Research Prospectus:
LEARNING STRATEGY PREFERENCES, VERBAL-VISUAL COGNITIVE STYLES, AND
MULTIMEDIA DESIGN PREFERENCES OF ENGINEERS FROM JOHN ZINK, A
MIDWESTERN MANUFACTURING COMPANY
By
CHARLES E. BAUKAL, JR.
OKLAHOMA STATE UNIVERSITY
DISSERTATION COMMITTEE
____________________________________
Lynna Ausburn, Committee Chair
____________________________________
Chad Depperschmidt
____________________________________
Belinda McCharen
____________________________________
Khaled Sallam
____________________________________
Floyd Ausburn
TABLE OF CONTENTS
INTRODUCTION .......................................................................................................................... 1
CONTEXT AND SETTING FOR THE STUDY ........................................................................... 2
MULTIMEDIA AND LEARNING ................................................................................................ 4
LEARNING STRATEGY AND STYLE PREFERENCES OF ADULT LEARNERS ................ 7
THEORETICAL AND CONCEPTUAL FRAMEWORK ............................................................. 9
Dale’s Cone of Experience ....................................................................................................... 9
Mayer’s Cognitive Theory of Multimedia Learning .............................................................. 10
Multimedia Cone of Abstraction: A Proposed Update of Dale’s Cone of Experience .......... 12
STATEMENT OF THE PROBLEM ............................................................................................ 16
PURPOSE OF THE STUDY ........................................................................................................ 17
RESEARCH QUESTIONS .......................................................................................................... 18
DEFINITIONS OF KEY TERMS ................................................................................................ 19
Conceptual Definitions ........................................................................................................... 19
Operational Definitions ........................................................................................................... 20
METHODOLOGY ....................................................................................................................... 21
General Research Design ........................................................................................................ 21
Variables and Design Controls ............................................................................................... 21
Population and Sample ........................................................................................................... 23
Instrumentation ....................................................................................................................... 24
Procedures ............................................................................................................................... 24
Data Analysis .......................................................................................................................... 29
Timeline for Conducting the Study......................................................................................... 31
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LIMITATIONS AND ASSUMPTIONS OF THE STUDY ......................................................... 31
Limitations .............................................................................................................................. 31
Assumptions............................................................................................................................ 32
SIGNIFICANCE OF THE STUDY.............................................................................................. 32
PLANNED LITERATURE REVIEW .......................................................................................... 33
REFERENCES ............................................................................................................................. 33
APPENDIX A – MULTIMEDIA COMBINATIONS ................................................................. 41
APPENDIX B – SURVEY ........................................................................................................... 42
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LEARNING STRATEGY PREFERENCES, VERBAL-VISUAL COGNITIVE STYLES, AND
MULTIMEDIA DESIGN PREFERENCES OF ENGINEERS FROM JOHN ZINK, A
MIDWESTERN MANUFACTURING COMPANY
Introduction
Continuing education is critical for working engineers because of the breadth of processes and
equipment they design and use and because of rapid changes in technology. For example, plant
engineers take courses to learn how to operate different types of equipment specific to their
operations (Valencia, Link, Baukal, & McGuire, 2008). This training takes a variety of forms
including traditional classroom, on-the-job, and computer-based training (CBT). Classroom
training is led by an instructor or facilitator. In on-the-job training, a more-experienced employee
trains a less-experienced colleague on specific procedures and operations. This is usually less
structured but more personalized than classroom training. CBT involves course materials
delivered by computer, often over the Internet (Baukal, 2010).
Moore and Kearsley (2005) identified two general types of online training: synchronous and
asynchronous. In synchronous training, an instructor and one or more students are online at the
same time, interacting with each other in real time. In asynchronous training, the participants are
not usually online at the same time and the courses may or may not be instructor-led. Online
courses without an instructor are generally referred to as standalone or self-directed (Horton &
Horton, 2003) and are typically used to provide learners with information but not usually to teach
new skills (Colbrunn & Van Tiem, 2002). Many companies use asynchronous self-directed
courses to provide their employees with periodic legal, safety, and environmental training. These
courses are generally short in length and can be completed at the convenience of the participants.
Instructional and graphic design are major challenges for self-directed courses. They are often
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poorly designed with too much text, not enough graphics, and very little interaction between
learners and course materials or each other. These courses are frequently developed by subject
matter experts who know the content but not instructional design principles. Poor design and
weak learner appeal are problematic because employees have no option to avoid or opt out. They
must take these mandatory courses, frequently with the attitude of completing them as quickly as
possible. This situation and its detrimental effect on employee learning as an important aspect of
a company’s human capital provided the impetus for this study.
Context and Setting for the Study
The John Zink Company (JZC), headquartered in Tulsa, Oklahoma, manufactures combustion
equipment which is used in refineries and chemical plants worldwide (Baukal, 2001). The
participants in the proposed research will be engineers working at JZC who develop, sell, design,
manufacture, test, and service that equipment. The John Zink Institute (JZI) is an organization
within JZC that offers technical training to customers and employees on JZC’s equipment. JZI
represents the training model popularized late in the 20th century under the general name of the
corporate university. Meister (1998) defined a corporate university as a “. . . centralized strategic
umbrella for the education and development of employees . . . [which] is the chief vehicle for
disseminating an organization’s culture and fostering . . . job skills, but also . . . core workplace
skills. . . .” (p. 38).
Shorter versions of the JZI courses are given in the company plants (Gilder, Campbell,
Robertson, & Baukal, 2010; Valencia, Link, Baukal, & McGuire, 2008), while the more
comprehensive versions are offered at JZI’s training facility in Tulsa, Oklahoma. A popular twoday face-to-face class called Process Burner Fundamentals has an online course prerequisite that
must be completed before students come to Tulsa for the face-to-face course (Baukal, 2008).
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This short online course, referred to as Process Burner Theory, was designed by this researcher
and consists of 16 modules that take approximately 15 minutes each to complete. The primary
students taking these classes are adult engineers working in refineries and chemical plants who
need this knowledge to safely and efficiently operate process burners while minimizing pollution
and downtime.
Self-directed asynchronous online courses can be used for several specific purposes. Two
common functions are (1) to teach fundamental principles, and (2) to supplement classroom
training (Baukal, 2008). These functions help ensure all students have at least a minimum
knowledge level before taking a course. In Process Burner Fundamentals, students need to have
some basic knowledge of combustion, heat transfer, and fluid flow. In the original version of the
classroom course, some students felt too much time was spent on those basics while others felt
not enough time was spent. This was one reason for developing the online theory course so
students could go as slow or as fast as they wanted as long as all modules are completed prior to
attending the face-to-face Process Burner Fundamentals course.
