1. No category

Faculty RA Requests for the 2008-2009 Academic Year
Cover Sheet/Routing Sheet
Proposal Title: A comparative study: The effects of the use of innovative technology on online MBA
students' learning outcomes in relation to students' temperament-oriented and academic-oriented
learning styles.
Faculty mentor:
Joselina Cheng (Primary Investigator),
Kelly Moyers (Co-Researcher)
Tim Bridges (Co-Researcher)
College: CBA
Department: ISOM
Campus Box: 115
E-mail address: jcheng@ucok.edu; kmoyersham@ucok.edu; tbridges@ucok.edu
A Time Line (Action Plan) has been included with this proposal.
I understand that, as a condition of funding, the student and/or myself (faculty mentor) must
present a poster at Oklahoma Research Day.
Faculty Mentor Signature_____________________________________ Date _____________
Department Chairperson Signature_____________________________ Date_____________
College Dean Signature______________________________________ Date_____________
Proposal Title
A comparative study: The effects of the use of innovative technology on online MBA
students' learning outcomes in relation to students' temperament-oriented and academic-oriented
learning styles.
Project Description
Project Overview
Faculty members’ use of innovative technology in virtual classrooms can present
pedagogical challenges in fully addressing students' learning styles and enhancing e-learning
effectiveness. The purpose of this quantitative study is to examine the effects of innovative
multimedia-based learning modules on online MBA students' learning outcomes in relation to
students’ temperament-oriented (personality orientation of introversion and extroversion) and
academic-oriented (auditory, visual, and kinesthetic) learning styles. The sample population
includes students who enroll in MBA online courses for the fall and spring semesters of 20082009 at the University of Central Oklahoma (UCO). A researcher-constructed survey will be
used to collect primary data including student demographics and learning styles. Secondary data,
which will be provided by the UCO Enrollment Office, will include documented student learning
outcomes (grade point averages). Statistical Package for the Social Sciences (SPSS) will be used
to conduct statistical analyses to answer the research questions and hypotheses. The findings of
the proposed study can provide administrators and faculty members with insights into how to
best incorporate technology innovatively to enhance e-teaching and e-learning effectiveness in
21st century virtual classrooms.
Research Project Map
In an effort to align with UCO’s strategic objectives of providing students with quality
online education and transformative learning experiences, this project has been carefully
2
designed to support student engagement in innovative research and scholarly activities. Research
assistants and MBA graduate students will assist in data collection. Additional research assistant
responsibilites include project preparation, web-based survey construction, data coding, data
imports, statistical analysis, dissemination of results, and submission paperwork for conference
presentations and journal publications. The research project map, as shown in Figure 1, outlines
the formal steps of this proposed study. Additional details are availble in the timeline section of
this proposal.
Figure 1: Research Project Map
Research Background
The current knowledge-based, global economy requires new methods of delivering
education, partly to enhance traditional methods of knowledge acquisition and distribution in
brick-and- mortar higher education institutions (Chen, Gupta & Hoshower, 2006). The advanced
technology enables higher education institutions to enhance education delivery and knowledge
acquisition in the e-learning environment where learners and faculty members can be at a
distance from one another but are connected by technological media (Saba, 2005). E-learning
can be a strategic alternative to accommodate the needs of adult learners who are often too
constrained to attend traditional classrooms due to working schedules (Zhang, 2004). Since the
3
flexibility of e-learning allows adult learners to engage in knowledge acquisition and online
education at anytime and anywhere, the number of students enrolled in online course has more
than doubled in the past five years, from “483,113 in 2002 to 1,501,005 in 2006” (Romano,
2006, A06). In 2005, over 500,000 online courses were available for enrollment at U.S.
postsecondary institutions (Carr-Chellman, 2006). As the demands for online education
continues, many traditional brick-and-mortar higher education institutions are transitioning to
become hybrid institutions that offer both ground and online courses to meet the needs of adult
learners and sustain long-term competitiveness (Picciano, 2006; De Simone, 2006; Folkers,
2005; Waterhouse, 2005). According to a survey study conducted by the Association to Advance
Collegiate Schools of Business (AACSB), 60% of full-time faculties were involved in online
course creation, updating, and delivery through the Internet and course management systems
such as Blackboard/WebCT (Singh & Bernard, 2004; Trees, 2000).
Statements of Problem and Purpose
As the demand of using technology to deliver educational content electronically
continues, faculty members in higher education are expected to transition from teaching in the
traditional face-to-face classrooms to teaching in the virtual classrooms (Alshare, Kwun, &
Grandon, 2006; Cao, 2005; Zhang, 2004). The problem is that teaching with innovative
technology in the virtual classrooms (e-teaching) can present faculty members with pedagogical
challenges in terms of addressing learning styles (Cao, 2005; Zhang, 2004; Bourne & Moore,
2004). While the literature is filled with e-learning architectural design, examining effects of
innovative multimedia-based learning modules on online students’ learning outcomes in relation
to students’ learning styles remains under explored (Aduwa-Ogiegbaen & Isah, 2005; Alshare,
4
Kwun, & Grandon, 2006; Blass & Davis, 2003; Britt, 2006; Carr-Chellman, 2006; Durrington,
Berryhill, & Swafford, 2006; Lessen & Sorensen, 2006).
To bridge the gap in literature, the purpose of this study is to examine the effects of the
use of innovative technology on online MBA students' learning outcomes in relation to
temperament-oriented and academic-oriented learning styles. The objectives of the study include
(a) to compare the effect of multimedia-based learning modules on MBA students who are
introverted and extrovetred (temperamental-oriented learning styles); and (b) to compare the
effect of multimedia-based learning modules on MBA students who are auditory, visual, and
kinesthethic learners (academic-oriented learning styles).
