Journal of Technology Education


JTE Editor: Mark Sanders

Volume 3, Number 2
Spring 1992


DLA Ejournal Home | JTE Home | Table of Contents for this issue | Search JTE and other ejournals

A Framework for Technology Education Curricula Which Emphasizes Intellectual
Processes
 
          Scott D. Johnson
 
              As the field of technology education evolves, its
          unique mission to provide relevant and experiential
          learning opportunities for students is becoming clear.
          Through well developed curricula, technology education
          programs are able to reinforce academic content, enhance
          higher order thinking skills, and promote active involvement
          with technology (Johnson, 1991). The development of cur-
          ricula which addresses such goals is both difficult and
          complex.
              A variety of curriculum perspectives exist which
          greatly influence the direction and results of curriculum
          development efforts (Eisner & Vallance, 1974; Miller &
          Seller, 1985; Zuga, 1989). These perspectives include
          academic rationalist, technical/utilitarian, intellectual
          processes, social reconstruction, and personal
          relevance. While curricula developed through each curriculum
          perspective vary in their contribution toward a well-rounded
          education, this article is based on the assumption that the
          development of intellectual processes should be the primary
          goal of education. Therefore, the purpose of this article is
          to establish a rationale for technology education
          curricula which emphasizes the development of intellectual
          processes and lay the foundation for an intellectual
          processes curriculum framework.
 
          The Importance of Intellectual Skills in the Future
              There is little doubt that the development of
          intellectual processes is critical in this age of advancing
          technology. Tremendous changes have occurred and will
          continue to occur in the workplace. Equipment and proc-
          esses are becoming more sophisticated. This sophistication
          has resulted in fundamental changes in the skills needed by
          workers. Increased levels of skills are required to
          maintain the complex equipment. There has been a switch from
          concrete (hands-on) tasks to abstract (minds-on) tasks which
          require mental skills such as symbolic and abstract thinking
          (Grubb, 1984). Management strategies have also changed in
          recent years. Just-in-time manufacturing, participative
          management techniques, statistical process control, and an
          increased emphasis on teamwork are just a few examples of
          the changing nature of the workplace.
              As a result of the advances in technology and the
          organizational changes to the industrial infrastructure,
          job expectations for workers have changed. Rather than
          simply performing repetitive tasks, workers are now expected
          to be skilled in many jobs. While technical skills are still
          needed, they are not enough. Workers need to have a broader
          understanding of their role in the organization, be able
          to work in teams, and possess   higher levels of
          communication and computational skills. Consequently,
          business and industry needs a workforce that possesses a
          broad general education with heavy emphasis on math and
          science. While these changes suggest the need for a greater
          emphasis on academic skills, the most important job skills
          may be the ability to think creatively, solve problems,
          and make decisions. In actuality, the workforce must have
          the ability to learn in order to keep pace with the
          constantly changing world.
              While technological and organizational changes are
          impacting the workforce, similar challenges face the general
          public. The impacts of technology on our society, culture,
          environment, and political systems need to be analyzed and
          evaluated by citizens. Without well developed intellectual
          skills and an understanding of technology, it is doubtful
          that the general public will be willing nor able to make
          critical decisions regarding technological issues.
              Given the fact that the skills needed by the workforce
          are changing and the increased need for all citizens to have
          high level thinking skills, are students being provided with
          the opportunity to acquire those skills? The answer to that
          question is a disappointing NO! These skills are not being
          taught in the majority of the schools; students are left to
          discover them on their own. School curricula has
          traditionally been developed based on behavioral psychology
          foundations and traditional task analysis methods which lead
          to a focus on rote learning and physical and basic skill
          development.
              Because contemporary curriculum needs to emphasize
          understanding rather than rote memorization and heighten
          higher level cognitive skills in addition to physical and
          basic skills, curriculum development is more complex than
          it has been in the past. Part of the difficulty in
          developing curriculum that emphasizes intellectual processes
          is the fact   that these processes occur only in the mind
          and are therefore not directly observable to the curriculum
          developer. In addition, good thinkers and problem solvers do
          not know how they think and solve problems because intel-
          lectual processes become so automated that they occur
          instinctively (Ericsson & Simon, 1984). Because the
          intellectual processes are not directly observable, teachers
          often neglect these processes in their instruction.
              Zuga (1985) acknowledges that there have been few
          attempts to design and operationalize an intellectual
          processes curriculum; partly because of the lack of a co-
          herent framework. However, recent research in cognitive
          psychology has provided conceptions and techniques for
          identifying intellectual processes. Findings from these
          studies can provide an initial framework for the development
          and implementation of an intellectual processes
          curriculum.
 
