). Educational research: An introduction ( Sixth ed.). White Plains, NY: Longman.

Reigeluth, C. M. (1999). What is instructional-design theory and how is it changing? In C. M. Reigeluth (Ed.), Instructional design theories and models (Vol. II: A New paradigm of instructional theory, pp. 5-29). Mahwah, NJ: Lawrence Erlbaum Associates.

Seels, B.B. & Richey, R.C. (1994). Instructional technology: the definition and domains of the field. Washington, DC: Association for Educational Communications and Technology.

http://www.personal.psu.edu/users/w/x/wxh139/Theory_1.htm

Learning theories are concerned with what learning is and how learning occurs.

In the late 1950s, learning psychology underwent a scientific revolution on paradigm shift from behaviorism, which focuses the observable behavioral changes, to cognitive psychology, which is more interested in what learners know and how it is acquired, i.e. mental structure and mental process.

According to Jonassen (1991), such psychological evolution resulted in little effect on IST (Instructional Systems Technology) theory and practice. Jonassen argued that there were needs of a philosophical paradigm shift to re-conceptualize the learners' mental state. In the 1990s, the IST field started the growing interest in constructivism, an epistemological belief about what "knowing" is and how one "come to know." Contructivists believe in individual interpretations of the reality, i.e. the knower and the known are interactive and inseparable.

Behaviorists proposed that psychological theories should exclusively address the physical stimuli that an organism encounters and its observable behavioral response to them. They focus on the scientific study of behavior, i.e. "to discover the lawful relationship between environment events and behaviors" (Gredler, 1997). Such scientific inquiry implies an objective philosophical belief that that there is a single reality, and objective knowledge can be acquired.

On the other hand, the focus on the mental structures and processes in cognitive psychology does not explicitly indicate its philosophical position about whether there is an objective reality. The internal representation can echo the external reality, which asserts a position of objectivism that the mind can stand separate and independent from the body. Thus, knowledge can be transferred from the outside of the mind into the inside of the mind. However, internal representation can also be regarded as a subjective construction of integrating incoming information and the existing knowledge structures, which entails a position of constructivism that there is no single objective reality and that knowledge cannot exist independently from the knower.

Constructivism is claimed to be the synthesis of empiricism, which sees knowledge as the product of sensory perception, and rationalism which sees it as the product of rational reflection (Driscoll, 2000). Thus, knowledge is no longer the correspondence or reflection of an objective ontological reality; it is an adaptive and active construction of subjective experience and interpretation of the world. This constructivist view of knowledge implies that the learners should be provided with an environment that encourages learners to interact with the objects in the environment and thus to actively participate and engage in thinking and reflection.

Based on a broad distinction in the assumptions about what is learning, what is the learning mechanism, three major broad views of learning are identified.

	What is learning?	What is the mechanism that the learning process operates on?
	Learning is behavioral change.	The association between the stimuli and response via the manipulation of reinforcement
	Learning is the growth of conceptual understanding. It focuses on the internal representation of some kind of external reality.	Information process and knowledge representation within the learner, i.e. cognitive processes take place within the heads of individuals
	Learning is the effective participation in practices of inquiry and discourse. It focuses on construction of meanings and use of concepts and skills.	A process of enculturation, emphasizing the socio-cultural setting and the activities of the people within the setting

References:

Drisoll, M. P.( 2000). Psychology of learning for instruction. 2nd. Needham Heights, MA: Allyn and Bacon.

Gredler, M. E. (1997). Learning and instruction: Theory into practice. Upper River, NJ: Prentice Hall.

Jonassen, D. H. (1991). Objectivism vs. constructivism: Do we need a new paradigm? Educational Technology Research and Development, 39 (3), 5-14.

http://www.personal.psu.edu/users/w/x/wxh139/Theory_1.htm

What is an instructional-design theory?

Gagné and Dick (1983) described the characteristics of instructional theories in terms their functions and foundations.

• Functions: Instructional theories are prescriptive in nature. They relate specific instructional events to learning processes and learning outcomes, identifies instructional conditions that optimize learning outcomes, and provides a rational description of causal relationships between procedures used to teach and their behavioral consequences in enhanced human performance.
• Foundations: Instructional theories are derived from learning research and theory.

Reigeluth (1999) used the term 'instructional-design theory', which is defined as a theory that "offers explicit guidance on how to between help people learn and develop. The kinds of learning and development may include cognitive, emotional, social, physical and spiritual."

Reigeluth (1999) explain instructional-design theory from several aspects:

Its characteristics
Reigeluth (1999) described four major characteristics of instructional-design theory:

1. It is design-oriented: it focuses on means to attain given goals for learning or development à it provides direct guidance on how to achieve their goals. Design-oriented theories are very different from descriptive theories, which describes the effects that occur when a given class of causal events occurs, or which describes the sequence in which certain events occur
2. It identifies methods of instruction, i.e. ways to support and facilitate learning, as well as the situations in which those methods should and should not be used.
3. In all instructional-design theories, the methods of instruction can be broken into more detailed component methods, which provide more guidance to educators about different components and different ways to perform the methods; different kinds of methods; offering criteria that methods should meet.
4. The methods are probabilistic rather than deterministic: focusing on control instead of description and explanation à In other words, instructional-design theories intend to control variables in the learning environment to achieve certain results

Its components
There should be two major components in instructional-design theory:

1. Methods of instruction: methods for facilitating human learning and development
2. Instructional situation: indications as to when and when not to use those methods and descriptions of the conditions under which the instruction will take place

• The nature of what is to be learned
• The nature of the learner (prior knowledge, learning strategies, motivation)
• The nature of learning environment
• The nature of the instructional development constraints

Its focus on value for decision making
Both values and empirics are important for making decisions about how to teach as well as what to teach. All the instructional-design-theories state explicitly what values guide their selection of goals and what values guide their selection of methods.

Its importance
It provides guidelines for practitioners. It transforms descriptive theory into methods of how to work, developing techniques and determine implementation details that are applicable to most conditions

Reigeluth provides (1999) three questions to examine what an instructional-design theory can offer:

1. What methods best facilitate learning and human development under different situations?
2. What learning-tool features best allow an array of alternative methods to be made available to learners and allow them to make decisions (with varying degrees of guidance) about both content (what to learn) and methods while the instruction is in progress?
3. What system features best allow an instructional design team (that preferable includes all stakeholders) to design quality learning tools?

What instructional-design theories are discussed?

The instructional theories discussed in this knowledge base are classified as follows based on the different theoretical foundations about learning.

References:

Reigeluth, C. M. (1999). (Ed.), Instructional-design theories and models: An new paradigm of instructional theory, Volume II.. Mahwah, NJ: Lawrence Erlbaum Associates.

http://www.personal.psu.edu/users/w/x/wxh139/Theory_1.htm

Human beings tend to impose rationales to explain the phenomena that surround them. Some employ the mechanistic scientific view, and some take a systems view. The former is an analytical, reductionist and linear-causal paradigm, in which the observed phenomenon is broken into parts, and the parts are isolated from the whole and examined separately. Systems theory opposes the reduction of systems. It criticizes the mechanistic view neglects the relationship of the components with the larger systems. It emphasizes the totality, complexity, and dynamics of the system. However, it also argues that, despite of the complexity and diversity of the world, models, principles and laws can be generalized across various systems, their components, and the relationships between them. In other words, corresponding abstractions and conceptual models can be applied to different phenomena.

Systems theory comes from the general systems theory proposed by the biologist Ludwig von Bertalanffy. He recognized a compelling need for a unified and disciplined inquiry in understanding and dealing with increasing complexities, complexities that are beyond the competence of any single discipline. The theory pursues scientific exploration, understanding, and controlling of systems.

The systems view investigates the components of the phenomena, the interaction between the components, and the relation of components to their larger environment. The underlying assumption of Bertalanffy's theory is that there are universal principles of organization across different fields. Boulding states that the objectives of GST aim to point out similarities in the theoretical constructions of different disciplines, and to develop something like a spectrum of theories -- a system of systems that may perform a gestalt in theoretical constructions.

Systems theory was furthered by Ross Ashby's concept of Cybernetics. Cybernetics means steersman in Greek. Wiener introduced this idea as the science of communication and control in the animal and the machine. The idea was first described to illustrate the transmission of information through communication channels and the concept of feedback. It evolved to emphasize the constructive power of the observer, who controls/constructs models of the systems with which the observer interacts.

Characteristics of systems theory
The major purpose of systems theory is to develop unifying principles by the integration of various sciences, natural and social. With focus on the structures and functions of the system, the system can be viewed from different perspectives:

• Open system: a system keeps evolving and its properties keep emerging through its interaction with environment
• Holistic view: systems theory focuses on the arrangement of and relations between the parts that connect them into a whole. The mutual interaction of the parts makes the whole bigger than the parts themselves.
• Goal-directedness: systems are goal oriented and engage in feedback with the environment in order to meet the goals. Also, every part of the system is interdependent with each other working together toward the goals.
• Self-organizing: productive dynamic systems are self-organizing. It implies the adaptive ability of the systems to the changes in the environment. Using a metaphor of social interaction, Pask (1975, 1984) described the self-organizing process as "a conversation between two or more participants, whose purpose is to arrive at "an agreement over an understanding."

What are the assumptions about systems view?
Reigeluth, Bathany, and Olson (1993) described the following assumption in terms of design:

• "A systems view suggests that essential quality of a part resides in its relationship to the whole."
• "The system and its parts should be designed from the perspective of the whole system and in view of its embeddedness in its environment."
• "The systems design notion requires both coordination and integration. We need to design all parts operating at a specific system level of the organization interactively and simultaneously. This requires coordination. The requirement of designing for the interdependency across all system levels invites integration."

The importance to Instructional Systems Design: Theory into Practice
From a systems view, the instructional system is an open system that interacts with the educational system and is an interdisciplinary subject matter that incorporates different fields, such as psychology, communication, education, and computer science. Also, the systems approach applied to instructional design brings forth an extensive analysis of components that engage in carrying out the instructional goal as well as the input-output-feedback transformational process that interacts between the components (Banathy, 1991).

From a systems view, examination of the processes and components of the instructional system is not adequate to fully understand the system itself. Thus, it shifts the attention from the design components, such as instructional strategies, media selection and material development, to implementation. How the system adopts the instructional innovation or the change becomes the major issue. The systems theory provides a comprehensive perspective for designers to foresee the resistance to change and enables designers to understand the complexity of educational systems.

Banathy (1996) suggests that besides paying attention to this functional structure of the system, we should also look at the system from two other perspectives. One is to examine the instructional system as a synthetic organism in the context of its community and the larger society. The other is to explore what the instructional system does through time. The suggestions, in fact, echoes the ways that Reigeluth, Bathany, and Olson (1993) proposed to adopt systems design:

"We should explore educational change and renewal from the larger vistas of the evolving society, and envision a new design. We should view the system we design from the perspectives of the overall societal context. Approaching education from this perspective, we shall enlarge our horizon and develop the largest possible picture of education within the largest possible context."

Impacts to Educational Systems
Systemic change recognizes the interrelationships and interdependencies among the parts of the educational system, with the consequence that desired changes in one part of the system are accompanied by changes in other parts that are necessary to support those desired changes and recognizes the interrelationships and interdependencies between the educational systems and its community, including parents, employers, social service agencies, religious organizations, and much more, with the consequence that all those stakeholders are given active ownership over the change effort (Jenlink et al 1996.)

According to Banathy (1987), there are four subsystems in any educational enterprise:

1. The learning experience subsystem: the cognitive information processing of the learner
2. The instructional subsystem: the production of the environment or opportunities for learners to learn by the instructional designers and teachers
3. The administrative subsystem: decision making of resource allocation by the administrators based on the instructional needs and governance input
4. The governance subsystem: the production of policies which provide directions and resources for the educational enterprise in order to meet their needs by "owners"

Based on the interpretations of such analysis, the instructional system is part of educational system. Reigeluth (1996) gave more of his thought on the comparison of ESD and ISD.

What is the relationship between ESD (Educational Systems Development) and ISD (Instructional Systems Development)?

1. First, let's examine their definitions. Based on the definitions, ISD is within ESD.
   ESD is the "knowledge base about the complete educational enterprise" (Reigeluth, 1995).
   ISD is the "knowledge base about the instructional subsystem" (Reigeluth, 1995)
2. In what way do these two knowledge bases relate to each other?

• The function of ESD aims to create a new paradigm of education. It is not concerned with making changes within the existing paradigm. It encompasses all subsystems of the educational enterprise. It entails radical changes.
• ESD needs ISD: ISD, as a more fully developed knowledge base, can contributes insights to developing ESD; design skills and systems thinking of ISD are needed in EDS.
• ISD needs ESD: ISD needs changes in the larger organizations, such as administrative and governance systems) to support their success; The new paradigm in ESD will create a greater needs for ISD expertise; ESD will initiate ISD's search for new directions in instructional theory.

