ACADEMIC MOTIVATION FOR BUSINESS INFORMATION SYSTEMS STUDENTS

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ACADEMIC MOTIVATION FOR BUSINESS INFORMATION SYSTEMS

STUDENTS

Catalin Maican

maican@unitbv.ro

Radu Lixandroiu

lixi.radu@unitbv.ro Transilvania University of Brasov

Academic Motivation Scale AMS was applied to Business )nformation Systems students for finding out their reasons and motives for enrolling this academic field, for undergraduate and postgraduate academic cycles. The students were presented the AMS scale translated in Romanian, together with other questionnaires. The first part of the paper makes a short introduction to AMS, the second describes its objectives, while the third presents the results.

Key words: academic motivation scale, Business )nformation Systems.

Introduction

One of the most frequently used scales to measure the regulation of motivation according to self-determination theory is the Academic Motivation Scale Alivernini & Lucidi, ; Vallerand, R. J., Pelletier, L. G., Blais, M. R., Brière, N. M., Senécal, C., Vallières, , . The AMS consists of items, in which students respond to the question stem Why are you going to college? There are seven subscales on the AMS: The subscales reflected Amotivation e.g., (onestly, ) don t know; ) really feel that ) am wasting my time in school , External Regulation e.g., )n order to obtain a more prestigious job later on , )ntrojected Regulation e.g., Because of the fact that when ) succeed in school ) feel important , )dentified Regulation e.g., Because ) think that a college education will help me better prepare for the career ) have chosen , and )ntrinsic Regulation e.g., Because ) experience pleasure and satisfaction while learning new things . The items are rated on a scale, ranging from one does not correspond at all to seven corresponds exactly . Each subscale consists of four items each; thus subscale scores can range from to . A high score on a subscale indicates high endorsement of that particular academic motivation Kusurkar, Croiset, Kruitwagen, & ten Cate, . This scale was validated with various populations including English- and French-speaking students, from high school to university levels, and it was also tested for factorial invariance across gender and across time

Grouzet, F. M. E., Otis, N., Pelletier, .

Although the original version of the AMS Vallerand, R. J., Pelletier, L. G., Blais, M. R., Brière, N. M., Senécal, C., Vallières, , consisted of seven subscales, four of which reflecting different types of extrinsic motivation and three distinguishing between forms of intrinsic motivation, more recent studies e.g., Otis, Grouzet, & Pelletier, ; Ratelle, Guay, Larose, & Senécal, n.d. took into account only one measurement of intrinsic motivation intrinsic motivation to know and consequently evaluated five subscales instead of seven Grouzet, F. M. E., Otis, N., Pelletier, .

Other measuring tools have been established to measure internal motivation but they failed to achieve the adhesion of the AMS. One such instrument is one developed by Finney and called Achievement Goal Questionnaire Finney, Pieper, & Barron, . This instrument was intended to measure four developments of motivation: mastery approach, mastery-avoidance approach, performance approach, and performance-avoidance approach. Validating the Achievement Goal Questionnaire, later studies conducted by McCollum, D., Kajs, indicate that older students in an educational leadership program display higher levels of mastery-approach to learning as they are more internally motivated. Other scales such as the Mastery, Performance, and Alienation Goal Scale Archer, also did not succeed in achieving the acceptance and validation of the AMS in a variety of studies. Nevertheless, with the creation of these instruments, the motivation domain gained credibility as it now has accurate tools in the assessment of motivation in individuals (egarty, . On the whole, these results recommended that AMS is a valid and useful scale to measure academic motivation according to the multidimensional perspective of the self-determination theory.

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of academic motivation together with the evaluation of learning strategies, part of The Motivated Strategies for Learning Questionnaire P. R. Pintrich, ; P. Pintrich et al., n.d. and adapted for Romanian language by Clinciu Clinciu, . Moreover, the AMS was never tested for factorial invariance across gender and study program in Romanian higher education.

)n the present study the psychometric properties of a Romanian version of the AMS were evaluated in a sample of university students in the economic field. More specifically, the purpose of this part of the study consisted of the following:

. to evaluate the five-factor and the seven-factor model of academic motivation and to estimate the internal consistency of the scores;

. to test for factorial invariance across gender and study programs in the economic higher education field;

. to evaluate the correlations among the AMS subscales to assess the simplex pattern hypothesized by Vallerand, R. J., Pelletier, L. G., Blais, M. R., Brière, N. M., Senécal, C., Vallières, ; specifically, adjacent subscales should have stronger positive correlations than subscales that are farther apart, and the scales that are the farthest apart should have the strongest negative relationships;

Methodology and results

Study participants completed the described measures in class at the end of the school year. Students from the Business )nformation Systems study program and the ones in the corresponding postgraduate studies were informed that we were interested in understanding the reasons why they went to school. The questionnaire was completed anonymously and no compensation was given for participation.