          The Content of an Intellectual Processes Curriculum
              Before laying the groundwork for an intellectual
          processes curriculum, conceptual and operational definitions
          of intellectual processes are needed. Intellectual processes
          are those mental operations which enable one to acquire new
          knowledge, apply that knowledge in both familiar and
          unique situations, and control the mental processing that is
          required for knowledge acquisition and use.
              There are many paradigms which attempt to describe
          intellectual processes. In this article, the framework
          provided by Marzano, Brandt, Hughes, Jones, Presseisen,
          Rankin, and Suthor (1988) will be used to depict in-
          tellectual processes. Through a synthesis of recent
          research, Marzano et al. identified five, nondisparate
          dimensions of thinking; (a) thinking processes, (b) core
          thinking skills, (c) critical and creative thinking, (d)
          metacognition, and (e) the relationship of content to
          thinking. These five dimensions become the focus of an
          intellectual processes curriculum.
 
          Thinking Processes
              Thinking processes are complex mental operations which
          result from a combination of specific thinking skills.
          Marzano et al. (1988) identify eight thinking processes
          which are used during knowledge acquisition and use. The
          first three processes (i.e., concept formation, principle
          formation, and comprehension) are used primarily to acquire
          new knowledge. The next four processes (i.e., problem
          solving, decision making, inquiry, and composition) are
          used primarily during the application of knowledge. The
          final process, oral discourse, is used during both knowledge
          acquisition and knowledge application.
 
          Core Thinking Skills
              Core thinking skills are the specific mental operations
          that are used in combination to achieve a particular goal
          (Marzano et al., 1988). It is the unique combination of
          these core thinking skills which define the broader thinking
          processes identified above. Marzano et al. have generated a
          list of 21 core thinking skills which they have grouped into
          eight broad categories. The following list of thinking
          skills is not all inclusive, however, it does provide a way
          of organizing the specific skills which students must learn
          in order to become good thinkers (see Figure 1).
 
Focusing Skills                   Analyzing Skills
1. Defining problems              11. Identifying attributes and components
2. Setting goals                  12. Identifying relationships and patterns
                                  13. Identifying main ideas
Information Gathering Skills      14. Identifying errors
3. Observing
4. Formulating questions          Generating Skills
                                  15. Inferring
Remembering Skills                16. Predicting
5. Encoding                       17. Elaborating
6. Recalling
                                  Integrating Skills
Organizing Skills                 18. Summarizing
7. Comparing                      19. Restructuring
8. Classifying
9. Ordering                       Evaluating Skills
10. Representing                  20. Establishing criteria
                                  21. Verifying
 
     Figure 1. Core Thinking Skills (Marzano et  al., 1988, pg. 69).
 
          Critical and Creative Thinking
              While many people equate critical and creative thinking
          with thinking processes, Marzano et al. (1988) suggest that
          they are unique aspects of all thinking irrespective of the
          type of process used. People can engage in varying degrees
          of creative and critical thinking while solving problems,
          making decisions, and conducting research. For example,
          when attempting to design a more efficient alternative
          energy collector, one student may develop a very creative
          solution while another student contemplates a typical
          design. Problem solvers may also differ greatly in the
          degree of critical thought used to reflect on the process
          needed to solve the problem.
 