What are the common characteristics between ESD and ISD?

1. Both use systems thinking to examine and explain the mutually interdependent relationships:

• Between the new system and its suprasystem
• Between the new system and its peer system
• Among the many functions and components that compose the new system

2. Both use design theory to inform the process, which consists of the fundamental elements, such as analysis, synthesis, evaluation and basic activities of deign, development and implementation
3. Both are not linear: both needs simultaneity and recursion during the process.

Why a New Paradigm in ESD?

1. Changes in Society: the major paradigm shifts in society is from Agrarian to Industrial to Information. Such shifts bring in changes in all of the society's subsystems including family, business and education.
2. The need for a new paradigm of education is based on massive changes in both the conditions and educational needs of an information society.
3. Selection vs. Learning: In terms of the educational function, the industrial age is to use standardization strategy to separate the laborers from the managers, and to build up conformity and compliance in bureaucratic organization. On the contrary, the education and training in the information age should be designed to foster active thinkers, who can take initiatives and think critically in team-based organization.
4. The systemic changes in the family requires school to become a caring environment due to the systemic changed in the family

References:
Banathy, B. H. (1968). Instructional systems. Palo Alto, CA: Fearon Publishers.

Banathy, B. H. (1987). Instructional systems design. In R. M. Gagne (Ed.), Instructional technology: Foundations. HIllsdale, NJ: Lawrence Erlbaum.

Banathy, B. H. (1991). Systems design of education. Englewood Cliffs, NJ: Educational Technology Publication.

Banathy, B. H. (1996). Systems inquiry and its application in education. In D. H. Jonassen (Ed), Handbook of research for educational communications and technology. New York: Macmillan.

Jenlink, P.M., Reigeluth, C.M., Carr, AA & Nelson, L.M. (Jan-Feb. 1996). An Expedition for Change: Facilitating the Systemic Change Process in School Districts. Tech Trends. Vol 41, No. 1, page 21-30.

Bertalanffy, L. V (1968). General systems theory. New York: Braziller.

Reigeluth, C. , Banathy, B. H. & Olson, J. R. (1993). Comprehensive systems design: A new educational technology. Berlin: Springer-Verlag.

http://www.personal.psu.edu/users/w/x/wxh139/Theory_1.htm

Ellsworth (2000) commented that Rogers' Diffusion of Innovations (1995) is an excellent general practitioner's guide. Rogers' framework provide "a standard classification scheme for describing the perceived attributes on innovations in universal terms" (Rogers, 1995). Research in educational change has applied and explored Rogers' model to different contexts.

Rogers' model studies diffusion from a change communication framework to examine the effects of all the components involved in the communication process on the rate of adoption. Rogers (1996) identified the differences both in people and in the innovation. The model provides the guidelines for the change agents about what attributes that they can build into the innovation to facilitate its acceptance by the intended adopter. Rogers also identified the sequence of change agent roles:

1. To develop a need for change.
2. To establish an information-exchange relationship.
3. To diagnose problems.
4. To create an intent in the client to change.
5. To translate an intent to action.
6. To stabilize adoption and prevent discontinuance.
7. To achieve a terminal relationship

How is diffusion defined in Rogers' Model?
Diffusion is a process by which an innovation is communicated through certain channels over time among the members of a social system.

The definition indicates that:

• The adopters can be an individual, groups, or organization at different levels of social system.
• The target is innovation
• The process is communication
• The means is communication channels
• The context of innovation is a social system
• It is a change over time.

How can we categorize different types of adopter?

• Innovators (risk takers)
• Early adopters (hedgers)
• Early majority (waiters)
• Late majority (skeptics)
• Late adopters (slowpokes)

What are the factors affecting the rate of adoption of an innovation?
According to Rogers (1995), there are five major factors affecting the rate of adoption:

1. Perceived Attributes of Innovation
   An innovation is a idea, practice or object that is perceived as new by an individual or other unit of adoption. How the adopter perceived characteristics of the innovation has impacts on the process of adoption.

• Relative advantage: the degree to which an innovation is perceived as better than the idea it supersedes. The underlying principle is that the greater the perceived relative advantage of an innovation, the more raid its rate of adoption
• Compatibility: the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopters
• Complexity: the degree to which an innovation is perceived as difficult to understand and use
• Trialability: the degree to which an innovation may be experimented with on a limited basis. If an innovation is trialable, it results in less uncertainty for adoption
• Observability: the degree to which the results of an innovation are visible to others. The easier it is for individuals to see the results of an innovation, the more likely they are to adopt.

2. Type of Innovation-Decision

• Optional: an individual flexibility
• Collective: a balance between maximum efficiency and freedom
• Authority: it yields the high rate of adoption, but produces high resistance.

3. Communication Channels

• Mass Media
• Interpersonal

4. Nature of the Social System
   A social system is defined as a set of interrelated units that are engaged in joint problem solving to accomplish a common goal. The members or units of a social system may be individuals, informal groups, organizations, and or subsystems. All members cooperate at least to the extent of seeking to solve a common problem in order to reach a mutual goal: Sharing of a common objective binds the system together. The social structure affects the innovation's diffusion in several ways:

• Social structure and communication structure: patterned arrangements of the units in a system
• System norms: norms are established behavior patterns for the members of a social system
• Roles of opinion leaders and change agents: opinion leadership is the degree to which an individual is able to influence other individual's attitudes or overt behavior informally in a desired way with relative frequency
• Types of innovation decisions: optional innovation-decision, collective innovation -decision, authority innovation-decision; contingent innovation-decision
• The consequences of innovation: desirable vs. undesirable, direct vs. indirect, anticipated vs. unanticipated

5. Extent of Change Agent's Promotion

Siegel (1999) listed four additional factors of Rogers' theory:

6. Pro-innovation Bias: three assumptions about innovation:

• It should be diffused and adopted by all members of a social system
• It should be diffused more rapidly
• It should be neither reinvented nor rejected

7. Reinvention: people use innovations in ways not originally intended
8. Individual characteristics of adopters

What is innovation-decision process for individual or other decision making unit?

• Knowledge: it occurs when an individual is exposed to the innovation's existence and gains some understanding of how it functions
• Persuasion: it occurs when an individual forms a favorable or unfavorable attitude toward the innovation
• Decision: it occurs when an individual engages in activities that lead to a choice to adopt or reject the innovation
• Implementation: it occurs when an individual puts an innovation into use
• Confirmation: it occurs when an individual seeks reinforcement of an innovation decision or reverse the previous decision due to the conflict

What are the contributions of Rogers' Model?
Ellsworth (2000) pointed out the most critical benefits of Rogers' model is the innovation attributes. He said:

"Practitioners are likely to find this perspective of the greatest use if they are engaged in the actual development of the innovation or if they are deciding whether (or how) to adapt the innovation to meet local requirements…Rogers' framework can be useful in determining how it is to be presented to its intended adopters." (p.40)

Rogers' model has identified the critical components in the change system and their characteristics. The model is relatively systematic because the consequence of the change is confined with a predetermined "innovation", a predetermined goal. The interrelationship and dynamic exchange between the components in the change system is not expected to contribute to the continuous shaping of the vision, but to be controlled to adopt a desirable idea, object, or program.

References:
Ellsworth, J. B. (2000). Surviving changes: A survey of Educational change models. Syracuse, NY: ERIC Clearinghouse.

Rogers, E. (1995). Diffusion of Innovations. (4th ed.). New York, NY: The Free Press.

http://www.personal.psu.edu/users/w/x/wxh139/Theory_1.htm

Michael Fullan has focused his work on educational change. His model focused on "the human participants taking part in the change process" (Ellsworth, 2001). Ellsworth (2001) commented that Fullan and Stiegelbauer's (1991) The New Meaning of Educational Change presents guidelines for resisting, coping, or leading change efforts from perspective ranging from the student to the national government. Different from Rogers, whose work focused more on the characteristics of the innovation and the adopters, Fullan (1982, 1991) focuses on the roles and strategies of various types of change agents.
Ellsworth (2001) pointed out that the issues that Fullan's model helps the change agent to deal with include:

• What are the implications of change for people or organizations promoting or opposing it at particular levels?
• What can different stakeholders to do promote change that addresses their needs and priorities?

According to Rogers (1996), a change agent is an individual who influences clients' innovation-decisions in a direction desirable by a change agency. Rogers' Diffusion of Innovation seems to have a clear cut between the change agent and its client system. On the contrary, Fullan views every stakeholder in the educational change as a change agent. Fullan and Stiegerlbauer (1991) have given a promise for the change agent that "there is enormous potential for true, meaningful change simply in building coalition with other change agents, both within one's own group and across all group." (Ellsworth, 2001)
Fullan (1982, 1991) proposed that there are four broad phases in the change process: initiation, implementation, continuation, and outcome.

Image from Sarah Fitzpatrick's site

Initiation
The factors that affecting the initiation phases include:

1. Existence and quality of innovations
2. Access to innovations
3. Advocacy from central administration
4. Teacher advocacy
5. External change agents

Implementation
Fullan and Stigelbauer (1991) identified three areas of the major factors affecting implementation: characteristics of change, local characteristics and external factors (government and other agencies). They identified different stakeholders in local, and federal and governmental levels. They also identified characterizations of change to each stakeholder and the issues that each stakeholder should consider before committing a change effort or rejecting it.
Characteristics of Change Local Factors External Factors

Characteristics of Change	Local Factors	External Factors
Need of change Clarity about goals and needs Complexity: the extent of change required to those responsible for implementation Quality and practicality of the program	The school district Board of community Principal Teacher	Government and other agencies

Continuation
Continuation is a decision about institutionalization of an innovation based on the reaction to the change, which may be negative or positive. Continuation depends on whether or not:

1. The change gets embedded/built into the structure (through policy/budget/timetable)
2. The change has generated a critical mass of administrators or teachers who are skilled and committed to
3. The change has established procedures for continuing assistance

Outcome
Attention to the following perspectives on the change process may support the achievement of a positive or successful change outcome:

1. Active initiation & participation: change does not end in recognizing or initial context with the innovation, but starts with the contact and evolves along with the continuous interaction with it and the environmental changes that it brings forth
2. Pressure, support and negotiation
3. Changes in skills, thinking, and committed actions
4. Overriding problem of ownership

What can we learn from the complexity of change process?
Fullan (1993) provide eight basic lessons about thinking about change:

1. You can't mandate what matters: complexity of change in skills, thinking and committed actions in educational enterprise. Fullan commented that "effective change agents neither embrace nor ignore mandates. They use them as catalysts to reexamine what they are doing." (p.24)
2. Change is a journey not a blueprint: changes entails uncertainty with positive and negative forces of change.
3. Problems are our friends: problems are the route to deeper change and deeper satisfaction; conflict is essential to any successful change effort.
4. Vision and strategic planning come later: vision comes later because the process of merging personal and shared visions take time. This different from Rogers'conception of innovation, as an idea, practice or object, that drives the change process. Rogers' model is similar to what Fullan's critics on Beckhard and Pritchard's (1992) vision-driven, which emphasizing the creating and setting of the vision, communicating the vision, building commitment to the vision, and organizing people and what they do so that they are aligned to the vision. People learn about the innovation through their interactions with the innovation and others in the context of innovation. Deep ownership comes through the learning that arise form full engagement in solving problems.
5. Individualism and collectivism must have equal power: Stacy's concept of "dynamic system" helps clarify Fullan's ideas of innovation collaboration:

"The dynamic systems perspective leads to a view of culture as emergent. What a group comes to share in the way of culture and philosophy emerges from individual personal beliefs through a learning process that builds up over years." (Stacy, 1992, p. 145)

6.      Neither centralization nor decentralization works: the center and local units need each other. Successful changes require a dynamic two-way relationship of pressure, support and continuous negotiation.

7.      Connection with the wider environment is critical for success: change should recognize a broader context, to which change asserts its constant action.

8.      Every person is a change agent: " It is only by individuals taking action to alter their own environments that there is any change for deep change."

Fullan (1993) provided suggestions of elements that successful change requires:

• The ability to work with polar opposites: imposition of change vs. self-learning; planning vs. uncertainty; problems vs. creative resolution; vision vs. fixed direction; individual vs. groups; centralizing vs. decentralizing; personal change vs. system change
• Dynamic interdependency of state accountability and local autonomy
• Combination of individuals and societal agencies
• Internal connection within oneself and within one's organization and external connections to others and to the environment

Fullan (1999) pointed out the importance of the recognition that the educational change process is complex. To deal with such complexity is not to control the change, but to guide it. Fullan provides eight new lessons about guiding change.

