nach oben

Education and Information Technologies

Erschienen in:

20.07.2017

The relationship between sources of self-efficacy in classroom environments and the strength of computer self-efficacy beliefs

verfasst von: Yuwarat Srisupawong, Ravinder Koul, Jariya Neanchaleay, Elizabeth Murphy, Emmanuel Jean Francois

Erschienen in: Education and Information Technologies | Ausgabe 2/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Motivation and success in computer-science courses are influenced by the strength of students’ self-efficacy (SE) beliefs in their learning abilities. Students with weak SE may struggle to be successful in a computer-science course. This study investigated the factors that enhance or impede the computer self-efficacy (CSE) of computer-science students. Data collection involved a survey of 524 undergraduate computer-science students from 10 Thai universities. The survey measured four items of CSE, 13 items pertaining to the classroom learning environment (CLE), and 14 items related to information sources of SE. Results revealed that perceptions of a CLE with autonomy, meaningfulness, and involvement were positively associated with strong CSE. In addition, perceptions of social persuasions such as meaningful and encouraging feedback or judgment from influential people demonstrated a statistically positive relationship with CSE. Perceptions of vicarious experiences whereby students determine and compare their own abilities with observational experiences of role models also demonstrated a statistically positive relationship with CSE. Perceived physiological and affective states such as anxiety and stress demonstrated a negative influence CSE. Implications for practice relate to students’ perceptions of autonomous learning, the value of positive feedback, students’ input into learning content and activities, role models for students and observation of how peers perform tasks better or worse.

Vorheriger Artikel Students’ participation in peer-to-peer communication supported by social media

Nächster Artikel Language play in a second language: Social media as contexts for emerging Sociopragmatic competence

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren

Akinbobola, O., & Adeleke, A. (2013). The influence of user efficacy and expectation on actual system use. Interdisciplinary Journal of Information, Knowledge, and Management, 8, 43–57 Retrieved from http://www.ijikm.org/Volume8/IJIKMV8p043-057Akinbobola0725.pdf.CrossRef

Alexander, P., & Twinomurinzi, H. (2012). Changing career choice factors as the economic environment changes. Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference (pp. 295–305). Pretoria: ACM.

Alt, D. (2015). Assessing the contribution of a constructivist learning environment to academic self-efficacy in higher education. Learning Environments Research, 18(1), 47–67. doi:10.1007/s10984-015-9174-5.CrossRef

Anderson, R. (2000). Vicarious and persuasive influences on efficacy expectations and intentions to perform breast self-examination. Public Relations Review, 26(1), 97–114. doi:10.1016/s0363-8111(00)00033-3.CrossRef

Aronson, E. (1969). The theory of cognitive dissonance: A current perspective. Advances in Experimental Social Psychology, 4, 1–34. doi:10.1016/s0065-2601(08)60075-1.CrossRef

Australian Computer Society (2016). Developing the digital workforce to drive growth in the future. Retrieved from https://www.acs.org.au/news/australias-digital-pulse-2016.html. Accessed 24 Mar 2017.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs: Prentice-Hall, Inc..

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company.

Bassi, M., Steca, P., Delle Fave, A., & Caprara, G. (2007). Academic self-efficacy beliefs and quality of experience in learning. Journal of Youth and Adolescence, 36(3), 301–312. doi:10.1007/s10964-006-9069-y.CrossRef

Beaubouef, T., & Mason, J. (2005). Why the high attrition rate for computer science students: Some thoughts and observations. ACM SIGCSE Bulletin, 37(2), 103–106. doi:10.1145/1083431.1083474.CrossRef

Beaubouef, T., & McDowell, P. (2008). Computer science: Student myths and misconceptions. Journal of Computing Sciences in Colleges, 23(6), 43–48 Retrieved from http://dl.acm.org/citation.cfm?id=1352392.

Beaubouef, T., & Zhang, W. (2011). Where are the women computer science students? Journal of Computing Sciences in Colleges, 26(4), 14–20 Retrieved from http://dl.acm.org/citation.cfm?id=1953576.

