Journal of Technology Education


JTE Editor: Mark Sanders

Volume 2, Number 2
Spring 1991


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

Implementing Technology Education Problem-Solving Activities
 
                        V. William DeLuca
 
               Teaching students how to solve problems
          is an important goal of education and indus-
          trial arts/technology education has had a
          long history of providing an environment for
          developing these skills.  The congruence of
          technology education and problem solving is
          based on the fact that technologies are, in
          many ways, a product of problem solving.
          Technological problems require the applica-
          tion of knowledge from many different disci-
          plines and the laboratory provides a medium
          to develop and test solutions.
               Greenfield (1987, p. 20) suggests that
          students do not acquire thinking skills sim-
          ply by practice in problem solving, drill, or
          osmosis. Problem-solving activities must be
          implemented with careful planning to insure
          intended student outcomes. Curriculum plan-
          ning must involve careful consideration of
          the goals of problem-solving instruction, how
          an activity fits in relation to the goals,
          and the teaching style that would best facil-
          itate goal attainment. Also, there is a dif-
          ference between the product and the process
          when considering the value of problem-solving
          activities.  Perkins (1986, p. 7) cautions
          against focusing on the products we produce
          and only indirectly the process by which we
          produce them. Specifically, how to proceed in
          a stepwize fashion to reach a goal.  The es-
          sence of problem-solving is the application
          of knowledge and process that leads to a sol-
          ution. Like any skill, the problem solver
          must acquire knowledge related to the prob-
          lem, thinking skills needed to process this
          knowledge, and the ability to identify and
          apply appropriate processes to reach a sol-
          ution.
 
                    PROBLEM-SOLVING PROCESSES
               Problem solving is a process of resolv-
          ing a known difficulty. Anderson (1980) em-
          phasizes the processes undertaken during the
          act of problem solving by defining this be-
          havior as goal directed sequence of oper-
          ations-- an organized sequence of mental
          steps.  Accordingly, several different
          problem-solving processes have been docu-
          mented. Brightman (1981) discussed a process
          model first proposed by John Dewey in 1933.
          The three step process included the diagnosis
          phase, analysis phase, and solution phase.
          Other, more specific, models have been de-
          scribed by Polya (1971), Soloway (1988),
          Bransford & Stein (1984), Hatch (1988),
          Seymour (1987), and Devore (1987). Following
          are summaries of these problem-solving proc-
          esses.
 
          1.  Troubleshooting/Debugging: Isolate the
              problem, identify possible cause, test,
              implement solution, test solution.
          2.  Scientific Process: Observation, develop
              hypothesis, experimentation, draw conclu-
              sion.
          3.  Design Process: Ideation/brainstorm,
              identify possible solution, prototype,
              finalize design.
          4.  Research and Development: Conceptualize
              the project, select research procedure,
              finalize research design, develop pro-
              posal, conduct research, analyze result,
              report result, evaluate research project.
          5.  Project Management: Identify project
              goal, identify tasks to reach the goal,
              develop a plan to accomplish the tasks,
              implement the plan, evaluate the plan.
 
               The problem type determines the appro-
          priate process to select and use. Therefore,
          the task of the problem solver is to select
          the best process for a given problem. To se-
          lect from these processes, the problem solver
          must understand each process and how and when
          to use the appropriate one. Advanced problem
          solvers perceive the process of solving prob-
          lems as a cycle and selected processes or
          subprocesses are used when needed.
 
                         THINKING SKILLS
               The mental abilities needed to solve
          problems are not fully understood because of
          the many levels and integrations of knowledge
          sets that are manifested in the act of solv-
          ing problems. In its simplest form, problem-
          solving involves the application of recalled
          knowledge. Woods (1987, p. 55) discusses the
          importance of a knowledge base pertinent to
          the content of the problem and further ex-
          plains the value of the problem solver's
          ability to identify, locate, and evaluate
          missing information needed in the problem-
          solving process. These thinking skills, as
          they relate to technology education, may be
          classified as follows:
 
          1.  Prior Technological Knowledge: Knowledge
              and skills gained from previous study in
              technology education class.
          2.  Related Knowledge: Knowledge gained from
              classes other than technology education
              such as math and science.
          3.  Knowledge Seeking: Ability to identify
              missing information, and locate and ob-
              tain relevant information.
 