The modules in the online course were originally taught at the beginning of the face-to-face
course. The instructors struggled to cover the course materials in the allotted two days. Another
reason for developing the online course was to move three hours of content out of the face-toface course to give instructors more time to cover other content. However, in moving the
instructional content from its original classroom context, little effort was made to adapt the
materials specifically for online instruction. This may have created weak instructional designs
for the online modules.
Online courses need to be well designed. Many are mandatory for company employees and must
be taken repeatedly, so it is particularly important that they are well designed because the content
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is important enough that it must be refreshed on a regular basis. Self-directed asynchronous
online courses must be well designed so students can easily complete the materials and master
the content on their own. Because of their increasing usage, it is important that online courses are
properly designed both to increase student learning and to motivate students to take them
(Martens, Bastiaens, & Kirschner, 2007). Despite extensive literature review, the researcher
found no recommendations for designing online courses for the continuing education of
professional engineers. Much research has been done on educating engineering students, but
apparently very little on the continuing education of working engineers. This suggested to the
researcher a need for empirical study in this area.
Multimedia and Learning
Because multimedia itself does not require an instructor for delivery, it can be used in a variety
of educational settings, including the self-directed online context of interest in this study.
Research has shown that multimedia used in online courses can be as effective as a traditional
classroom, for a wide range of topics. For example, Buzzell, Chamberlain, and Pintauro (2002)
showed that web-based tutorials incorporating multimedia were as effective as traditional
classroom lectures for teaching human body composition analysis. Kekkonen-Moneta and
Moneta (2002) found that online students performed as well as classroom students in an
introductory computer course where multimedia was incorporated into the online version of the
course. Aly, Elen, and Willems (2004) experimentally determined that an online instructional
program incorporating multimedia was as effective as traditional lectures for undergraduate
training in orthodontics. Backer (2005) showed experimentally that students taking a technology
and civilization hybrid (online + classroom) course with multimedia performed as well as or
better than students taking the same course in a traditional classroom. Stephenson, Brown, and
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Griffin (2008) found that students using online modules incorporating multimedia outperformed
students taking traditional lectures on human genetics.
Not all forms of multimedia are equally preferred in instructional settings. It is often naturally
assumed that dynamic visuals such as videos and animations are superior to static visuals (i.e.,
the dynamic media hypothesis) such as photographs and drawings because of their ability to
show temporal relationships (Hegarty, 2004; Lowe, 1999). The transient nature of dynamic
visuals can help learners develop dynamic mental models (Kozma, 1991). Many studies have
found that students prefer dynamic over static visuals (e.g., Smith & Woody, 2000), and a slight
but statistically significant improvement in learning has been documented (e.g., Rieber, 1991).
Baek and Layne (1988) found performance ranged from highest to lowest for students viewing
presentations with: (1) animations, (2) static graphics, and (3) text only. Höffler and Leutner
(2007) did a meta-analysis of 26 primary studies that compared dynamic and static visualizations
and found a statistically significant advantage for animations over static pictures. Lin and Dwyer
(2010) found a statistically significant learning advantage measured with four different types of
tests for students viewing animations compared to those viewing static pictures. These are
examples of studies that showed learning superiority of dynamic over static visuals.
However, other studies have shown no significant difference between learning with and without
multimedia (e.g., Lewalter, 2003). In some cases, a reduction was found in learning with
multimedia compared to learning without multimedia (e.g., Lowe, 1999). Mayer, Hegarty,
Mayer, and Campbell (2005) conducted four experiments on technical topics (e.g., lightning
formation) where one group of learners had annotated illustrations and the other group had
narrated animations. The annotated illustration group did as well as, if not better than, the
narrated animation groups, which supported the static media hypothesis that static media are
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superior to dynamic media for learning. Tversky, Morrison, and Betrancourt (2002) questioned
those studies showing an advantage for dynamic over static visuals on grounds that the visuals
may not have been informationally equivalent or there may have been some confounding
variables.
Other studies have found mixed results in comparing static and dynamic visuals, depending on
learner characteristics and learning conditions. Schnotz, Böckheler, and Grzondziel (1999) found
empirically that animations aided learning in one type of learning, but that static pictures
provided superior learning in most conditions tested. This can perhaps be explained by the
increased extraneous cognitive load (Chandler & Sweller, 1991) caused by the animations
compared to static pictures.
There is currently no consensus among media researchers that dynamic visuals such as
animations enhance learning (Mayer & Moreno, 2002). This may be at least partially explained
by the increased cognitive load on learners caused by dynamic visuals compared to static visuals
within a given (usually short) time period (Hegarty, 2004; Lewalter, 2003). Viewers may look at
a static visual for as long as they want, while non-interactive dynamic visuals are transitory and
play automatically at a predefined rate (Höffler, Prechtl, & Nerdel, 2010). Here, interactive
dynamic visual means more than the ability to merely start and stop the visual; it also includes
the capability to move to a specific frame, change the playing speed (i.e., slower or faster), and
zoom in or out. While viewers may replay a dynamic visual, they often do not take advantage of
this capability, which means they may miss some details. One recommendation is to divide
longer dynamic visuals into shorter segments (Ayres & Paas, 2007). An important advantage of
interactive dynamic visuals such as virtual reality compared to non-interactive dynamic visuals
such as animation is that the learner controls how the visual is displayed (Ausburn & Ausburn,
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2008; Hegarty, 2004). Learner control addresses one possible explanation why non-interactive
dynamic visuals may not be superior to static visuals. This explanation relates to the viewer’s
previous knowledge of the subject, where novices often lack sufficient background to process
complicated information from animations quickly enough (Lowe, 1999). A further possible
explanation why non-interactive dynamic visuals may not be superior to static visuals is a
reduction in the degree to which learners engage in processing activities (Lowe, 2003). The
studies cited here show there is no current consensus regarding what type of multimedia is best
for learning.