Population and Sampling Frame
The general population includes MBA online students at the University of Central
Oklahoma (UCO). The target population consists of MBA students who enroll in online courses
in the College of Business Administration for the fall and spring semesters 2008-2009. The
sample for this study will include online MBA students who volunteer to participate in the study
and sign the consent form as shown in Appendix A.
Research Questions and Hypotheses
Answers to the following research questions will be sought:
1. What are the effects of innovative multimedia-based learning modules on online
MBA students’ learning outcomes in relation to students’ personality orientation of
introversion and extroversion?
2. What are the effects of innovative multimedia-based learning modules on online
MBA students’ learning outcomes in relation to students’ auditory, visual, and
kinesthetic learning style?
5
The research hypotheses that this study seeks to prove are summarized below.
1. The effects of innovative multimedia-based learning modules on online MBA
students’ learning outcomes differ in relation to students’ personality orientation of
introversion and extroversion.
2. The effects of innovative multimedia-based learning modules on online MBA
students’ learning outcomes differ in relation to students’ auditory, visual, and
kinesthetic learning styles.
Literature Review
While online education can be an alternative strategy for traditional universities to
accommodate adult learners who are unable to attend traditional face-to-face classes on campus,
the success of online education depends on the design and quality of learning modules that
address students’ learning styles sufficiently in the virtual classrooms (Zhang, 2004; Waterhouse,
2005). To better serve adult learners in the virtual classrooms, multimedia-based learning
modules that will be used in the study are based on the following theoretical frameworks.
Examples of innovative learning modules include, but are not limited to, podcast lectures and
streamed videos of virtual tutors.
Technology Mediated Learning Theory
Technology mediated learning (TML) is defined as “an environment in which the
learner’s interaction with learning materials such as readings, assignments, and instructions are
mediated through advanced information technologies” (Alavi & Leidner, 2001, p. 2). TML is
implemented in forms of computer-assisted instruction, computer-based training, Web-based
instruction, or Web-based training. These different forms of TML are multimedia-based learning
which can be accommodated by the use of computer mediated communication (CMC)
technology to deliver planned learning modules asynchronously and synchronously (Chute,
2002). Asynchronous communication allows the interaction between the learners and the
6
faculties to occur at different times through the use of technological tools such as email and
threaded discussion. In contrast, synchronous communication allows real-time, instructor-led
online learning events where faculty and students interact at the same time through the use of
technological tools such as chatting and teleconferencing (Palloff & Pratt, 1999; Waterhouse,
2005).
Multimedia-Based Learning Theory
According to Multimedia Learning Theory, to address students with auditory, visual, and
kinesthetic learning styles, faculty members can use hypermedia technology to develop learning
modules and content with components of sounds, graphics, and interactions (Yu, Wang, & Che,
2005; Zhang, 2004). Multimedia is the delivery of information in a computer-based presentation
that integrates two or more media (Beckman, 1996). Multimedia involves technologies that
combine several media of communication such as text, graphics, video, animation, and sound.
Since the Internet supports the delivery of full-motion audio and video to personal computers,
multimedia technology that carries multimedia learning contents can be easily retrieved and
downloaded over increasing network bandwidth (Zhang, 2003).
Furthermore, multimedia courseware can address various learning styles by enticing
learners to pay full attention through the vividness of presentation, sound, and hands-on
activities. Multimedia-based learning modules have a dramatic impact on both the process of
learning because the multi-sensory learning environments can help maximize the learner’s ability
to retain information (Syed, 2001). Research has shown that multimedia instruction can enhance
an individual’s problem-solving skills and entice learners to focus full attention on a task through
the vividness of the presentation (Weston & Barker, 2001; Zhang, 2004).
7
Theoretical Framework for E-teaching Strategies
Teaching in the virtual environment requires different pedagogical strategies than those
used in the traditional face-to-face classroom (McKnight, 2004). Despite the fact that online
education “has gained momentum and now accounts for a significant proportion of course
offerings in higher education,” (McKnight, p. 510) limited pedagogical guidance is available to
faculty members. Faculty members undergo the pragmatic process by unlearning past teaching
habits and philosophies for online courses. Research has shown that incorporating sound
pedagogy with innovative technology such as podcasting and streamed videos can enhance elearning effectiveness (Tangdhanakanond, Pitiyanuwat, & Archwamety, 2006; Waterhouse,
2005). The following sections present e-teaching strategies that are based on the theoretical
framework of Adult Learning Theory, cognitive/social learning, constructivism, and Bloom’s
Taxonomy.
Adult Learning, Cognitive and, Constructive Theories
The core of Adult Learning Theory is the art of helping adult learners (also known as
Andragogy) learn by making the educational content professionally and personally relevant
(Knowles, 1980). In the e-learning context, online faculty members can incorporate innovative
technology to design and develop multimedia-based learning modules that (a) address adult
learners’ needs, (b) engage adult learners in problem solving, and (c) acquire knowledge to apply
to real-life situations (Cheren, 2002; Mungania & Hatcher, 2004). Research has shown that
online learning modules that incorporate both innovative technology and Andragogy can help
adults learn more effectively in virtual classrooms (Waterhouse, 2005).
8
Theory of Cognitive and Constructive Learning
Incorporating cognitive and constructive learning theories into online learning modules
can help adult learners learn autonomously (Folkers, 2005; Waterhouse, 2005). Cognitive and
constructive learning underlines the importance of goal setting and the types of feedback that are
given to online students to motivate learning (Bellefeuille, 2006). Cognitive and constructive
learning also develops students’ self-regulatory skills to manage course workload and succeed in
the virtual learning environment (Whipp & Chiarelli, 2004). Faculty members’ teaching
philosophy also changes from knowledge transmission to knowledge construction (Yu, Wang, &
Che, 2005).