          Metacognition
              Metacognition refers to one's awareness about their own
          thinking processes while performing specific tasks. Often
          called "strategic thinking," metacognition involves the
          planning that takes place before engaging in a thinking
          activity, regulation of one's thinking during the activity,
          and evaluation   of the appropriateness of one's thinking
          performance upon the completion of the activity.
 
          Relationship of Content Knowledge to Intellectual
          Processes
              A curriculum which focuses on the development of
          intellectual processes cannot be developed in isolation.
          Attempting to teach thinking skills without something to
          think about is like teaching computer-aided design
          principles without access to a computer; the theories and
          procedures can be talked about, but the necessary skills can
          never be fully developed.
              Early attempts to create instructional programs to
          develop intellectual processes were unsuccessful because
          they focused solely on the thinking skills essential for
          problem solving and neglected the importance of domain
          knowledge (Newell & Simon, 1972). Recent cognitive
          research clearly establishes the link between content
          knowledge and intellectual processes. The classic study by
          Chase and Simon (1973) found that the superior performance
          of chess masters could be attributed more to their ability
          to recognize board layout patterns from past experiences
          than to their hypothesized superior mental capability. In
          fact, Chase and Simon found that when the chess masters were
          confronted with unconventional chess layouts, the experts
          performed much like novices. A recent study by Chi,
          Feltovich, and Glaser (1984) also provides support for the
          importance of teaching intellectual processes within a con-
          text of a domain of knowledge. In a study of the thought
          processes of experts and novices in physics, Chi et al.
          found that the two groups approached mechanics problems very
          differently. The better performance by the experts was
          attributed to their deeper understanding of physics
          principles. Without this deep understanding of the domain,
          the novices' intellectual processes proved to be in-
          adequate for solving similar problems.
 
          The Structure of an Intellectual Processes Curriculum
              Given the importance of intellectual processes in this
          world of constant change, what kind of curriculum design can
          ensure that the processes are developed in students? The
          following discussion provides an initial framework for
          curricula which emphasize the development of intellectual
          processes.  Goals of an Intellectual Processes Curriculum
          Curricula which emphasize intellectual processes seek to
          develop the capacity for general and complex thinking
          skills. While not exhaustive, the following list identifies
          several key goals for a technology education curriculum
          which is designed to emphasize intellectual processes:
          1. Students should acquire a repertoire of cognitive and
             metacognitive skills and strategies that can be used when
             engaged in technological activity such as problem
             solving, decision making, and inquiry.
          2. Through explicit emphasis on intellectual processes,
             students should gain an awareness of the nature of
             thinking and their mental capability to control
             attitudes, dispositions, and development.
          3. Through the numerous experiential activities found in
             technology education curricula, students should be able
             to use thinking skills and strategies with increasing
             independence and responsibility.
          4. Because technology itself is interdisciplinary,
             students should attain high levels of knowledge in a
             variety of subject areas including technology,
             mathematics, science, social studies, and composition.
          5. Because learning occurs best when related to experience
             and transfers to situations similar to the conditions of
             learning, students should be provided with activities
             that closely represent real world situations and
             contexts.
 
