Academic motivation profile in business classes.

Abstract

The Academic Motivation Profile (AMP) was successfully developed and tested in education classes as a theoretically based tool for measuring students' attitudes about a course. The suitability of the AMP in business classes is evaluated in this study that indicates that the AMP applies equally well in the business classes studied as it does in the education classes previously studied.

Introduction

Academic achievement and motivation are frequent topics in education. Many variables influence academic achievement, such as cognitive factors, achievement orientations (Licht and Dweck, 1984, Pintrich, 2000), achievement goals (Elliot and Dweck, 1988, Boekaerts et al., 2000), academic self-concept (Reynolds, 1988), and motivational orientation (Hagberg, 1992). Educators agree that student motivation is important; however, there is little research describing motivational curriculum development.

Keller used principles from academic motivation theory to develop the Attention, Relevance, Confidence, Satisfaction (ARCS) Model of Motivational Design (Keller, 1983, Keller, 1987b). The ARCS Model is a useful framework for motivational instructional design (Small, 2000), and is the theoretical base for the Academic Motivation Profile (AMP) developed to assess students' end-of-course attitudes. The profile focuses on motivation (Carey et al., 2001, Pearson and Carey, 1995). The AMP was tested successfully with undergraduate education students enrolled in education classes; it does not appear, however, the AMP has been tested in business classes. It is reasonable to suggest that using the AMP to measure student motivation may also be useful in the development and evaluation of business classes. The purpose of this study is to evaluate the applicability of AMP for use in business classes by examining the AMP scores of students enrolled in different sections of the same course as suggested in previous research (Pearson and Carey, 1995).

Background

Motivation research includes several theories such as behavioral theory, self-determination theory, expectancy-value theory, and attribution theory (Eccles and Wigfield, 2002). Early motivation research (Atkinson, 1957) employed behavioral theories including deprivation, reinforcement, and failure avoidance. Expectancy-value theory (Porter and Lawler, 1968, Vroom, 1964, Bandura et al., 2001) postulates that fundamental principles are required to evoke "effort." Self-determination theory postulates about the roles of self-determined and controlled behavior in academic performance (Deci et al., 1991, Deci and Ryan, 1985, Grolnick et al., 2000). Attribution theory provides a framework for examining the factors to which individuals attributed their academic successes or failures such as luck, effort, or ability (Graham, 1997). Keller incorporates principles from attribution theory, attention, relevance, confidence, and satisfaction into the ARCS Model of academic motivation (Keller, 1987a, Keller, 1987b, Keller, 1987c). As conceived by Keller, academic motivation is complex and multidimensional; therefore, to assess students' levels of academic motivation, information must be collected for each dimension. These dimensions are detailed below.

Attention Attention is the extent to which different aspects of a course arouse and maintain a student's interest and curiosity. The theoretical base for attention includes theories of information processing related to human learning and memory, including curiosity, arousal, and sensation seeking (Berlyne, 1965, Zuckerman, 1971).

Relevance Relevance is the perceived value of the course for fulfilling a student's current and future goals. Related theories include hierarchy of needs and self-actualization. Students who perceive course outcomes as relevant to their personal needs and professional futures are more likely to attend class and to put effort into a course.

Confidence Confidence is the student's level of self-assurance in their ability to succeed. The theoretical base for confidence includes elements from theories of locus of control, self-efficacy (Bandura et al., 2001), attribution (Weiner and Kluwe, 1987), and expectancy of success (Porter and Lawler, 1968, Vroom, 1964). Either overconfidence or lack of confidence can affect how a student learns. Students who believe that new skills are beyond their capability will not persevere and master the new skill, while students who believe they already know all they need to know will not put forth the effort required to master the new skill. Students who are challenged yet believe they can succeed learn most readily.

Satisfaction Satisfaction is the degree of personal gratification a student derives from a course. The theoretical base for this dimension includes feedback, reinforcement, self worth, and social context. Students are more likely to sustain learning activities when they believe the resulting new capabilities will increase their personal value and provide them more skills to offer others.

There has been little published research in this area in the recent past (Carey and colleagues is an exception). Despite a thorough literature review, we were able to find little empirical work in student motivation, and no work in the area of business classes, despite the development of several instruments for assessing the motivational quality of instructional situations (Small, 2000) based on the ARCS Model. One of the instruments that uses the ARCS Model as its foundation is the Academic Motivation Profile (AMP) that is used to assess college students' perceptions of higher education courses (Pearson and Carey, 1995, Carey et al., 2001). The AMP instrument has been tested in educational psychology, social foundations of education, and curriculum education classes (Carey et al., 2001). The AMP consistently displays strong internal consistency reliability (Cronbach's alpha > .94), and the four ARCS dimensions consistently yield high internal consistency (Cronbach's alpha 0.83 0.94) (Carey et al., 2001, Dedrick et al., 1995, Pearson and Carey, 1995). In the current study, the AMP is tested in multiple undergraduate business classes.

Methodology

This study follows the methodology used in several previous studies and follows the suggestion of Pearson and Carey (Pearson and Carey, 1995) that multiple sections of courses should be examined. The details are discussed below.

