Abstract
Employers lament that science graduates, particularly engineering students, lack professional skills, despite increasing emphasis on teaching professional skills in their curriculum. Using the Theory of Planned Behavior as an overarching framework, one explanation for skill development gaps may be students’ attitude towards learning professional skills. Our study purpose was to create a scale that accurately and consistently measures engineering students’ attitudes towards learning professional skills. To create the scale, we used a rigorous measurement development methodology, beginning with survey item generation and critical review by subject matter experts. Data from a sample of 534 engineering college students were split into two sets to provide (1) a development sample upon which exploratory factor analyses and parallel analyses were conducted to form the initial scale, and (2) a confirmatory sample whereby we verified the scale structure and obtained initial validity evidence for distinct dimensions. A five-factor scale of 25 items for assessing engineering students’ attitudes towards learning professional skills (ATLPS) obtained high-reliability estimates. Validity evidence supported five distinct dimensions in leadership in teams, communication, civic and public engagement, cultural adaptability, and innovation. The ATLPS can be used to facilitate improvements in engineering education and research by understanding students’ attitudes towards learning professional skills. Furthermore, researchers can expand the scale to include additional dimensions of professionalism and modify items to fit STEM disciplines where professional skill training is essential.
Similar content being viewed by others
References
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T.
Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: a theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918. https://doi.org/10.1037/0033-2909.84.5.888.
American Educational Research Association, American Psychological Association, and National Council on Measurement in Education (US) (2014). Standards for educational & psychological testing.
American Society for Engineering Education (2013). Transforming undergraduate education in engineering: Phase I: Synthesizing and integrating industry perspectives. Retrieved from https://www.asee.org/TUEE_PhaseI_WorkshopReport.pdf.
Anseel, F., Lievens, F., Schollaert, E., & Choragwicka, B. (2010). Response rates in organizational science, 1995–2008: a meta-analytic review and guidelines for survey researchers. Journal of Business and Psychology, 25(3), 335–349. https://doi.org/10.1007/s10869-010-9157-6.
Areni, C. S., & Lutz, R. J. (1988). The role of argument quality in the Elaboration Likelihood Model. Advances in Consumer Research, 15(1), 197–203.
Armstrong, R. L. (1987). The midpoint on a five-point Likert-type scale. Perceptual and Motor Skills, 64(2), 359–362. https://doi.org/10.2466/pms.1987.64.2.359.
Baytiyeh, H., & Naja, M. K. (2010). Impact of college learning on engineering career practice. ASEE/IEEE Frontiers in Education Conference in Washington, D.C. https://doi.org/10.1109/FIE.2010.5673241
Besterfield-Sacre, M., Atman, C. J., & Shuman, L. J. (1998). Engineering student attitudes assessment. Journal of Engineering Education, 87(2), 133–141. https://doi.org/10.1002/j.2168-9830.1998.tb00333.x.
Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: an elaboration likelihood model. MIS Quarterly, 30, 805–825.
Blue, A. V., Crandall, S., Nowacek, G., Luecht, R., Chauvin, S., & Swick, H. (2009). Assessment of matriculating medical students’ knowledge and attitudes towards professionalism. Medical Teacher, 31(10), 928–932. https://doi.org/10.3109/01421590802574565.
Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.
Chan, J. C. (2009). When does retrieval induce forgetting and when does it induce facilitation? Implications for retrieval inhibition, testing effect, and text processing. Journal of Memory and Language, 61(2), 153–170. https://doi.org/10.1016/j.jml.2009.04.004.
Chan, C. Y., Zhao, Y., & Luk, L. Y. (2017). A validated and reliable instrument investigating engineering students’ perceptions of competency in generic skills. Journal of Engineering Education, 106(2), 299–325. https://doi.org/10.1002/jee.20165.
Chiang, F.-K., Wuttke, H., Knauf, R., Sun, C.-S., & Tso, T.-C. (2009). Students’ attitudes toward using innovative information technology for learning based on theory of planned behavior. International Journal of Advanced Corporate Learning, 2(4), 9–14. https://doi.org/10.3991/ijac.v2i4.969.
Cialdini, R. B., Petty, R. E., & Cacioppo, J. T. (1981). Attitude and attitude change. Annual Review of Psychology, 32, 357–404. https://doi.org/10.1146/annurev.ps.32.020181.002041.
Conway, J. M. (2002). Method variance and method bias in industrial and organizational psychology. In S. G. Rogelberg (Ed.), Handbook of research methods in industrial and organizational psychology (pp. 344–365). Malden: Blackwell Publishing.
Conway, J. M., & Huffcutt, A. I. (2003). A review and evaluation of exploratory factor analysis practices in organizational research. Organizational Research Methods, 6(2), 147–168. https://doi.org/10.1177/1094428103251541.
Crawford, A. V., Green, S. B., Levy, R., Lo, W., Scott, L., Svetina, D., & Thompson, M. S. (2010). Evaluation of parallel analysis methods for determining the number of factors. Educational and Psychological Measurement, 70(6), 885–901. https://doi.org/10.1177/0013164410379332.
