Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Journal of Computing in Higher Education
Published in: Journal of Computing in Higher Education 2/2009

01-08-2009

Think, feel, act: motivational and emotional influences on military students’ online academic success

Author: Anthony R. Artino

Published in: Journal of Computing in Higher Education | Issue 2/2009

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This study employed a social-cognitive view of self-regulated learning to examine how several personal factors relate to academic success in an online course. Service academy undergraduates (N = 481) completed a survey that assessed their motivational beliefs (self-efficacy and task value); negative achievement emotions (boredom and frustration); and several outcomes that included their use of self-regulated learning strategies (elaboration and metacognition), course satisfaction, and continuing motivation to enroll in future online courses. Results from several multiple regressions revealed that task value beliefs were the strongest and most consistent positive predictors of elaboration, metacognition, satisfaction, and continuing motivation; whereas self-efficacy beliefs were moderately strong positive predictors of satisfaction and continuing motivation only. On the other hand, students’ boredom and frustration were statistically significant predictors of metacognition, with boredom emerging as a negative predictor and frustration unexpectedly emerging as a positive predictor. Furthermore, both boredom and frustration were negatively related to satisfaction and continuing motivation. Taken together, results from this study provide some insight into the complex relations between students’ thoughts, feelings, and actions in an online course. Theoretical and empirical implications are discussed, as are study limitations and future directions.
previous article Scaffolded video self-analysis: discrepancies between preservice teachers’ perceived and actual instructional decisions