Bentler, P. (2006). EQS structural equations program manual. Encino: Multivariate Software.

Bentler, P., & Bonnet, D. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. doi:10.1037/0033-2909.88.3.588.CrossRef

Braught, G., Wahls, T., & Eby, L. (2011). The case for pair programming in the computer science classroom. ACM Transactions on Computing Education, 11(1), 1–21. doi:10.1145/1921607.1921609.CrossRef

Brislin, R. (1980). Translation and content analysis of oral and written material. In H. C. Triandis & J. W. Berry (Eds.), Handbook of cross-cultural psychology (pp. 389–444). Boston: Allyn & Bacon.

Britner, S., & Pajares, F. (2006). Sources of science self-efficacy beliefs of middle school students. Journal of Research in Science Teaching, 43(5), 485–499. doi:10.1002/tea.20131.CrossRef

Carnevale, A., Smith, N., & Melton, M. (2011). STEM: Science technology engineering mathematics. Resource document: Georgetown University Retrieved from https://eric.ed.gov/?id=ED525297.

Carroll, J., Rosson, M., & Zhou, J. (2005). Collective efficacy as a measure of community. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1-10). Portland: ACM.

Çelik, H. (2015). Effects of computer course on computer self-efficacy, computer attitudes and achievements of young individuals' in Siirt, Turkey. Educational Research Review, 10(3), 249–258. doi:10.5897/ERR2014.2037.CrossRef

Celik, V., & Yesilyurt, E. (2013). Attitudes to technology, perceived computer self-efficacy and computer anxiety as predictors of computer supported education. Computers & Education, 60(1), 148–158. doi:10.1016/j.compedu.2012.06.008.CrossRef

Chen, X., & Soldner, M. (2013). STEM attrition: College students' paths into and out of STEM fields. In Statistical Analysis Report, NCES 2014–001, 1–57. Resource document. U.S.: Department of Education Retrieved from https://nces.ed.gov/pubs2014/2014001rev.pdf.

Chen, J., & Usher, E. (2013). Profiles of the sources of science self-efficacy. Learning and Individual Differences, 24, 11–21. doi:10.1016/j.lindif.2012.11.002.CrossRef

Close, W., & Solberg, S. (2008). Predicting achievement, distress, and retention among lower-income Latino youth. Journal of Vocational Behavior, 72(1), 31–42. doi:10.1016/j.jvb.2007.08.007.CrossRef

Compeau, D., & Higgins, C. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. doi:10.2307/249688.CrossRef

Deechuay, N., Koul, R., Maneewan, S., & Lerdpornkulrat, T. (2016). Relationship between gender identity, perceived social support for using computers, and computer self-efficacy and value beliefs of undergraduate students. Education and Information Technologies, 21(6), 1699–1713. doi:10.1007/s10639-015-9410-8.CrossRef

Diseth, Å. (2011). Self-efficacy, goal orientations and learning strategies as mediators between preceding and subsequent academic achievement. Learning and Individual Differences, 21(2), 191–195. doi:10.1016/j.lindif.2011.01.003.CrossRef

Dorman, J. (2001). Associations between classroom environment and academic efficacy. Learning Environments Research, 4(3), 243–257. doi:10.1023/A:1014490922622.CrossRef

Durndell, A., & Haag, Z. (2002). Computer self efficacy, computer anxiety, attitudes towards the internet and reported experience with the internet, by gender, in an east European sample. Computers in Human Behavior, 18(5), 521–535. doi:10.1016/s0747-5632(02)00006-7.CrossRef

Durndell, A., Haag, Z., & Laithwaite, H. (2000). Computer self efficacy and gender: A cross cultural study of Scotland and Romania. Personality and Individual Differences, 28(6), 1037–1044. doi:10.1016/s0191-8869(99)00155-5.CrossRef

Elliot, A., & Devine, P. (1994). On the motivational nature of cognitive dissonance: Dissonance as psychological discomfort. Journal of Personality and Social Psychology, 67(3), 382–394. doi:10.1037/0022-3514.67.3.382.CrossRef

EU SME Centre (2015). The ICT market in China. Retrieved from http://www.eusmecentre.org.cn/report/ict-market-china.