Bloom’s Taxonomy
The concepts of Benjamin Bloom’s (1956) Taxonomy, which includes six increasingly
sophisticated levels of cognitive skills, can also be incorporated into multimedia-based modules
to foster online students’ critical thinking in a learner-centered learning environment where
learners “become more actively engage in the learning process” (Waterhouse, 2005, p. 37). This
theoretical framework allows faculty members to design and develop quality online learning
modules that cultivate an innovative, collegial, and collaborative learning environment to
enhance online students’ learning (De Simone, 2006). The following section presents theoretical
foundation for research variables to be investigated in this study.
Theoretical Framework for Research Variable: Learning Style
Learning style is the preference, predisposition, or habitual mode of an individual to
acquire information and knowledge (Curry, 1991; Riding & Cheema, 1991; Zapalska & Brozik,
2007). Research has shown that learning styles can affect learners to encode, process, and
retrieve information differently (Brace-Govean & Clulow, 2000; Pachnowski & Jurczyk, 2000).
9
Temperament-oriented and academic-oriented learning styles are variables of interest in this
study.
Temperament-oriented Learning Styles
Temperament-oriented learning styles affect how the individual learns formally or
informally by his or her inborn nature and traits in a virtual learning environment (Dewar &
Whittington, 2000). Jung (1923) was one of the earliest psychiatrists to postulate the effect of
personality types on learners (a) in a formal educational and professional setting; and (b) in an
informal setting of real-life circumstances (Myers, 1962; Myers, McCaulley, Quenk, & Hammer,
1998). People with different personalities also differ in their attitudes, response, and collection of
information from external stimuli (McCaulley, Quenk, & Hammer, 1998). This study will focus
on Jung’s personality typology of introversion and extroversion.
Personality of introversion. Introversion is an attitude of people who prefer to focus on
their own inner world of ideas and experiences (Myers, 1962). Introverts direct their energy and
attention inward. Introverts also receive energy from reflecting on their thoughts, memories, and
feelings. The characteristics of introverts include (a) working out ideas by reflecting on them, (b)
being private and self-contained, (c) communicating in writing, and (d) taking the initiative when
a situation or issue is very important to the person (Myers, 1962). In the context of e-learning,
introverts prefer to asynchronous computer-mediated communication (Fink, 1999).
Asynchronous communication allows students the ability to internalize thought process
(Koszalka & Ganesan, 2004). Examples of asynchronous communication include, but are not
limited to, threaded discussions, emails, posted lectures, and pre-planned assignments.
Personality of extroversion. Extroversion is defined as “a trait or attitude of people who
like to focus on the outer world of people and activity” (Myers, 1962, p. 9). Extroverts receive
10
energy from interacting with external world of things, people, and social activities (Myers,
1962). Extroverts also prefer to communicate verbally and solve problems by talking through
issues, and learn by actions or discussions (Myers, 1962). In the context of e-learning, research
shows that extroverts tend to prefer synchronous communication (Waterhouse, 2005). Examples
of synchronous media include, but are not limited to, online chat sessions, interactive video,
teleconferencing, internet voice telephone, instant messaging systems, and graphical virtual
reality environments (Lavooy & Newlin, 2003).
Academic-Oriented Learning Styles
Academic-Oriented Learning Style Theory addresses specific skills and tasks generally
incorporated into formal pedagogy (Groble, 2002). Of the researched academic learning styles,
the consistently identifiable and validated styles include visual, auditory, and kinesthetic learning
styles (MacInnis & Price, 1987; Richardson, 1983; Zapalska & Brozik, 2007). For visual
learners, thinking and problem-solving processes consisted of graphics and pictorial
representations in which multisensory information is represented (MacInnis & Price, 1987;
Drago & Wagner, 2004). In contrast, auditory learners prefer to verbalize in order to hear words
or numbers spoken whereas kinesthetic learners prefer hands-on activities (Richardson, 1983;
Drago & Wagner, 2004).
In the context of e-teaching and e-learning, research has shown that using hypermedia
technology to develop learning modules and content with components of sounds, videos, images,
diagrams, and graphics can enhance learning effectiveness for students with auditory and visual
learning styles (Yu et al., 2005; Waterhouse, 2005). Learners with a kinesthetic learning style
learn best by doing. Research also shows that learning modules with emphasis of integrating
11
high interactivity to address students’ learning styles can enhance students’ participation elearning effectiveness (Moallem, 2008; Zhang, 2004).
Theoretical Framework for Research Variable: Learning Outcomes
In past studies that focus on learning, a student’s learning outcome was often measured
by grade point average (Yu, Wang, & Che, 2005). In the context of e-learning, research has
shown a correlation between the multimedia-oriented learning modules and a student learning
outcome. A study conducted by Morales, Cory, and Bozell (2001) compared students’
performance between scores of students in traditional face-to-face classrooms and those in
virtual classrooms. The study found significant differences in learning effectiveness that were
measured by test scores for online and ground students. Online students who were exposed to
both a text-based lecture and multimedia-based learning modules (streamed video) outperformed
those who were exposed to text-based lecture (Morales, Cory, & Bozell, 2001).
Methodology
The time dimension of the proposal is cross-sectional such that the study will be
conducted in the academic year 2008-2009. The sampling frame for this quantitative study is
convenient sampling, which comprises graduate students who will enroll in online MBA courses
at the College of Business Administration (CBA) at UCO for the fall semester in 2008 and the
spring semester in 2009. This study will use primary and secondary data. The following section
presents discussion for the primary data collection process as shown in Figure 2.
Figure 2. Web-based data collection
12
Instrumentation and Pilot Test
The web-based survey, as shown in Appendix B, will be used to collect primary data
including students’ unique identifier, demographics, and preferred learning styles. A pilot test
will be conducted to validate the researcher-constructed instrument to be constructed by the
researchers and RA. Upon the completion of the pilot test, the web survey will be available for
participants on a secured website. Other duties for researchers and RAs to perform include
testing the web-based data collection protocols (data validation, survey submission, etc.,)
performing administrative activities to monitor the website, and downloading data from the
secured website at the end of data collection.