1. Moral purpose is complex and problematic
2. Theories of education and theories of change need each other
3. Conflict and diversity are our friends
4. Understanding the meaning of operating on the edge of chaos
5. Emotional intelligence is anxiety provoking and anxiety containing
6. Collaborative cultures are anxiety provoking and anxiety containing
7. Attack incoherence connectedness and knowledge creation are critical
8. There is no single solution. Craft your own theories and actions by being a critical consumer.

References:
Ellsworth, J. B. (2000). Surviving changes: A survey of Educational change models. Syracuse, NY: ERIC Clearinghouse.
Fullan, M. (1982). The meaning of educational change. New York: Teachaers College Press.
Fullan, M. G. (1993). The complexity of the change process. In Change forces: Probing the depth of educational reform, pp. 19-41. Falme Press.
Fullan, M. G. (1999). Change Forces: The sequel. Philadelphia, PA: Falmer Press.
Fullan, M., & Stiegelbauer, S. (1991). The new meaning of educational change. 2nd ed. New York: Teachers College Press.

Ely (1990) referred conditions of changes to the factors in the environment that affects the implementation in the change process. When the implementation plan to launch out innovation is carefully crafted to satisfy all the perceived attributes that facilitate the rate of adoption, what else can make the adoption easier or impede the adoption? This is exactly the question that Ely's Conditions of Changes intend to answer.

Ely (1999) listed eight conditions that should exist or be created in the environment where in the innovation is implemented to facilitate its adoption:

1. Dissatisfaction with the status quo: the precondition for people to accept a change is that they perceive a needs to change the environment. Perception of such needs usually is revealed in people's dissatisfaction of the existing methods, products, or programs. Understanding of the cause of the dissatisfaction and identifying who has dissatisfaction can help the change agent to communicate the innovation to the adopters in a more effective way. Ellisworth (2001) said that understanding sources and the levels of dissatisfaction can help the change agent to position the innovation to be more compatible with their 'felt needs' (in Rogers' term).
2. Sufficient knowledge and skills: In order to make the implementation succeed, "the people who will ultimately implement any innovation must possess sufficient knowledge and skills to do the job." (Ely, 1995). It is especially evident when the innovation involves in use of a certain tool or a technique. Without enough training to use the tool or technique, the innovation will die out soon.
3. Availability of resources: A good recipe itself does not guarantee the tasty results of cooking. There must be right ingredients and right cooking utensils available for the cook to use. In the same logic, an innovation without resources, such as money, tools and materials, to support its implementation, will not be successful.
4. Availability of time: The adoption of the innovation takes time. As it is put by Ely, "the implementers must have time to learn, adapt, integrate, and reflect on what they are doing." Their 'confirmation' of the acceptance of the innovation does not necessarily bring forth the change. It needs time for the people to understand the innovation and develop the abilities to adapt the innovation.
5. Reward or incentives: People need to be encouraged in their performance of innovation or use of the innovation. Extrinsic or intrinsic rewards can add some value of the innovation, and thus, promote its implementation.
6. Participation: Participants in the implementation should be encouraged to involve in decision-making. With the opportunities to communicate their ideas and opinions, the participants can have sense of the ownership of the innovation. Moreover, the communication among all parties can help monitor the progress of the innovation.
7. Commitment: Since the implementation take a great deal of endeavors and time, the people who are involved in the implementation need to make commitment to their efforts and time. There must be "firm and visible evidence that there is endorsement and continuing support for implementation" (Ely, 1995).
8. Leadership: Unless to say, the leaders' expectations and commitment have a great impacts on the process of implementation. Leadership also include the availability of affective support thorough the process.

References:

Ely, D. P. (1990). Conditions that facilitate the implementation of educational technology innovations. Journal of Research on Computing in Education, 23 (2), 298-305.

Ely, D. P. (1999). New perspectives on the implementation of educational technology innovation.

What is instructional technology? Whenever I introduced myself as an instructional systems major to someone I just met, they always asked me what this major was about. If I used the term "instructional technology" to explain what the instructional systems is, they seemed to come to an understanding of what I study for my major. They immediately related the instructional technology to the web-based instruction, educational CD-ROMs, and computers. We need to understand that the use of the machine is only one aspect of the technology. Solomon (2000) pointed out that "alternative perspectives in our field assume a broader interpretation of technology as the systematic application of all sources of organized knowledge." Based on this viewpoint, technology consists the products, the artifacts such as machines and tools, as well as the processes, the ways of doing things such as strategies and techniques.

It is from this view of a broader interpretation that Seels and Richey (1994) defined the field of instructional technology, i.e. "the theory and practice of design, development, utilization, management and evaluation of processes and resources for learning." Their definition reflects the evolution of instructional technology from a movement to a field and a profession and the contributions this field has made to theory and practice.

Different terms have been used to represent the field. Schrock (1995) used the term instructional development as a broader context for her description of the history of the field; Reiser (2001) used the term instructional design and technology to define the field. To Shrock (1995), instructional development is "a self-correcting, systems approach that seeks to apply scientifically derived principles to the planning, design, creation, implementation, and evaluation of effective and efficient instruction"; To Reiser (2001), "the field of instructional design and technology encompasses the analysis of learning and performance problems, and the design, development, implementation, evaluation and management of instructional and non-instructional processes and resources intended to improve learning and performance in a variety of settings, particularly educational institutions and the workplace." Both terms encompass the same broader scope of the field as the term instructional technology.

The following descriptions of the historical development of the field of instructional technology incorporated Reiser's and Shrock's thoughts.

Before 1920's	Instruction was interpreted in the metaphor of exercise, in which the mind was thought to consist of faculties in need of exercise The advent of scientific investigation into human and animal learning Edward Thorndike's influence of laws of learning, his advocacy of social engineering, his advocacy of educational measurements. It led to establish education as a science
1920's	Bobbitt: the goals for schooling could be derived from an objective analysis of those skills necessary for successful living· The design of instruction was the connection between the desirable outcomes and the planning of the instructional experience that could facilitate their acquisition. The emergence of the concepts of objectives, individualized instruction and mastery learning
1930's	Tyler's Eight Year Study: refining the procedures for writing instructional objectives; recognizing the cyclical nature of evaluation within the process of creating instruction designed to produced specific outcomes, i.e. the recognition of the formative evaluation process
1940's	World War II: the creation and distribution of the mediated learning materials A large number of psychologists and educators were called on to conduct research and develop training materials for the military services. Development of training materials were based on their work on instructional principles derived from research and theory on instruction, learning and human behavior. Robert Gagne Leslie Briggs John Flanagen Psychologists used their knowledge of evaluation and testing to help assess the skills of trainees and select the individuals who were most likely to benefit from particular training programs à examining general intellectual, psychomotor and perceptual skills Research and development effort directed toward education. Emergence of the role of the instructional technologist; formation of the basic instructional development team: designer, SME and producer calling for professional development of a new field
1950's	Skinner's research into operant conditioning Skinner's programmed instruction: behavioral objectives, small frames of instruction, self-pacing, active learner response to inserted question, immediate feedback. Shifting education's focus to the outcome behavior of the learner instead of the process of the behavior of the teacher. Reaffirming the feasibility of a self-pacing and mastery learning· Task analysis was first used by Air Force personnel in the early 1950s. Bloom's Taxonomy of Educational Objectives (1956)
1960's	Articulation of the components of instructional systems and the recognition of their systems properties Robert Gagné's The conditions of Learning (1965): a milestone that elaborated the analysis of learning objectives and the relationship between different classes of learning objectives and appropriate instructional designs 1965: Robert Gagné's The conditions of learning: five domains of learning outcomes: verbal information, intellectual skills, psychomotor skills, attitudes, and cognitive strategies - each of which required a different set of conditions to promote learning Gagne's nine events of instruction: "Gagne's working the area of learning hierarchies and hierarchical analysis also has had a significant impact on the instructional design field… Gagne indicted that skills within the intellectual skills domain have a hierarchical relationship to each other, so that in order to readily learn to perform a superordinate skill, one would first have to master the skill subordinate to it. This concept leads to the important notion that instruction should be designed so as to ensure that learners acquire subordinate skills before they attempt to acquire superordinate ones." (Reiser, 2001). A learning task analysis or instructional task analysis for identifying subordinate skills becomes a key feature in many instructional design models. The essential features of systems, i.e. evaluation and feedback resulted in the refinement of evaluation procedures, developing criterion-referenced measures Federal support of the instructional development: in 1957, after the launching of Sptunik by the Soviet Union, the USA government poured millions of dollars into improving math and science education. The instructional materials developed with these funds were usually written by the subject matter experts and produced without tryouts with learners. In the mid-1960, Michael Scriven (1967) pointed to the need to try out drafts of instructional materials with learners prior to the time and the materials were in their final form. Scriven indicated that this process would enable educators to evaluate the effectiveness of materials while they were still in their formative stages and, if necessary, revise them before they were produced in their final form. Scriven named this tryout and revision process "formative evaluation", and contrasted it with what he labeled "summative evaluation", the testing of instructional materials after they are in their final form. The broadening of the field of audiovisual instruction to embrace the larger concept of instructional development and technology.
1970's	A decade of consolidation: Proliferation of ID models Addition of needs assessment to the collection of steps that defined the ID process The field reached out to the literature of consulting and change agents for information to assist with its growing complexity· Graduate education programs focusing on instructional systems design grew Existing associations of professionals were redefined: DAVI became AECT; publication of Journal of instructional development
1980's	The instructional application s of microcomputers have come to dominate Performance technology movement, with its emphasis on front-end analysis, on-the-job performance, business results, and non-instructional solutions to performance problems, was beginning to have an effect on instructional design practice (Rosenberg, 1988, 1990; Rossett, 1990) The growth in the utilization of instructional development by business and other non-school agencies Merrill, Li and Jones (1990) discussed the need to develop new models of instructional design to accommodate the interactive capabilities of this technology à computers began to be used as tools to automate dome instructional design tasks
1990's	The influence of the performance technology movement: broadening the scope of the instructional design field to include analysis of the causes of performance problems and non-instructional solution Growing interest in constructivism. The instructional principles includes: Solve complex and realist problems Examine the problems from multiple perspectives Take ownership of the learning process Become aware of their own role in the knowledge construction process (Driscoll, 2000) How consideration of constructivist principles can enhance instructional design practices (Coleman, Perry and Schwen, 1997; Dick, 1996; Lebow, 1993; Lin et al., 1996). Use and development of electronic performance support systems (computer-based systems designed to provide workers with the help they need to perform certain job tasks, at the time they need that help, and in a form that will be most helpful) Information base Intelligent coaching and expert advisement systems Customized performance support tools that automate and greatly simplify many job tasks Rapid prototyping: this design technique has been advocated as a means of producing quality instructional materials in less time than is required when more conventional instructional design techniques are employed The rapid prototyping process involves quickly developing a prototype product in the very early stages of an instructional design project Then going through a series of rapid tryout and revision cycles until an acceptable version of the product is produced (Gustafson & Branch, 1997a; Jones and Richey, 2000) Use of the Internet for distance learning The programs cannot be online replicas of the instruction delivered in classrooms; instead such programs must be carefully designed in light of the instructional features that can, and cannot, be incorporated into Internet-based courses Knowledge Management§ Rossett (1999): knowledge management involves identifying, documenting, and disseminating explicit and tactic knowledge within an organization in order to improve the performance of that organization. Current-day technologies such as database programs, groupware, and intranets allow organizations to "manage" (i.e. collect, filter, and disseminate) such knowledge and expertise in ways that were not previously possible. Rosenberg (2001): designing training programs vs. creating knowledge management systems Rossett and Donello (1999): instructional designers and other training professionals not only will be responsible for improving human performance, but also will be responsible for locating and improving access to useful organizational knowledge. Reiser (2001) the growing interest in knowledge management is likely to change and perhaps expand the types of tasks instructional designers are expected to undertake.

References:

Reiser, R. A. (2001). A history of instructional design and technology: Part II: A history of instructional design. Educational Technology, Research and Development, 49 (2), 57-67.

Seels, B. B., & Richey, R. C. (1994). Instructional technology: The definition and domains of the field. Washington, D. C.: Association of Education Communications and Technology.

Shrock, S. A. (1995). A brief history of instructional development. In G. J. Anglin (Ed.), Instructional technology: Past present and future (Second ed., pp. 11-18). Englewood, CO: Libraries Unlimited Inc.

Solomon, D. (2000). Toward a post-modern agenda in instruction technology. Educational Technology, Research and Development, 48 (4), 5-20.

ISD (Instructional Systems Design) model is an organized procedure that includes steps of analyzing, designing, developing, implementing and evaluating instruction to improve the quality and effectiveness of instruction and to enhance learning.

What are systems characteristics of ISD?