Sample The study examined 336 students enrolled in seven required undergraduate business classes at a large university in the southeastern United States. In keeping with the student population at this university, the study population included more male students (198) than female students (138); the top three majors represented in the sample were undeclared and non-business (109), accounting (76), and other business (151). The study included five instructors teaching seven courses. One instructor taught two sections of one course, two different instructors taught two sections of the same course, and the remaining three courses were different courses with different instructors. Based on a review of the syllabi, all the instructors employed similar teaching methods, and the same textbook was used in the common courses. The business classes were selected because of large enrollments of students from various business disciplines.

Instrumentation Each dimension included in the AMP is divided into three parts with three questions each. The parts in the attention dimension include text/computer materials, class presentations, and participation during class. Scaling on this section ranges from 1 (not the least bit interested and my attention wandered) to 5 (extremely interested and my attention did not wander). The relevance dimension includes relevance to course work, transition from college to career, and as a professional. Scaling on this section ranges from 1 (not the least bit relevant (useful) for helping me ...) to 5 (extremely relevant (useful) for helping me ...). The confidence dimension for the business courses includes course terminology, tools used in financial decisionmaking, and communication. The confidence dimension in education included curriculum design/development, analysis/evaluation of student progress, and communication. Scaling on this section ranges from 1 (I do not feel at all confident in my ability to...) to 5 (I feel totally confident in my ability to ...). The satisfaction section includes the student's perception of their participation, personal development, and professional affiliation. Scaling on this section ranges from 1 (I was not at all satisfied with...) to 5 (I was totally satisfied with...). Scores are obtained for each section by summing the items. The overall academic motivation score is obtained by taking the mean of the section averages.

The specific questions in each section must be tailored to course material used in the course under study. The development of the original instrument used education majors enrolled in educational instruction courses involving student evaluation methodology. Student evaluation was the primary task identified throughout the AMP in the previous study. This study uses finance and accounting classes. Based on a review of the textbooks and syllabi used for the classes included in the study, the common task in these classes related to decision-making using financial information; therefore, financial decision-making was the common task used to tailor the AMP.

Results

To examine the construct validity of the AMP, confirmatory factor analysis with equimax rotation was performed using the SPSS statistical package. A second confirmatory factory analysis was conducted using the AMOS statistical package and structural equation modeling to verify the results. All questions loaded as anticipated on the four factors (all attention questions loaded together, relevance questions loaded together, etc.). Internal consistency reliability was determined using Cronbach alpha coefficient. Total scale reliability was .94 on motivation as a whole. Section reliability for attention was .82; relevance was .90; satisfaction was .91; and confidence was .93. Results of this study indicate that internal consistency reliabilities of the total motivation scores and all subscale scores for the AMP are consistent with the developer's findings in the field of education (Carey et al., 2001, Pearson and Carey, 1995).

Consistent with previous studies of the AMP, the correlation of motivation and academic achievement are considered in this study to provide evidence of the applicability of AMP in business. The correlation among questions ranged from 0 to .20. Average overall motivation to achievement was .352 in this study and .30 in the previous study (Carey et al., 2001), which is typical of attitude to achievement comparisons (Carey et al., 2001). These correlations demonstrate that the AMP measures a characteristic distinct from that of course achievement.

Attention Students were asked to rate their level of attention to the various sources of information presented. The first three items related to the textbook and the first two of these loaded at .30; however, these two items did load most strongly with attention versus any of the other three factors. There were no cross loadings. Using criteria set by Hair et al. (1998), factor loadings of .30 are considered to meet minimal level; loadings of .40 are considered more important; and loadings of .50 or greater are considered practically significant. Theses guidelines are applicable when the sample is over 100, and so would apply in this study. The students appear to perceive textbook explanations and information and textbook examples differently from chapter practice exercise and feedback. Loadings related to class presentation and participation loaded more consistently between .57 and .76.

Relevance Students were asked to judge the degree of course relevance for meeting their immediate academic and future professional goals. All items loaded appropriately on the same designated factor with loadings ranging from .40-.82.

Confidence Students were asked to judge their degree of confidence in performing the skills related to the financial decision-making. All of these items loaded at levels (.69 -.77) indicating these questions measured the same dimension over all three sections (terminology, use, and communication).

Satisfaction Students were asked to judge their degree of self-satisfaction related to participation, personal development, and professional affiliation. All items loaded together (.54 - .77) indicating all items measure the same dimension.

Prior to further testing, analyses for potential covariates were conducted. Analysis revealed that neither course nor instructor had a significant effect on the main variables of interest. There was also no significant difference between sections or between majors. To examine the AMP's sensitivity in detecting differences in academic achievement, the motivation scores were blocked into motivation groups, high (> M + 1 SD), moderate (M to + 1 SD), low (M to -1 SD), and very low (< M -1 SD). The same procedure was used to block attention, relevance, confidence, and satisfaction. Analysis of variance (ANOVA) was used to detect any achievement difference among the different groups. There were significant differences in academic achievement found between high motivation and the other three groups. There was also a significant difference in academic achievement between moderate motivation and very low motivation. This is consistent with prior findings (Pearson and Carey, 1995).

