Last update:

10/28/2002

Motivational Strategies via Technology and Their Effects on Performance, Satisfaction, and Self-Directedness of USMA Cadets

To educate, train, and inspire the Corps of Cadets so that each graduate is a commissioned leader of character committed to the values of Duty, Honor, Country; professional growth throughout a career as an officer in the United States Army; and a lifetime of selfless service to the nation.    -USMA Mission

The United States Military Academy (USMA) at West Point, New York is an institution steeped in tradition yet recognizing the need for change in todayís world.  Cadets lead structured lives at the academy where academic, physical, and military development are utilized to cultivate leaders.  A strong emphasis is placed on self-directedness and lifelong learning.

Problem Statement

The structured environment at USMA leaves little free time for cadets.  Ideally they would use at least some of their free time to pursue self-directed learning.  In Educating Army Leaders for the 21^st Century (1998), this goal is emphasized, ìThe reality of rapid change will require officers to be self-directed learners who update and expand their knowledge though self-study, continued formal education, and experience.î  However, Preczewski (in Long, 1999, p. 121) concluded that at the Academy, "the undergraduate experience fails to increase self-directedness as measured during and at the end of the undergraduate experience.î The motivated, autonomous learner will satisfy the curiosity to learn outside the context of the classroom and will progress to USMAís goal for cadets of continued educational development through lifelong learning.   While the focus of this research is not on lifelong learning, the literature also suggests that self-directed learners are more likely to become lifelong learners (Long, 1999) .

This issue of motivation and self-directedness is not isolated to USMA; it is ubiquitous throughout higher education.  However, most institutions do not structure their studentsí demanding schedules to the level that a military academy does.  While there is a strong emphasis on motivation, there is a formidable absence of literature on the topic of academic motivation in military institutions.  Prior studies at USMA suggest that self-directedness (Preczewski, 1997) and learner motivation (Hancock, 1991) require further study.

Moreover, motivation has been the topic of research for decades in pedagogy, but there is little formal research on the topic as it relates to technology-mediated instruction (Keller, 1999a).  Finally, existing research is often not grounded in theory and is instead typically descriptive (Perraton, 2000), stressing the need for further empirical development of the literature. 

Theoretical Framework

The theoretical framework of this study is grounded in research on self-directed learning and intervention strategies of motivation.  Literature on self-directedness has progressed significantly in the past 25 years (Long, 1999), as has research on motivation. Kellerís ARCS model of motivational design is based on four dimensions of motivation: attention, relevance, confidence, and satisfaction (Keller, 1987).  The model has been successfully tested for its validity and reliability many times and in a variety of contexts including classroom-based instruction, distance learning, and computer-aided instruction (Song, 1998; Visser, 1998).

A relatively recent focus in research in the field has been on the social context of learning (Jonassen, 2000; Wegerif, 1998).  These social theories include social constructivism and socio-cultural learning theory.  Wenger (1998) developed a framework of communities of practice through this social participation that stresses communication and interaction.  These theories will drive the development of ARCS motivational strategies that will be mediated through technology at the USMA. For example, social participation will occur through course-specific asynchronous online threaded discussions or synchronous chat sessions.  The intervention of these strategies will occur from motivationally-adaptive instruction (MAI) based on the research of Song (1998) and the motivational messages support system (MMSS) based on research by Visser (1998).  Song found that MAI improved effectiveness, overall motivation, and attention in computer-based instruction.  Visser found that the use of MMSS increased completion rates, self-confidence, and satisfaction of distance learners and she concluded that contrary to practice, it may be more beneficial to focus on the support system for the learners rather than to revise existing instruction.

Proposal Details

The Academy provides a unique opportunity to conduct research with experimental and control groups. Cadets are randomly assigned to courses by USMA's Operations and Registrar division.  Each course section has cadets who are comparable in terms of age, gender, ethnicity, GPA, and other demographic variables.  Cadets must be self-directed in order to succeed at USMA, but in order to excel they must think outside the constraints of the classroom.  Motivational strategies will be employed via technologies including personal digital assistants (PDAs), email, instructional hyperlinks, online feedback, and online instruction to encourage self-directedness.  These opportunities are strictly voluntary and therefore do not require any additional time of cadets unless they choose to use them.  However, in some courses extra credit will be offered as an incentive for participation, and in all cases cadets will be encouraged to participate.  Because of already challenging schedules, additional time demands for cadets and instructors should not exceed 10-15 minutes per week.