Table presents the fit indices for the five-factor and seven-factor models with and without extracting variables from the factorization. We used Factorial Analisys, Extraction Method: Maximum Likelihood, Rotation Method: Promax with Kaiser Normalization. We emphasize that we could not validate the AMS for the studies population, but we did a partial validation by eliminating variables from the model.

Table . Fit indices for the model

Model CM)N df CM)N/df GF) AGF) CF) RMSEA

subscale – original , , , , , ,

subscale - without: extr_extreg_ , , , , , ,

subscale - without: extr_extreg_ +

intr_accompl_ , , , , , ,

subscale - without: Extr_extreg_ +

intr_accompl_ +intr_tokonw_ , , , , , ,

subscale - without: extr_extreg_ +

intr_accompl_ + extr_introj_ , , , , , ,

subscale - without: extr_extreg_ + intr_accompl_ +

extr_introj_ +intr_accompl_ +intr_tok

now_ , , , , , ,

extr_introj_ +intr_accompl_ +intr_tok

now_ +extr_introj , , , , , ,

extr_introj_ +intr_accompl_ +intr_tok now_ +extr_introj +extr_identif +int

r_expstim_ +amotiv_ , , , , , ,

subscales - original , , , , , ,

subscales -

without:extr_extreg_ +intr_toknow_ , , , , , ,

subscales, without variables , , , ,

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)n these cases the variable loading on factors does not correspond to the theoretical model. Clearly identified factors were the Amotivation, Experiences simulation intrinsic motivation and introjected extrinsic motivation. The closest model that corresponds the best with the theoretical one, is the one with factors and Eigenvalue > Table .

Table . Pattern matrix Factor

amotiv_ ,

extr_extreg_ ,

extr_identif_ ,

extr_introj_ ,

intr_accompl_ ,

intr_expstim_ ,

intr_toknow_ ,

extr_identif_ ,

The Cronbach s coefficient alpha values indicated that the subscales demonstrate adequate internal consistency Table . )n general, the means follow the same pattern reported in previous studies Cokley, Bernard, Cunningham, & Motoike, ; Vallerand, R. J., Pelletier, L. G., Blais, M. R., Brière, N. M., Senécal, C., Vallières, with „Amotivation being the least endorsed, while „extrinsic regulation was the most endorsed.

Table . Factor Correlation Matrix

Factor extrinsic

regulation Amotiv

intrinsic_Exp_

Stim extrinsic_Introj intrinsic_Accompl

Extrinsic_regulation ,

Amotivation - , ,

)ntrinsic_Exp_Stim , - , ,

Extrinsic_)ntrojected , - , , ,

)ntrinsic_accomplish , - , , , ,

Cronbach s ALFA , , , , ,

Means , , , , ,

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and between the extrinsic_regulation and extrinsic_introj factors there is a medium positive correlation. Regarding the factor analysis and the correlations on genders Table , we can note stronger correlations for females participans, at least regarding the relation between the extrinsic_introj / intrinsic_accompl and Amotivation . We cannot see significant differences between the analyzed correlations for the origins rural or urban areas , between all the factors being weak or medium correlations.

Conclusions

Motivation analysis for Business )nformation Systems students emphasized the following aspects: % of the total students considered that that have strong motives for going to university, . % consider that they can get an important job or a better salary later in their career, while . % hope that the education obtained by following this study program would increase their competencies on the market; we can consider all these as external factors extrinsic motivation . On the other hand, we have only . % of the students who want to prove themselves that they are able to obtain a higher education diploma, or . % who enjoy surpassing their personal results internal factors .

By applying factorial and confirmatory analysis we extracted a number of factors that validate part of the motivation theory: Amotivation, intrinsic motivation experience stimulation and extrinsic motivation introjected .