          An Instructional Model for an Intellectual Processes
          Curriculum
              A variety of existing instructional models are
          appropriate for an intellectual processes curriculum.
          Possibly the most promising model of instruction for
          enhancing student intellectual processes is called cog-
          nitive apprenticeship (Collins, Brown, & Newman, 1989).
          Cognitive apprenticeship uses many of the instructional
          strategies of traditional apprenticeship but emphasizes
          cognitive skills rather than physical skills. Traditional
          apprenticeship contains three primary components; (a)
          modeling, (b) coaching, and (c) fading. In traditional
          apprenticeship programs, the master craftsman models
          expert behavior by demonstrating to the apprentice how to do
          a task while explaining what is being done and why it is
          done that way. By observing the master perform, the
          apprentice learns the correct actions and procedures and
          then attempts to copy them on a similar task. The master
          then coaches the apprentice through the task by providing
          hints and corrective feedback if needed. As the apprentice
          becomes more skilled, the master gives the apprentice more
          and more control over the task by "fading" into the
          background. Another important aspect of apprenticeship
          includes the emphasis on "real world" activities which are
          appropriately sequenced by the master to fit the
          apprentice's current level of ability.
              Cognitive apprenticeship uses the same modeling,
          coaching, fading paradigm to enhance students' cognitive
          abilities. During the modeling phase of cognitive
          apprenticeship, the instructor shows students how to
          complete a task or solve a problem while verbalizing the
          activity. However, in contrast to typical school
          instruction, the activity is modeled within the context of
          real world situations. For example, if a lesson deals with
          the concept of recycling, an activity for students should be
          designed around a real  problem such as the development of a
          community recycling program. As an introduction to this
          lesson, the instructor should work through a similar problem
          with the class to model the thinking processes to be used.
          By modeling the desired intellectual processes, students
          will discover that there are many ways to solve problems,
          that experts make mistakes, and that seemingly simple
          problems are very complex in the real world.
              Following the modeling of the desired processes,
          instructors need to become coaches. This involves observing
          students while they carry out a task, analyzing their
          performance, and providing hints and assistance if needed.
          Finally, as the students' cognitive skills become more
          accomplished they will be able to perform with less and less
          instructor intervention. This fading aspect of cognitive
          apprenticeship results in the gradual transfer of
          responsibility for learning from teacher to student.
              In addition to the three primary components, the
          cognitive apprenticeship model includes several other
          defining characteristics. These characteristics include
          increasing complexity and diversity in lesson sequences and
          providing a learning environment which promotes intrinsic
          motivation, cooperation, and competition (Collins et al.,
          1989). For example, the student space simulation activity at
          McCullough High School in The Woodlands, Texas began as an
          activity in one class and quickly expanded into a project
          which involved virtually every program in the school. This
          project also generated considerable interest and cooper-
          ation among students and teachers due to its real world
          relevance (McHaney & Bernhardt, 1989).
 
          Instructional Principles for Developing Intellectual
          Processes
              Five broad, general principles emanate from the
          cognitive research literature which   emphasize the
          development of intellectual processes (Thomas, Johnson,
          Cooke, DiCola, Jehng, & Kvistad, 1988). Those principles
          include making thinking and learning easier, building on
          what students already know, facilitating information
          processing, facilitating "deep thinking," and making
          thinking processes explicit. The following list identifies
          the instructional principles which are used to enhance
          intellectual processes. See Thomas et al. (1988) for more
          detailed descriptions of these principles.
 
              Principle 1: Help Students Organize  Their Knowledge.
          Research shows that experts are able to process large
          amounts of information when solving problems while novices
          often get "mentally bogged down" when confronted with lots
          of information. Instruction to improve intellectual
          processes must reduce the overload on student's working
          memory in order to enhance their ability to learn and solve
          problems. One way to reduce the "load" on working memory is
          through the use of an external memory. Use of an external
          memory enables problem solvers to keep track of where they
          are in the process of solving a problem, thereby easing the
          load on working memory (Larkin, 1988). External memories
          can be as simple as a bill of materials for a project or as
          complicated as a diagram of an electronic device or complex
          social system. Concept mapping is another form of external
          memory that helps students organize new information (Novak,
          Gowin, & Johansen, 1983).
 
              Principle 2: Build on What Students Already Know.
          Learning theories state that the ability to gain and use new
          knowledge is greatly affected by the knowledge students
          bring to a learning situation. Students use their existing
          knowledge to interpret and understand what is presented
          each day. If a student does not come to class with the ap-
          propriate prerequisite knowledge, the student will have
          difficulty understanding and remembering the new content.
          In essence, prerequisite knowledge serves as an "anchor"
          to hold new information in memory. Without an appropriate
          anchor in the student's memory, the new information will
          simply "float away." As a result, in order for learning to
          take place, teachers must be sure that students have the
          prerequisite knowledge needed to learn. Two instructional
          techniques which address this principle are advanced
          organizers and analogies.
 