• Goal-directed: ISD guides the preparation of instruction to accomplish specific goals and objective
• Interdependence of each step in the process: ISD emphasizes the congruency among the objectives, instruction, and evaluation
• An closed system: ISD mainly focuses on the system of instruction, which is "the intentional arrangement of experiences, leading to learners acquiring particular capabilities" (Smith& Ragan, 1999)

Why Models?
Gustafson (1991) explained the models serve a variety of purposes, such as theory-building and testing, description, prediction, and explanation; the ISD models are used for three primary functions in the ID practice:

• Communication device
• Planning Guides for management activities
• Prescriptive algorithms for decision making

Andrews and Goodson (1980) defined a model as "an abstraction and simplification of a defined referent system or process, presumably having some noticeable fidelity of the referent system or process." Based on this definition, theories can use models to represent their assumptions, ideas and propositions, but models are lesser than theories.

Gustafson's (1991) taxonomy of ID models
Gustafson (1991) proposed three categories of ID models based on different focuses:

• Classroom focus: the goal is to do better job of instruction within the constraints of the situation, in which a teacher, students, a curriculum and facility already exist. The emphasis is on selecting and adapting existing materials and instructional strategies. Examples: The Kemp Model (1985)
• Product focus: The goal is production of instructional products. The development of the product, and the product's objectives may have been given. Examples: The Leshi, Pollockk, and Reigeluth Model (1990)
• Systems focus: The goal is to develop instructional output, which may include material, equipment, a management plan or an instructor's training package. The focus demands extensive analysis of the use environment, the characteristics of the task, and whether or not development should even take place. It is a problem solving approach requiring data collection to determine the precise nature of the problem. Examples: The Dick and Carey's Model (1990), The Diamond's Model (1989)

Schiffman's (1995) five views of instructional systems design:
Media view, embryonic systems view, narrow systems view, standard systems view and the instructional systems design view.
The standard systems view

1. The system includes major processes: conduct needs assessment, establish overall goals, conduct task analysis, specify objectives, develop assessment strategies, select media, produce materials, conduct formative evaluation and summative evaluation.

• Formative evaluation: gathering information on adequacy and using this information as a basis for further development - during the development of improvement of a program or product
• Summative evaluation: gathering information on adequacy and using this information to make decisions about utilization à after completion and for the benefit of some external audience or decision maker agency, or further possible users

2. This view seems to be most dominant in the field.
3. The comments on the standard systems view:

• It is linear. It indicates the generic procedural framework that includes the steps of analyzing, designing, developing, implementing and evaluating instruction.
• "The input-output structure and the emphasis on task analysis, objectives, and assessment of learning outcomes conjures up visions of machine gradable training." (Schiffman, 1995)
• The view is "unaware of the theoretical/research context from which they are derived from and upon which they are dependent for enlightened and insightful implementation…"(Schiffman, 1995)
• It lacks attention to the matters of diffusion and the linking the practice with relevant learning theory and research.

How should Instructional Systems Design be?
Schiffman (1995) proposed a systemic view showing ISD to be a synthesis of theory and research related to

• How humans perceive and give meaning to the stimuli in their environment
• The nature of information and how it is composed and transmitted
• The concept of systems and the interrelationships among factors promoting or deterring efficient and effective accomplishment of the desired outcomes
• The consulting and managerial skills necessary to meld point 1 through 3 into a coherent whole

The knowledge base for this systems view of ISD integrates five major categories: educational theory and research, systems analysis, diffusion, consulting/interpersonal relations and project management.

1. Educational theory and research: general educational psychology, specific theories of learning and varieties of human capability:

• Designers need to have an understanding of the principles of human physical, emotional, social, and mental growth and development.
• Without a broad-based foundation in learning theory the practice of ISD becomes narrowly focused on means (the steps in the systems model) rather than on the rightful end (learning)
• The instructional designers have to distinguish different human capabilities. This knowledge enables the designers to utilize the research on the particular conditions under which each type of human capability is more likely to be learned, and to identify objectives of instructional unit that reflect the needs of the system

2. Systems Analysis: needs assessment to collect and analyze data about problems with instructional solution or problems with other solutions.

• Data Collection and Data Analysis: What data needs to be collected? Why analysis?

	Designers must know the goals, functions, resources, constraints, chain-of-command culture of the organization
	Data must be gathered on the specific target population to determine their general characteristics, motivation, sophistication as learners, and performance levels.
	Learning environment must be studied: on-job training, formal instruction, small group interaction
	Analysis can determine whether there are any gaps between what is and what should be, and to determine the causes of the problem: instructional, motivational, or environmental
	If the solution lies in instruction, then proceed with tasks in task, content, learner analysis, testing and measurement, media selection and production, and evaluation.

• Needs Analysis:

	Determine to what extent the problem can be classified as instructional in nature
	Identify constraints, resources, and learning characteristics
	Determine goals and priorities What is the problem? Determine the gap between what it is and what it should be (the gap between the capabilities of performers and the desired performance); prioritize the needs How do we solve it? To identify the causes of the problem and propose instructional or non-instructional solutions depending on the situation
	Analysis can determine whether there are any gaps between what is and what should be, and to determine the causes of the problem: instructional, motivational, or environmental

• Task Analysis: the process of defining what to be learned

	The analysis phase involves analysis of the learner, the task, and the context. However, task analysis is essential to identify the content and the process that are required to achieve the desired learning goals.
	For instructional designers, first we have to determine an instructional need exists, and then to specify what to be learned in order to develop how to learn and how to evaluate the learning.
	The analysis of the context is much more strongly influenced by systems theory and by sociological theories
	The attention given to the analysis of the learner has grown since the learner plays a constructive role according to cognitive theory. The learner's characteristics, i.e. attitudes, motivations, attributions, and interests, are considered in the design.
	How a learning task is analyzed: Observable behaviors + mental tasks; difference between the ways of novices and various levels of experts complete mental and physical tasks; Attention is given within objectives to tapping the understanding underlying a performance

Diffusion
An understanding of the process of change, resistance to change and categories of adopters prepares the designer to work well to bring about changes in an organization.
Consulting/Interpersonal relations
It focuses on the relationship between the designers and the clients. Five phases of a consultancy (Bell and Nadler, 1979): entry, diagnosis, response, disengagement and closure.
Project Management
Knirk and Gustafson (1986) listed six stages of project management: Planning, organizing, staffing, budgeting, controlling and communicating
References:
Diamond, R. M. (1989). Designing & improving courses and curricula in higher education: A systematic approach. San Francisco, CA: Jossey-Bass.
Dick, W., & Carey, L. (1996). The systematic design of instruction. 4th ed. New York, NY: Harper Collin
Gustafson, K. L. (1991). Survey of Instructional Development Models. US Department of Education. Public Domain.
Kemp, J. E. (1985). The instructional design process. New York: Haper and Row.
Kemp, J. E., Morrison, G. R., & Ross, S. V. (1994). Design effective instruction, New York: Macmillan
Schiffman, S. S. (1995). Instructional systems design: Five views of the field. In G. J. Anglin (Ed.), Instructional technology: Past, present and future (Second ed., pp. 131-142).Englewood, CO: Libraries Unlimited Inc.
Smith, P., & Ragan, T. J. (1999). Instructional Design. 2nd ed. John, Wiley & Sons, Inc.

Rossett (1995) described needs assessment as an initial inquiry of information about situation. , Jonassen, Tessmer, and Hannum (1999) explained the purposes of needs assessment include:

1. To determine if learning is a solution to an identified need, and if so, how serious the learning need is; the result is prioritized inventory of learning goals.
2. Needs analysis is the data gathering and decision making process that instructional designers go through to determine the goals of any instructional system
3. Needs analysis identifies the present capability of prospective learners or trainees, the desired outcomes, and the discrepancies between those

When do we do needs assessment?
Rossett (1995) pointed out the importance of the needs assessment as a driving force affecting every other aspects in the instructional design system, i.e. design, development, use and evaluation.

"Needs assessments are done when the instructional technologist is trying to respond to a request for assistance. Needs assessments gather information to assist professionals in making data-driven and responsive recommendations about how to solve the problem or introduce new technology." (p. 184)

Rossett (1995) described the major information that needs assessment tends to identify:

1. Optimal Performance: What is it that the learner/performer need to know or do?
2. Actual Performance: What is it that the learner/performer actually know and do?
3. Feelings: How do the learner/performer feel about the topic, training about the topic, the topic as priority, and confidence surrounding the topics
4. Causes: Rossett incorporated the work of Bandura (1977) and Keller (1979, 1983) into a system that recognizes four kind of causes:
• Lack of skill or knowledge: Can the learner or performer do the task?
• Flawed Environment: Does the environment support the task performance? The support includes tools, forms, work space, etc.
• Improper Incentives: What are the consequences of doing the job badly or not doing at all?
• Unmotivated Employees: What is the internal state of the individuals involved, i.e. their value toward the task, and their confidence of their ability

	Lack of skill or knowledge	Flawed Environment	Improper Incentive	Unmotivated Employees
Information needed	Are the learners able to do the task?	Environmental support	Feeling, consequences of task performance	Feelings
Possible Data Sources	Records and outcomes, observations, interviews	Observations, interviews, focused groups	Observations, records, interviews, questionnaire	Interviews, questionnaires
Possible Solutions	Training, job aids	Improved tools or forms, workplace redesign, job redesign	Improved policies, better supervision, improved incentives	Training, information, coaching, better supervision

Data Collection Tools

• Observations: fining out optimal and actual performance, the environmental factors
• Interviewing: optimal knowledge, environment, incentive, and motivation
• Records and Outcomes: finding out optimal and actual performance; environmental factors from the complaints; examining policies to identify incentives
• Facilitating Groups: to assemble an organizational-wide accord on optimal; it can be used to seek other information, but we need to be careful about the honest discuss of actual performance, feeling and causes.
• Surveying through questionnaires: It is efficient to gather information from a large number of respondent as well as information about feeling, causes, solution.

The process of Needs Assessment

1. Identify Purpose Based on Initiators: According to Rossett (1995)There are three initiators:
• Performance problems: if there is a gap between ultimate and actual performance, the focus is to find out the causes.
• New stuff: Because the new technologies, systems or approaches are used, the focus will be more on the optimals, and feelings
• Mandates: There might be a performance problem; then there might be not. It can be approached as performance problem or as a new stuff.

2. Identify Sources: Where is/Who has the information that I need? Can I access such information?
3. Select Tools for getting information: What are appropriate ways to collect data? What are the questions to ask in the interviews and in the surveys? What are under observations?
4. Conduct the needs assessment in stages in order to search for the information needed:
5. Use findings to make decision: Analyze the data and identify the gaps, determine the causes of the gaps and identify the kinds of interventions to resolve the gap.

Typology of Questions (Rossett, 1995)

• Problem finding: Is there a problem? What is the nature of the problem?
• Problem selecting: Prioritize identified problem
• Knowledge/skills proving: Ask to perform the task
• Finding feelings: Questions about the feelings and attitudes about the problem
• Cause findings: Questions about the cause of the problems

Smith and Ragan (1999) categories three sides of needs assessment:

1. Discrepancy Model: this focuses on the gaps between "what is" and "what should be"
• List the goals of instructional system]
• Determine how well the identified goals are already being achieved
• Determine the gaps between what is and what should be
• Prioritize gaps according to agreed-upon criteria
• Determine which gaps are instructional needs and which are most appropriate for design and development of instruction

2. Problem-Finding, Problem Solving model: this takes a broad view in terms of performance technology. The model focuses on resolving the causes of the problem, and the non-instructional solutions are considered.
• Determine whether there really is a problem
• Determine whether the cause of the problem is related to employees' in training environments or to learners' achievement in educational environments.
• Determine whether the solution to the achievement/performance problem is learning
• Determine whether instruction for these learning goals is currently offered: if yes, carry out the discrepancy model; if no, carry out the innovation model.

3. Innovation Model: it examines changes or innovations in the educational system or organization and determines whether new learning goals should be added to the curriculum.

References:

Jonassen, D. H., Tessmer, M., & Hannum, W. H. (1999). Task analysis methods for instructional design. Mahwah, NJ: Lawrence Erlbaum Associates.

Rossett, A. (1995). Needs Assessment. In Anglin, G. J. (Ed). Instructional technology: Past, present, and future, p.183-196. Englewood, CO: Libraries Unlimited, Inc.

Smith, P. L. & Ragan, T. J. (1999). Instructional Design. 2nd. Danvers, MA: John Wiley & Sons, Inc.

Task analysis basically is a process to identify human capabilities that supports the performance of a task under analysis. Therefore, it usually involves breaking down a task performance into smaller steps, and identifying different human capabilities that support the task performance. Within the structural framework of the IT field, task analysis is one segment of instructional design process. It is also the foundation for instructional design. Jonassen, Tessmer, and Hannum (1999) stated the purposes of task analysis as follows:

• It determines what must be learned to achieve the learning goal.
• The results of task analysis can be transformed into statements of learning goals, which determine what actually gets taught or trained.
• It analyzes the learning situation for the purpose of making instructional design decisions.
• It is used as a basis to organize tasks and task components as well as to sequence them.