Learning Strategy and Style Preferences of Adult Learners
Learning strategy preferences are important characteristics that vary among learners. Conti and
Fellenz (1991, p. 1) defined learning strategies as “techniques or skills that an individual elects to
use in order to accomplish a learning task.” Through a complex and lengthy process, Conti and
his associates developed and validated the instrument known as Assessing The Learning
Strategies of AdultS or ATLAS. Three distinct learning strategy groups have been identified:
Navigators, Problem Solvers, and Engagers (Conti, 2009). Navigators plan their learning and
focus on completing the necessary activities to achieve their goals. Order and structure are
important to Navigators, who tend to be logical, objective, and perfectionists. They want clear
objectives and expectations at the beginning of a course and in advance of activities, such as in
an explicit and detailed syllabus. Problem Solvers are critical thinkers who like to explore
multiple alternatives. For them, the process is important so they need flexibility in completing
learning activities. They may have difficulties making decisions because they have to make a
choice among multiple alternatives and because the exploration process which they enjoy must
come to an end. This may cause them to appear to procrastinate in making decisions because
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they do not want the process to end. Engagers are more affective learners who enjoy learning
they perceive to be fun or personally beneficial. They are interested in building relationships
with both teachers and fellow students during learning, which means they typically enjoy group
activities. The emotional aspect of learning is important to Engagers (Conti, 2009).
Different professions may have different learning strategy preference profiles. For example,
Birzer and Nolan (2002) found that law enforcement had a distinctive profile compared to the
general population in a comparison of known population norms to the preferred learning
strategies of urban police in a Midwestern city. They found there were some differences between
those working in community policing environments and those who were not. Police involved in
community policing tended to be Problem Solvers. To date there have not been any studies to
determine the learning strategy preferences of engineers, the occupational group of interest to
this researcher.
Learning strategies as defined and measured by ATLAS represent the strategic aspect of adult
learning preferences. This is included in this study to examine possible relationships between
strategic learning choices and media preferences.
A major dimension of cognitive style is the visualizer-verbalizer dimension (Riding, 2001).
People who are better at processing pictures are known as visualizers and those better at
processing words are known as verbalizers. This is a particularly important dimension in the
design of multimedia learning environments (Mayer and Massa, 2003).
The visualizer/verbalizer preference as measured by a question established by Mayer and Massa
(2003) represents the perceptual cognitive aspect of adult learning styles. This is included in this
study to examine possible relationships between perceptual/cognitive learning choices and media
preferences. It is also included in the study to compare with visual/verbal media preferences.
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Theoretical and Conceptual Framework
Dale’s Cone of Experience
Dale’s Cone of Experience (CoE), shown in Figure 1, is a visual analogy to illustrate the
progression of learning experiences from direct, firsthand participation to purely abstract,
symbolic expression (Dale, 1969). This iconic theoretical model has been influential in the fields
of instructional technology and design since it was introduced by Dale in 1946. It was intended
to show the level of abstraction for various types of learning activities to help teachers design
appropriate instructional materials using audiovisuals. Grounded in Piagetian psychology
(Ausburn & Ausburn, 2008), Dale’s Cone positions various learning experiences according to
their level of abstraction or concreteness. The lowest and least abstract level is “Direct
Purposeful Experiences” where students participate directly in an activity and use their senses to
help learn. The highest and most abstract level of experience is “Verbal Symbols” where
students use written symbols to express a concept. For example, H2O represents the chemical
compound for water which shows that water consists of two hydrogen atoms bonded with one
oxygen atom.
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Figure 1. Dale’s Cone of Experience.
Source: Dale, E. (1969). Audiovisual methods in teaching. New York: Dryden Press.
Dale (1969) emphasized the CoE was not designed to attribute worth to a particular level, such
as the top being better than the bottom or vice versa. Rather, he proposed that in some learning
contexts, more direct interaction may be needed, such as when the learner has no previous
experience or foundation with a subject. In other learning contexts, symbolic expression may be
preferred, such as when a graduate chemistry student no longer needs direct experience and uses
the symbol H2O instead of the word water. At a lower level, a very young child can only
understand the concept of “water” through experiencing it hands-on, while he can later relate
simply to the word “water.”
Mayer’s Cognitive Theory of Multimedia Learning
Multimedia has become an important element in instructional design. Multimedia instruction can
be defined as “the presentation of material using both words and pictures, with the intention of
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promoting learning” (Mayer, 2009, p. 5). Multimedia can be used to effectively communicate
complex concepts. It has become easier to develop and use because of advancements in both
hardware and software. Multimedia can refer to (a) sensory modalities such as text vs. narration,
(b) representational modes such as graphics vs. text, or (c) delivery media such as paper vs.
computer (Mayer & Moreno, 2002).
There is growing research showing learning is enhanced by well-designed multimedia
presentations compared to text-only (Mayer, 2003). Mayer presented some general
recommendations for effective instructional design involving multimedia regardless of whether
the delivery method is paper-based or computer-based. For example, Mayer claimed that:
1. Graphics plus text is more effective than text-only (p. 131).
2. Extraneous materials, such as interesting but nonessential facts referred to as
seductive details, should be excluded as they generally reduce learning (p. 132).
3. Graphics should be placed as close as possible to the text they support (p. 133).
4. Text presented in conversational style is more effective than in formal style (p. 134).
Mayer (2009) proposed 12 research-based principles for designing effective multimedia
presentations which are based on his Cognitive Theory of Multimedia Learning. This theory was
derived from three other theories: (1) Baddeley’s Working Memory Theory, (2) Paivio’s Dual
Coding Theory, and (3) Sweller’s Cognitive Load Theory. According to Baddeley’s (1986)
Working Memory Theory, humans have a limited capacity to process information in memory
channels. This means multimedia designs should not overload a learner’s memory channels or
learning will be reduced. In Paivio’s (1986) Dual Coding Theory, text and graphics are encoded
into two different memories: verbal and nonverbal. The theory suggested that multimedia
designers should use both channels to reinforce concepts for the learner. According to Sweller’s
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(Chandler & Sweller, 1991) Cognitive Load Theory, instructional materials should not overload
a learner’s mental processing. For example, having a figure on one page and the text describing
the figure on a different page increases the mental integration required by the learner which
increases the cognitive load that could reduce learning. This theory implies that multimedia
designs should eliminate unnecessary processing for the learner.
Multimedia Cone of Abstraction: A Proposed Update of Dale’s Cone of Experience
Multimedia has become an important element in instructional design. Virtual reality is a
relatively new element of multimedia which has the potential to show very realistic simulations
that were not readily available for teachers when Dale proposed his CoE. Some of the elements
in the original CoE are not as relevant today as they were at the time the CoE was first
developed. These include, for example, contrived experiences, study trips, exhibits, and
educational television. To accommodate new multimedia technologies and eliminate outdated
methods, Dale’s CoE needs to be updated for today’s learning context.