EU-Japan Centre for Industrial Cooperation (2015). Digital economy in japan and the EU-An assessment of the common challenges and the collaboration potential-. Retrieved from http://cdnsite.eu-japan.eu/sites/default/files/publications/docs/digitaleconomy_final.pdf.

Fast, L., Lewis, J., Bryant, M., Bocian, K., Cardullo, R., Rettig, M., & Hammond, K. (2010). Does math self-efficacy mediate the effect of the perceived classroom environment on standardized math test performance? Journal of Educational Psychology, 102(3), 729–740. doi:10.1037/a0018863.CrossRef

Festinger, L. (1957). A theory of congnitive dissonance. Stanford: Stanford University Press.

Fraser, B. J. (2002). Learning environments research: Yesterday, today and tomorrow. Studies in educational learning environments (pp. 1-25). Singapore: World Scientific Publishing. doi:10.1142/9789812777133_0001.

Giannakos, M., Hubwieser, P., & Ruf, A. (2012). Is self-efficacy in programming decreasing with the level of programming skills?. Proceedings of the 7th Workshop in Primary and Secondary Computing Education (pp. 16-21). ACM: Hamburg.

Hasan, B. (2003). The influence of specific computer experiences on computer self-efficacy beliefs. Computers in Human Behavior, 19(4), 443–450. doi:10.1016/s0747-5632(02)00079-1.CrossRef

Hauser, R., Paul, R., & Bradley, J. (2012). Computer self-efficacy, anxiety, and learning in online versus face to face medium. Journal of Information Technology Education, 11(1), 141–154 Retrieved from http://www.jite.org/documents/Vol11/JITEv11p141-154Hauser0910.pdf.CrossRef

Hodges, C. (2013). Suggestions for the design of e-learning environments to enhance learner self-efficacy. Proceedings of the 2013 IADIS: International Conference on Cognition and Exploratory Learning in the Digital Age (pp. 10-16). Fort Worth: IADIS.

Hodges, C., & Murphy, P. (2009). Sources of self-efficacy beliefs of students in a technology-intensive asynchronous college algebra course. The Internet and Higher Education, 12(2), 93–97. doi:10.1016/j.iheduc.2009.06.005.CrossRef

Howland, J., Jonassen, D., & Marra, R. (2012). Meaningful learning with technology. Upper Saddle River: Pearson.

Hsu, W., & Huang, S. (2006). Determinants of computer self-efficacy-an examination of learning motivations and learning environments. Journal of Educational Computing Research, 35(3), 245–265. doi:10.2190/k441-p725-8174-55x2.CrossRef

Hu, L., & Bentler, P. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. doi:10.1080/10705519909540118.CrossRef

Huang, M. (2008). Factors influencing self-directed learning readiness amongst Taiwanese nursing students (doctoral dissertation). Retrieved from http://eprints.qut.edu.au/20709/.

Hung, M., Chou, C., Chen, H., & Own, Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090. doi:10.1016/j.compedu.2010.05.004.CrossRef

Johnson, R. (2005). An empirical investigation of sources of application-specific computer-self-efficacy and mediators of the efficacy-performance relationship. International Journal of Human-Computer Studies, 62(6), 737–758. doi:10.1016/j.ijhcs.2005.02.008.CrossRef

Jöreskog, K., & Sörbom, D. (1986). LISREL VI: Analysis of linear structural relationships by maximum likelihood and least squares methods. Mooresville: Scientific Software.

Jöreskog, K., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language. Chicago: Scientific Software International Inc..