The secondary data will be provided by UCO Enrollment office at the end of the fall and
spring semesters of 2008-2009 after faculties turn in semester grades. Both the primary and
secondary data will be merged by the researchers and RA by matching the students’ unique
identifier. Data import, data coding, and data analysis will be conducted by the researchers and
RA using Statistical Package for the Social Sciences (SPSS) software. Multivariate analyses will
be used to test for statistical significance. Aggregated findings of online MBA students' learning
outcomes in relation to learning styles will also be dissimilated by the researcher and RA to
provide insights for academic stakeholders including policy makers, administrators, faculties,
students, and researchers.
Study Limitations
This quantitative study has several limitations. First, the study uses a population frame
with a convenient sampling scheme to include students who self-select themselves when they
enroll in online MBA courses. Collecting data from a non-probability sample may result in the
possibility of sampling errors due to heterogeneity. Second, the sample size of this study may be
13
small. While the general and target population comprises a larger sampling frame, the sample
size may be further decreased when students opt not to participate in the study. Third, this study
will only be conducted over a two-semester period (fall 2008 and spring 2009) due to time and
resource constraints. Fourth, this study relies on participants to self-report his or her preferred
temperament-oriented (personality orientation of introversion and extroversion) and academicoriented learning styles (auditory, visual, and kinesthetic). Self-reporting instrumentation can
subject the data to personal biases and veracity of the respondents since survey data fall “mostly
in the realm of the honesty and accuracy of the respondents’ reporting” (Ulmer & Wilson, 2003,
p. 535). Measurement error can result from self-reporting instrument tools (Neuman, 2003).
These limitations may hinder the researcher’s ability to generalize the findings to a larger
population.
Significance of the Study to Leadership
Traditional higher education institutions are no longer protected by geographic service
areas since advanced technology and e-teaching models allow virtual universities such as the
University of Phoenix to recruit working adults without geographic constraints (Drucker, 2001;
Folkers, 2005). Online education can be a critical strategy for traditional higher education
institutions to accommodate adult learners’ needs (Murphy, Mahoney, Chen, Noemi, & Yang,
2005). Specifically, online education can be a possible competitive strategy for traditional
Oklahoma higher education institutions since Oklahoma ranked in the bottom one-third of all
states for higher educational attainment (Bauman & Graf, 2003). The unique findings of this
study can provide academic stakeholders including students, faculties, administrators, and policy
makers with several benefits. First, the findings of the proposed study can help educators
understand the effects of using innovative technology so that quality online learning modules can
14
be developed to address students’ learning styles and enhance e-learning effectiveness. Next, the
insight to be gained from the study can help administrators align with UCO’s goals by
supporting faculty with resources and training to enhance e-teaching. Furthermore, the insights to
be gained from the study enables traditional brick-and-mortar universities to make the transition
to becoming hybrid institutions and align with Oklahoma’s Brain Gain 2010 initiative to seek
funding so that quality online courses can be developed to attract working adult learners, which
will in turn increase college degree holders, and therefore improve Oklahoma’s intellectual
capital (Oklahoma State Regents, 1999, 2003).
In conclusion, while the delivery of innovative technology and multimedia-oriented
learning modules can be challenging for many faculty members, the success of online education
depends on the academic stakeholders’ collaboration to provide quality education (De Simone,
2006; Folkers, 2005). Institutional administrators and policy makers need to support online
faculty members’ efforts to design quality online courses with innovative technology to address
online students’ temperamental and academic learning styles (Waterhouse, 2005). The
knowledge of helping online students learn more effectively in the virtual classrooms becomes
increasingly important as more traditional brick-and-mortar institutions make the transition to
become hybrid institutions in order to sustain long-term competitiveness in the global e-learning
environment (Zapalska & Brozik, 2007).
15
Literature Citations
Aduwa-Ogiegbaen, S., & Isah, S. (2005). Extent of faculty members' use of internet in the
University of Benin, Nigeria. Journal of Instructional Psychology, 32(4), 269-277.
Alavi, M., & Leidner, D. (2001). Research commentary: Technology-mediated learning – A call
for greater depth and breadth of research. Information Systems Research 12(1), 1-10.
Alshare, K., Kwun, O., & Grandon, E. (2006). Determinants of instructors’ intentions to teach
online courses: A cross-cultural perspective. The Journal of Computer Information
Systems, Stillwater, 46(3), 87-95.
Alshare, K., Kwun, O., & Grandon, E. (2006). Determinants of instructors’ intentions to teach
online courses: A cross-cultural perspective. The Journal of Computer Information
Systems, 46(3), 87-95.
Beckman, C. (1999). Collaborative work networks among distributed learners. Proceedings of
the 32nd Hawaii International Conference on System Sciences, IEEE Computer Society
Press.
Bellefeuille, G. (2006). Rethinking reflective practice education in social work education: A
blended constructivist and objectivist instructional design strategy for a web-based child
welfare practice course. Journal of Social Work Education, 42(1), 85-103.
Blass, E., & Davis, A. (2003). Building on solid foundations: Establishing criteria for e-learning
development. Journal of Further & Higher Education, 27(3), 227-245.
Bloom B. S. (1956). Taxonomy of educational objectives, handbook I: The cognitive domain.
New York: David McKay Co, Inc.
Bourne, J., & Moore, J. (2004). Quality of online education: Into the mainstream. Solan-C
Series, 5. Retrieved from http://www.sloan-c.org.
Brace-Govan, J. & Clulow, V. (2000). Varying expectations of online students and the
implications for teachers: Findings from a journal study. Distance Education, 21(1), 118135.