Because of the ubiquity of using computers to display instructional content, it is assumed
here that multimedia specifically refers to materials that can be displayed on a computer. This is
particularly important because of the growth of distance learning using computers. That
assumption necessarily limits the senses that can be used in materials delivered by computer to
visual and auditory. This means some of the elements in Dale’s CoE would not be appropriate in
a multimedia environment. For example, a study trip where students actually travel to another
location would not be included in an updated CoE for the specific context applied here.
Dale’s (1969) focus was on the experience of the learner, although he admitted his ranking of
learning experiences was based on their level of abstraction or removal from direct real-world
experience. However, the impact of experiences can vary among learners and some experiences
12
may be quite similar, such as study trips and exhibits. Therefore, level of abstraction seems to be
a more relevant way to classify the experience levels. Also, some of Dale’s levels appear to be
somewhat overlapping. For example, educational television and motion pictures both consist of
moving graphics of real images. While the content may vary between the two, they seem to be
different variations within the same media category.
Figure 2 shows the conceptual framework for the new Multimedia Cone of Abstraction
(MCoA) proposed by this researcher to underpin this study. Baddeley’s Working Memory
Theory, Paivio’s Dual Coding Theory, and Sweller’s Cognitive Load Theory all contributed to
Mayer’s Cognitive Theory of Multimedia Learning. Combining Dale’s Cone of Experience and
Mayer’s Cognitive Theory of Multimedia Learning yields the proposed MCoA which provides
guidelines for instructional designers using multimedia technologies, particularly via computer,
to enhance learning.
Figure 2. Conceptual framework for the proposed multimedia cone of abstraction.
Figure 3 shows the proposed MCoA designed by the researcher to update Dale’s CoE
specifically for the use of multimedia. Like the original CoE, the MCoA applies the Piagetian
principles of concreteness and abstraction. The closer to the bottom of the cone, the more
realistic or concrete the representation of reality and the closer to the top, the more abstract the
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representation. The lowest level is referred to in the MCoA as “Real VR” which is a usercontrollable virtual reality simulation using actual images such as photographs of something like
an object or a scene. Today’s photo-real VR is so realistic that the experience is almost like
actually being in the place represented. “Simulated VR” is also a user-controllable virtual reality
simulation, but in this case using simulated graphics such as computer-aided drawings. While
today’s drawings can be very realistic, they are not quite as realistic as actual photographs. “Real
Video” is a moving (dynamic) representation using actual images. These are not as usercontrollable in the sense that VR is because the user can only control the sequence of the video
display (e.g., start, stop, rewind, fast forward), and not the location that is being viewed (e.g.,
zoom in, zoom out, pan left, pan right, pan up, pan down) which is controllable by the user in
VR. “Simulated Video” is where the dynamic representation uses moving simulated graphics
such as animation or computer-aided drawings. “Real Audio” is a recording of actual sound.
“Simulated Audio” is where, for example, a computer is used to recreate sounds such as in
electronic instruments or voices. “Real Image” is a static graphic (e.g., photograph) of an actual
object or scene. “Simulated Image” is a simulated static graphic such as a drawing. “Narration”
is spoken language with no images or written text. Narration is less abstract than the next level,
“Text,” because the spoken language includes changes in volume and tone that contain additional
meaning compared to written words. “Text” refers to written words. “Visual Symbol” refers to a
graphic which is short-hand notation for something else. For example, a circle with a slash across
it on top of an image means do not do whatever is in the image. The most abstract level is
“Verbal Symbol” which is short-hand notation for something more complex. The symbol for
water, H2O, can be further refined to show the state of the water: H2O(s), H2O(l), and H2O(g)
refer to water in the solid (ice), liquid, and gaseous (steam) states.
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Figure 3. Researcher’s proposed Multimedia Cone of Abstraction.
The proposed MCoA demonstrates the many levels of media abstraction that are possible for
instructors to convey concepts to learners. Borrowing from Dale’s (1969) CoE concepts, the
researcher maintains that the appropriate amount of abstraction depends on both the topic and on
the prior knowledge of the learners. For example, students with no prior background in a subject
area will likely need less abstract multimedia initially, but will be capable of understanding more
abstract multimedia as their knowledge of the subject increases. No single level will be
appropriate for all content. In addition, some levels may not be appropriate for all learners. For
example, more visually-oriented learners may prefer virtual reality, while more verbally-oriented
learners may prefer narration and text. To reiterate Dale’s (1969) point, the proposed MCoA is
not intended to rank multimedia types from best to worst, because no single level is best for all
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learners and all subjects. Rather, it is intended to give some guidance to instructional designers in
selecting appropriate multimedia for specific applications.
Statement of the Problem
Engineers need to take continuing education courses that are frequently delivered online.
However, those courses are often poorly designed and do not follow research-based
recommendations for using multimedia effectively to enhance learning. No instructional design
guidelines appear to be available for designing effective distance courses specifically for
engineers. No previous research has studied the strategic learning strategy preferences and the
perceptual verbal-visual cognitive styles of engineers. The underlying problem for this study is a
lack of current guidelines for developing continuing education of working engineers using
distance education. Instructional design should be continuously improved for both classroom and
online courses (Herrington & Oliver, 2000). “How to develop a cost-effective multimedia
instructional material according to the properties of instructional content is emerging as an
important issue of e-learning. Unfortunately, there is a lack of extant literature to address this
critical issue” (Sun & Cheng, 2007, p. 663). The specific problem addressed in this study is the
lack of available information about the learning strategy preferences, verbal-visual cognitive
styles, and multimedia preferences of working engineers. This information could be used for
designing effective asynchronous self-directed online course content, including multimedia, for
working engineers.
While most of the results of the proposed research will also pertain to teaching engineers in the
classroom, learners do not have direct control over the multimedia in the classroom as they do in
online learning. For example, the instructor controls how videos and virtual reality simulations
are displayed in the classroom, while the learner controls them in an online course.
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Process burners are potentially dangerous pieces of equipment, consume large quantities of fuel,
can generate large amounts of pollution emissions, and can cause significant business downtime
if they are not properly maintained (Baukal, 2001). Failure to conduct this study may mean the
fundamental principles in the online Theory course are not adequately learned, which could
reduce learning in the face-to-face Fundamentals course. This could lead to safety concerns,
reduced fuel efficiency, excessive pollution emissions, and unscheduled downtime. Those
problems could cause damage to people and equipment, loss of valuable energy resources, harm
to the environment, and loss of revenue.