Kerr, M., Rynearson, K., & Kerr, M. (2006). Student characteristics for online learning success. The Internet and Higher Education, 9(2), 91–105. doi:10.1016/j.iheduc.2006.03.002.CrossRef

Kinnunen, P., & Simon, B. (2011). CS majors' self-efficacy perceptions in CS1: Results in light of social cognitive theory. Proceedings of the Seventh International Workshop on Computing Education Research (pp. 19-26). Providence: ACM.

Kline, R. (2015). Principles and practice of structural equation modeling. New York: Guilford Publications.MATH

Koh, J., & Frick, T. (2009). Instructor and student classroom interactions during technology skills instruction for facilitating preservice teachers' computer self-efficacy. Journal of Educational Computing Research, 40(2), 211–228. doi:10.2190/ec.40.2.d.CrossRef

Koul, R., Roy, L., & Lerdpornkulrat, T. (2012). Motivational goal orientation, perceptions of biology and physics classroom learning environments, and gender. Learning Environments Research, 15(2), 217–229. doi:10.1007/s10984-012-9111-9.CrossRef

Kvasny, L., Joshi, K., & Trauth, E. (2011). The influence of self-efficacy, gender stereotypes and the importance of it skills on college students' intentions to pursue IT careers. Proceedings of the 2011 iConference (pp. 508–513). Seattle: ACM.

Lai, H., Chou, W., Miao, N., Wu, Y., Lee, P., & Jwo, J. (2015). A comparison of actual and preferred classroom environments as perceived by middle school students. Journal of School Health, 85(6), 388–397. doi:10.1111/josh.12263.CrossRef

Lei, P., & Wu, Q. (2007). Introduction to structural equation modeling: Issues and practical considerations. Educational Measurement: Issues and Practice, 26(3), 33–43. doi:10.1111/j.1745-3992.2007.00099.x.CrossRef

Lerdpornkulrat, T., Koul, R., & Poondej, C. (2016). Relationship between perceptions of classroom climate and institutional goal structures and student motivation, engagement and intention to persist in college. Journal of Further and Higher Education, 1–14. doi:10.1080/0309877x.2016.1206855.

Lin, C., Liang, J., Su, Y., & Tsai, C. (2013). Exploring the relationships between self-efficacy and preference for teacher authority among computer science majors. Journal of Educational Computing Research, 49(2), 189–207. doi:10.2190/ec.49.2.d.CrossRef

Linnenbrink, E., & Pintrich, P. (2003). The role of self-efficacy beliefs in student engagement and learning in the classroom. Reading & Writing Quarterly, 19(2), 119–137. doi:10.1080/10573560308223.CrossRef

Lopez Jr., A., Giguette, M., & Schulte, L. (2006). Large dataset offers view of math and computer self-efficacy among computer science undergraduates. Proceedings of the 44th Annual Southeast Regional Conference (pp. 158–163). Melbourne: ACM.

Lüdtke, O., Robitzsch, A., Trautwein, U., & Kunter, M. (2009). Assessing the impact of learning environments: How to use student ratings of classroom or school characteristics in multilevel modeling. Contemporary Educational Psychology, 34(2), 120–131. doi:10.1016/j.cedpsych.2008.12.001.CrossRef

Luszczynska, A., Scholz, U., & Schwarzer, R. (2005). The general self-efficacy scale: Multicultural validation studies. The Journal of Psychology, 139(5), 439–457. doi:10.3200/jrlp.139.5.439-457.CrossRef

Marsh, C. (2010). A sub-saharan comparative study of university students' attitudes towards computer programming. Proceedings of the Fifteenth Annual Conference on Innovation and Technology in Computer Science Education (pp. 33–37). Bilkent: ACM.