               Higher order thinking skills involve the
          processing of knowledge in memory. In this
          respect, thinking is the process of changing
          knowledge.  Comparing ordinary thinking and
          good thinking, Lipman (1988, p. 40) uses
          terms such as estimating, evaluating, classi-
          fying, assuming, and hypothesizing to define
          good thinking. Similar thinking processes
          have been identified by Bloom (1956); Duke
          (1985); Kurfman & Cassidy (1977); and
          Feuerstein, Rand, Hoffman, & Miller (1980).
          Presseisen (1985, p.45) classified thinking
          skills as follows:
 
          1.  Qualifications -- finding unique
              characteristics: units of basic identity,
              definitions, facts, problem/task recogni-
              tion.
          2.  Causations -- establishing cause and ef-
              fect, assessment: predictions, infer-
              ences, judgments, evaluations.
          3.  Transformation -- relating known to un-
              known characteristics, creating meanings:
              analogies, metaphors, logical inductions.
          4.  Relationships -- Detecting regular
              operations: parts and wholes, patterns,
              analysis and synthesis, sequence and or-
              der, logical deduction.
          5.  Classification -- determining common
              qualities: similarities and differences,
              grouping and sorting, comparisons,
              either/or distinctions.
 
               This list encompasses the thinking
          skills presented in the literature. The five
          categories describe ways people mentally
          process knowledge to change its form and
          function.
 
                   TEACHING METHODS AND STYLES
               When implementing problem-solving activ-
          ities, the level of achievement is determined
          by the teaching methods used to initiate and
          maintain students' goal directed behaviors.
          Maley (1978) describes 15 teaching methods
          appropriate for industrial arts. Nader (1984)
          and Costa (1984) also referenced similar
          methods in addition to several other commonly
          used teaching methods. Refer to Table 2 col-
          umn 4 for a listing of these methods.
               Which of these methods are best for de-
          veloping students' problem-solving skills?
          Given the diversity of technology education
          content and the need to teach basic content
          and skills, this question is not easily an-
          swered. When students have had no experience
          with the subject matter, recall is the start-
          ing point. Basic knowledge and skills may
          best be taught with a lecture-demonstration
          teaching approach. To develop problem-solving
          skills, Sternberg & Martin (1988), and
          Nickerson, Perkins, & Smith (1985) recommend
          deemphasizing lecture. These researchers
          point out the value of encouraging inter-
          action between student and teacher and main-
          taining a balance between structure and
          unstructured learning environments.
               The teaching style defines the inter-
          action of student and teacher. The steps in-
          volved in developing problem-solving skills
          move the student from teacher dependence to
          independence. Sternberg & Martin (1988, p.
          569) describe a four step process beginning
          with direct instruction followed by intra-
          group problem solving, intergroup problem-
          solving, and individual problem solving.  The
          process begins by fostering teacher-to-
          student interaction then encouraging student-
          to-student interaction. When students
          internalize the problem-solving skills, indi-
          vidual problem-solving skills can be devel-
          oped.
               Problem-solving activities implemented
          in technology education are characterized by
          the problem-solving processes and thinking
          skills that are taught. The teaching method
          and teaching style determine the environment
          in which learning occurs. The interactions of
          these variables define the level of student
          development on the continuum of problem-
          solving performance.
               Problem solving, whether direct or indi-
          rect, has long been a part of technology edu-
          cation because of the nature of technological
          content. To continue to develop and improve
          technology education problem-solving activ-
          ities, it is worthwhile to establish a
          baseline that quantifies the best in current
          practices. The purpose of this study was to
          identify and describe problem-solving proc-
          esses, thinking skills, teaching methods, and
          teaching styles typically used by technology
          education teachers that were recognized for
          their teaching excellence.
 