The shift of paradigm from behaviorism to cognitivism has changed the focus of task analysis on behaviors to the internal mental representations and processes. From the perspectives of behaviorism and cognitivism, learning is an outcome, either behavioral change as a result of shaping by a series of reinforcements or a reconstruction of knowledge representation as a result of mental process. Under these circumstances, if learning focuses on behaviors, then the target of task analysis should focus on the desired behaviors. Job task analysis, procedural analysis and functional job analysis (Jonassen, Tessmer, & Hannum, 1999) seem to serve the purpose. If learning focuses on transmission of "knowledge" as mental representation, then the target of task analysis should focus on the required "knowledge" entailed in the task. Methods, such as learning hierarchy, information processing, the methods that Jonassen, Tessmer, and Hannum (1999) classify as cognitive task analysis methods, meet the ends.

Chipman, Schrragen, and Shalin (2000) classified task analysis into two major categories, traditional task analysis, and cognitive task analysis, when they gave an overview of each chapter in their edited book Cognitive Task Analysis. Traditional task analysis refers to a breakdown of observable task performance into a series of overt observable behaviors that support the performance; cognitive analysis is "the extension of traditional task analysis techniques to yield information about the knowledge, thought processes, and goal structures that underlie observable task performance." (Chipman, Schrragen, & Shalin, 2000). The distinction mainly lies in overt physical actions and covert cognitive process. The development of cognitive task analysis was initiated because of the evolution from industrial age to information age, which was explained by Reigeluth (1999) as changes in instruction's supersystems that have impacts on the paradigm of education and training. The needs for standardization and efficiency gave more weight to the mechanistic analysis of the job performance; the demands for customization and effectiveness call for understanding of complex thinking and of process of problem-solving underlying the task performance. In fact, a lot of cognitive task analysis methods arise from analyses of human-computer interaction, which tackle the mental activities distributing and interacting between human and machines in decision-making, critical diagnostic and control tasks.

Jonassen, Tessmer, and Hannum (1999) described task analysis as a breakdown of performance into detailed levels of specificity", and as a front-end analysis, which consists of description of mastery performance and criteria, breakdown of job tasks into steps, and the consideration of the potential worth of solving performance problems. They also classified types of task analysis:

1. Job/performance analysis: focusing on the behaviors engaged in by the performer

• It was evolved from the industrial revolution, which focused on time-motion study techniques to reduce jobs to their simplest activities so that they could be learned quicker and performed more reliable

2. Leaning analysis: focusing on the cognitive activities required to efficiently learn

• The revolution in learning psychology in the 1960s focused the attention of designers on the way learners were processing information as they performed tasks
• Techniques such as learning hierarchy analysis and information processing and path analysis were developed as part of this movement

3. Cognitive task analysis: focusing on the performances and their associated knowledge states

• When learning psychology assumed a more cognitive psychological basis, methods for conducting cognitive task analysis emerged.
• The growth of cognitive task analysis methods was fueled by military efforts in designing intelligent tutoring system

4. Content and subject matter analysis: examining the concepts and relationships of the subject matter

• Through the 1950s and 1960s, subject matter analysis evolved as the dominant curriculum planning tool in education
• Analysis of the structure of subject matter became the focus of instruction

5. Activity-based method: examining human activity and understanding in context

• Anthropological methods have been applied to analyzing the learning process, ushering in situated and everyday conceptions of the human activity.
• These activity analysis approaches analyze how people perform in natural, everyday settings. They attempt to document how humans act and the social and contextual values that affect that activity.

Such classifications recognize the differences in the functional purposes of task analysis and the types of human knowledge and capabilities to be analyzed. For example, learning hierarchical analysis, decomposing human cognitive skills into the rules and concepts in a hierarchical structure, could be used to identify topics that need to be taught and the sequence of teaching those topics. Activity theory, exploring the interaction between the individual in the society and the environment in terms of tools, rules and division of labors, could help identify what types of support need to be provided in the learning environment.

How do we describe tasks? Scholars developed different taxonomies of learning to help classify the tasks in order to identify the mental behavior, physical performance and affective state required by the task. There are three general domains: cognitive domain, i.e. knowledge and abilities requiring memory, thinking, and reasoning processes; affective domain, i.e. attitudes, dispositions, and emotions states; psychomotor domain, i.e. motor skills and perceptual processes.

Bloom's Taxonomy of Cognitive Domain

Knowledge	Recall previous learned information: specific, universals, and abstraction
Comprehension	Grasp the understanding of precious learned information
Analysis	Break down informational materials into their component parts to develop divergent conclusions by identifying motives or causes, making inferences, and/or finding evidence to support generalizations
Synthesis	Creatively or divergently apply prior knowledge and skills to produce a new or original whole
Evaluation	Judge the value of material based on personal values/opinions, resulting in an end product, with a given purpose, without real right or wrong answers.

Robert Gagné's five learned capabilities

Intellectual Skills	Mental operations that permit individuals to respond to conceptualizations of the environment Discrimination Concrete concept/Defined concept Rule using Problem solving
Cognitive Strategy	An internal process by which the learner controls his/her own ways of thinking and learning
Verbal Information	Retrieve stored information
Attitude	An internal state that affects an individual choice of action
Motor Skills	Capability to perform a sequence of physical movement

Ausubel's rote vs. meaningful learning

Ausubel (1968) described learning in terms of the relationship between learned materials and prior knowledge in the cognitive structure.

Rote Learning	Meaningful Learning
"learned materials are discrete and relative isolated entities which are only related to cognitive structure in an arbitrary, verbatim fashion, not permitting the establishment of significant relationships"	learning "take place if the learning task can be related in a nonarbitrary, substantive fashion to what the learner already knows, and if the learning adopts a corresponding learning set to do so"

Anderson's two types of knowledge

Anderson (1983) proposed two long-term memory stores: a declarative and a procedural memory. The knowledge in the declarative memory, i.e. facts and goals, is represented in terms of chunks. At the symbolic level, chunks are structured as a semantic network. On the other hand, the knowledge in the procedural memory is represented as production rules in forms of condition-action pairs, in which the flow of control passes from one production to another when the actions of one production create the conditions needed for another production to take place.

Declarative Knowledge	Procedural Knowledge
Knowledge about what it is	Knowledge about how to do things

References:

Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

Ausubel, D. P. (1968). Educational psychology: a cogntive view. New York: Holt, Rinehart and Winston.

Jonassen, D. H., Tessmer, M., & Hannum, W. H. (1999). Task analysis methods for instructional design.

In J. M. Schraggen, S. F. Chipman, & V. L. Shalin (2000), (Eds). Cognitive Task Analysis, p.p 365-383.Mahwah, Nj: Lawrence Erlbaum Association.

With the emergence of constructivism, the practice of instructional design, which was deeply rooted in behaviorist and cognitive learning theories, was challenged. Constructivism, viewing reality as individual consecration, has caused a shift of the ways of thinking about what knowledge is and what learning is. The challenge, therefore, lies in what to do in the process of instructional design and how to do instructional design to adapt the shift. The constructivist orientations in the field have resulted in a lot of dialogues in different aspects of ID process as well as suggestions of alternative instructional-design theories (Duffy and Jonassen, 1992; Reigeluth, 1999).

From the constructivist perspective, knowledge is neither behavioral changes nor organizational structure that within the learner. Instead, knowledge is viewed a construction o understanding in a context or is located in the actions of persons and groups. Thus, the ultimate goal of learning is to facilitate the active cognitive reorganization in learners, and their active engagement in the world Moreover, the focus of design of instruction in the constructivist paradigm has shifted from how to structure instructional events in order to maximize the effectiveness of information transmission to the development of meaningful learning environments that will help students construct their understanding by engaging in meaning-making. Such changes in epistemological and pedagogical beliefs have challenged the practice in the ICED process. Perkins (1992), from a standpoint of cognitive constructivism whose focus is more on the active construction of the mind, has proposed to emphasize on the analysis of the tasks in a meaningful context, on the design of a manipulative space, and on understanding and use of knowledge as assessment measurement. On the hand, Brown, Collins and Dugid (1989), from a socio-cultural constructivist viewpoint, described how participation in social interactions and culturally organized activities influences psychological development.

Below is a list of contrast in the ID process between so-called traditional ID practice (behaviorism and cognitivism), and constructivist ID process abstracted from different literature (Bednar, Cunningham, Duffy, & Perry, 1995; Duffy & Cunninghum, 1996; Duffy & Jonassen).

	Traditional	Constructivism
The consequence of learning	Behavioral changes and the transmission of knowledge from expert to novice	Active construction of knowledge by learners
Content Analysis	Simply and regularize the components to be learned, to translate them into process of method, i.e. classifying the components based on the nature of the content and the tasks Specify prerequisite learning Knowledge domain is divided up on a logical analysis or dependencies	A core knowledge domain may be specified: the students are encouraged to search for other relevant knowledge domains that may be relevant to the issue and to seek a new perspective. We can and must define a control or core body of information; we simply cannot define the boundaries of what may be relevant To avoid the segregation of knowledge domains, students need to see the use of information outside the traditional limits of the domain or the setting in which it was learned· Consider what the real people in a particular knowledge domain and real life context typically do: to think in the knowledge domain as an expert user of that domain might think Identify the variety of expert users and the tasks they do· We may not be able to start the student with an authentic task; in some way, we must simplify the task
Analysis of learners	Learners is the pool of learners, the average conditions. Some models for measure individual progress toward learning goals as part of the system, but those models are not the norm in instructional system.	Identify the skills of the learner in term of his or her reflectivity, not remembering. Focus on the process of knowledge construction and the development of reflective awareness of that process.
Specification of objectives	Classify the characteristics of the content and learner so as to facilitate their translation in the synthesis phases to instructional method The categories used by the designers are applied across content, regardless of the nature of domain	Every field has its unique ways of knowing, and the function of analysis is to try to characterize this. Constructivists do not have learning and performance objectives that are internal to the content domain, e.g. to apply the principles, but rather the designers search for authentic tasks and let more specific objective emerge and be realized as they are appropriate to the individual learner in solving the the real world task
Synthesis	Design an instructional sequence and instructional message in order to achieve a specified performance objective The design principles are considered to be generally applicable across content and across context	Focus on the development of learning environments that encourage construction of understanding from multiple perspectives Macro design strategies are inappropriate, so too are design strategies at the micro level Situate cognition in the real world context Teaching through cognitive apprenticeship Construction of multiple perspective
The role of instructor	The authoritative source of knowledge source Model the cognitive process	Facilitator or guide: the instructor needs to look at what issues and question will generated from students' perspectives Modeling, coaching and scaffolding
Evaluation	To measure the outcomes: it focuses on the end-unit assessment Criterion-referenced instruction and evaluation: the goals of learning objectives drive the instruction Evaluation is a tool for reinforcement and behavioral control	To examine the thinking process, e.g. to ask learners to address a problem and defend their decision; to ask learners to reflect on their own learning and document the process It emphasizes ongoing formative assessment. Context driven evaluation: the criteria must be based on multiple perspectives; the evaluation should be multi-modal; use of negotiation of evaluation for guiding learned during the learning process and for self-evaluation of learning outcomes Evaluation is a self-analysis and metacognitive tool

 References:

Brown, J. S., Collins, A., & Dugid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18, 32-42.

Duffy, T. M., & Cunningham, D. J. (1996). Constructivism: Implications for the design and delivery of Instruction. In D. H. Jonassen, (Ed.), Handbook of research for educational communication, pp.170-198. New York, NY: Simon & Schuster Macmillan.

Duffy, T. M, & Jonassen, D. H. (1992). (Eds.), Constructivism and the Technology of Instruction: A conversation, p.45-55 Hillsdale, NJ: Lawrence Erlbaum Associates.

Perkins, D. N. (1992). Technology meets constructivism: Do they make a marriage? In T. M. Duffy and D. H. Jonassen, (Eds.), Constructivism and the Technology of Instruction: A conversation, p.45-55 Hillsdale, NJ: Lawrence Erlbaum Association.

Reigeluth, C. M. (1999). (Ed.), Instructional-design theories and models: An new paradigm of instructional theory, Volume II.. Mahwah, NJ: Lawrence Erlbaum Associates.

Research is a systematic inquiry to describe, explain, predict and control the observed phenomenon. Research involves inductive and deductive methods (Babbie, 1998). Inductive methods analyze the observed phenomenon and identify the general principles, structures, or processes underlying the phenomenon observed; deductive methods verify the hypothesized principles through observations. The purposes are different: one is to develop explanations, and the other is to test the validity of the explanations.