A Self-Directed Learning Readiness Scale, or SDLRS, survey (Guiglielmino, 1978) will be administered to a random selection of 100 control and 100 experimental participants in the beginning of the semester.  For those cadets in the experimental group, short weekly self-directed learning (SDL) surveys will be administered.  For all cadets in the study, performance (measured by existing course assessments including grades on projects, papers, and tests) will be tracked throughout the semester and satisfaction (measured by an ARCS survey instrument) will be measured at the end of the semester.  To provide for a richer study, qualitative data will be collected via interviews, focus groups, and web forums.  This use of triangulation methods will provide for a more reliable and valid study.

It is important that the course instructors participate in the study by working closely with the researcher to ensure that the provided resources are in line with the curricula and course objectives.  The following courses are involved in the study in Spring 2002, along with the number of sections and instructor names:

…    PL100 General Psychology (BS&L), 4- LTC Scott Hampton

…    PL300 Military Leadership (BS&L), 4- MAJ Nate Allen

…    CH101A General Chemistry repeated (CHEM), 2- MAJ Robert ìBozeî Bozic

…    CH102 General Chemistry (CHEM), 2-COL Buddy Blackman, 3-Dr. Eileen Kowalski, 2-MAJ Maria Miller

…    CH384 Organic Chemistry (CHEM), 3- COL Patty Dooley, 2- LTC David Pursell

…    CS105 Intro. to Information Technology (EECS), 3- LTC Rachel Borhauer

…    CS383 Information Systems (EECS), 2- LTC Curt Carver

…    PE210 Intro. to Wellness (DPE), 2- Dr. Ralph Pim

…    HI302 Military History (HIST), 4- CPT Kevin Clark

…    MA104 Single Variable Calculus (MATH), 3- CPT Libby Schott

…    EN102 Literature (ENG), 4- CPT Chris Corbett, 4- CPT Dave Harper

…    EN302 Advanced Composition (ENG), 4- MAJ Kris Nakutis and CPT Todd Tinius

Each participating course has a minimum of 2 sections that are taught by the same instructor, so half will be used as experimental groups and half as control groups.  Class sizes typically consist of 15-18 cadets, making the sample size approximately 700.  Coordination will take place with the course instructors, with approval from each course director and Department head.  The following table represents some of the motivational strategies that will be used, what technologies will be employed, and which ARCS strategies the interventions address.

For example, all incoming cadets are issued PDAs primarily for scheduling functions.  "Skill Briefs" will be used to provide 5-10 minutes of chunked information that will be beamed to the cadets' PDAs.  The information will be directly related to their course content and will attempt to pique their curiosity to motivate them to want to learn outside the context of the classroom and beyond the course requirements.  They can retrieve these Skill Briefs when they are waiting for the bus, sitting in their dorms, or at any time or place that is convenient.

            Cadets who choose to participate will be exposed to these various motivational interventions during spring semester 2002.  Data will be collected electronically via SDL and ARCS surveys to measure motivation, attention, relevance, confidence, and demographic information. Data will also be collected via electronic tracking for web-based instruction, with follow-up interviews through focus groups and individual sessions. Brief weekly assessments will occur electronically to determine the time, if any, spent outside required coursework, as well as to determine cadet perceptions of the interventions.  This data will be correlated with the ARCS and SDLRS surveys to see what relationship, if any, exists between self-directedness (including self-efficacy and self-regulation), performance, and satisfaction.

Critical dependent variables:  Performance, Satisfaction, Self-Directedness, Self-Regulation, Self-Efficacy

Critical independent variables:  Motivation, Attention, Relevance, Confidence, Demographics

Research Questions

1. Does the use of motivational strategies via technology enhance student self-directedness outside the classroom?
2. Does the use of motivational strategies via technology enhance student satisfaction?
3. Does the use of motivational strategies via technology enhance student performance?
4. Are these differences more significant based on topic area (i.e. hard or soft sciences) or academic level (i.e. freshman versus sophomores)?
5. Do any of the following eight demographic factors serve as predictors of self-directedness, satisfaction, or performance: age, gender, minority status, athletic participation, parental level of education, ACT/SAT score, educational major, or prior completion of a prep course (RS101, Student Success)?
6. Which motivational strategies employed are most effective in the various contexts of this study?