Purpose of the Study
The purpose of this study is to describe (a) the learning strategy preferences, verbal-visual
cognitive styles, and multimedia preferences of working engineers, and (b) relationships among
these variables and to selected demographic variables. The results of this study will be used to
design more effective online continuing education courses. Because the existing research is
inconclusive about which type of multimedia is most effective for learning, the proposed
research will determine multimedia preferences for the study’s population. The static and
dynamic visuals that will be used in the proposed research will be designed according to Mayer’s
Multimedia Design Principles.
Learner preferences would give the instructional designer some guidance for what distribution of
visuals should be used in a course. More research needs to be done on multimedia learning that
focuses on factors that differentiate learners (Samaris, Giouvanakis, Bousiou, & Tarabanis,
2006), which is the subject of the proposed study where the differentiating factors are learning
strategy preference, verbal-visual cognitive style, and learner demographics. The problem to be
studied here is primarily of interest to practitioners who design online courses, but will also be of
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interest to researchers as it will provide additional information for further research on what type
of online format may be preferable for a particular type of learner: employed engineers.
Research Questions
The following questions will guide the proposed study:
1.
What is the learning strategy preference profile for working engineers?
2.
How do the learning strategy preferences of working engineers compare to the norms for
the general population?
3.
What is the verbal-visual cognitive style profile for working engineers?
4.
How do the verbal-visual cognitive styles of working engineers compare to the norms for
the general population?
5.
6.
What are the multimedia preferences of working engineers?
5.1
What are the verbal preferences of engineers?
5.2
What are the static graphic preferences of engineers?
5.3
What are the non-interactive dynamic graphic preferences of engineers?
5.4
What are the interactive dynamic graphic preferences of engineers?
What are the relationships of engineers’ learning strategy preferences to the demographic
variables of age, gender, education level, years of engineering experience, engineering
specialty, management level, and prior knowledge of the topic?
7.
What are the relationships of engineers’ verbal-visual cognitive styles to the demographic
variables of age, gender, education level, years of engineering experience, engineering
specialty, management level, and prior knowledge of the topic?
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8.
What are the relationships of engineers’ multimedia preferences to the demographic
variables of age, gender, education level, years of engineering experience, engineering
specialty, management level, and prior knowledge of the topic?
9.
What is the relationship between engineers’ learning style preferences and their multimedia
preferences?
10.
What is the relationship between engineers’ verbal-visual cognitive styles and multimedia
preferences?
Definitions of Key Terms
Conceptual Definitions
Animation
Moving (dynamic) representation of simulated objects
Dynamic graphic
Moving image such as a video or animation
Dynamic media hypothesis
Proposition that learning is enhanced more by dynamic than by
static media
Interactive
User (e.g., learner) controls display of visuals
Learning strategy preference
“Learning strategies are the techniques or skills that an individual
elects to use in order to accomplish a specific learning task.
Learning strategies differ from learning style in that they are
techniques rather than stable traits and they are selected for a
specific task” (Conti & Fellenz, 1991, p. 1)
Multimedia
“Combination of multiple technical resources for the purpose of
presenting information represented in multiple formats via
multiple sensory modalities” (Schnotz & Lowe, 2003, p. 117)
Multimedia instruction
“Presentation of material using both words and pictures, with the
19
intention of promoting learning” (Mayer, 2009, p. 3)
Static graphic
Fixed, non-moving image such as a photograph or drawing
Static media hypothesis
Proposition that learning is enhanced more by static than by
dynamic media
Video
Moving (dynamic) representation of an object
Virtual reality
Controllable movable representation of an object or environment
Operational Definitions
Engager learning strategy
preference
Subject selects Engager on ATLAS instrument
Learning strategy preference
Subject selects Engager, Navigator, or Problem Solver on
ATLAS
Multimedia preference
Preference self-selected by subjects on survey
Navigator learning
strategy preference
Subject selects Navigator on ATLAS instrument
Problem Solver learning
strategy preference
Subject selects Problem Solver on ATLAS instrument
Verbal cognitive style
Subject selects Strongly more verbal than visual or Moderately
more verbal than visual on the Verbal-Visual Learning Style
Rating
Visual cognitive style
Subject selects Strongly more visual than verbal or Moderately
more visual than verbal on the Verbal-Visual Learning Style
Rating
Visual-verbal cognitive style
Subject selects their style on the Verbal-Visual Learning Style
Rating
Working engineer
Subject has an engineering degree or related degree and is
20
employed full time as an engineer
Methodology
General Research Design
This study will use a quantitative descriptive design based on survey methodology, which uses
instruments such as questionnaires to collect information from one or more groups of subjects
(Ary, Jacobs, Razavieh, & Sorensen, 2006). Surveys are used by the researcher to determine the
characteristics of different groups or to measure attitudes and opinions toward an issue. Survey
research describes distributions of variables in groups, rather than making causal inferences. This
study will study a portion of the total population of John Zink engineers, which is referred to as a
sample survey. The survey technique that will be used here is directly administered
questionnaires, which are given to a group of participants assembled for a particular purpose at a
certain place.
Variables and Design Controls
The general discipline for all subjects in the study will be engineering and most subjects will be
mechanical engineers. The subject matter for the study will also be fixed. The sensory modality
in which the subject matter is presented (written text vs. narration), representational modes
(verbal, static graphics, dynamic graphics), dimensionality (2D, 3D), and color (black-and-white,
color) will be independent variables. Information equivalence (Mayer, Hegarty, Mayer, &
Campbell, 2005) will be maintained as much as possible between designs. For example, the
labels, narration, and instructional time used with the static visuals will be identical to those used
with the dynamic visuals. The same voice will be used for all narrations, as changes in narration
voice tone can add additional information compared to text only (Mayer et al., 2005).
The preferred learning strategy of subjects will be a key independent variable and has three
21
levels: Engager, Navigator, and Problem Solver. A second key independent variable will be the
subjects’ visual/verbal cognitive style. The highest attained engineering degree (Bachelors,
Masters, and Ph.D.) and engineering discipline (mechanical, chemical, etc.) will be recorded as
independent variables for each subject. Management position will also be an independent
variable and will have three levels: individual contributor (no management responsibilities),
middle management (team leader, supervisor, director), and senior management (vice president
or president). Some subjects will have a professional engineering license and some will not.