One thing that we have to pay attention to research is that the heart of the research is not on statistics, but the thinking behind the research. How we really want to find out, how we build arguments about ideas and concepts, and what evidence that we can support to persuade people to accept our arguments.

Gall, Borg and Gall (1996) proposed four types of knowledge that research contributed to education as follows:

1. Description: Results of research can describe natural or social phenomenon, such as its form, structure, activity, change over time, relationship to other phenomena. The descriptive function of research relies on instrumentation for measurement and observations. The descriptive research results in our understanding of what happened. It sometimes produces statistical information about aspects of education.
2. Prediction: Prediction research is intended to predict a phenomenon that will occur at time Y from information at an earlier time X. In educational research, researchers have been engaged in:
• Acquiring knowledge about factors that predict students' success in school and in the world of work
• Identifying students who are likely to be unsuccessful so that prevention programs can be instituted.

3. Improvement: This type of research is mainly concerned with the effectiveness of intervention. The research approach include experimental design and evaluation research.
4. Explanation: This type research subsumes the other three: if the researchers are able to explain an educational phenomenon, it means that they can describe, can predict its consequences, and know how to intervene to change those consequences.

What are the purposes of research?
Patton (1990) pointed out the importance of identifying the purpose in a research process. He classified four types of research based on different purposes:

1. Basic Research: The purpose of this research is to understand and explain, i.e. the research is interested in formulating and testing theoretical construct and propositions that ideally generalize across time and space. This type of research takes the form of a theory that explains the phenomenon under investigation to give its contribution to knowledge. This research is more descriptive in nature exploring what, why and how questions.
2. Applied Research: The purpose of this research is to help people understand the nature of human problems so that human beings can more effectively control their environment. In other words, this type of research pursues potential solutions to human and societal problems. This research is more prescriptive in nature, focusing on how questions.
3. Evaluation Research (summative and formative): Evaluation research studies the processes and outcomes aimed at attempted solution. The purpose of formative research is to improve human intervention within specific conditions, such as activities, time, and groups of people; the purpose of summative evaluation is to judge the effectiveness of a program, policy, or product.
4. Action Research: Action research aims at solving specific problems within a program, organization, or community. Patton (1990) described that design and data collection in action research tend to be more informal, and the people in the situation are directly involved in gathering information and studying themselves.

What is the research process?
Gall, Borg, and Gall (1996) described the following stages of conducting a research study:

1. Identify a significant research problem: in this stage, find out the research questions that are significant and feasible to study.
2. Prepare a research proposal: a research proposal usually consists of the sections including introductory, literature review, research design, research method, data analysis and protection of human subject section, and timeline.
3. Conduct a pilot study: the purpose is to develop and try out data-collection methods and other procedures.
4. Conduct a main study
5. Prepare a report

Gall, Borg, and Gall (1996) also explained that these five stages may overlap or occur in a different order depending the nature of the study. Qualitative studies which involve emergent research design may gather and analyze some data before developing the proposal, or a pilot study can be done before writing a research proposal or not at all.

Anglin, Ross, and Morrison (1995) took a closer look at the stages of identifying a research problem and preparing the research proposal. They advised a sequence of planning steps:

Select a Topic

Research requires commitment. As a researcher, you want to make sure you are doing something that you have a great interest in doing.

Identify the Research Problem

Based on your own understanding and interest of the topic, think about what issues can be explored? Sometimes, a research problem cannot be immediately identified. But, through reviewing the existing literature and having continuous discourse with peers and scholars, the research problem will start take its shape.

Conduct a Literature Search

Reviewing literature has two major purposes: one is to build up the researcher's knowledge base of the topic under exploration for a deeper understanding, and the other is to ensure the significance of the research. The researcher needs to make sure how the research will be able to contribute to the knowledge in the related field compared with the existing research literature.

State the Research Question

The research problem will evolve during your pursuing knowledge base through reviewing literature and discourse with peers and scholars. To specify what questions your research study want to answer helps to provide the basis of planning other parts of your study, e.g. the research design, the methods for data collection and analysis. Experimental/Positivist Study Correlational Study Qualitative/Naturalist Study Questions about whether a certain instructional method or strategy improve a certain skill or learning outcome Questions about whether a certain student characteristics have effects on a certain skill or learning outcome, or whether the characteristics interact with the instructional strategy or method to affect learning of a certain skill or cognitive process Questions about whether two or more variables are related to each other? Those questions intend to use or control one variable to predict a future performance of a particular variable Questions to generate a theory to describe certain patterns of interaction or process of an observed phenomenon Questions about lived experience of research participants Questions about the cultural patterns or social patterns in the classroom Ideas abstracted from Anglin, Ross, and Morrison (1995)

Determine the Research Design

In the intention of the research study is to verify a causal relationship between certain variables, use an experimental design; if the intention of the research study is to find out how variables relate to one another, use a correlational design; if the intention of the research study is to describe and understand a particular social condition/pattern and meaning of a social experience, conduct a qualitative study.

Determine Methods

Three major elements in the research study need to be considered: participants, materials, and instruments.

Participants: It concerns whom to study. For experimental studies, the researcher needs to consider statistical sampling to make sure that sample is representative of the population, e.g. techniques of random sampling and stratified sampling. For qualitative research, purposeful sampling is the major principle. The selection of individuals, groups, or cases depends on how the characteristics, or properties of the individuals, groups, or cases will best inform the researcher with the focus of what is under investigation. Materials and Instrumentation: For experimental research, operationalization of the variables is the focus, i.e. what are different treatment conditions, and how to measure the dependent variables. The researcher has to consider issues about the reliability (the consistency of the test), and validity (whether the test is testing what is meant to test) of the measurement. The design of the experimental conditions has taken the threats of the internal and external validity into account. The researcher wants to make sure that the establishing of the causal relationship is not influenced by other factors than the controlling factors, and the researcher needs to consider to what extent the results of the research can be generalized to the population beyond the sample under study. For qualitative research, the issues are the sources of data, where the researcher can find the information and what methods the researcher can use to get the information. Qualitative research usually focuses on the verbal information gathered from the interviews, observations, documents or cultural artifacts. The very distinctive feature about the qualitative research is that the researcher is part of the instrument. The recognition of this researcher's subjective interpretation of the information yields the process of triangulation, which emphasizes use of multiple sources, methods, investigators, and theories to ensure the credibility of the research. Procedures: A procedural planning of how to get approval from IRB, how to get entry to research participants or to the field, how to implement the experimental treatment or to schedule observations and interviews, and how to prepare for write-up. A general outline of the process and a timeline will facilitate the research progress.

Identify Analysis Procedures

Different research questions and different research designs entail different analysis method to take. Experimental design employs statistical analysis to give statistical descriptions of the groups in terms of different independent variables and dependent variables, and to determine the significance of the differences whether the dependent variables are caused by the independent variables. On the other hand, qualitative design employs semantic analysis to identify themes, categories, processes, and patterns of an observed phenomenon, and provides rich descriptions of the phenomenon in order to develop a deeper understanding of human systems.

References:

Anglin, G. J., Ross, S. M., & Morrsion, G. R. (1995). Inquiry in instructional design and technology: Getting started. In G. J. Anglin (ed.), (2nd ed.) Instructional technology: Past, present, and future. Englewood, CO: Libraries Unlimited, Inc.

Gall, M. D., Borg, W. R., & Gall, J. P. (1996). Educational Research: An Introduction ( Sixth ed.). White Plains, NY: Longman.

Patton, M. Q. (1990). Qualitative Evaluation and Research Methods. ( 2nd ed.). Newbury Park, CA: Sage.

Webster Dictionary defines paradigm as "an example or pattern: small, self-contained, simplified examples that we use to illustrate procedures, processes, and theoretical points." The most quoted definition of paradigm is Thomas Kuhn's (1962, 1970) concept in The Nature of Science Revolution, i.e. paradigm as the underlying assumptions and intellectual structure upon which research and development in a field of inquiry is based. The other definitions in the research literature include:

1. Patton (1990): A paradigm is a world view, a general perspective, a way of breaking down the complexity of the real world.
2. Paradigm is an interpretative framework, which is guided by "a set of beliefs and feelings about the world and how it should be understood and studied." (Guba, 1990). Denzin and Lincoln (2001) listed three categories of those beliefs:

• Ontology: what kind of being is the human being. Ontology deals with the question of what is real.
• Epistemology: what is the relationship between the inquirer and the known: "epistemology is the branch of philosophy that studies the nature of knowledge and the process by which knowledge is acquired and validated" (Gall, Borg, & Gall, 1996)
• Methodology: how do we know the world, or gain knowledge of it?

When challenging the assumptions underlying positivism, Lincoln and Guba (2000) also identified two more categories that will distinguish different paradigms, i.e. beliefs in causality and oxiology. The assumptions of causality asserts the position of the nature and possibility of causal relationship; oxiology deals with the issues about value. Specific assumptions about research include the role of value in research, how to avoid value from influencing research, and how best to use research products (Baptiste, 2000).

Dill and Romiszowski (1997) stated the functions of paradigms as follows:

• Define how the world works, how knowledge is extracted from this world, and how one is to think, write, and talk about this knowledge
• Define the types of questions to be asked and the methodologies to be used in answering
• Decide what is published and what is not published
• Structure the world of the academic worker
• Provide its meaning and its significance

Two major philosophical doctrines in the social science inquiry are positivism and postpositivism. The following is a contrast of the research approach that are entailed from these two different philosophical paradigms.

	Positivism	Postpostivism
Philosophical Inquiry	The physical and social reality is independent of those who observe it Observation of this reality, if unbiased, constitutes scientific knowledge. Behavioral researchers in education and psychology exemplify an approach to scientific inquiry that is grounded in positivist epistemology.	Social reality is constructed by the individuals who participate it. It is constructed differently by different individuals. This view of social reality is consistent with the constructivist movement in cognitive psychology, which posts that individuals gradually build their own understandings of the world through experience and maturation. The mind is not tabula rasa (blank slate) upon which knowledge is written.
Research Design	The inquiry focuses on the determination of the general trends of a defined populations. The features of the social environment retain a high degree of constancy across time and space. Local variations are considered "noise"· Study of samples and population Generalization: first defining the population of interest, select a representative of the population, the researcher generalizes the findings obtained from studying the sample to the larger population using the statistical techniques to determine the likelihood that sample findings are likely to apply to the population.	The scientific inquiry must focus on the study of multiple social realities, i.e. the different realities created by different individuals as they interact in a social environment. Find a ways to get individuals to reveal their constructions of social realities, including the person being studied and the researcher. Reflexivity: focus on the researcher's self as an integral constructor of the social reality being studied The study of individuals' interpretations of social reality must occur at the local, immediate level. Study of cases: have you learned something about his case that informs us about another cases? Generalization of case study findings must be made on a case-by-case basis. In other words, it is the reader who made the generalization based on his or her own interpretation: The focus is on the transferability instead of generalization.
Data Collection and Design	The use of mathematics to represent and analyze features of social reality is consistent with positivist epistemology: a particular feature can be isolated and conceptualized as a variable. The variables can be expressed as a numerical scales. Deductive analysis: identify underlying themes and patterns prior to data collection and searching through the data for instances of them: hypothesis testing	Focuses on the study of individual cases and by making "thick" verbal descriptions of what they observe. Analytic induction: search through data bit by bit and then infers that certain events or statements are instances of the same underlying themes or patterns
View of causality	A mechanistic causality among social objects	Individuals' interpretation of situations cause them to take certain actions

Lincoln and Guba (2000) made the following distinctions between positivist and naturalist inquiries.

Positivist	Naturalist
Reality is single, tangible, and fragmentable.	Realities are multiple, constructed, and holistic.
Dualism: the knower and the known are independent.	The knower and the known are interactive and inseparable.
Time and context free generalization	Only time-and context-bound working hypotheses are possible.
Real causes, temporally precedent to or simultaneous with their effects (causal relationship)	All entities are in a state of mutual simultaneous shaping, so that it is impossible to distinguish causes from effects.
Inquiry is value free.	Inquiry is value bounded.

References:

Baptiste, I. (2000). Calibrating the "instrument": Philosophical issues framing the researcher's role. Class notes in ADTED 550.

Dills, C. R., & Romiszowski, A. J. (1997). The instructional development paradigm: An introduction. In C. R. Dills, and A. J. Romiszowski (Eds)., Instructional development paradigms. Englewood, NJ: Educational Technology Publications, Inc.

Gall, M. D., Borg, W. R., & Gall, J. P. (1996). Educational Research: An Introduction ( 6th ed.). White Plains, NY: Longman.