Britt, R. (2006, January/February). Online education: A survey of faculty and students.
Radiologic Technology, 77(3), 183-190.
Cao, J. (2005). Learning with Virtual Mentors: How to make e-learning interactive and
effective? The University of Arizona, AAT 3176282.
Carr-Chellman, A. (2006). Desperate technologists: Critical issues in e-learning and implications
for higher education, Journal of Thought, 41(1), 95-115.
16
Capretz, l. (2002, December). Implications of MBTI in software engineering education. SIGCSE
Bulletin, 34(4), 134-137.
Chen, Y., Gupta, A., Hoshower, L. (2006). Factors that motivate business faculty to conduct
research: An expectancy theory Analysis. Journal of Education for Business, 81(4), 179189.
Cheren, M. (2002). A concise review of adult learning theory. Journal of Continuing Education
the Health Professions, 22(3), 199-201.
Church, A., & Waclawski, J. (1996). The effects of personality orientation and executive
behavior on subordinate perceptions of workgroup enablement. International Journal of
Organizational Analysis, 4(1), 20-32.
Chute, A. (2002). Evolving from distance education to knowledge management and e-learning.
Presented at Ohio Learning Network 2002 Conference. Retrieved May 11, 2008, from
http://www.oln.org/conferences/OLN2002/OLN2002webcasts.php
Curry, L. (1991). Patterns of learning style across selected medical specialties. Educational
Psychology, 11, 247–278.
Collins, J. (2001). Good to Great: Why some companies make the leap and others don’t (1st ed.).
New York: Harper Business.
De Simone, C. (2006). Preparing our teachers for distance education. College Teaching, 54(1),
183-184.
Dewar, T., & Whittington, D. (2000). Online learners and their learning strategies. Journal of
Educational Computing Research, 23(4), 385-403.
Drago, W., & Wagner, R. (2004). Vark preferred learning styles and online education.
Management Research News, 27(1), 1.
Drucker, P. (2000, May 15). Webucation, Forbes.
Durrington, V., Berryhill, A., & Swafford, J. (2006). Strategies for enhancing student
interactivity in an online environment. College Teaching, 54(1), 190-193.
Fink, J. (1999). How to use computers and cyberspace in the clinical practice of psychotherapy.
Northvale, NJ: Jason Aronson Inc.
Folkers, D. (2005). Competing in the marketspace: Incorporating online education into higher
education - an organizational perspective. Information Resources Management Journal,
18(1), 61-78.
17
Groble, M. (2002). Process and outcome efficacy of Internet counseling. Retrieved May 31,
2008, from ProQuest database.
Jung, C. (1923). Personality types. Collected Works of C. G. Young, 4(2), Princeton, NY:
Bollinger Press.
Knowles, M. (1980). The modern practice of adult education: From pedagogy to andragogy
(2nd ed.). New York, NY: Cambridge Books.
Koszalka, R., & Ganesan, R. (2004). Designing online courses: Taxonomy to guide strategic use
of features available in course management systems (CMS) in distance education.
Distance Education, Melbourne, 25(2), 243-256. Retrieved May 1, 2008, from ProQuest
database.
Lavooy, M., & Newlin, M. (2003). Computer-mediated communication: Online instruction and
interactivity. Journal of Interactive Learning Research, 14(2), 157-165.
Lessen, E., & Sorensen, C. (2006, March/April). Integrating. Change, 38(2), 44-49.
MacInnis, D., & Price, L. (1987). The role of imagery information processing: Review and
extensions. Journal of Consumer Research, 13, 473-491.
McKnight, R. (2004). Virtual necessities: assessing online course design. International Journal
on E-Learning, 3(1), 510.
Moallem, M. (2008). Accommodating Individual Differences in the Design of Online
Learning Environments: A Comparative Study. Journal of Research on
Technology in Education, 40(2), 217-235. Retrieved June 1, 2008, from
ProQuest database.
Morales, C., Cory, C., & Bozell, D. (2001, May 23). A comparative efficiency study between a
live lecture and a Web-based live-switched multi-camera streaming video distance
learning instructional unit. In proceedings of 2001 Information Resources Management
Association International Conference, Toronto, Ontario, Canada.
Mungania, P., & Hatcher, T. (2004). Systemic, flexible, and multidimensional models for
evaluating e-learning programs, Symbolic Interaction, 43(7), 33-39.
Murphy, K, Mahoney, E., Chen, C, Noemi, V., & Yang, M. (2005). A constructivist model of
mentoring, coaching, and facilitating online discussions. Distance Education, 26(3), 341367.
Myers, I. (1962). The Myers-Briggs Type Indicator. Princeton, NJ: Educational Testing
Service.
18
Myers, I., McCaulley M. H., Quenk N. L. & Hammer A. (1998). Manual: A Guide to the
Development and Use of the Myers-Briggs Type Indicator. Palo Alto CA:
Consulting Psychologists Press.
Neuman, W. L. (2003). Social research methods (5th ed.). Upper Saddle River, NJ: Prentice Hall.
Oklahoma State Regents for Higher Education. (1999). Brain gain 2010: Building Oklahoma
through intellectual power. Oklahoma City, OK: Author.
Oklahoma State Regents for Higher Education. (2003). Oklahoma’s EDGE: Economic
development generating excellence. Oklahoma City, OK: Author.
Palloff, R. M., & Pratt, K. (1999). Building learning communities in cyberspace: effective
strategies for the online classroom. San Francisco: Jossey-Bass, Inc.
Picciano, A. (2006). Online learning: Implication for higher education pedagogy and policy.
Journal of Thought, 41(1), 75-95.
Pachnowski, L., & Jurczyk, J. (2000, February). Correlating self-directing learning with distance
learning success. Paper presented at the annual meeting of the Eastern Educational
Research Association, Clearwater, FL. (ERIC Document reproduction service No.