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
Abrami, P. C., & Bernard, R. M. (2006). Research on distance education: In defense of field experiments. Distance Education, 24, 5–26.CrossRef
Alexander, P., Graham, S., & Harris, K. (1998). A perspective on strategy research: Progress and prospects. Educational Psychology Review, 10, 129–154.CrossRef
Arbuckle, J. L. (2006). Amos 7.0 user’s guide. Chicago, IL: SPSS, Inc.
Artino, A. R. (2007). Online military training: Using a social cognitive view of motivation and self-regulation to understand students’ satisfaction, perceived learning, and choice. Quarterly Review of Distance Education, 8, 191–202.
Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training. Journal of Computer Assisted Learning, 24, 260–270.CrossRef
Artino, A. R., & McCoach, D. B. (2008). Development and initial validation of the online learning value and efficacy scale. Journal of Educational Computing Research, 38, 279–303.CrossRef
Artino, A. R., & Stephens, J. M. (2006). Learning online: Motivated to self-regulation? Academic Exchange Quarterly, 10(4), 176–182.
Azevedo, R. (2005). Using hypermedia as a metacognitive tool for enhancing student learning? The role of self-regulated learning. Educational Psychologist, 40, 199–209.CrossRef
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman and Company.
Bandura, A. (2006). Guide for constructing self-efficacy scales. In F. Pajares & T. Urdan (Eds.), Adolescence and education, Vol. 4: Self-efficacy beliefs of adolescents (pp. 307–337). Greenwich, CT: Information Age Publishing.
Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41, 586–598.CrossRef
Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., et al. (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74, 379–439.CrossRef
Boekaerts, M., & Cascallar, E. (2006). How far have we moved toward the integration of theory and practice in self-regulation? Educational Psychology Review, 18, 199–210.CrossRef
Chiu, C., Sun, S., Sun, P., & Ju, T. L. (2007). An empirical analysis of the antecedents of web-based learning continuance. Computers & Education, 49, 1224–1245.CrossRef
Chyung, S. Y. (2001). Systematic and systemic approaches to reducing attrition rates in online higher education. The American Journal of Distance Education, 15(3), 36–49.CrossRef
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
Dabbagh, N., & Kitsantas, A. (2004). Supporting self-regulation in student-centered web-based learning environments. International Journal on E-Learning, 3(1), 40–47.
Eccles, J., & Wigfield, A. (1995). In the mind of the actor: The structure of adolescents’ achievement task values and expectancy-related beliefs. Personality and Social Psychology Bulletin, 21, 215–225.CrossRef
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132.CrossRef
Flavell, J. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34, 906–911.CrossRef
Gable, R. K., & Wolfe, M. B. (1993). Instrument development in the affective domain: Measuring attitudes and values in corporate and school settings. Boston: Kluwer Academic Publishers.
Goetz, T., Pekrun, R., Hall, N., & Haag, L. (2006). Academic emotions from a social-cognitive perspective: Antecedents and domain specificity of students’ affect in the context of Latin instruction. British Journal of Educational Psychology, 76, 289–308.CrossRef
Gunawardena, C. N., & McIsaac, M. S. (2004). Distance education. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (2nd ed., pp. 355–396). Mahwah, NJ: Erlbaum.
Hadwin, A. F., Nesbit, J. C., Jamieson-Noel, D., Code, J., & Winne, P. H. (2007). Examining trace data to explore self-regulated learning. Metacognition and Learning, 2, 107–124.CrossRef
Hamilton, R. J. (1997). Effects of three types of elaboration on learning concepts from text. Contemporary Educational Psychology, 22, 299–318.CrossRef
Hartley, K., & Bendixen, L. D. (2001). Educational research in the Internet age: Examining the role of individual characteristics. Educational Researcher, 30(9), 22–26.CrossRef
Hsu, J. T. (1997). Value, expectancy, metacognition, resourced management, and academic achievement: A structural model of self-regulated learning in a distance education context. Dissertation Abstracts International, 59(5), 1458. (UMI No. 9835152).
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.CrossRef
Joo, Y., Bong, M., & Choi, H. (2000). Self-efficacy for self-regulated learning, academic self-efficacy, and Internet self-efficacy in Web-based instruction. Educational Technology Research and Development, 48(2), 5–17.CrossRef
Judd, C. M., & Kenny, D. A. (1981). Estimating the effects of social interventions. Cambridge: Cambridge University Press.
Kinzie, M. B., & Sullivan, H. J. (1989). Continuing motivation, learner control, and CAI. Educational Technology Research and Development, 37(2), 5–14.CrossRef
Klein, J. D., Erchul, J. A., & Pridemore, D. R. (1994). Effects of individual versus cooperative learning and type of reward on performance and continuing motivation. Contemporary Educational Psychology, 19, 23–32.CrossRef
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: The Guilford Press.
Lane, A. M., Whyte, G. P., Terry, P. C., & Nevill, A. M. (2005). Mood, self-set goals and examination performance: The moderating effect of depressed mood. Personality and Individual Differences, 39, 143–153.CrossRef
Larreamendy-Joerns, J., & Leinhardt, G. (2006). Going the distance with online education. Review of Educational Research, 76, 567–605.CrossRef
Lee, C. (2002). The impact of self-efficacy and task value on satisfaction and performance in a web-based course. Dissertation Abstracts International, 63(05), 1798. (UMI No. 3054599).
Lent, R. W., Brown, S. D., & Larking, K. C. (1984). Relation of self-efficacy expectations to academic achievement and persistence. Journal of Counseling Psychology, 31, 356–362.CrossRef
Linnenbrink, E. A., & Pintrich, P. R. (2002). Achievement goal theory and affect: An asymmetrical bidirectional model. Educational Psychologist, 37, 69–78.CrossRef