Subjects will also have different ages, genders, total years of engineering experience, years of
experience at JZC, and prior knowledge of the subject matter. Subjects will complete a
demographic survey and ATLAS (Conti, 2009) to determine their learning strategy preferences.
The principal independent variable will be multimedia design (verbal, static graphics, noninteractive dynamic graphics, and interactive dynamic graphics). Some related independent
variables will be degree of control (non-interactive vs. interactive dynamic graphics), graphic
type (e.g., photograph vs. drawing), static vs. dynamic graphics, 2D vs. 3D, and black-and-white
vs. color.
The dependent variable will be the preferences of the participating engineers for the various
multimedia designs presented to them. Learning performance will not be a dependent variable in
this study because of both the type of training and the proposed research design. Because the
course type of interest concerns continuing education, students taking these courses are expected
to achieve at least 80% on a posttest to show satisfactory completion. The posttest questions are
designed to test basic factual information but not deeper level comprehension. Therefore, it
would be difficult to determine significant differences in learning using various types of
multimedia unless more challenging questions are developed than are actually used in the
22
courses.
It is anticipated approximately 80 engineers from JZC will be participating in the study. Even if
the challenge discussed above did not exist, there would not be enough participants to measure
differences in learning performance for all the various types of multimedia that will be
considered in the proposed study. Learning performance could be experimentally measured for
each type of multimedia if there were enough participants to form separate groups to view each
type. Each group would only see one design because if they saw other designs they might have
too much prior knowledge which could bias the results. However, there are too many multimedia
designs and not enough participants in this study to make the groups large enough to provide
statistical power to likely yield statistically significant results.
As an exploratory study, this research has the purpose of describing learner and multimedia
preferences and characteristics, not of experimentally determining the effectiveness of
multimedia formats on learning performance.
Population and Sample
All subjects will be engineers from JZC. It is anticipated the volunteer sample will be a high
percentage of the population of engineers working at the company (N ≈ 80). Most of the
engineers are mechanical or chemical, with other sub-disciplines represented as well. These
engineers are mostly male and have a wide range of years of experience (and therefore age
levels) and management levels. Some have professional engineering licenses and some do not.
Although the company has engineers located all over the U.S. and around the world, most of the
subjects are expected to be from the Tulsa location. Some of the subjects will have some
knowledge of the subject matter, while others will not.
23
Instrumentation
A participant survey developed by the researcher (see Appendix B) will be used to collect
demographic information. ATLAS (Conti, 2009) will be used to determine each subject’s
learning strategy preference. The Verbal-Visual Learning Style Rating (Mayer & Massa, 2003)
consists of a single question (see Appendix B) which will be used to determine each subject’s
verbal-visual cognitive style. The subjects’ multimedia design preferences will be measured in
two phases. The participant survey developed by the researcher (see Appendix B) will be used to
collect the subjects’ preferences within each type of multimedia in the first phase. The second
phase of the survey will be used to determine preferences between multimedia types, based on
the results of the first phase, as described in the procedures below.
Procedures
The subject matter that will be used for this investigation is the COOLstar™ burner (Meinen,
Poe, Lewallen, Baukal, & Schnepper, 2005) shown in Figure 4. This burner produces very low
pollutant emissions and superior performance compared to previous generations of technology.
This design will be used as the subject matter in this study because a significant portion of the
subjects will have substantial prior knowledgeable while another portion will not. The typical
condition for students in a formal learning context is that they generally do not know much about
the subject matter, which is why they are there. Having subjects with a range of prior knowledge
will be used to determine if that variable has a significant influence on their multimedia
preferences. The specific aspect of the subject matter that will be used for this study will be the
major component parts of this burner. This type of explanatory representation is referred to as a
system topology (Mayer & Gallini, 1990). This presentation would form the basis of more
detailed training on this burner design as students need to know the major component parts
24
before they learn about the operational principles.
(a)
(b)
Figure 4. COOLstar burner: (a) drawing, (b) in operation.
Source: John Zink Company, LLC.
The procedural design for this study will have two phases. Phase 1 will determine preferences
within each multimedia type as shown in Table 1. The text and narration will be identical in
Cases 1.1 and 1.7. There will be no narration for Cases 1.2 through 1.6. There will be identical
labels identifying components in Cases 1.2 through 1.7.
25
Table 1.
Phase 1 Cases (Within Multimedia Type).
Case
#
Verbal
1.1
Text vs. bullet
points + narration
1.2a
Labels
Non-Interactive
Dynamic Graphic
Static Graphic
2D black-and-white vs.
3D black-and-white
1.2b Labels
2D color drawing vs. 3D
color drawing
1.3a
Labels
2D black-and-white
drawing vs. 2D color
drawing
1.3b Labels
3D black-and-white
drawing vs. 3D color
drawing
1.4a
Labels
2D black-and-white
drawing vs. Photograph
1.4b Labels
3D black-and-white
drawing vs. Photograph
1.4c
Labels
2D color drawing vs.
Photograph
1.4d Labels
3D color drawing vs.
Photograph
1.5
Labels
1.6
Labels
1.7
Text + labels vs.
narration + labels
Interactive
Dynamic Graphic
Animation vs. video
Simulation vs.
actual
Photograph
Two slides will be shown for each case. The left slide will be one version of the particular case
and the right slide will be the other version. For example, for Case 1.1, if the left slide shows
26
text, the right slide would show bullet points + narration. Both slides will be shown side-by-side
in a room with two projectors and two large screens (see Figure 5). Because the narration will be
identical, they will be shown simultaneously so participants can directly compare them and rate
each using the following 7-point scale: strongly prefer left slide, moderately prefer left slide,
slightly prefer left slide, no preference, slightly prefer right slide, moderately prefer right slide,
strongly prefer right slide.
Figure 5. Training room with dual projectors.
Source: John Zink Company, LLC.
Participants will make pairwise comparisons to determine preferences within multimedia types of
verbal only, static graphics, non-interactive dynamic graphics, and interactive dynamic graphics
in Cases 1.1, 1.2-1.4, 1.5, and 1.6, respectively. Case 1.2 will be used to determine any
dimensionality preference and Case 1.3 will be used to determine any color preference. Case 1.7
will be used to determine what type of verbal presentation to use in Phase 2. Participants will
also rate and rank each choice within each type. This will give three methods of comparing
choices within a type to help triangulate the most preferred within a type. These methods will
also help assess the consistency of participants’ selections.
