JTE v2n2 - Implementing Technology Education Problem-Solving Activities
Volume 2, Number 2
Spring 1991
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.
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Journal of Technology Education Volume 2, Number 2 Spring 1991