              Principle 3: Facilitate Information  Processing.
          Cognitive science research has consistently indicated that
          the way something is learned influences later use of that
          knowledge. New knowledge is "indexed" in the mind when it
          is learned so that it can be easily found and retrieved when
          needed (Phye & Andre, 1986; Reiser, 1986). Indexing of
          information in memory is analogous to using a card catalogue
          to "index" books in a library. With such an indexing system,
          specific books can be identified and located easily. Conse-
          quently, instruction must ensure that new information is
          indexed in ways that make it accessible at a later time.
          Strategies which facilitate information processing include
          supporting instruction through written, verbal, and graphic
          materials, providing outlines and organizing schemas for
          new content, and using real world scenarios for examples and
          activities which match student interests and experiences.
 
              Principle 4: Facilitate "Deep Thinking."  Any
          instructional method that causes students to consciously
          work harder at learning will help them achieve the
          instructional outcomes. Thinking hard increases the clarity
          of new information and aids understanding and recall. One
          of the best ways to get students to think is to have them
          elaborate on the material. In general, elaboration means
          that students think about the meaning of the material,
          identify relationships to other information, connect new
          information to what is already familiar, and generate
          expectations, predictions, and questions about the mate-
          rial. Techniques such as cooperative learning, peer
          tutoring, and paired problem solving can be used to get
          students to think.
 
              Principle 5: Make Thinking Processes Explicit. There
          appears to be a growing consensus among researchers and
          teachers that it is beneficial to explicitly and directly
          teach students both the concept of metacognition and the use
          of metacognitive processes. When using direct instruction,
          teachers should explicitly teach strategies and skills by
          explaining not only what the strategy is, but also how,
          when, where, and why the strategy should be employed.
          Problem solving, decision making, planning, evaluating,
          and reflecting are all skills that can be reinforced in
          technology education classrooms. The direct teaching of
          these skills will improve student's overall performance by
          teaching them how to learn better rather than teaching them
          to perform isolated skills. In essence, the approach can be
          described by the old adage "Give people fish and they are
          fed for a day, but teach them to fish and they are fed for a
          lifetime."
 
          The Role of the Teacher
              For an intellectual processes curriculum to be
          effective, the instructor must view teaching as a
          cooperative learning venture between student and instructor.
          The instructor's role is not to transmit information to
          the student, rather, the instructor should serve as a
          facilitator for learning. This involves creating and
          managing meaningful learning experiences and stimulating
          student thinking through questions and probes. Above all
          else, the instructor must be knowledge able about and pay
          close attention to student reasoning and thinking processes.
              An excellent example of the role of the teacher in an
          intellectual processes curriculum has been developed for
          teaching mathematical problem solving (Schoenfeld, 1983).
          In this approach, Schoenfeld teaches a set of problem
          solving strategies for solving mathematical problems to
          his students. His teaching involves showing students how he,
          as a mathematician, solves problems. However, unlike most
          teachers, he does not work the problems out in advance in
          order to show the students a smooth and successful solution.
          He even encourages his students to bring problems to class
          for him to solve. By being confronted with unfamiliar
          problems, Schoenfeld is forced to solve them as a math-
          ematician would; by using a variety of strategies and by
          making errors. Through this technique, the students have the
          opportunity to see that there are many ways to solve
          mathematics problems and that even expert mathematicians
          make mistakes.
              Schoenfeld does not stop his problem solving activity
          when an answer has been found because mathematicians in the
          "real world" continue looking for alternative solutions,
          easier methods to solve the problem, and then attempt to
          generalize the solution to other problems.
              Because technology education content is often taught
          through a problem solving method, Schoenfeld's instructional
          approach can be easily adapted to the technology education
          classroom. Technology teachers need to act like
          technologists in their classrooms. They need to solve
          unfamiliar technological problems for students and not be
          afraid to make errors or have difficulties finding
          solutions. By serving as a role model, technology teachers
          can show students how to collect and use information to
          solve technological problems and help them realize  that not
          all problems have straight forward and simple solutions.
 