                           METHODOLOGY
          SUBJECTS
               The sample consisted of 44 technology
          education teachers from the population of
          teachers recognized for their teaching excel-
          lence. Two groups of teachers were identified
          to participate in this study. One group con-
          sisted of the International Technology Educa-
          tion Association's 1989 Teacher of the Year
          award winners and members of the other group
          were nominated by state directors for
          technology/vocational education. State direc-
          tors were asked to nominate teachers from
          their state who were noted for providing in-
          struction of high quality and developing
          and/or implementing innovative learning expe-
          riences related to problem solving. Since the
          intent of this study was to describe the best
          in current practices, teachers of each group
          were asked to participate if they had suc-
          cessfully implemented innovative problem-
          solving activities.
               Twenty-two of the 44 ITEA Teachers of
          the Year award winners participated in the
          study. Twenty-two teachers nominated by state
          supervisors participated.  Twenty teachers
          taught high school students, 15 taught middle
          school students and 5 taught students at both
          the middle and high school level. Four teach-
          ers did not respond to the question regarding
          grade level.
 
          INSTRUMENTATION
               A survey instrument was designed to
          identify problem-solving activities that
          teachers had successfully implemented and
          variables associated with the implementation
          process. The survey consisted of two parts.
          In the first part, participants were asked to
          list and briefly describe one or more innova-
          tive problem-solving activities that they
          found to be positive student learning experi-
          ences. The second part of the survey con-
          tained 33 items. These items, included the
          variables that affect implementation of
          problem-solving activities as identified in
          the review of literature. A verbal frequency
          scale was used to measure the frequency of
          use of the five problem-solving processes de-
          scribed by Polya (1971), Soloway (1988),
          Bransford & Stein (1984), Hatch (1988),
          Seymour (1987), and Devore (1987); the eight
          thinking skills described by Woods (1987, p.
          55) and Presseisen (1985, p.45); and the 17
          teaching methods described by Maley  (1978),
          Nader (1984) and Costa (1984). Four questions
          were used to measure the continuum of
          teacher-to-student interaction as described
          by Sternberg & Martin (1988), and  Nickerson,
          Perkins, & Smith (1985).  Participants re-
          corded their responses to the second part of
          the survey on a CompuTest form using the fol-
          lowing verbal frequency scale: A = always, B
          = usually, C = occasionally, D = seldom and E
          = never. For data analysis, these response
          categories were coded on a one (i.e always)
          to five (i.e never) point ordinal scale.
 
                             RESULTS
               The participants identified and briefly
          described 109 activities, an average of 2.5
          activities per participant. Sixty-nine of
          these activities were different in title and
          description. The activities listed were used
          in a variety of grade levels ranging from 8th
          grade to post secondary. The subject area
          also varied. Teachers of CAD, construction,
          drafting, electronic communication, engineer-
          ing, exploring technology, general technology
          education, graphics communication, industrial
          technology, introduction to industry, intro-
          duction to technology, manufacturing, power
          and energy, product design, transportation,
          and woodworking reported the activities.
               Survey items were categorized according
          to problem-solving processes, thinking
          skills, teaching methods, and teaching
          styles. These items were used to determine
          typical techniques used by the teachers sur-
          veyed when they implemented problem-solving
          activities.
               A cluster analysis, the Ward's Method,
          was used to classify the set of variables
          into homogeneous groups based on similarity
          of response. With this analysis, the mean
          verbal frequency scores of each item were
          grouped to minimize the overall sum of
          squared within-cluster distances. Therefore,
          the clusters represent questionnaire items
          that shared similar frequency of use when
          teachers implemented problem-solving activ-
          ities. To understand the similarity of the
          items in each cluster and the differences be-
          tween the five clusters, Table 1 shows the
          characteristic response that items in each
          cluster share. For clarity the clusters were
          labeled according to mean rank of cluster
          characteristics, therefore cluster one re-
          presents items most frequently used and clus-
          ter five represents items least frequently
          used.
 