ED441000).
Richardson, A. (1969). Mental imagery. New York: NY: Springer Publishing Company Inc.
Riding, R., & Cheema, I. (1991). Cognitive Styles: An Overview and Integration. Educational
Psychology, 11, 193–215.
Romano, L. (2006). Online degree programs take off. The Washington Post, A06. Retrieved on
October 25, 2007, from
http://www.washingtonpost.com/wpdyn/content/article/2006/05/15/AR2006051501496.h
tml
Saba, F. (2005, August). Critical issues in distance education: A report from the United States.
Distance Education, Melbourne, 26(2), 255-272.
Singh, R., & Bernard, M. (2004). Computers in education and business: A model for maintaining
interoperability of coarse XML sharable learning objects after re-authoring in a
standards-based editor. Proceedings of the winter international symposium on
Information and communication technologies WISICT '04.
Syed, M. (2001, July-September). Diminishing the distance in distance education. IEEE
Multimedia, 18-21.
19
Tangdhanakanond, K., Pitiyanuwat, S., & Archwamety, T. (2006). Assessment of achievement
and personal qualities under constructionist learning environment. Education, 126(3),
495-504. Retrieved May 18, 2008, from ProQuest database.
Trees, M. (2000). E-learning accelerates and transforms business school pedagogy: A special
report to AACSB. The International Association for Management Education Annual
Meeting. San Diego, CA.
Waterhouse, S. (2005). The power of eLearning: The essential guide for teaching in the digital
age. Boston: Pearson.
Weston, T., & Barker, L. (2001). Designing, implementing, and evaluating Web-based learning
modules for university students. Educational Technology, 41(4), 15-22.
Whipp, J. L., & Chiarelli, S. (2004). Self-regulation in a web-based course: A case study.
Educational Technology Research and Development, 52(4), 5-22.
Yu, S., Wang, M., & Che. K. (2005). An exposition of the crucial issues in China’s educational
information. Educational Technology Research and Development, 53(4), 88-101.
Retrieved May 1, 2008, from ProQuest database.
Ulmer, J. T. & Wilson, M. S. (2003). The potential contributions of quantitative research to
symbolic interactionism. Symbolic Interaction, 26(4), 531.
Zapalska, A., Brozik, D. (2007). Learning styles and online education. Campuswide Information
Systems, 24(1), 6. Retrieved May 31, 2008, from ProQuest database.
Zhang, D. (2003). Powering e-learning in the new millennium: An overview of e-learning and
enabling technology. Information Systems Frontiers, 5(2), 207-218.
Zhang, D. (2004). Virtual mentor and the lab system-toward building an interactive,
personalized, and intelligent e-learning environment. The Journal of Computer
Information Systems, 44(3), 35-43.
Zorn, Diane. (2007). Using video streaming and podcasting to design rich-media online courses.
Retrieved May 28, 2008, from
http://connect.educause.edu/Library/Abstract/UsingVideoStreamingandPod/45661?time=
1211986767
20
Appendix A
Covered Letter and Informed Consent Form
January 2, 2009
Dear Online Student
As educators at the University of Central Oklahoma, we are interested in exploring the effect of
the use of innovative technology on students’ learning outcomes. This research study is titled: A
comparative study: The effects of the use of innovative technology on online MBA students' learning
outcomes in relation to students' learning styles. The purpose of this research study is to examine the
effect of the use of online multimedia-based learning modules on students’ learning outcomes in relation
to students’ temperament-oriented and academic-oriented learning styles. A web-based survey will be
administered in November 2008 and April 2009 to collect students’ perceptions. Students’ grades will be
provided by administration at the end of fall2008 and spring 2009 semesters. The finding and knowledge
to be gained from the study can provide insight for faculty members, administrators, and policy makers to
better understand the effects of the use of innovative technology in order to provide graduate students
with transformative experience in an e-learning environment.
There are no foreseeable risks to you for participating in this research study. You can withdraw
from the study at any time without further obligation. Please be assured that your identity and your
answers will be kept confidential: Your name will not be used and your individual grade will not be
published.
If you are 18 years old or older and would like to participate, please copy and paste the following
URL link to a browser and login to the secure SurveyMoney website to complete an online survey that
will take five minutes approximately. Since going to the website and filling out the online survey
constitutes your consent to participate in the study, you may want to print and keep a copy of the cover
letter for your records.
Please contact the UCO Research & Grant (IRB office) via phone (405) 974-2100 or via email
jcheng@ucok.edu for any questions regarding this study. Thank you for your time and participation.
Sincerely,
Dr. Joselina Cheng, Dr. Kelly Moyers, and Dr. Tim Bridges
21
Appendix B
Web-Based Survey for Online MBA Students
1.
The lack of collaborative and social community hinders my ability to learn
in an online environment.
2.
Online MBA courses allow me to complete a degree and secure professional
advancement.
3.
Collaborating group project with other online students is difficult for me in
a virtual classroom.
4.
The lack of timely feedback from faculty hinders my ability to learn in an
online environment.
5.
I take online MBA courses to prepare for a job change.
6.
The lack of interactive and multimedia-based learning modules for MBA
courses hinders my ability to learn in an online environment because my
learning style(s) are not addressed.
7.
Online MBA courses save me time from travelling to campus.
8.
The lack of structure and user-friendly navigation of online MBA course(s)
hinders my ability to learn in virtual classroom.
9.
Online MBA courses are more accommodating to my working and family
schedules.
10. The lack of technical support 24 hours and 7 days a week hinders my
ability to learn an online environment.
11. Taking online MBA courses reduce the cost of travelling to campus.
12. The lack of time management skills on my part hinders my ability to
complete assignment for online course(s).
13. I take online MBA courses to achieve an educational goal.
14. The lack of technical ability on my part hinders my ability to learn in an
online environment.