Lincoln, Y. S., & Guba, E., G. (2000). Paradigmatic controversies, contradictions and emerging confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of Qualitative Research (2nd ed., pp. 163-188). Thousand Oaks, CA: Sage Publications, Inc.

Patton, M. Q. (1990). Qualitative Evaluation and Research Methods ( 2nd ed.). Newbury Park, CA: Sage.

Smith, P., & Ragan, T. J. (1999). Instructional Design. 2nd ed. John, Wiley & Sons, Inc.

Webster Dictionary defines paradigm as "an example or pattern: small, self-contained, simplified examples that we use to illustrate procedures, processes, and theoretical points." The most quoted definition of paradigm is Thomas Kuhn's (1962, 1970) concept in The Nature of Science Revolution, i.e. paradigm as the underlying assumptions and intellectual structure upon which research and development in a field of inquiry is based. The other definitions in the research literature include:

1. Patton (1990): A paradigm is a world view, a general perspective, a way of breaking down the complexity of the real world.
2. Paradigm is an interpretative framework, which is guided by "a set of beliefs and feelings about the world and how it should be understood and studied." (Guba, 1990). Denzin and Lincoln (2001) listed three categories of those beliefs:

• Ontology: what kind of being is the human being. Ontology deals with the question of what is real.
• Epistemology: what is the relationship between the inquirer and the known: "epistemology is the branch of philosophy that studies the nature of knowledge and the process by which knowledge is acquired and validated" (Gall, Borg, & Gall, 1996)
• Methodology: how do we know the world, or gain knowledge of it?

When challenging the assumptions underlying positivism, Lincoln and Guba (2000) also identified two more categories that will distinguish different paradigms, i.e. beliefs in causality and oxiology. The assumptions of causality asserts the position of the nature and possibility of causal relationship; oxiology deals with the issues about value. Specific assumptions about research include the role of value in research, how to avoid value from influencing research, and how best to use research products (Baptiste, 2000).

Dill and Romiszowski (1997) stated the functions of paradigms as follows:

• Define how the world works, how knowledge is extracted from this world, and how one is to think, write, and talk about this knowledge
• Define the types of questions to be asked and the methodologies to be used in answering
• Decide what is published and what is not published
• Structure the world of the academic worker
• Provide its meaning and its significance

Two major philosophical doctrines in the social science inquiry are positivism and postpositivism. The following is a contrast of the research approach that are entailed from these two different philosophical paradigms.

	Positivism	Postpostivism
Philosophical Inquiry	The physical and social reality is independent of those who observe it Observation of this reality, if unbiased, constitutes scientific knowledge. Behavioral researchers in education and psychology exemplify an approach to scientific inquiry that is grounded in positivist epistemology.	Social reality is constructed by the individuals who participate it. It is constructed differently by different individuals. This view of social reality is consistent with the constructivist movement in cognitive psychology, which posts that individuals gradually build their own understandings of the world through experience and maturation. The mind is not tabula rasa (blank slate) upon which knowledge is written.
Research Design	The inquiry focuses on the determination of the general trends of a defined populations. The features of the social environment retain a high degree of constancy across time and space. Local variations are considered "noise"· Study of samples and population Generalization: first defining the population of interest, select a representative of the population, the researcher generalizes the findings obtained from studying the sample to the larger population using the statistical techniques to determine the likelihood that sample findings are likely to apply to the population.	The scientific inquiry must focus on the study of multiple social realities, i.e. the different realities created by different individuals as they interact in a social environment. Find a ways to get individuals to reveal their constructions of social realities, including the person being studied and the researcher. Reflexivity: focus on the researcher's self as an integral constructor of the social reality being studied The study of individuals' interpretations of social reality must occur at the local, immediate level. Study of cases: have you learned something about his case that informs us about another cases? Generalization of case study findings must be made on a case-by-case basis. In other words, it is the reader who made the generalization based on his or her own interpretation: The focus is on the transferability instead of generalization.
Data Collection and Design	The use of mathematics to represent and analyze features of social reality is consistent with positivist epistemology: a particular feature can be isolated and conceptualized as a variable. The variables can be expressed as a numerical scales. Deductive analysis: identify underlying themes and patterns prior to data collection and searching through the data for instances of them: hypothesis testing	Focuses on the study of individual cases and by making "thick" verbal descriptions of what they observe. Analytic induction: search through data bit by bit and then infers that certain events or statements are instances of the same underlying themes or patterns
View of causality	A mechanistic causality among social objects	Individuals' interpretation of situations cause them to take certain actions

Lincoln and Guba (2000) made the following distinctions between positivist and naturalist inquiries.

Positivist	Naturalist
Reality is single, tangible, and fragmentable.	Realities are multiple, constructed, and holistic.
Dualism: the knower and the known are independent.	The knower and the known are interactive and inseparable.
Time and context free generalization	Only time-and context-bound working hypotheses are possible.
Real causes, temporally precedent to or simultaneous with their effects (causal relationship)	All entities are in a state of mutual simultaneous shaping, so that it is impossible to distinguish causes from effects.
Inquiry is value free.	Inquiry is value bounded.

References:

Baptiste, I. (2000). Calibrating the "instrument": Philosophical issues framing the researcher's role. Class notes in ADTED 550.

Dills, C. R., & Romiszowski, A. J. (1997). The instructional development paradigm: An introduction. In C. R. Dills, and A. J. Romiszowski (Eds)., Instructional development paradigms. Englewood, NJ: Educational Technology Publications, Inc.

Gall, M. D., Borg, W. R., & Gall, J. P. (1996). Educational Research: An Introduction ( 6th ed.). White Plains, NY: Longman.

Lincoln, Y. S., & Guba, E., G. (2000). Paradigmatic controversies, contradictions and emerging confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of Qualitative Research (2nd ed., pp. 163-188). Thousand Oaks, CA: Sage Publications, Inc.

Patton, M. Q. (1990). Qualitative Evaluation and Research Methods ( 2nd ed.). Newbury Park, CA: Sage.

Smith, P., & Ragan, T. J. (1999). Instructional Design. 2nd ed. John, Wiley & Sons, Inc.

Quantitative research is basically a hypothesis testing process. Based on some theoretical foundations, hypotheses are formulated. After the design and implementation of determining human subjects, developing and selecting instrumentations, and operationalization of some controlling factors, data are collected and analyzed to test hypotheses. It is a hypothetico-deductive approach, which usually collects quantitative data from experimental or quasi-experimental designs and statistical analysis.

Gall, Borg and Gall (1996) described the quantitative research as the inquiry " that is grounded in the assumption that features of the social environment constitute and objective reality that is relatively constant across time and settings. The dominant methodology is to describe and explain features of this reality by collecting numerical data on observable behaviors of samples and by subjecting these data to statistical analysis."

The major process of conducting a quantitative research is as follows:

Identify the Research Problem

Review of the Literature

State Research Questions and Hypotheses

Plan Research Design: whom to study, i.e. sampling and human subject concerns; how to study, i.e. operationalization of the variables; what to study, i.e. instrumentation, data collection, and data analysis

Implementation of Research Study

Presentation and Explanation of Results

Statistical Analysis
There are two types of statistics: descriptive statistics and inferential statistics.

1. Descriptive Statistics:
• Mathematical technique for organizing and summarizing a set of a numerical data
• Means, Mode, Standard Deviation
• Central Tendency: a single numerical value that is used to describe the average of an entire set or sets of scores. Let think about behind the inference

2. Inferential Statistics:
• Parameter estimation
• Significance testing: a negative, falsification approach

Thinking behind the inferential statistics:

1. If the descriptive statistics is described within a sample, how well does this represent the descriptive statistics of population? This is an issue of inferential statistics.
2. If you study a population, no needs for significance testing. But, if the research wants to project the result into a bigger population, significance testing is necessary.
3. Inferential statistics assume that research starts with a simple random sample, i.e. equal and independent chance to being selected from a population. Sample will never be representative of the entire population. But, using simple random sampling, we can have a mathematical explanation, i.e. probability, behind it.

Statistical inference refers to a set of mathematical procedures of generalizing the statistical results obtained from a sample to the population from which the sample presumable was drawn. In other words, by using statistical inference techniques, we are attempting to use statistics computed from a sample to make inferences about population parameters.

What does the statistical significance mean?
Significance refers to the confidence level of rejecting the null hypothesis by accepting a certain level of error. In other words, if the result is non-significant, it means that the result is unable to reject the null hypothesis because the chance of having such result is greater than a confidence level or level of error that we can accept.

Null Hypothesis: A prediction that no relationship between two measured variables will be found, or that no difference between groups on a measured variable will be found.

Type I error: The rejection of the null hypothesis when it is true.

With Type One error, we reject the null hypothesis claiming that we have a real difference when in fact the difference is not real but is due to sampling and chance variation. When we make a statement that the treatment is effective but it is not, we are making a Type I error.

Type II error: the failure to reject the null hypothesis of no difference, when there is in fact a difference.

	Do not reject Null Hypothesis	Reject Null Hypothesis
Null Hypothesis (Ho) is true	Correct Decision 1-a	Type I error a
Null Hypothesis (Ho) is false	Type II error ß	Correct decision (1-ß)

All statistical tests begin with certain assumptions that, together with the laws of probability, enable statisticians to develop the tables we use to determine statistical significance, for example, tables for the normal distribution, t, chi-square, and F.

Parametric Statistics vs. Nonparametric statistic
Instrumentation is a process of operationalize the variables and scaling (converting something into numbers). In statistics, numbers are categories into the following taxonomy:

• Nominal: a verbal label, such as categories
• Ordinal: hierarchical rating or order
• Interval: consistent difference between two different numbers, such as height, weights; Zero is not absolute
• Ratio: zero is not absolute

Interval and ratio are cardinal numbers, which are usually described in parametric statistics, such as means, standard deviation, t test, and ANOVA. Nominal and ordinal are described in nonparametric statistics (no additions, subtraction, square root), such as mode, median, range of scores, and chi-square test.

What are statistical significance tests?
The level of significance does not indicate how much likely it is that your research hypothesis is correct; it only helps you to make a decision about rejecting the null hypothesis. It has only an indirect bearing on confirmation of your research hypothesis

chi-square: a nonparametric test of statistical significance that is used when the research data are in the form of frequency counts for two or more categories.

1. When to use? chi-square handles only categorical (nominal) data, frequencies, or figures based on them like percentages or probabilities
2. Why to use?
• Eliminate the alternative explanation of sampling and chance error
• Test a hypothesis about whether one variable is related to another
• Test whether the data fit a particular model or distribution
• Combine probabilities derived from independent samples in a single study or across studies into a single probability (another way of doing meta-analysis)

3. What's the formula? The formula for chi-square is simple. It involves finding the difference between the observed frequency and the frequency that would be expected by chance, squaring it, dividing it be the expected frequency, and summing these over all the observe data.

Degree of freedom: the freedom of the cell data in successive samples to vary once the column and row totals are fixed. In general, chi-square tables have (r-1) (c-1) degrees of freedom, where r is the number of rows and c the number of columns

t test: A test of statistical significance that is used to determine the null hypothesis that two sample means come from identical populations can be rejected.

Research studies, such as a comparison of two experimental treatments or a comparison of a control with an experimental group, examine a difference between two means with t test.

The degree of freedom in t test is (n1+n2-2)

ANOVA (Analysis of Variance): Testing differences among several means:

• A procedure for determining whether the difference between the mean scores of two or more groups on a dependent variable is statistically significant.
• When the groups have been classified on several independent variables, the procedure can be used to determine whether each factor and the interactions between the factors have a statistically significant effect on the dependent variable.

1. When to use it?
   It is widely used for complex experimental designs where more than two groups or where multiple conditions are being compared. For example, 2x2x3

2. Why to use?
• Allow to partition the variance of the study to find the part that is attributable to each of the variables as well as the combined effect of variable.
• After accounting for these variables and their combinations, the residual variance is a purer measure of sampling and chance error, and it provides for ore precise tests of statistical significance.

3. What is ANOVA?
   The logic used by analysis of variance involves deriving two estimates of the population variance: first, an estimate that includes the effect of one or more of the variables; second, an estimate, which is free of it. If there is no effect, on average, the two estimates are equal and the expected value of dividing the first by the second, called an F ration, is one. However, given a possible effect, and in any event, sampling and chance error, the first of these estimates will typically be the larger, so the ration will usually be grater than one. We consult an F table to determine how much above one to allow for sample and chance error.

About Sampling
Sample is part of the targeted population. The major issue is generalization: the less the sample is, the less generalizability the conclusion is; the bigger the sample size, the less error. The concern is representativeness. Sample size is a function of population size and desired confidence level, the statistical power.

Two major random probability sampling: simple random sampling and stratified random and cluster samples:

1. Simple random sampling: It permits generalization from sample to the population it represents

2. Stratified random and cluster samples: It increase confidence in making generalization to particular subgroups or areas.