Davidson, R. J., Gray, J. A., Lazarus, R., Rothbart, M. K., & Ekman, P. (1994). How do individuals differ in emotion-related activity? In P. Ekman & R. J. Davidson (Eds.), The nature of emotion: fundamental questions (pp. 319–343). New York: Oxford University Press.
de Jong, J., & den Hartog, D. (2010). Measuring innovative work behaviour. Creativity and Innovation Management, 19(1), 23–36. https://doi.org/10.1111/j.1467-8691.2010.00547.x.
DeVellis, R. F. (2012). Scale development. United States: SAGE Publications, Inc.
Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method, 4th Edition. John Wiley & Sons, Inc.
Douglas, K. A., & Purzer, S. (2015). Validity: meaning and relevancy in assessment for engineering education research. Journal of Engineering Education, 104(2), 108–118. https://doi.org/10.1002/jee.20070.
Farr, J. V., & Brazil, D. M. (2010). Leadership skills development for engineers. IEEE Engineering Management Review, 38(4), 110–118.
Fishbein, M. (1963). An investigation of the relationship between beliefs about an object and an attitude toward that object. Human Relations, 16, 233–239.
Fisher, D. (2014). Fostering 21stcentury skills in engineering undergraduates through co-curricular involvement. Presented at the annual conference for the American Society of Engineering Education in Indianapolis.
Ford, J. K., MacCallum, R. C., & Tait, M. (1986). The application of exploratory factor analysis in applied psychology: a critical review and analysis. Personnel Psychology, 39(2), 291–314. https://doi.org/10.1111/j.1744-6570.1986.tb00583.x.
Forman, S. M., & Freeman, S. F. (2013). The unwritten syllabus: It’s not just equations—student thoughts on professional skills. Presented at the 120th ASEE Annual Conference & Exposition in Atlanta, Georgia.
Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: the broaden-and-build theory of positive emotions. American Psychologist, 56(3), 218–226. https://doi.org/10.1037/0003-066X.56.3.218.
Fredrickson, B. L., Cohn, M. A., Coffey, K. A., Pek, J., & Finkel, S. M. (2008). Open hearts build lives: positive emotions, induced through loving-kindness meditation, build consequential personal resources. Journal of Personality and Social Psychology, 95(5), 1045–1062. https://doi.org/10.1037/a0013262.
Furnham, A. (1992). Relationship between knowledge of and attitudes towards AIDS. Psychological Reports, 71(3, Pt 2), 1149–1150. https://doi.org/10.2466/PR0.71.8.1149-1150.
Gardner, P. L. (1995). Measuring attitudes to science: unidimensionality and internal consistency revisited. Research in Science Education, 25(3), 267–281.
Garland, R. (1991). The mid-point on a rating scale: is it desirable? Marketing Bulletin, 2, 66–71.
Green, S. B., Levy, R., Thompson, M. S., Lu, M., & Lo, W. (2012). A proposed solution to the problem with using completely random data to assess the number of factors with parallel analysis. Educational and Psychological Measurement, 72(3), 357–374. https://doi.org/10.1177/0013164411422252.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. https://doi.org/10.1080/10705519909540118.
Humphreys, L. G., & Montanelli, R. G. (1975). An investigation of the parallel analysis criterion for determining the number of common factors. Multivariate Behavioral Research, 10, 193–205.
Jaschik, S. (2015). Well-prepared in their own eyes. Retrieved from https://www.insidehighered.com/news/2015/01/20/study-finds-big-gaps-between-student-and-employer-perceptions.
Judge, T. A., Bono, J. E., & Locke, E. A. (2000). Personality and job satisfaction: the mediating role of job characteristics. Journal of Applied Psychology, 85(2), 237–249. https://doi.org/10.1037/0021-9010.85.2.237.
Kar, Y. T., & Ho, S. Y. (2005). Web personalization as a persuasion strategy: an Elaboration Likelihood Model perspective. Information Systems Research, 16(3), 271–291. https://doi.org/10.1287/isre.1050.0058.
Katz, S. M. (1993). The entry-level engineer: problems in transition from student to professional. Journal of Engineering Education, 82(3), 171–174.
Kitchen, P. J., Kerr, G., Schultz, D. E., McColl, R., & Pals, H. (2014). The elaboration likelihood model: review, critique and research agenda. European Journal of Marketing, 48(11/12), 2033–2050. https://doi.org/10.1108/EJM-12-2011-0776.
Kok, B. E., Coffey, K. A., Cohn, M. A., Catalino, L. I., Vacharkulksemsuk, T., Algoe, S. B., Brantley, M., & Fredrickson, B. L. (2013). How positive emotions build physical health: perceived positive social connections account for the upward spiral between positive emotions and vagal tone. Psychological Science, 24(7), 1123–1132. https://doi.org/10.1177/0956797612470827.