          TABLE 1
          CLUSTER CHARACTERISTICS
          ---------------------------------------------
          Cluster      Mean      MDN        SD
          ---------------------------------------------
 
          1            2.30      2.0       .966
 
          2            2.68      3.0       1.11
 
          3            3.07      3.0       1.20
 
          4            3.18      3.0       1.12
 
          5            3.96      4.0       1.08
 
          ---------------------------------------------
 
               The five clusters are summarized in Ta-
          ble 2.  Cluster one contained eight items.
          One problem-solving process, the design proc-
          ess, was a member of this cluster. The think-
          ing skills in this cluster included
          application of related knowledge gained from
          classes other than technology education and
          prior technological knowledge gained from
          technology education class. The teaching
          style clustered in this group was described
          as the teacher shared goals and objectives
          with the student and decisions
 
          TABLE 2
CLUSTER GROUPINGS OF SURVEY ITEMS
-------------------------------------------------------------------------------
Cluster  PS Process       Thinking Skills   Teaching Methods  Teaching Style
-------------------------------------------------------------------------------
 
1        Design Process   Related Knowledge Discussion        Goals are shared 
                                                              by teacher.  
                                                              Decisions
                          Prior             Demonstration     reached through
                          Technological                       agreement.
                          Knowledge         Experimentation
 
                                            Lecture
-------------------------------------------------------------------------------
2                                           Individual        Goals are set by
                                            Instruction       teacher.  Teacher
                                                              facilitates goal
                                            Media             attainment.
-------------------------------------------------------------------------------
3       Troubleshooting                     Discovery         Teacher directs 
                                                              all learning     
                                                              experiences.
        Scientific                          Simulation
 
        Project Management                  Readings
 
        Research & Develop                  Game-Structured
                                            Competition
-------------------------------------------------------------------------------
4                         Classification    Competency-based
 
                          Causations
 
                          Qualifications
 
                          Relationships
 
                          Knowledge Seeking
-------------------------------------------------------------------------------
5                                           Seminar           Student develops
                                                              goals and means
                                            Scenario          to reach them.
 
                                            Contract
 
                                            Case Study
 
                                            Panel Discussion
                                            Role Play
-------------------------------------------------------------------------------
 
          were reached through agreement.  The charac-
          teristics of this cluster, listed in Table 1,
          indicate that these methods were the most
          frequently used by technology teachers with a
          mean of 2.30.  Sixty-one percent of the
          teachers
 
          surveyed used the items listed in this clus-
          ter usually or always and 98.3% used them at
          least sometimes.
               Cluster two was characterized by mean of
          2.68.  Four items were always or usually used
          by 43.9% of the teachers. Individualized in-
          struction and media were teaching methods
          grouped in this cluster. The teaching style,
          like the teaching method, was teacher di-
          rected with goals and objectives set by the
          teacher and the teacher guided goal attain-
          ment. These methods and this style are condu-
          cive to attainment of basic level knowledge
          that is a prerequisite to successful problem
          solving.
               Cluster three contained items typically
          used often by the teachers surveyed. The mean
          response for items in this cluster was 3.07
          with 34.8% of the teachers using them always
          or usually. Four of the five problem-solving
          processes were part of this cluster.  They
          included troubleshooting/debugging, scien-
          tific process, research and development and
          project management. Teaching methods included
          in this cluster were discovery, simulation,
          and reading. The teaching style that was
          close to the mean of this cluster was one
          where the teacher directed all learning expe-
          rience.  Six of the eight thinking skills
          were grouped in cluster four. Competency
          based instruction was also grouped in this
          cluster. The characteristics of cluster four
          were similar to cluster three with 33.8% of
          the teachers using the members of this clus-
          ter usually or always.
               The items with the lowest frequency,
          typically seldom used, were grouped in clus-
          ter five. This cluster was characterized by a
          mean of 3.96 with 9.7% of the teachers sur-
          veyed indicating that they used the teaching
          methods and style usually or always. Seminar,
          scenario, contract, case study, panel dis-
          cussion and role play were members of this
          cluster. Also, the teaching style that was
          defined as students develop goals and objec-
          tives and the means to reach them was seldom
          used by the teachers surveyed.
 