          Evaluation of an Intellectual Processes Curriculum
              Evaluating student attainment of the desired
          intellectual processes is the weakest component of this
          curricular approach. Evaluation for this type of
          curriculum must focus on the acquisition of complex
          intellectual skills. However, because students' intellec-
          tual processes are not directly observable, it is difficult
          to determine when students have reached the desired level of
          performance. Current approaches to evaluation through
          written examinations are not adequate for testing the
          attainment of intellectual processes. Instructors are left
          with evaluation methods which rely on their intuitive
          skills to subjectively assess student intellectual
          abilities. Clearly, considerable research in this area is
          needed.  Constraints to an Intellectual Processes Cur-
          riculum While there are many reasons for developing an
          intellectual processes curriculum there are also several
          obstacles which must be faced by curriculum designers
          (Miller & Seller, 1985). First, the intellectual processes
          curriculum can be criticized for its narrowness. An
          intellectual processes curriculum focuses primarily on
          left-brain oriented logical thinking and problem solving
          while ignoring the more intuitive, rightbrain thinking.
          However, a well planned curriculum which incorporates
          learning experiences with ill-structured, designoriented
          problems may help avoid this constraint.
              A second constraint faced by an intellectual
          processes curriculum involves a perception that many of
          the learning experiences can be characterized as "playing
          school, scientist, or engineer." To counteract this po-
          tential constraint, students need to see the relevance of
          the activities and be allowed to act on the issues so
          problem solving is integrated at a deeper, more holistic
          level.
              Third, intellectual processes curricula can be
          criticized for its apparent neglect of content knowledge. On
          the surface an intellectual processes curriculum can
          appear to focus solely on thinking. However, as indicated
          earlier, an intellectual processes curriculum cannot be
          effective unless it includes a substantial amount of
          emphasis on content knowledge. As a result, this con-
          straint can be resolved by developing high quality
          curricula.
 
          Summary
              Building on the assumption that the most important
          skill for the future is the ability to think, an initial
          framework for an intellectual processes curriculum theory
          has been described. While it is acknowledged that the
          curricular framework is incomplete, it is hoped that a
          critical examination and elaboration of the framework will
          be undertaken by technology educators. Many of the exemplary
          programs described in recent issues of The  Technology
          Teacher (McHaney & Bernhardt,  1988; Thode, 1989a; Thode,
          1989b) and TIES  magazine (Craig, 1990; Neuman, 1991; Todd &
          Hutchinson, 1991) contain aspects of the proposed
          intellectual processes curriculum and should serve as a
          testing ground for further refinements of this initial
          framework.
 