Power Analysis: A method to determine the sample size. The analysis makes sure that you have sufficient power to determine the conclusion. When you hold the power constant, then look at the relationship of effect size, the variance, and the sample size.

About Reliability and Validity
Reliability: it refers to the consistency of an instrument. It is the extent to which other researchers would arrive at similar results if they studied the same case using exactly the same procedures as the first researcher. In classical test theory, the amount of measurement error in the score yielded by a test.

Validity: it refers the appropriateness, meaningfulness, and usefulness of specific inferences made from test scores.

• Construct Validity: The extent to which inferences from a test' scores accurately reflect the construct that test is claimed to be measure.
• Content Validity: the extent to which inferences from a test's scores adequately represent the content or conceptual domain that the test is claimed to measure.
• Ecological validity: The extent to which the results of an experiment can be generalized from conditions in the research setting to particular naturally occurring condition.

Internal Validity: The extent to which extraneous variables have been controlled, so that any observed effects can be attributed solely to the treatment variable. In other words, your conclusion about the cause-effect is right and how right it is.

The common rival explanations about the cause-effect relationship: testing and regression.

Threats to Internal Validity: (notes from EDPSY 475)

1. Sampling and chance error
2. Hawthorne Effect, i.e. novelty effect
3. Pygmalion Effect, i.e. expectancy effect
4. John Henry Effect: In experiments, a situation in which control group participants perform beyond their usual level because they perceive that they are in competition with the experimental group
5. Resentful Demoralization: the control group performs worse
6. Experimental Diffusion: the control group adopt the treatments from the experimental groups
7. Treatment fidelity: what you plan to do is different from what you actually do: actually treatment carried out is very different form the original

Cambel and Stanely: Classical threats to internal validity:

1. Something is happening simultaneously with your experiment. In other words, something changes along the situation that affects the statistical differences.
2. Maturation: something happens in the situation because of the natural development or growth, e.g. the subject ability matures
3. Testing (Pretesting), i.e. students become test wise: Pretest can prompt somebody to improve their ability
4. Instrumentation: different instruments used in pretest and posttest
5. Experimental Mortality: Attrition
6. Regression to the mean: this concerns with the tendency of flotation: low ability have more tendency to go up, and high ability have more tendency to go down.
7. Selection: the effect is attributed to the fact that different types of students are selected for two groups. Randomization is the best safe grad against different selection.
8. Selection/Maturation Interaction: one group is changing naturally, or two groups have different maturation rates.

External Validity: The extent to which the results of a research study can be generalized to individuals and situations beyond those involved in the study. It concerns whether you can generalize or extend your findings?

1. Interaction with testing (pre-testing): Without the pretest, people will not pay attention to certain treatment. In other words, combination of the pretest and treatment makes the results different. Thus, it cannot applied to outside the experiment because of the lack of the pretest in the population.
2. Selection-Treatment interaction: One group is more acceptable to the treatment. It is possible that treatment on a certain type of people work better.
3. Multiple Treatment Interference: It is common in a single-subject study. The same group is used again and again to try different treatments, e.g. A, B, C, D. Howeer, if D works, but it cannot prove that if only D works, or A, B, C, help. In other words, the other treatments may interfere a certain treatment. Therefore, the findings cannot be generalized with confidence to a situation in which treatment D is administered alone.

The relationship between internal validity and external validity:
Usually we use to controlled conditions to gain internal validity, but we kind of lose external validity; we use the field study to gain the external validity, but we lost internal validity.

Threats to Internal/External validity in observation

1. Observation Reactivity: Hawthorne Effects
2. Reliability decay: the tendency for observational data recorded during the latter phases of data collection to be less reliable than those collected earlier. As an observer, you become less sharp as the day goes on.
3. Observer Drifts: Rater Drifts: Over time, observer changes the criteria or definition. How to avoid it? The rater should grade the same question one at a time; use second observer to observe occasionally at different point of time.
4. Consensual Drifts: Inter-influence between observers

References:

Gall, M. D., Borg, W. R., & Gall, J. P. (1996). Educational Research: An Introduction ( Sixth ed.). White Plains, NY: Longman.

Anderson (1990) explained that research in education is a disciplined attempt to address questions or solve problems through the collection and analysis of primary data for the purpose of description, explanation, generalization, and prediction (Anderson,1990, p. 4).

Driscoll (1984) summarized eight paradigms for research in instructional systems:

1. Experimental research design: this research is designed to establish causal influence on a phenomenon of interest. The focus of the instructional systems research is to examine the effects on learning of single or interacting instructional variables, e.g. the effects of the concept mapping strategy on students' performance in comprehension.
2. Quasi-experimental design: most of time in instructional research, the random sampling of students to different treatment conditions is not possible. The internal validity will be an issue.
3. Meta-analysis: to use the previously report research findings for a statistical analysis, i.e. a statistical means for synthesizing research findings to determine the effect size.
4. Case Study/Ethnography: instead of controlling the contextual influence on learning variables, case studies and ethnographical studies describe those contextual factors in a natural setting and investigate the interactional pattern of those contextual factors in a learning situation.
5. Systems-based evaluation: study of the design, development, implementation, and effectiveness of a new instructional product or program in order to improve or adjust the product or program
6. Cost-effectiveness and cost analysis
7. Technique and model development and validation

Driscoll and Dick (1999) categories two inquiry types in the papers published in the IT field: empirical and nonempirical. Nonempirical inquiry includes literature reviews, conceptual article, and description of projects, models, tools or software. Empirical inquiry includes:

1. Case study: A study of how or why something occurs in a particular situation, a defined boundary
2. Experiment: A study of the effect of a manipulated variable on an observed variable
3. Survey: A study describing the distribution of responses to a questionnaire or exploring relations among variables
4. Program evaluation: A study to determine the impact or outcomes of an educational program
5. Development Research: A study of design, development, or evaluation processes, tools or models, and the conditions that facilitate their use
6. Qualitative-Naturalistic: A study aimed at developing an understanding of human systems, involving the collection of non-numerical data and detailed rich descriptions of natural events.

What is developmental research?
Instructional development connotes two major definitions:

• A process of producing instructional materials: "the process of translating the design specifications into physical form (Seels & Richey, 1994)
• The ISD process: "the process of analyzing needs, determining what content must be mastered, establishing educational goals, designing materials to reach the objectives, and trying out and revising the program in terms of learner achievement" (Heinch, Molenda, & Russell, 1993)

Developmental research intends to produce knowledge with the ultimate aim of improving the processes of instructional design, development and evaluation. Seels and Richey (1994) defined it as "the systematic study of designing, developing and evaluating instructional programs, processes, and products that must meet the criteria of internal consistency and effectiveness." (p. 127). Three major endeavors of developmental research:

1. Performing and studying the processes of design, developing or/and evaluation
2. Study of the impacts of someone else's instructional design and development efforts
3. Study of the instructional design, development, and evaluation process as a whole, or of a particular process component:

According to Richey and Nelson (1996), there are two types of developmental research:

	Type One	Type Two
Conclusion	Contextually Specific	Generalizable
Focus	Description and documentation of a particular design, development, and evaluation project Drawing contextually-specific conclusions Dissemination vehicles for exemplary design, development, or evaluation strategies	The use of a particular technique, tool or process, e.g. formative evaluation The use of a comprehensive design, development, or evaluation model A general examination of design and development
Product	Lesson learned Evaluative report on the design, development and evaluation process of a specific product	Evidence of the validity and or effectiveness of a particular technique of model Conditions and procedures that facilitate the successful use of a particular technique or model Explanations of the successes or failure encountered in using a particular technique or model A synthesis of events and or opinions related to the use A new or enhanced design, development, and or evaluation model
Major Research Methods	Case studies: exploration and descriptions of complex situation, including description of goals, the processes used, general evaluation data, and reflections on the experiences with implications for future development efforts	Experimental and· Quasi-experimental Verification in terms of the impacts on student performance
Major Evaluation Components	Observations· Qualitative techniques Surveys Some quantitative reports on the effectiveness or impact of the resulting instruction	Instruments on the impacts on students performance Surveys Interviews

Ideas abstracted from Richey and Nelson (1996)

To Richey and Nelson (1996), the non-developmental research is referred to instructional psychology studies, media or delivery system comparison and impact studies, message design and communication studies, policy analysis or formation studies, and research on the profession.

The Developmental Research Process
Richey and Nelson (1996) provided methodological direction about the developmental research:

1. Defining the Research Problem

The focus of the research problem is on the particular aspect of the design, development, or evaluation process instead of a particular variable that impacts learning, or the impact of a type of media. The research topics include one of the following dimensions in the instructional development: design, development or evaluation model or process, instructional product, program, process or tool, identification of general development principles or situation-specific recommendations.

2. Review of Related Literature

The topics under review that may be related to developmental research include: procedural models, characteristics of effective instructional products, programs, or development systems, factors regarding the use of the target development processes, factors regarding the implementation and management of instruction.

3. Research Procedure
   Population and Samples
   The potential research participants can be designers, developers, evaluators; instructors, program facilitators; learners. These participants can be the sources of the data that shed light to the research under investigation. Usually the project itself is the object of the developmental study.

Research Design
This addresses the planning of the process: How and when will the development take place? When will the instruction be implemented? How and when will the evaluation take place?

For example, an experimental study should consider operationalization of the variables, e.g. what is the treatment? how long will the treatment be? how to measure the variables? what is the validity and reliability issues of the variables?

Data Collection and Analysis Procedures
The information sources related to the research may include: documentations of the design, development and evaluation tasks; documentations of the conditions under which development takes place; needs assessment, formative evaluation, and summative evaluation; profiling of the target populations, profiling of the design/implementation contexts, and the impacts of the instruction and the context associated with the impact

4. Results and Conclusions

The developmental research contributes to the field's knowledge based with more understanding of the new procedural models, generalizable principles or the lesson learned in a particular project.

What are the future development of the developmental research?
According to Richey and Nelson (1996), constructivism has influenced the shift of the attention of developmental topics to the role of context in design and the development of anchored instruction. Also, the research of the development process emphasizes on designer decision-making, knowledge acquisition tools, and the use of automated development tools

1. Research on the design and designer decision making process intends to contribute understanding of the design process, producing the design models that match the design activities, and identifying the impacts of various design environments. Research topics include exploration of the design task environment, cognitive process of instructional designers, role of knowledge in the design process
2. Research on techniques for knowledge acquisition focuses on producing new content analysis tools and procedures, determining the conditions under which they can be best used. Designers, subject matter experts and the design tasks are units of analysis in these studies.

Cognitive science on theories of knowledge representations (Qullian's semantic networks; Anderson's declarative and procedural knowledge) and the process of knowledge acquisition (Atkinson & Shiffrin, 1968; Fitts' 1966: three stage of skill acquisition; Anderson's ACT*R: 1993) provide directions and advanced techniques on how to elicit subject matter experts' knowledge required for problem solving in a specific domain and how to present and describe experts' knowledge performance and knowledge base.

Recently the constructivist view point of knowledge helps designers to explore the different aspects of the environmental factors on knowledge acquisition, e.g. social and cultural (Vygotsky's signification and scaffolding), learning as the enculturation process into community of practice (Browns, Collins and Duguid's situated cognition), tool uses and collaborative learning (Lave's distributed cognition, Banduara's modeling, Vygotsky's externalization via social interaction). Those explorations give rise to the research on the context where the knowledge is applied and used, the social interaction with tools, rules, and the members in the community that the designers through such understanding have a more solid knowledge base on how to simulate such context in the learning environment. This type of research can focus on the effectiveness of different techniques and tools for task analysis or instructional design.

3. Research on knowledge-based design systems focuses on the production and testing of tools that would change design procedures, e.g. systems and tools that support the instructional processes.

The systems and tools under exploration include: Merrill and Li's ID experts (1993; 1998), and Kearsley's (1985) expert system tools for instructional design.

Research problems that can be explored regarding the developmental research in the future include:

• Individual tools for self-contained instructional design tasks
• Integrated systems that provide decision support and structure for the process
• Integrated system that act as drafting boards for the design process

References:

Driscoll, M. P. (1984). Alternative paradigms for research i instructional systems. Journal of Instructiional Development, 7(4), 2-5.

Driscoll, M.P., & Dick, W. (1999). New research paradigms in instructional technology: An inquiry. Educational Technology, Research and Development, 47 (2), 7-18.

Richey, R. C., & Nelson, W. A. (1996). Developmental research. In D. H. Jonassen (Ed.), Handbook of Research for Educational Communications and Technology (pp.1213-1242). New York: Macmillan.

Seels, B. B., & Richey, R. C. (1994). Instructional technology: The definition and domains of the field. Washington, D.C.: Association of Educatoinal Communications and Technology.