Meece, J., Anderman, E., & Anderman, L. (2006). Classroom goal structure, student motivation, and academic achievement. Annual Review of Psychology, 57, 487–503. doi:10.1146/annurev.psych.56.091103.070258.CrossRef

Montgomery, H., Sharafi, P., & Hedman, L. (2004). Engaging in activities involving information technology: Dimensions, modes, and flow. Human Factors: The Journal of the Human Factors and Ergonomics Society, 46(2), 334–348. doi:10.1518/hfes.46.2.334.37345.CrossRef

Moos, D., & Azevedo, R. (2009). Learning with computer-based learning environments: A literature review of computer self-efficacy. Review of Educational Research, 79(2), 576–600. doi:10.3102/0034654308326083.CrossRef

Morin, A., Marsh, H., Nagengast, B., & Scalas, L. (2014). Doubly latent multilevel analyses of classroom climate: An illustration. The Journal of Experimental Education, 82(2), 143–167. doi:10.1080/00220973.2013.769412.CrossRef

Mueller, R. (1999). Basic principles of structural equation modeling: An introduction to LISREL and EQS. New York: Springer Science & Business Media.MATH

National Science Foundation (2016). CS for all. Retrieved from https://www.nsf.gov/news/special_reports/csed/csforall.jsp.

Nichols, J. (2006). Empowerment and relationships: A classroom model to enhance student motivation. Learning Environments Research, 9(2), 149–161. doi:10.1007/s10984-006-9006-8.MathSciNetCrossRef

Niemiec, C., & Ryan, R. (2009). Autonomy, competence, and relatedness in the classroom: Applying self-determination theory to educational practice. Theory and Research in Education, 7(2), 133–144. doi:10.1177/1477878509104318.

Office of Higher Education Commission. (2017). Higher education statistics (in Thai). Higher Education Information: Resource document Retrieved from http://www.info.mua.go.th/information.

Opdenakker, M., & Minnaert, A. (2011). Relationship between learning environment characteristics and academic engagement. Psychological Reports, 109(1), 259–284. doi:10.2466/09.10.11.pr0.109.4.259-284.CrossRef

Pajares, F., & Urdan, T. (2006). Self-efficacy beliefs of adolescents. Greenwich: IAP.

Pajares, F., Britner, S., & Valiante, G. (2000). Relation between achievement goals and self-beliefs of middle school students in writing and science. Contemporary Educational Psychology, 25(4), 406–422. doi:10.1006/ceps.1999.1027.CrossRef

Pajares, F., Johnson, M., & Usher, E. (2007). Sources of writing self-efficacy beliefs of elementary, middle, and high school students. Research in the Teaching of English, 42(1), 104–120 Retrieved from http://www.jstor.org/stable/40171749.

Papastergiou, M. (2008). Are computer science and information technology still masculine fields? High school students’ perceptions and career choices. Computers & Education, 51(2), 594–608. doi:10.1016/j.compedu.2007.06.009.CrossRef

Ramalingam, V., LaBelle, D., & Wiedenbeck, S. (2004). Self-efficacy and mental models in learning to program. Proceedings of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (pp. 171-175). Leeds: ACM.

Robertson, M., & Al-Zahrani, A. (2012). Self-efficacy and ICT integration into initial teacher education in Saudi Arabia: Matching policy with practice. Australasian Journal of Educational Technology, 28(7), 1136–1151. doi:10.14742/ajet.793.CrossRef

Robinson, D. (2008). Relationship of student self-directedness, computer self-efficacy, and student satisfaction to persistence in online higher education programs (doctoral dissertation). Retrieved from http://search.proquest.com/docview/304562846?pq-origsite=gscholar.

Roca, J., & Gagné, M. (2008). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior, 24(4), 1585–1604. doi:10.1016/j.chb.2007.06.001.CrossRef

Rosson, M., Carroll, J., & Sinha, H. (2011). Orientation of undergraduates toward careers in the computer and information sciences. ACM Transactions on Computing Education, 11(3), 1–23. doi:10.1145/2037276.2037278.CrossRef

Ryan, R., & Deci, E. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. doi:10.1037/0003-066x.55.1.68.CrossRef

Ryan, A., & Patrick, H. (2001). The classroom social environment and changes in adolescents’ motivation and engagement during middle school. American Educational Research Journal, 38(2), 437–460. doi:10.3102/00028312038002437.CrossRef