          References
 
          Chase, W.G. & Simon, H.A. (1973). Perceptions in chess.
              Cognitive Psychology, 4,  55-81.
          Chi, M.T.H., Feltovich, P.J. & Glaser, R. (1984).
              Categorization and representation of physics problems
              by experts and novices. Cognitive Science, 5,
              121-152.
          Collins, A., Brown, J.S. & Newman, S.E. (1989). Cognitive
              apprenticeship: Teaching the craft of reading,
              writing and mathematics. In L.B. Resnick (Ed.), Know-
              ing, learning, and instruction: Essays in honor of
              Robert Glaser. Hillsdale, NJ:  Erlbaum.
          Craig, D. (1990). A Martian chronicle. TIES, 2(5), 29-31.
          Eisner, E.W. & Vallance, E. (1974). Conflicting
              conceptions of curriculum.  Berkeley, CA: McCutchan.
          Ericsson, K.A. & Simon, H.A. (1984). Protocol analysis.
              Cambridge, MA: The MIT  Press.
          Grubb, W.N. (1984). The bandwagon once more: Vocational
              preparation for high-tech occupations. Harvard
              Business Review, 54(4), 429-451.
          Johnson, S.D. (1991). Productivity, the workforce, and
              technology education. Journal of Technology Education,
              2(2),  32-49.
          Larkin, J.H. (1988). Display-based problem solving. In D.
              Klahr & K. Kotovsky (Eds.), Complex information
              processing:  The impact of Herbert A. Simon (pp. 1-39).
              Hillsdale, NJ: Erlbaum.
          Marzano, R.J., Brandt, R.S., Hughes, C.S., Jones, B.F.,
              Presseisen, B.Z., Rankin, S.C. & Suthor, C. (1988).
              Dimension of  thinking: A framework for curriculum and
              instruction. Alexandria, VA: Association  for
              Supervision and Curriculum Development.
          McHaney, L.J. & Bernhardt, J. (1989). The central project
              model: A practical approach to interdisciplinary
              education. In T.L. Erekson & S.D. Johnson (Eds.), Pro-
              ceedings of Technology Education Symposium  XI,
              Technology education: An interdisciplinary endeavor
              (pp.1-9). Champaign, IL:  Department of Vocational and
              Technical Education, University of Illinois at
              UrbanaChampaign.
          McHaney, L.J. & Bernhardt, J. (1988). The Woodlands, Texas.
              The Technology Teacher,  48(1), 11-16.
          Miller, J.P. & Seller, W. (1985). Curriculum  perspectives
              and practice. New York:  Longman Inc. 
          Neuman, J. (1991). Hooked on learning at the Minnesota science
              museum. TIES, 3(4),  26-33.
          Newell, A. & Simon, H.A. (1972). Human problem solving.
              Englewood Cliffs, NJ:  Prentice-Hall.
          Novak, J.D., Gowin, D.B. & Johansen, G.T. (1983). The use of
              concept mapping and knowledge vee mapping with junior
              high school science students. Science Education, 67,
              625-645.
          Phye, G.D. & Andre, T. (1986). Cognitive  classroom
              learning: Understanding, thinking, and problem
              solving. Orlando, FL:  Academic.
          Reiser, B.J. (1986). The encoding and retrieval of
              memories of real-world experiences. In J.A. Galambos,
              R.P. Abelson, & J.B. Black (Eds.), Knowledge structures
              (pp. 71-99). Hillsdale, NJ: Erlbaum.
          Schoenfeld, A.H. (1983). Problem solving in the mathematics
              curriculum. Washington,  DC: The Mathematical
              Association of America.
          Thode, B. (1989a). Applying higher level thinking skills.
              The Technology Teacher,  49(2), 6-13.  Thode, B.
              (1989b). Technology education in the elementary school.
              The Technology  Teacher, 49(1), 12-15.
          Thomas, R.G., Johnson, S.D., Cooke, B., DiCola, C., Jehng,
              J. & Kvistad, L. (1988). Cognitive science research as
              a  basis for instructional design: Implications for
              vocational education (Unpublished technical report).
              Berkeley, CA: National Center for Research in
              Vocational Education.
          Todd, R. & Hutchinson, P. (1991). Design & technology: Good
              practice and a new paradigm. TIES, 3(3), 4-11.
          Zuga, K.F. (1989). Relating technology education goals to
              curriculum planning. Journal of Technology Education,
              1(1), 34-58.
 
 
          ______________________________________________________________________________
          Scott D. Johnson is Assistant Professor and Chair, Technology
          Education Division, Department of Vocational and Technical
          Education, University of Illinois at Urbana-Champaign, Champaign,
          IL. The preparation of this article was supported in part by the
          National Center for Research in Vocational Education, under a grant
          from the Office of Vocational and Adult Education, U. S. Department
          of Education. This article has not been reviewed by the National
          Center and is not an official publication of the Center.
 
         

 
Journal of Technology Education   Volume 3, Number 2       Spring 1992

DLA Ejournal Home | JTE Home | Table of Contents for this issue | Search JTE and other ejournals