Table . Gender correlations for Academic Motivation Scale

Gender Fact1_extrinsic_regulat ion Fact2_Amotivati e Fact3_intrinsic_expsti m Fact4_extrinsic_int roj Fact5_intrinsic_acco mpl Pearson

Correlation 1

Fact1_extrinsic_ regulation

Sig. (2-tailed)

Pearson

Correlation -,656** 1

Fact2_Amotivati e

Sig. (2-tailed) _,000

Pearson

Correlation ,348** -,100 1

Fact3_intrinsic_ expstim

Sig. (2-tailed) _,000 _,217

Pearson

Correlation ,616** -,360** ,492** 1

Fact4_extrinsic_i ntroj

Sig. (2-tailed) _,000 _,000 _,000

Pearson

Correlation ,439** -,352** ,451** ,530** 1

Females, N=155

Fact5_intrinsic_ accompl

Sig. (2-tailed) _,000 _,000 _,000 _,000

Pearson

Correlation 1

Fact1_extrinsic_ regulation

Sig. (2-tailed)

Pearson

Correlation -,582** 1

Fact2_Amotivati e

Sig. (2-tailed) _,000

Pearson

Correlation ,237 ,133 1

Fact3_intrinsic_ expstim

Sig. (2-tailed) _,071 _,314

Pearson

Correlation ,586** -,229 ,318* 1

Fact4_extrinsic_i ntroj

Sig. (2-tailed) _,000 _,081 _,014

Pearson

Correlation ,459** -,159 ,271* ,559** 1

Males, N=59

Fact5_intrinsic_ accompl

Sig. (2-tailed) _,000 _,229 _,038 _,000

References

1. Alivernini, F., & Lucidi, F. (2008). The academic motivation scale (AMS): Factorial structure, invariance, and validity in the Italian context. TPM - Testing, Psychometrics, Methodology in Applied Psychology, 15(4), 211–220.

2. Archer, J. (1994). Achievement Goals as a Measure of Motivation in University Students. Contemporary

Educational Psychology, 19(4), 430–446. http://doi.org/10.1006/ceps.1994.1031

3. CAZAN, A. M., & ANITEI, M. (2010). MOTIVATION, LEARNING STRATEGIES AND ACADEMIC ADJUSTMENTS.

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4. Clinciu, A. I. (2003). Chestionar de inadaptare scolara. Eficienta, legalitate etica in Romania mileniului tre. Lux Libris.

5. Cokley, K. O., Bernard, N., Cunningham, D., & Motoike, J. (2001). A psychometric investigation of the Academic Motivation Scale using a United States sample. Measurement and Evaluation in Counseling and Development, (34), 109–119.

6. Finney, S. J., Pieper, S. L., & Barron, K. E. (2004). Examining the Psychometric Properties of the Achievement Goal Questionnaire in a General Academic Context. Educational and Psychological Measurement, 64(2), 365–382. http://doi.org/10.1177/0013164403258465

7. Gherasim, L. R., Maireana, C., & Butnaru, S. (2012). Prediction of School Performance: the Role of Motivational Orientation and Classroom Environment. Procedia - Social and Behavioral Sciences, 46, 3931–3935. http://doi.org/10.1016/j.sbspro.2012.06.174

8. Grouzet, F. M. E., Otis, N., Pelletier, L. G. (2006). Longitudinal cross-gender factorial invariance of the Academic Motivation Scale. Structural Equation Modeling, 13, 73–98.

9. Hegarty, N. (2010). Application of the Academic Motivation Scale to Graduate School Students. The Journal of Human Resource and Adult Learning, 6(2), 48–56. Retrieved from http://hraljournal.com/Page/6 Niall Hegarty.pdf

10. Kusurkar, R., Croiset, G., Kruitwagen, C., & ten Cate, O. (2011). Validity evidence for the measurement of the strength of motivation for medical school. Advances in Health Sciences Education, 16(2), 183–195. http://doi.org/10.1007/s10459-010-9253-4

11. McCollum, D., Kajs, L. (2007). Applying goal orientation theory in an exploration of student motivations in the domain of educational leadership. Educational Research Quarterly, 31(1), 45–60.

12. Otis, N., Grouzet, F. M. E., & Pelletier, L. G. (2005). Latent Motivational Change in an Academic Setting: A 3-Year Longitudinal Study. Journal of Educational Psychology, 97(2), 170–183. http://doi.org/10.1037/0022-0663.97.2.170

13. Pintrich, P. R. (2004). A Conceptual Framework for Assessing Motivation and Self-Regulated Learning in College Students. Educational Psychology Review, 16(4), 385–407. http://doi.org/10.1007/s10648-004-0006-x

14. Pintrich, P., Smith, S., Genthon, M. L., Martens, G. G., Hauen, C. L., Martens, G. G., … Wren, P. (n.d.). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).

15. Ratelle, C. F., Guay, F., Larose, S., & Senécal, C. (n.d.). Family Correlates of Trajectories of Academic Motivation During a School Transition: A Semiparametric Group-Based Approach.

16. Vallerand, R. J., Pelletier, L. G., Blais, M. R., Brière, N. M., Senécal, C., Vallières, E. F. (1992). The Academic Motivation Scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52, 1003–1019.