15. Taking online MBA courses allow me to complete a master degree and
enhance my qualification for pay increase.
16. The lack of pedagogical guideline from online instructor(s) hinders my
ability to learn in an online environment.
17. Online MBA courses provide me with global access to obtain learning
material via the Internet at anytime and anywhere.
22
Agree
Strongly
Agree
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
Neutral
=
=
=
=
=
Strongly
Disagree
1
2
3
4
5
Disagree
Description of Survey Item
18. The lack of involvement or interaction from online instructor(s) hinders my
ability learn in an online environment.
19. I am self-motivated to complete course load and succeed in an online
environment.
20.
Taking online MBA courses allow me to complete a master degree and
enhance my qualification for a job promotion.
Demographic Data
1.
1=18-26
2=27-35
3=36-44
4=45-52
5=53 and above
Age
Gender
1=Male
2=Female
3.
Preferred learning styles
Select only one
(learn best by)
1=Auditory (hearing)
2=Visual
(learning)
3=Kinesthetic (doing)
4.
Personality Orientation
Select only one
1=Introverted (reserved)
2=Extroverted (outgoing)
5.
Level of computer expertise
1=Beginner
2=Intermediate
3=Advanced
6.
What is GPA?
Numeric value
2.
Time Line (Action Plan)
To prepare for this study, online faculty members will develop multimedia-based learning
modules to incorporate innovative technology with sound e-teaching pedagogy. Examples of
innovative multimedia-based learning modules include podcasting, stream videos, etc. These
multimedia-based learning modules will be incorporated into course design and development for
MBA online courses that will be offered for the fall and spring semesters in 2008-2009.
To collect primary and secondary data, the researchers and RA will submit an application to the
Institutional/Academic Review Board (ARB/IRB) at the Research and Grant office in July 2008
prior to the data collection that will take place in the fall and spring semesters in 2008-2009.
To compile a list of online courses, the researchers and RA will contact the UCO Enrollment
office via email at the beginning of fall and spring semesters in 2008-2009. The researchers and
RA will email participants the cover letter and the consent form as shown in Appendix A.
Online MBA students who agree to particpate in the study and sign the consent form will be
included in the study. Participants will receive a URL link to login at secure website using an
unique identifier to complete the survey.
To collect primary data, a researcher-constructed survey will be used. The researchers and RA
will construct the Web-based survey to be placed on a secured website, test online data-
23
collection protocols, perform administrative activities to monitor the Website, and download the
collected data into SPSS.
To answer the research questions and hypotheses, the researchers and RA will import the
primary (collected) data from the secure website and secondary data from the UCO Enrollment
Office into SPSS at the end of the data collection periods for the fall and spring semesters of
2008-2009. Researchers and RA will conduct statistical analysis and disseminate the findings in
May, 2009.
To publish the progress and findings, the assigned RA will submit project progress reports twice:
one in December, 2008, and one in May, 2009. The completed report will be sent to the UCO
Research and Grant Office as well as making it available at the primary investigator’s website in
summer 2009. The researchers and RA will also submit the final paper for presentations
(including Oklahoma Research Day, national/international conferences), journal publication
opportunities, and external funding for further research.
24
Previous Grants Received (on-campus and external) & List of Activities
(specifically that have engaged students in RCSA activities during the past 3
years)
Dr. Joselina Cheng has collaborated with cross-disciplined faculty members, research assistants,
graduate/undergraduate students at UCO and other universities to engage in the following
innovative research and scholarly activities.
•
•
•
•
•
•
•
•
•
•
•
•
Presentation at the National Faculty Leadership Conference, "Serving students with
innovative technology in the 21st Cyber Classrooms," Washington DC, (June 25-28,
2008).
Presentations at International of Business and Public Administration Disciplines,
“Virtual Tutor for the 21st Cyber Classroom," and “Emergent E-teaching Model for
Traditional Brick and Mortar Higher Education Institution” in Dallas (April, 24-27,
2008).
Grant award - “E-learning motivators and deterrents” (funded by UCO Research &
Grant Office, spring semester, 2008).
Grant award – “Innovative technology mini grant funded by UCO Information
Technology, spring, 2008).
Panel presentation - Moyers, K., Tyner, L., Parrish, R., Ferguson, S., Jeck, P., Noel, D.
E., Cheng, J., Southwest Business Symposium, "Innovative Technology for Teaching
Business Disciplines," University of Central Oklahoma, Edmond, OK. (March 27, 2008).
Presentation at Southwest Business Symposium with titles, "Innovative Technology for
Teaching Business Disciplines," “An emergent e-teaching model “, and “Virtual tutor:
Pedagogical tool for teaching “, at University of Central Oklahoma, Edmond, OK
(March 27, 2008).
Transformational Learning Fair, "Using advanced technology to integrate diversity in
global e-learning environment” at UCO (2008).
Grant award & student supervision - “A correlation study: Online quality and learning
outcomes and attrition” (funded by UCO Research & Grant Office, fall, 2007). Study
has been completed. Submissions have been made to present at 2008 fall conferences.
Presentations at Faculty Enhancement Day, “e-teaching tools,” “Who moved my
classrooms,” “Innovative pedagogy,” and “Technological tools to turbo charge
classrooms” at UCO, Edmond, Oklahoma (2005-2007).
Grant award and presentation- “How to optimize research with advanced technology”, at
the second Faculty Summer Institute (funded by UCO faculty Enhancement Center,
summer, 2007).
Presentation: "Virtual Tutor," and “E-teaching model for traditional brick-and-mortar
universities” at International of Business and Public Administration Disciplines, Dallas,
Texas (May 2-5, 2007). Study has been completed. Paper had been accepted and
presented at international conferences. Paper has been submitted to Cabell journals.