Linnenbrink, E. A., & Pintrich, P. R. (2004). Role of affect in cognitive processing in academic contexts. In D. Y. Dai & R. J. Sternberg (Eds.), Motivation, emotion, and cognition: Integrative perspectives on intellectual functioning and development (pp. 57–87). Mahwah, NJ: Lawrence Erlbaum Associates.
Lynch, R., & Dembo, M. (2004). The relationship between self-regulation and online learning in a blended learning context. International Review of Research in Open and Distance Learning, 5(2), 1–16.
Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for Research in Mathematics Education, 30, 520–540.CrossRef
Maehr, M. (1976). Continuing motivation: An analysis of a seldom considered educational outcome. Review of Educational Research, 46, 443–462.
Miltiadou, M., & Savenye, W. C. (2003). Applying social cognitive constructs of motivation to enhance student success in online distance education. Association for the Advancement of Computing in Education Journal, 11(1), 78–95.
Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of Educational Research, 66, 543–578.
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341.CrossRef
Pekrun, R., Goetz, T., & Perry, R. P. (2005). Achievement emotions questionnaire (AEQ): User’s manual. Munich, Germany: University of Munich, Department of Psychology.
Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist, 37, 99–105.CrossRef
Pekrun, R., Hall, N. C., & Perry, R. P. (2008). Boredom in academic settings: Control-value antecedents and performance consequences of a neglected emotion. Paper presented at the annual meeting of the American Educational Research Association, New York, NY.
Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31, 459–470.CrossRef
Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning component of classroom academic performance. Journal of Educational Psychology, 82, 33–40.CrossRef
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educational and Psychological Measurement, 53, 801–813.CrossRef
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, K. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130, 261–288.CrossRef
Roca, J. C., Chiu, C., & Martinez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. Human-Computer Studies, 64, 683–696.CrossRef
Salomon, G. (1984). Television is “easy” and print is “tough”: The differential investment of mental effort in learning as a function of perceptions and attributions. Journal of Educational Psychology, 76, 647–658.CrossRef
Schunk, D. H. (2005). Self-regulated learning: The educational legacy of Paul R. Pintrich. Educational Psychologist, 40, 85–94.CrossRef
Schunk, D. H., Pintrich, P. R., & Meece, J. L. (2008). Motivation in education: Theory, research, and applications (3rd ed.). Upper Saddle River, NJ: Pearson Education.
Schunk, D. H., & Zimmerman, B. J. (Eds.). (2008). Motivation and self-regulated learning: Theory, research, and applications. New York: Lawrence Erlbaum Associates.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton-Mifflin.
Tallent-Runnels, M. K., Thomas, J. A., Lan, W. Y., Cooper, S., Ahern, T. C., Shaw, S. M., et al. (2006). Teaching courses online: A review of the research. Review of Educational Research, 76, 93–135.CrossRef
Thorndike, R. M. (2005). Measurement and evaluation in psychology and education (7th ed.). Upper Saddle River, NJ: Pearson Education, Inc.
Wang, M. C., Haertel, G. D., & Walberg, H. J. (1990). What influences learning? A content analysis of review literature. Journal of Educational Research, 84, 30–43.
Wang, A. Y., & Newlin, M. H. (2002). Predictors of web-student performance: The role of self-efficacy and reasons for taking an on-line class. Computers in Human Behavior, 18, 151–163.CrossRef
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.CrossRef
Wood, R. E., & Bandura, A. (1989). Social cognitive theory of organizational management. Academy of Management Review, 14, 361–384.CrossRef
Wosnitza, M., & Volet, S. (2005). Origin, direction and impact of emotions in social online learning. Learning and Instruction, 15, 449–464.CrossRef
Zembylas, M., Theodorou, M., & Pavlakis, A. (2008). The role of emotions in the experience of online learning: Challenges and opportunities. Educational Media International, 45, 107–117.CrossRef
Zhao, Y., Lei, J., Yan, B., Lai, C., & Tan, H. S. (2005). What makes the difference? A practical analysis of research on the effectiveness of distance education. Teachers College Record, 107, 1836–1884.CrossRef
Zimmerman, B. J. (2000a). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). San Diego, CA: Academic.CrossRef
Zimmerman, B. J. (2000b). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25, 82–91.CrossRef
Zimmerman, B. J. (2008a). Goal setting: A key proactive source of academic self-regulation. In D. H. Schunk & B. J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research, and applications (pp. 267–296). New York: Lawrence Erlbaum Associates.
Zimmerman, B. J. (2008b). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45, 166–183.CrossRef
Zimmerman, B. J., & Martinez-Pons, M. (1990). Student differences in self-regulated learning: Relating grade, sex, and giftedness to self-efficacy and strategy use. Journal of Educational Psychology, 82, 51–59.CrossRef
Zimmerman, B. J., & Tsikalas, K. E. (2005). Can computer-based learning environments (CBLEs) be used as self-regulatory tools to enhance learning? Educational Psychologist, 40, 267–271.CrossRef
Zusho, A., Pintrich, P. R., & Coppola, B. (2003). Skill and will: The role of motivation and cognition in the learning of college chemistry. International Journal of Science Education, 25, 1081–1094.CrossRef
Metadata
Title
Think, feel, act: motivational and emotional influences on military students’ online academic success
Author
Anthony R. Artino
Publication date
01-08-2009
Publisher
Springer US
Published in
Journal of Computing in Higher Education / Issue 2/2009
Print ISSN: 1042-1726
Electronic ISSN: 1867-1233
DOI
https://doi.org/10.1007/s12528-009-9020-9

Premium Partner

    Image Credits