The literature suggests that motivation plays a critical role in performance (Keller & Song, 2001).  Based on existing research, we might expect to see certain patterns such as more senior cadets exhibiting greater self-directedness as well as variables such as gender playing a role (Preczewski, 1997).  We might also expect that the use of these motivational techniques would enhance the teaching and learning process and improve learner satisfaction (Visser, 1998) and performance (Song & Keller, 1999). The quasi-experimental model will use triangulation with a mixed method approach of quantitative data and qualitative data to provide for a richer study. 

Summary

While technology will be utilized as a tool to deliver these motivational strategies, it is not the focus of the study, nor should it be the focus of pedagogy.  By examining existing literature and applying Kellerís ARCS model to technology-mediated instruction, this research is intended to utilize a systems approach to take the focus off the technology itself and put it on the systematic instructional methods that encourage self-directedness and enhance learner motivation, satisfaction, and performance.  

This research is important at the United States Military Academy because it corresponds with the academyís mission and its emphasis on encouraging self-directedness and lifelong learning.  It also helps link technology tools being used in the field to the cadetsí classroom instruction. The technology-mediated motivational techniques developed for this research, with their effectiveness confirmed, can be applied to other courses at USMA.  Finally, the findings can be applied beyond the academy to progress the literature and instructional theory.

References

(1998). Educating Army Leaders for the 21st Century. West Point, NY, United States Military Academy, Office of the Dean: 50.

Guiglielmino, L. M. (1978).  Development of the Self-Directed Learning Readiness Scale.  (Doctoral Dissertation, University of Georgia, 1977).  Dissertation Abstracts International, 38, 6467A.

Hancock, D. R. (1991). Effects of conceptual levels and direct and nondirect instruction patterns on achievement and motivation in course content (direct instruction), Fordham University: 257

Keller, J. M. (1979).  Motivation and instructional design:  A theoretical perspective.  Journal of Instructional Development, 2, 26-34.

Keller, J. M. (1987).  Strategies for stimulating the motivation to learn.  Performance and Instruction, 26(9), 1-8.

Keller, J. M. (1999a, August). Motivation in Cyber Learning Environments.  International Journal of Educational Technology, 1(1), 7-30.

Keller, J. M. (1999b, Summer).  Using the ARCS motivational design process in computer-based instruction and distance education. New Directions for Teaching and Learning, no. 78.  Jossey-Bass. 

Jonassen, D. (2000, October).  Learning as activity.  Unpublished paper presented at the Learning Development Institute Presidential Session of the Association for Educational Communications & Technology Convention, Denver, CO.

Long, H. B. et al. (1999). Contemporary Ideas and Practices in Self-Directed Learning. University of Oklahoma College of Education, Public Managers Center.

Preczewski, S. C. (1997). Measuring Self-Directedness for Continuing Learning:  A Cross-Sectional Survey Approach Using the ODDI Continuing Learning Inventory (OCLI). Higher Education. Columbia, University of Missouri-Columbia: 106.

Reigeluth, C. M. (1999). Instructional-design theories and models: A new paradigm of instructional theory (2nd). Mahwah, NJ: Lawrence Erlbaum Associates.

Reigeluth, C. M. (2000).  Proceedings at the AECT Distance Learning Conference, Denver.

Song, S. H. & Keller, J. M. (2001).  Effectiveness of motivationally adaptive computer-assisted instruction on the dynamic aspects of motivation.  Educational Technology Research & Development, 49(2).

Song, S. H. & Keller, J. M. (1999, February).  The ARCS model for developing motivationally-adaptive computer-assisted instruction.  Proceedings at the AECT Distance Learning Conference, Denver.

Song, S. H. (1998).  The effects of motivationally adaptive computer-assisted instruction developed through the ARCS model. (Doctoral dissertation, Florida State University). Dissertation Abstracts International, 59: 1539.

Stipek, D. (1998)  Motivation to Learn:  From Theory to Practice.  Boston: Allyn and Bacon.

Visser, L. (1998).  The Development of Motivational Communication in Distance Education Support.  Den Haag:  CIP- Gegevens Koninklijke Bibliotheek.

Visser, L. P., T.; Kuiper, W. (1999). Development Research Applied to Improve Motivation in Distance Education. Association for Educational Communications and Technology, Houston, TX.

Wegerif, R. (March 1998).  The social dimension of asynchronous learning networks.  Journal of Asynchronous Learning Networks, 2(1).

Wenger, E. (1998). Communities of practice: Learning, meaning and identity. New York: Cambridge University Press.