Ryan, S., Bordoloi, B., & Harrison, D. (2000). Acquiring conceptual data modeling skills. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 31(4), 9–24. doi:10.1145/506760.506762.CrossRef

Saadé, R., & Kira, D. (2009). Computer anxiety in e-learning: The effect of computer self-efficacy. Journal of Information Technology Education, 8(1), 177–191 Retrieved from http://www.jite.org/documents/Vol8/JITEv8p177-191Saade724.pdf.CrossRef

Sam, H., Othman, A., & Nordin, Z. (2005). Computer self-efficacy, computer anxiety, and attitudes toward the internet: A study among undergraduates in Unimas. Journal of Educational Technology & Society, 8(4), 205–219 Retrieved from http://www.ifets.info/journals/8_4/19.pdf.

Scheja, M. (2006). Delayed understanding and staying in phase: Students’ perceptions of their study situation. Higher Education, 52(3), 421–445. doi:10.1007/s10734-004-7765-7.CrossRef

Schilling, J., & Klamma, R. (2010). The difficult bridge between university and industry: A case study in computer science teaching. Assessment & Evaluation in Higher Education, 35(4), 367–380. doi:10.1080/02602930902795893.CrossRef

Schunk, D., & Pajares, F. (2001). The development of academic self-efficacy. In A. Wigfield & J. Eccles (Eds.), Development of achievement motivation (pp. 1–27). San Diego: Academic Press.

Sheard, J., Carbone, A., & Hurst, A. (2010). Student engagement in first year of an ICT degree: Staff and student perceptions. Computer Science Education, 20(1), 1–16. doi:10.1080/08993400903484396.CrossRef

Simon, J. (2012). The ICT landscape in BRICS countries, Brazil, India, China. Communications and Strategies, 85(1), 191–202 Retrieved from http://ftp.jrc.es/EURdoc/JRC66110.pdf.

Statistical Office of the European Union (2017). ICT specialists in employment. Retrieved from http://ec.europa.eu/eurostat/statistics-explained/index.php/ICT_specialists_in_employment.

Steiger, J., & Lind, J. (1980). Statistically based tests for the number of common factors. Annual Spring Meeting of the Psychometric Society (pp. 424–453). Iowa: University of British Columbia.

Tzeng, J. (2009). The impact of general and specific performance and self-efficacy on learning with computer-based concept mapping. Computers in Human Behavior, 25(4), 989–996. doi:10.1016/j.chb.2009.04.009.MathSciNetCrossRef

Urdan, T., & Schoenfelder, E. (2006). Classroom effects on student motivation: Goal structures, social relationships, and competence beliefs. Journal of School Psychology, 44(5), 331–349. doi:10.1016/j.jsp.2006.04.003.CrossRef

Usher, E., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the literature and future directions. Review of Educational Research, 78(4), 751–796. doi:10.3102/0034654308321456.CrossRef

Usher, E., & Pajares, F. (2009). Sources of self-efficacy in mathematics: A validation study. Contemporary Educational Psychology, 34(1), 89–101. doi:10.1016/j.cedpsych.2008.09.002.CrossRef

Van Acker, F., van Buuren, H., Kreijns, K., & Vermeulen, M. (2013). Why teachers use digital learning materials: The role of self-efficacy, subjective norm and attitude. Education and Information Technologies, 18(3), 495–514. doi:10.1007/s10639-011-9181-9.CrossRef

Van Dinther, M., Dochy, F., & Segers, M. (2011). Factors affecting students’ self-efficacy in higher education. Educational Research Review, 6(2), 95–108. doi:10.1016/j.edurev.2010.10.003.CrossRef

Van Gorp, M., & Grissom, S. (2001). An empirical evaluation of using constructive classroom activities to teach introductory programming. Computer Science Education, 11(3), 247–260. doi:10.1076/csed.11.3.247.3837.CrossRef

Vandewaetere, M., & Clarebout, G. (2011). Can instruction as such affect learning? The case of learner control. Computers & Education, 57(4), 2322–2332. doi:10.1016/j.compedu.2011.05.020.CrossRef

Veilleux, N., Bates, R., Allendoerfer, C., Jones, D., Crawford, J., & Floyd Smith, T. (2013). The relationship between belonging and ability in computer science. Proceedings of the 44th ACM Technical Symposium on Computer Science Education (pp. 65-70). Denver: ACM.