                           DISCUSSION
               Problem-solving activities develop im-
          portant skills. They teach students how to
          think and provide them with opportunities to
          experience knowledge seeking, selection, ap-
          plication, and evaluation.  Implementing
          problem-solving activities means more than
          just giving students assignments. The out-
          comes of activities are dependent on the
          problem-solving processes and thinking skills
          that are taught and applied. The environment
          that fosters problem solving is created by
          the teaching methods and styles that define
          the teacher-to-student and student-to-student
          interaction.
               This study identified elements of
          problem-solving activities that were fre-
          quently used by a sample of technology educa-
          tion teachers recognized for their teaching
          excellence. The inferential qualities of the
          data are limited due to the sample size, but
          the cluster analysis does establish norms for
          describing the characteristics of technology
          education problem-solving activities. The
          typical activities required students to apply
          knowledge gained in technology education
          class as well as other classes.  The design
          process was used to structure a procedure for
          reaching a solution. Lecture, discussion,
          demonstration, and experimentation were meth-
          ods most frequently used to implement activ-
          ities. Teachers typically shared the goals of
          the activity with students and decisions were
          reached through agreement.
               The results represent a hierarchal
          paradigm that emphasizes the design process
          and application of knowledge learned in
          school.  Four of the five problem-solving
          processes and six of the eight thinking
          skills were typically used occasionally.  In-
          creasing the application of those elements
          less frequently used could be the focus for
          improving technology education problem-
          solving activities.  Relating to thinking
          skills, Feuerstein, Miller, Hoffman, Rand,
          Mintzker & Jensen (1981) have shown that the
          development of thinking skills increases
          problem-solving performance.  Narrol,
          Silverman & Waksman (1982) have shown that
          remedial students in vocational education
          programs benefit from thinking skill instruc-
          tion.
               The teaching methods used by teachers
          represent techniques that are associated with
          teaching low as well as high level cognitive
          skills. As discussed by Nickerson, Perkins, &
          Smith (1985, p. 327), the use of several
          teaching methods is common when implementing
          problem-solving activities. Often students
          need to gain basic knowledge to apply to the
          solution especially in a new area of study.
          The sequence of instruction then leads stu-
          dents to methods such as experimentation,
          game structured competition, and discovery
          that give them a more active role in know-
          ledge seeking. The teaching methods listed in
          cluster five were seldom used by the teachers
          surveyed. These methods are associated with
          developing cognitive skills associated with
          effective problem solving. Likewise, the
          teaching style used least frequently (cluster
          five) is associated with high-level perform-
          ance. Methods such as case study, contract
          and scenario could be used to focus activ-
          ities on current technological problems.
               This study showed that technology educa-
          tion is providing students with experiences,
          as defined by the literature cited, that de-
          velop valuable problem-solving skills. To im-
          prove technology education problem-solving
          activities, the intent of instruction and
          scope of problem-solving skill developed are
          the issues. If the intent of instruction is
          to focus on certain elements and treat others
          as subsets then a hierarchal paradigm should
          be the focus for further development. If the
          elements are to be treated with equal value
          then a paradigm representing a balance in
          scope should be pursued. With this paradigm,
          students should be taught to identify the
          problem type and select the appropriate proc-
          ess.
               As problem-solving activities continue
          to evolve, educators must insure that appro-
          priate processes and thinking skills are
          taught and teaching methods and styles allow
          students to grow. Curriculum developers
          should consider the variables identified and
          described in this study to analyze the
          paradigm that characterizes the learning po-
          tential of problem-solving activities within
          the scope and sequence of technology educa-
          tion instruction.
 
 
          ----------------
          V. William DeLuca is Assistant Professor, De-
          partment of Occupational Education, North
          Carolina State University, Raleigh, North
          Carolina.
 