Poster presentations at Oklahoma Research Day, "Innovative pedagogy: Virtual Tutor,"
“E-teaching: A case study of Oklahoma higher education institution”, UCO, Edmond,
Oklahoma. (2006- 2007).
25
•
•
•
•
Presentation at Southwest Business Symposium, “Virtual tutor: Pedagogical tool for
teaching “ at University of Central Oklahoma, Edmond, OK (March 29, 2007)
Grant award - “Virtual Tutor” (funded by UCO Research & Grant Office (December,
2006).
Grant award - “Innovative use of technology” (funded by UCO Information Technology
Center, January, 2005).
Grant award for WebCT Title III (funded by UCO Information Technology Center,
2004-2005)
Dr. Kelly Moyers has engaged in the following innovative research and scholarly activities with
colleagues and students at UCO, St. Joseph’s College of Business in Bangalore, India and with
faculty members from other universities from across the country.
• Faculty mentor, SEED Forum - Business Plan Competition, Westmont College (2008).
• Presentation - Moyers, K., Tyner, L., Parrish, R., Ferguson, S., Jeck, P., Noel, D. E.,
Cheng, J., Southwest Business Symposium, "Innovative Technology for Teaching
Business Disciplines," University of Central Oklahoma, Edmond, OK. (March 27, 2008).
• Presentation - Moyers, K., Perry, L., American Society of Business and Behavioral
Sciences - Annual Conference 2008, "CLASSROOM MANAGEMENT IN AMERICAN
BUSINESS COLLEGES: THE POTENTIAL FOR AND IMPACT OF GENDER ISSUES,
CULTURAL AND BEHAVIORAL CHALLENGES," ASBBS, Las Vegas, NV. (2008).
•
Presentation at Southwest Business Symposium, "Innovative Technology for Teaching
Business Disciplines," “An emergent e-teaching model “, and “Virtual tutor:
Pedagogical tool for teaching “, at University of Central Oklahoma, Edmond, OK
(2006-2008).
•
Transformational Learning Fair, "Share Fair - Transformational Learning," UCO (2008).
•
Grant Award: Innovative technology mini grant - $500.00 - (funded by UCO
Information Technology, spring, 2008).
•
Presentation: "Virtual Tutor" at International of Business and Public Administration
Disciplines, Dallas (May 2-5, 2007).
•
Faculty mentor, D.W. Reynold’s Gov Cup Business Plan Competition, (January 2007 May 2007).
•
Faculty mentor, NEW VENTURES Business Plan Competition, University of Texas at
Tyler, (January 2007 - May 2007).
•
Supervised Student Research, "UROGEN - business plan development," (2007).
26
Advised: Chaudry Affan, Rodriguez-Pico Michelle, Skaley Matthew
•
Grant Award: Virtual Tutor, $5,000 grant funded by the UCO Research & Grant Office
(December, 2006).
•
Supervised Student Research, "Determining the Correlation between Employee
Satisfaction and Customer Satisfaction in Public Agencies –Do the Organizational
Objectives of American Public Agencies Take Job Satisfaction Into Account?," (2006).
Students Advised: Shekar Bhavana, Bhattacharyya Devdetta (St. Joseph’s CollegeBangalore, India)
Dr. Tim Bridges has engaged in the following innovative research and scholarly activities
with colleagues and students at UCO.
●
Presentation: (2006). Shrinking Enrollment in MIS: What Can We Do?, Annual
Conference 2007, American Society of Business and Behavioral Sciences, published in
proceedings (vol. 13), ASBBS, Las Vegas, NV.
●
Presenter: "VOIP in the Next Ten Years," Research Day 2007, Graduate College,
University of Central Oklahoma, (April 6, 2007).
● Presenter: "VOIP: Good for Business?", Research Day 2005, UCO Graduate College,
University of Central Oklahoma, (October 2005).
● Presenter: "Learning and Forgetting Curves," Southwest Business Symposium, College
of Business Administration, University of Central Oklahoma. (March 2001).
● Unpublished Dissertation: “The Effect of Intermittent Forgetting Upon Learning and
Productivity Within Production Systems”, (July 2000), School of Industrial Engineering,
University of Oklahoma.
● Faculty Mentor, "What is TQM and How to Implement for Software Production."
Student Research, University of Central Oklahoma (August 18, 2003 - December 12,
2003).
● Faculty Mentor, "Benefits of Implementing Total Quality Management in Information
Technology," Student Research, University of Central Oklahoma (August 18, 2003 December 12, 2003).
● Faculty Mentor, “Computer System Security in the Small to Medium Sized Business”,
Student Research, University of Central Oklahoma (May 2002).
27
FORM TO BE COMPLETED BY EVALUATOR. All proposals will be evaluated by
faculty members of the Research Advisory Council (RAC) and Undergraduate Research
Creative Activities Team (URCAT).
Faculty Name
College and Department
EVALUATION CRITERIA FOR RA REQUESTS
Evaluator: Please rank proposal for each category with “1” being the lowest and “10” being the highest.
Provide a brief justification for scores.
Clear description of narrative with literature citations
1
2
3
4
5
6
7
8
9
10
4
5
6
7
8
9
10
Comments/justification:
Originality & creativity
1
2
3
Comments/justification:
Feasibility / probability of accomplishment / realistic timeline
1
2
3
4
5
6
7
8
9
10
6
7
8
9
10
Comments/justification:
Methodology / process / procedures
1
2
3
4
5
Comments/justification:
Significance / value of the project (contribution to the discipline)
1
2
3
4
5
6
7
8
9
10
8
9
10
Comments/justification:
Justification and utilization of student(s) in project
1
2
3
4
5
6
7
Comments/justification:
Reviewer:
Total Score
Please Sign and date the back of this evaluation form.
Overall Evaluation
Strengths of proposal:
Areas for improvement of proposal:
28