Krosnick, J. A., Boninger, D. S., Chuang, Y. C., Berent, M. K., & Carnot, C. G. (1993). Attitude strength: one construct or many related constructs? Journal of Personality and Social Psychology, 65(6), 1132–1151. https://doi.org/10.1037/0022-3514.65.6.1132.
Li, C. (2013). Persuasive messages on information system acceptance: a theoretical extension of elaboration likelihood model and social influence theory. Computers in Human Behavior, 29(1), 264–275. https://doi.org/10.1016/j.chb.2012.09.003.
Loraas, T. M., & Diaz, M. C. (2011). Learning new technologies: the effect of ease of learning. Journal of Information Systems, 25(2), 171–194. https://doi.org/10.2308/isys-10109.
Morreale, M. K., Balon, R., & Arfken, C. L. (2011). Survey of the importance of professional behaviors among medical students, residents, and attending physicians. Academic Psychiatry, 35(3), 191–195. https://doi.org/10.1176/appi.ap.35.3.191.
Muthén, L. K., & Muthén, B. O. (1998-2010). Mplus user’s guide (Sixth ed.). Los Angeles: Muthén & Muthén.
National Academy of Engineering. (2004). The engineer of 2020: Visions of engineering in the new century. Washington, DC: The National Academies Press. https://doi.org/10.17226/10999.
National Academy of Engineering. (2005). Educating the engineer of 2020: Adapting engineering education to the new century. Washington, DC: The National Academies Press. https://doi.org/10.17226/11338.
Nguyen, D. Q. (1998). The essential skills and attributes of an engineer: a comparative study of academics, industry personnel, and engineering students. Global Journal of Engineering Education, 2(1), 65–74.
O'Flynn, S., Power, S., Horgan, M., & O’Tuathaigh, C. P. (2014). Attitudes towards professionalism in graduate and non-graduate entrants to medical school. Education for Health, 27(2), 200–204. https://doi.org/10.4103/1357-6283.143770.
Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: classic and contemporary approaches. Dubuque: Brown.
Podsakoff, P. M., MacKenzie, S. B., Lee, J., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879.
Rees, C., Sheard, C., & Davies, S. (2002). The development of a scale to measure medical students' attitudes towards communication skills learning: the Communication Skills Attitude Scale (CSAS). Medical Education, 36(2), 141–147. https://doi.org/10.1046/j.1365-2923.2002.01072.x.
Royal Academy of Engineering (2015). Engineering for a successful nation. Retrieved from http://www.raeng.org.uk/publications/reports/engineering-for-a-successful-nation.
Salancik, G. R., & Pfeffer, J. (1978). A social information processing approach to job attitudes and task design. Administrative Science Quarterly, 23(2), 224–253. https://doi.org/10.2307/2392563.
Sauermann, H., & Roach, M. (2013). Increasing web survey response rates in innovation research: an experimental study of static and dynamic contact design features. Research Policy, 42(1), 273–286. https://doi.org/10.1016/j.respol.2012.05.003.
Schumann, D. W., Kotowski, M. R., Ahn, H.-Y., & Haugtvedt, C. (2012). The elaboration likelihood model: a 30-year review. In S. Rodgers & E. Thorson (Eds.), Advertising theory (pp. 51–68). NY: Routledge.
Shuman, L. J., Besterfield-Sacre, M., & McGourty, J. (2005). The ABET “professional skills”—can they be taught? Can they be assessed? Journal of Engineering Education, 94(1), 41–55. https://doi.org/10.1002/j.2168-9830.2005.tb00828.x.
Smith, G. (2015). The impact of a professional development programme on primary teachers’ classroom practice and pupils’ attitudes to science. Research in Science Education, 45(2), 215–239.
Stevens, J. (1996). Applied multivariate statistics for the social sciences (3rd ed.). Mahwah: Lawrence Erlbaum.
Thompson, B. (2004). Exploratory and confirmatory factor analysis: understanding concepts and applications. Washington, DC: American Psychological Association.
Winters, K. E., Matushovich, H. M, Brunhaver, S., Chen, H. L., Yasuhara, K., & Sheppard, S. (2013). From freshman engineering students to practicing professionals: Changes in beliefs about important skills over time. Presented at the 120th ASEE Annual Conference & Exposition in Atlanta, Georgia.
Acknowledgements
We would like to thank Alma Rosales and Alistair Cook for their early contributions to portions of this project, as well as Tom Siller and Anthony Maciejewski for suggestions on earlier versions of this manuscript.
Funding
This work was supported in part by the National Science Foundation, Engineering Education and Centers, under Grant EEC-1519438.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Byrne, Z.S., Weston, J.W. & Cave, K. Development of a Scale for Measuring Students’ Attitudes Towards Learning Professional (i.e., Soft) Skills. Res Sci Educ 50, 1417–1433 (2020). https://doi.org/10.1007/s11165-018-9738-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11165-018-9738-3