Vivian, R., Falkner, K., & Falkner, N. (2013). Computer science students' causal attributions for successful and unsuccessful outcomes in programming assignments. Proceedings of the 13th Koli Calling International Conference on Computing Education Research (pp. 125-134). Koli: ACM.

Wang, C., & Neihart, M. (2015). Academic self-concept and academic self-efficacy: Self-beliefs enable academic achievement of twice-exceptional students. Roeper Review, 37(2), 63–73. doi:10.1080/02783193.2015.1008660.CrossRef

Wardley, L., & Mang, C. (2015). Student observations: Introducing iPads into university classrooms. Education and Information Technologies, 21(6), 1715–1732. doi:10.1007/s10639-015-9414-4.CrossRef

Weng, F., Cheong, F., & Cheong, C. (2009). The combined effect of self-efficacy and academic integration on higher education students studying IT majors in Taiwan. Education and Information Technologies, 15(4), 333–353. doi:10.1007/s10639-009-9115-y.CrossRef

Wilfong, J. (2006). Computer anxiety and anger: The impact of computer use, computer experience, and self-efficacy beliefs. Computers in Human Behavior, 22(6), 1001–1011. doi:10.1016/j.chb.2004.03.020.CrossRef

Wolf, S., & Fraser, B. (2007). Learning environment, attitudes and achievement among middle-school science students using inquiry-based laboratory activities. Research in Science Education, 38(3), 321–341. doi:10.1007/s11165-007-9052-y.CrossRef

Wong, A., Quek, C., Divaharan, S., Liu, W., Peer, J., & Williams, M. (2006). Singapore students’ and teachers’ perceptions of computer-supported project work classroom learning environments. Journal of Research on Technology in Education, 38(4), 449–479. doi:10.1080/15391523.2006.10782469.CrossRef

Zeldin, A., & Pajares, F. (2000). Against the odds: Self-efficacy beliefs of women in mathematical, scientific, and technological careers. American Educational Research Journal, 37(1), 215–246. doi:10.2307/1163477.CrossRef

Zhang, Q. (2014). Assessing the effects of instructor enthusiasm on classroom engagement, learning goal orientation, and academic self-efficacy. Communication Teacher, 28(1), 44–56. doi:10.1080/17404622.2013.839047.CrossRef

Zingaro, D. (2014). Peer instruction contributes to self-efficacy in CS1. Proceedings of the 45th ACM Technical Symposium on Computer Science Education (pp. 373-378). Atlanta: ACM.

Titel: The relationship between sources of self-efficacy in classroom environments and the strength of computer self-efficacy beliefs
verfasst von: Yuwarat Srisupawong
Ravinder Koul
Jariya Neanchaleay
Elizabeth Murphy
Emmanuel Jean Francois
Publikationsdatum: 20.07.2017
Verlag: Springer US
Erschienen in: Education and Information Technologies / Ausgabe 2/2018
Print ISSN: 1360-2357
Elektronische ISSN: 1573-7608
DOI: https://doi.org/10.1007/s10639-017-9630-1

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 2/2018

Ubiquitous learning environments in higher education: A scoping literature review

Language play in a second language: Social media as contexts for emerging Sociopragmatic competence

Broadening communication yet holding back: Teachers’ perceptions of their relationship with students in the SNS-era

Factors, issues and interdependencies in the incorporation of a Web 2.0 based learning environment in higher education

Using socrative as an online homework platform to increase students’ exam scores

Students’ participation in peer-to-peer communication supported by social media