                           REFERENCES
          Anderson, J.  (1980).  COGNITIVE PSYCHOLOGY
             AND ITS IMPLICATIONS.  San Francisco: W.
             H. Freeman & Co.
          Bloom, B.  (1956).  TAXONOMY OF EDUCATIONAL
             OBJECTIVES.  New York: David McKay.
          Bransford, J., & Stein, B.  (1984).  THE
             IDEAL PROBLEM SOLVER: A GUIDE FOR IMPROV-
             ING THINKING, LEARNING AND CREATIVITY.
             San Francisco: W. H. Freeman.
          Brightman, H. J.  (1981).  PROBLEM SOLVING: A
             LOGICAL AND CREATIVE APPROACH.  Atlanta:
             Business Publication Division, College of
             Business Administration.
          Costa, A. L.  (1984).  Mediating the
             metacognitive.  EDUCATIONAL LEADERSHIP,
             42(3), 57-62.
          Devore, P.  (1987).  A perspective for tech-
             nical research.  In E.  Israel & R. Wright
             (Eds.), CONDUCTING TECHNICAL RESEARCH.
             Mission Hills, CA: Glencoe Publishing Co.
          Duke, L. E.  (1985).  Seven cardinal princi-
             ples for teaching higher-order thinking.
             THE SOCIAL STUDIES, 76(3), 129-132.
          Feuerstein, R., Rand, Y., Hoffman, M., &
             Miller R.  (1980).  INSTRUCTIONAL
             ENRICHMENT.  Baltimore: University Park
             Press.
          Feuerstein, R., Miller, R., Hoffman, M.,
             Rand, Y., Mintzker, Y., & Jenson, M.
             (1981).  Cognitive modifiability in
             adolescence: Cognitive structure and the
             effect of intervention, THE JOURNAL OF
             SPECIAL EDUCATION, 1(2), 269-287.
          Greenfield, L. B.  (1987).  Thinking teaching
             through problem solving.  In James E.
             Stice (Ed.), DEVELOPING CRITICAL THINKING
             AND PROBLEM-SOLVING ABILITIES.  San
             Francisco: Jossey Bass Inc., pp. 5-22.
          Hatch, L.  (1988).  Problem Solving Approach.
             In W. Kemp and A.  Schwaller (Eds), In-
             structional Strategies for Technology Edu-
             cation.  Mission Hills, CA: Glencoe
             Publishing Company.
          Kurfman, D., & Cassidy, E.  (1977).  DEVELOP-
             ING DECISION-MAKING SKILLS.  Arlington,
             VA: The National Council for the Social
             Studies.
          Lipman, M.  (1988).  Critical thinking --
             what can it be?  EDUCATIONAL LEADERSHIP,
             46(1), 38-43.
          Maley, D.  (1978).  THE INDUSTRIAL ARTS
             TEACHER'S HANDBOOK.  Boston: Allyn & Bacon
             Inc.
          Nader, L.  (1984).  THE HANDBOOK OF HUMAN RE-
             SOURCE DEVELOPMENT.  New York: John Wiley
             & Sons.
          Narrol, H., Silverman, H., & Waksman, M.
             (1982).  Developing cognitive potential in
             vocational high school students.  JOURNAL
             OF EDUCATIONAL RESEARCH, 76(2), 107-112.
          Nickerson, R., Perkins D., & Smith E.
             (1985).  The teaching of thinking.
             Hillsdale, NJ: Lawrence Erlbaum Associ-
             ates.
          Perkins, D. N.  (1986).  Thinking frames, ED-
             UCATIONAL LEADERSHIP.  43(8), 4-10.
          Polya, G.  (1971).  HOW TO SOLVE IT.
             Princeton: Princeton University Press.
          Presseisen, B. Z.  (1985).  Thinking skills:
             Means and models.  In Arthur L. Costa
             (Ed.), DEVELOPING MINDS: A RESOURCE BOOK
             FOR TEACHING THINKING.  Alexandria, VA:
             Association for Supervision and Curriculum
             Development.
          Seymour, R. D.  (1987).  A model of the tech-
             nical research project.  In E. Israel & R.
             Wright (Eds.), CONDUCTING TECHNICAL RE-
             SEARCH.  Mission Hills, CA: Glencoe Pub-
             lishing Co.
          Soloway, A.  (1988).  Do you know what your
             children are learning?  In R. Nickerson
             (Ed.), TECHNOLOGY IN EDUCATION: LOOKING
             TOWARD 2020.  Hillsdale, NJ: Lawrence
             Erlbaum Associates.
          Sternberg, R., & Martin, M.  (1988).  When
             teaching thinking does not work, what goes
             wrong?  TEACHERS COLLEGE RECORD89(4),
             555-578.
          Woods, D. R.  (1987).  How might I teach
             problem solving?  In James Stice (Ed.),
             DEVELOPING CRITICAL THINKING AND
             PROBLEM-SOLVING ABILITIES.  San Francisco:
             Jossey Bass Inc.


          Permission is given to copy any
          article or graphic provided credit is given and
          the copies are not intended for sale.
 
Journal of Technology Education   Volume 2, Number 2       Spring 1991

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