Appendix A shows the various types of slides that will be used in Phase 1. There are (13 x 12)/2
27
= 78 possible pairwise comparisons, which are too many for the subjects to reasonably compare.
The design in Table 1 effectively reduces the number of comparisons while still yielding the
desired results. The results from Phase 1 will be used to reduce the number of design choices in
Phase 2 so subjects can more easily compare the four types of multimedia being considered here.
After the results of Phase 1 have been analyzed, the slides will be prepared for Phase 2. Phase 2
will be conducted as soon as possible after Phase 1 and will measure preferences between
multimedia types for the Phase 1 subjects. Subjects will be shown the multimedia designs
presented in Table 2 in randomized order. Subjects will be asked to select their preference for
each pair of slides using the same scale as in Phase 1. Again, subjects will also rate and rank
multimedia types to give three methods of comparing preferences between types.
Table 2.
Phase 2 Cases (Between Multimedia Types).
Case
#
Verbal
2.1
Results from Case
1.1
2.2
Results from Case
1.1
2.3
Results from Case
1.1
Non-Interactive
Dynamic Graphic
Static Graphic
Interactive Dynamic
Graphic
Results from Cases
1.2-1.4 & 1.7
Results from Cases
1.5 & 1.7
Results from Cases
1.6 & 1.7
2.4
Results from Cases
1.2-1.4 & 1.7
2.5
Results from Cases
1.2-1.4 & 1.7
2.6
Results from Cases
1.5 & 1.7
Results from Cases
1.6 & 1.7
Results from Cases
1.5 & 1.7
Results from Cases
1.6 & 1.7
Both phases are planned to be done in several groups of subjects because the demonstration
28
room with side-by-side projectors, illustrated in Figure 5, is not large enough to handle the entire
sample at one time and because it is anticipated that not all subjects will be available at the same
time. The time between groups will be minimized to reduce the potential bias caused by
discussions among subjects in different groups. The order of the designs will be randomized in
both phases.
The results will be analyzed using appropriate statistical analyses as presented below to
determine the subjects’ preferences regarding multimedia designs and to see if there are any
significant differences based on subject demographics, learning strategy preferences, and verbalvisual cognitive styles. If the preferences determined in Phase 1 are dependent on, for example,
learning strategy preference, then the groups in Phase 2 may be designed according to those
preferences. For example, if Engagers prefer photographs as a static graphic, while Problem
Solvers and Navigators prefer drawings, then two different sets of cases for Phase 2 could be
developed with Engagers in one group and Problem Solvers and Navigators in another group.
Data Analysis
Table 3 shows the proposed methods for collecting the data and how the data will be analyzed
for each research question.
29
Table 3.
Data Source and Data Analysis Procedure for Each Research Question.
Research Question
Data Source
Procedure
1. What is the learning strategy preference
profile for working engineers?
ATLAS
Frequency distributions
2. How do the learning strategy
preferences of working engineers
compare to established norms for the
general population?
ATLAS
Frequency distributions
and chi-square
3. What is the verbal-visual cognitive
style profile for working engineers?
Verbal-Visual Learning
Style Rating
Frequency distributions
4. How do the verbal-visual cognitive
styles of working engineers compare to
the norms for the general population?
Verbal-Visual Learning
Style Rating
Frequency distributions
and chi-square
5. What are the multimedia preferences
for working engineers?
Phase 1 & 2 surveys
(pairwise comparisons,
rating, and ranking)
Frequency distributions
6. What are the relationships of engineers’ ATLAS and
learning strategy preferences to the
demographic survey
demographic variables of age, gender,
education level, years of engineering
experience, engineering specialty,
management level, and prior
knowledge of the topic?
ANOVA
7. What are the relationships of engineers’ Verbal-Visual Learning
verbal-visual cognitive styles to the
Style Rating and
demographic variables of age, gender,
demographic survey
education level, years of engineering
experience, engineering specialty,
management level, and prior
knowledge of the topic?
ANOVA
8. What are the relationships of engineers’ Phase 1 & 2 surveys and
multimedia preferences to the
demographic survey
demographic variables of age, gender,
education level, years of engineering
experience, engineering specialty,
management level, and prior
ANOVA
30
knowledge of the topic?
9. What is the relationship between
engineers’ learning strategy preferences
and their multimedia preferences?
ATLAS and Phase 1 &
2 surveys
Discriminant analysis
10. What is the relationship between
engineers’ verbal-visual cognitive
styles and their multimedia
preferences?
Verbal-Visual Learning
Style Rating and Phase
1 & 2 surveys
Discriminant analysis
Timeline for Conducting the Study
In Phase 1, subjects will be given a demographic survey first, then will complete ATLAS and the
Verbal-Visual Learning Style Rating, followed by their selections for their within multimedia
types preferences. At least two, and possibly more, groups will be tested in Phase 1, depending
on subject availability. Data collection is expected to be completed within two weeks. Data
analysis is estimated to be completed within one month after the data have been collected.
Depending on the Phase 1 results, either randomized or stratified groups will be formed for
Phase 2 to measure preferences between multimedia types. Data collection is expected to be
completed in approximately two weeks and data analysis within three months after all data have
been collected. The estimated completion date for the research is the summer of 2013 and the
estimated graduation date is the fall 2013 semester.
Limitations and Assumptions of the Study
Limitations
Several limitations must be accepted for the proposed study which may negatively affect the
outcomes and generalizability of the study:
1. Only degreed engineers, primarily mechanical, working at one particular company (JZC) and
primarily in one location (Tulsa) will be sampled.
2. Only one particular topic (the COOLstar burner) will be used.
31
3. Sampling will be done over a period of time so there will be possible diffusion of information
among participants.
4. The sample size will be too small and the demographics of the subjects too narrow to
generalize the results of this study to the entire population of engineers.
5. Learning performance will not be measured.
6. The researcher will control the display of the visuals so the subjects will not control the
exposure time.
7. The subjects will not be viewing the information on their own individual computers as they
would in an actual online course.
8. Subjects will not actually manipulate the virtual reality elements themselves as this will be
done by the researcher and will be recorded so all subjects will see the same manipulation.
Assumptions
The following assumptions must be accepted for this study:
1. Subjects understand all instructions and procedures.
2. Subjects answer questions truthfully.
Significance of the Study
As far as this researcher can determine, this will be the first study to describe the learning
strategy preference and verbal-visual cognitive style profiles of working engineers. This includes
how those learning strategy preferences and verbal-visual cognitive styles vary with
demographic variables such as years of experience, management level, prior knowledge of the
subject matter, and gender.