Analysis of variance was used to detect any achievement difference by attention, relevance, confidence, and satisfaction. The attention and relevance were nonsignificant, but confidence and satisfaction were significant in relation to academic achievement scores. This also is consistent with prior findings (Pearson and Carey, 1995).

Discussion

When motivation was blocked into high, moderate, low, and very low, the variance in academic achievement is significant between high motivation and all other motivation levels and between moderate and very low motivation. If a class were populated with students who have more low or very low motivation levels than high levels, the academic achievement levels would be expected to be lower. Lack of motivation in a classroom not only appears to affect performance, but also may have effects reaching outside the classroom. For instance, many colleges and universities take student performance into consideration when evaluating instructors. If the class population includes a majority of students with low motivation, academic achievement levels are likely to be lower, potentially negatively affecting the instructor's performance rating.

Confidence and satisfaction were significant in relation to academic achievement. This is consistent with previous studies (Pearson and Carey, 1995) and could indicate that the attention and relevance dimensions require further development for use in these classes. As previously noted, two of the questions in the attention dimension related to textbooks and had the lowest factor loadings in the AMP. Whereas there is little that can be done to directly manipulate a student's confidence level and little that can be done to increase their satisfaction as long as grading is a reality, it does appear that more attention to textbook selection may be a way for instructors to increase attention and relevance. If a student's attention and perception of relevance can be increased, this and other studies indicate that motivation may also increase, culminating in a win-win situation for both student and instructor of enhanced academic performance.

While there was no statistical significant difference between majors in the results, there do appear to be some differences that should be noted. For instance, the attention and relevance questions did not load as well with the group of other business students. This may be an indication that these students have different perceptions about the classes than the accounting and non-business/undeclared students. Perhaps once a business major is chosen; student perceptions related to attention and relevance are negatively affected when taking any courses outside that major. The Cronbach alpha for other business students' attention dimension was .55 compared to accounting students .86, and non-business/undeclared students of .79. The non-significant findings may be the result of the effect size, which is smaller than that of confidence and satisfaction. The sample size may be too small to detect the differences in attention and relevance. Certainly, a perception difference is apparent. Based on the responses of relevance to a student's college career and professional career, we find that students see more relevance in courses to their ultimate career plans than their advancement toward graduation. Because the underlying task was decision making in relation to financial information, this seems appropriate. Traditional college students may not have much opportunity to analyze financial data in order to make decisions until they begin their career, and yet understand that it will be a common occurrence in their professional life. This may explain why relevance was not significant and had two of the lower factor loadings (.40) in the factor analysis.

The attention dimension relates to characteristics such as curiosity (Berlyne, 1965) and sensation seeking (Zuckerman, 1971) and may be considered more extrinsic (Deci et al., 1991) than intrinsic (Vallerand and Bissonnette, 1992). For this study, confidence and satisfaction may provide a more accurate measurement of intrinsic motivation than relevance and attention. Attention may have little effect because it is more extrinsic, and relevance appears to be too long-term of a goal to have a significant effect in this particular study. Instructors or departments who want to increase student motivation and thereby performance may consider testing motivation levels and stratifying between (or less ideally, within) sections. This would enable an instructor to work toward overcoming the bias exhibited by unmotivated students by allowing the course content and delivery to be geared toward increasing interest and applicability. Because our results show a difference between majors in a course and non-majors in the same course, another potential for targeting specific populations may be to offer major oriented and non-major oriented courses. The effects of curriculum changes may be more evident when student motivation and major choice is considered.

Certainly, changes may be affected without separating students by motivation or level. As mentioned previously, textbook selection may be a key to changing motivation and perception of relevance. For instance, would case-based material do more to increase relevance for non-majors while retaining the necessary skills elevation required by majors? It is likely that injecting real examples will begin to build the bridge between the course material and relevance, as well as increased practice that should culminate in increased confidence and skills. Alternately, perhaps attention can be increased across all students with a variety of presentation styles, ranging from guest lecturers from various companies to multimedia-based delivery. These ideas form the basis of future research.

Conclusion

The results of this study indicate that the AMP measures the motivation of business students in business classes comparably to educational students. The correlation between motivation and academic achievement in this study is consistent with that of prior studies in education. The AMP is consistent over different sections of the same class taught by different instructors, and different sections taught by the same instructor. This finding contributes to curriculum literature by extending the use of an instrument into the business domain. Further, we suggest ways that instructors can manipulate the classroom environment in an attempt to increase a student's perception of relevance and increase attention.

As students arrive in college and university classrooms more computer savvy and more media conscious than in times past, educators must rise to the challenge of creating motivating environments in which students may learn the skills necessary to function as professionals. This and other research has shown that this issue is not clear-cut; however, educators and students alike will reap the rewards.

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Teresa Lang, Columbus State University, GA Dianne J. Hall, Auburn University, AL

Lang, PHD., is an assistant professor of Accounting and Information Systems, and Hall, PHD., is an assistant professor of Management Information Systems.