This will also be the first study to determine the specific preferences of working engineers for
various types of multimedia designs. Only one study was found considering multimedia effects
32
for adults (Wright, Milroy, & Lickorish, 1999), as nearly all other studies found in the literature
considered college students (Höffler & Leutner, 2007). This type of information will be
extremely valuable for instructional designers of continuing engineering education courses,
particularly online courses.
This study directly advances one of the recommendations from the report sponsored by the
National Academy of Engineering (2005, p. 45), “Research on Web-mediated learning must
continue so that we can better understand how to utilize the electronic multimedia approaches to
teaching and learning with respect to engineering content knowledge.”
Planned Literature Review
A comprehensive literature review is planned on the following major subjects: learning strategy
preference, verbal-visual cognitive style, instructional design of asynchronous online courses,
continuing education of working engineers, the use of multimedia in education including
Mayer’s Multimedia Design Principles, and Dale’s Cone of Experience.
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interactive texts. European Journal of Psychology of Education, 14, 203-224.
40
Appendix A – Multimedia Combinations
Table A1.
Multimedia Combinations to be Used in Phase 1.
Verbal
#
1
2
3
4
5
6
7
8
9
10
11
12
13
Text
x
Bullet
Points
Labels
x
x
Static Graphic
Narration
Drawing
Photograph
Non-Interactive
Dynamic Graphic
Animation
Video
Interactive Dynamic
Graphic (Virtual Reality)
Simulation
Actual
Dimensions
2D
3D
Color
BlackandWhite Color
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
41
x
x
x
x
Appendix B – Survey
Name:
________________________________________________
Date:
______________________
Question
Circle Your Choice / Fill in the Blank
Product Area
1 = Process Burners
2 = Boiler Burners
3 = Flares
4 = Thermal Oxidizers
5 = Vapor (Flare Gas Recovery, Vapor Recovery)
6 = Other ______________________________________
Gender
1 = Female
2 = Male
Age
__________ years old
Total engineering work
experience
__________ years
Total engineering work
experience at John Zink
__________ years
Management level
1 = individual contributor (no direct reports)
2 = middle management (e.g., director, supervisor – direct reports)
3 = senior management (e.g., vice president, president)
4 = Other _____________________________________________
Highest engineering
degree
1 = Bachelors
2 = Masters
3 = Ph.D.
4 = Other _____________________________________________
Specialty for highest
engineering degree
1 = Chemical Engineering
2 = Civil/Structural Engineering
3 = Electrical Engineering
4 = Mechanical Engineering
5 = Petroleum Engineering
6 = Other _____________________________________________
42
Your knowledge of the COOLstar burner:
○
○
Extremely knowledgeable
(e.g., design this burner)
Very
knowledgeable
○
○
Knowledgeable
Somewhat
knowledgeable
○
Little or no knowledge about
this technology
Learning Strategy Preference
ATLAS result (Place ONE check mark next to your learning strategy preference):
○ Navigator
○ Problem Solver
○ Engager
The description of your learning strategy group from the ATLAS Groups of Learners page is
reasonably accurate in describing you as a learner?
○
Strongly
agree
○
Moderately
agree
○
Slightly
agree
○
Neither
agree nor
disagree
○
Slightly
disagree
○
Moderately
disagree
○
Strongly
disagree
Visual-Verbal Preference
In a learning situation, sometimes information is presented verbally (e.g., with printed or spoken
words) and sometimes information is presented visually (e.g., with labeled illustrations, graphs,
or narrated animations). Please place a check mark indicating your learning preference.
○
○
○
Strongly
more verbal
than visual
Moderately
more verbal
than visual
Slightly
more verbal
than visual
○
Equally
verbal and
visual
○
○
○
Slightly
more visual
than verbal
Moderately
more visual
than verbal
Strongly
more visual
than verbal
Copyright 2002 by Richard E. Mayer. Reprinted by permission.
Question format that will be used to determine slide preferences:
○
Strongly
prefer left
slide
○
Moderately
prefer left
slide
○
Slightly
prefer left
slide
○
No
preference
43
○
Slightly
prefer right
slide
○
Moderately
prefer right
slide
○
Strongly
prefer right
slide
ATLAS
(Assessing The Learning Strategies of AdultS
Directions: The following statements are related to learning in real-life situations in which you
control the learning situation. These are situations that are not in a formal school. For each one,
select the response that best fits you, and follow the arrows to find the group to which you
belong.
When considering a new learning activity such as learning a new craft, hobby, or skill for use in
my personal life,
I usually will not begin
the learning activity until
I am convinced that I will
enjoy it enough to
successfully finish it.
I like to identify the best
possible resources such as
manuals, books, modern
information sources, or
experts for the learning
project.
It is important for me to:
Focus on the end
result and then set up
a plan with such
things as schedules
and deadlines for
learning it.
Think of a variety
of ways of learning
the material.
You are a Navigator
You are a Problem Solver
44
You are an Engager
Groups of Learners
Navigators
Description: Focused learners who chart a course for learning and follow it.
Characteristics: Focus on the learning process that is external to them by relying heavily on
planning and monitoring the learning task, on identifying resources, and on the critical
use of resources.
Instructor: Schedules and deadlines helpful. Outlining objectives and expectations,
summarizing main points, giving prompt feedback, and preparing instructional situation
for subsequent lessons.
Problem Solvers
Description: Learners who rely heavily on all the strategies in the area of critical thinking.
Characteristics: Test assumptions, generate alternatives, practice conditional acceptance, as
well as adjusting their learning process, use many external aids, and identify many
resources. Like to use human resources and usually do not do well on multiple-choice
tests.
Instructor: Provide an environment of practical experimentation, give examples from personal
experience, and assess learning with open-ended questions and problem-solving
activities.
Engagers
Description: Passionate learners who love to learn, learn with feeling, and learn best when
actively engaged in a meaningful manner.
Characteristics: Must have an internal sense of the importance of the learning to them
personally before getting involved in the learning. Once confident of the value of the
learning, likes to maintain a focus on the material to be learned. Operates out of the
Affective Domain related to learning.
Instructor: Provide an atmosphere that creates a relationship between the learner, the task, and
the teacher. Focus on learning rather than evaluation and encouraging personal
exploration for learning. Group work also helps to create a positive environment.
45