Validity Evidence for a Chinese Version of the Online Self-Regulated Learning Questionnaire With Average Students and Mathematically Talented Students

References

• Ally, M. (2004). Foundations of educational theory for online learning. In T. A. Anderson & F. Elloumi (Eds.), Theory and practice of online learning (pp. 3–31). Edmonton, AB, Canada: Athabasca University.
   Google Scholar
• Artino, A. R. (2008). Promoting academic motivation and self-regulation: Practical guidelines for online instructors. TechTrends, 52, 37–45. https://doi.org/10.1007/s11528-008-0153-x
   Google Scholar
• Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Freeman.
   Google Scholar
• Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S. L. (2009). Measuring self-regulation in online and blended learning environments. The Internet and Higher Education, 12, 1–6. https://doi.org/10.1016/j.iheduc.2008.10.005
   Google Scholar
• Barnard, L., Paton, V. O., & Lan, W. Y. (2008). Online self-regulatory learning behaviors as a mediator in the relationship between online course perceptions with achievement. International Review of Research in Open and Distance Learning, 9(2), 1–11.
   Google Scholar
• Barnard-Brak, L., Lan, W. Y., & Paton, V. O. (2010). Profiles in self-regulated learning in the online learning environment. International Review of Research in Open and Distance Learning, 11(1), 61–80. https://doi.org/10.19173/irrodl.v11i1.769
   Google Scholar
• Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York, NY: Guilford.
   Google Scholar
• Cavanaugh, C. (2007). Effectiveness of K–12 online learning. In M. Moore (Ed.), Handbook of distance education (2nd ed., pp. 157–168). Mahwah: NJ: Erlbaum.
   Google Scholar
• Chang, M. (2005). Applying SRL strategies in a web-based instruction: An investigation of motivation perception. Computer Assisted Language Learning, 18, 217–230. https://doi.org/10.1080/09588220500178939
   Google Scholar
• Chang, M. M., & Wu, Y. M. (2003). EFL learners' self-efficacy and strategies use in a web-based learning environment. In Proceedings of the 2003 International Conference on English Teaching and Learning in the Republic of China, Taiwan, ROC (pp. 117–125). Taiwan: Province University.
   Google Scholar
• DeVon, H. A., Block, M. E., Moyle-Wright, P., Ernst, D. M., Hayden, S. J., Lazzara, D. J., … Kostas-Polston, E. (2007). A psychometric toolbox for testing validity and reliability. Journal of Nursing Scholarship, 39, 155–164. https://doi.org/10.1111/j.1547-5069.2007.00161.x
   Google Scholar
• DiPietro, M., Ferdig, R. E., Black, E. W., & Preston, M. (2008). Best practices in teaching K–12 online: Lessons learned from Michigan Virtual School teachers. Journal of Interactive Online Learning, 7, 10–35.
   Google Scholar
• Dresel, M., & Haugwitz, M. (2005). The relationship between cognitive abilities and self-regulated learning: Evidence for interactions with academic self-concept and gender. High Ability Studies, 16, 201–218. https://doi.org/10.1080/13598130600618066
   Google Scholar
• Dykman, C. A., & Davis, C. K. (2008). Online education forum part two: Teaching online versus teaching conventionally. Journal of Information Systems Education, 19, 156–163.
   Google Scholar
• Ho, S. C. (2004). Self-regulated learning and academic achievement of Hong Kong secondary school students. Education Journal, 32, 87–108.
   Google Scholar
• Howland, J. L., & Moore, J. L. (2002). Student perceptions as distance learners in Internet-based courses. Distance Education, 23, 183–195. https://doi.org/10.1080/0158791022000009196
   Google Scholar
• Hu, L., & Bentler, P. M. (1999). Cut-off 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
   Google Scholar
• Johnson, J. E., & Christie, J. F. (2009). Play and digital media. Computers in the Schools, 26, 284–289. https://doi.org/10.1080/07380560903360202
   Google Scholar
• Leu, D. J., Jr., Kinzer, C. K., Coiro, J., & Cammack, D. W. (2004). Toward a theory of new literacies emerging from the Internet and other information and communication technologies. In R. B. Ruddell & N. Unrau (Eds.), Theoretical models and processes of reading (5th ed., pp. 1570–1613). Newark, DE: International Reading Association.
   Google Scholar
• Li, C. S., & Irby, B. (2008). An overview of online education: Attractiveness, benefits, challenges, concerns and recommendations. College Student Journal, 42, 449–458.
   Google Scholar
• Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational measurement (3rd ed., pp. 13–103). New York, NY: Macmillan.
   Google Scholar
• Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
   Google Scholar
• Pintrich, P. R., Smith, D., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire. Ann Arbor, MI: National Center for Research to Improve Postsecondary Teaching and Learning, University of Michigan.
   Google Scholar
• 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. https://doi.org/10.1177/0013164493053003024
   Google Scholar
• Rogelberg, S. G. (2002). Handbook of research methods in industrial and organizational psychology. Boston, MA: Wiley-Blackwell.
   Google Scholar
• Schunk, D., & Zimmerman, B. (2007). Influencing children's self-efficacy and self-regulation of reading and writing through modeling. Reading & Writing Quarterly, 23(1), 7–25. https://doi.org/10.1080/10573560600837578
   Google Scholar
• Tang, M., & Neber, H. (2008). Motivation and self-regulated science learning in high-achieving students: Differences related to nation, gender, and grade-level. High Ability Studies, 19, 103–116. https://doi.org/10.1080/13598130802503959
   Google Scholar
• Wang, M. T., & Holcombe, R. (2010). Adolescents' perceptions of school environment, engagement, and academic achievement in middle school. American Educational Research Journal, 47, 633–662. https://doi.org/10.3102/0002831209361209
   Google Scholar
• Winne, P. H. (1995). Inherent details in self-regulated learning. Educational Psychologist, 30, 173–187. https://doi.org/10.1207/s15326985ep3004_2
   Google Scholar
• Winne, P. H., & Jamieson-Noel, D. (2002). Exploring students' calibration of self-reports about study tactics and achievement. Contemporary Educational Psychology, 27, 551–572. https://doi.org/10.1016/S0361-476X(02)00006-1
   Google Scholar
• Yukselturk, E., & Bulut, S. (2009). Gender differences in self-regulated online learning environment. Educational Technology & Society, 12(3), 12–22.
   Google Scholar
• Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82–91. https://doi.org/10.1006/ceps.1999.1016
   Google Scholar
• Zimmerman, B. J., Greenberg, D., & Weinstein, C. E. (1994). Self-regulating academic study time: A strategy approach. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulation of learning and performance (pp. 181–202). Hillsdale, NJ: Erlbaum.
   Google Scholar
• Zimmerman, B. J., & Marinez-Pons, M. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American Educational Research Journal, 23, 614–628. https://doi.org/10.3102/00028312023004614
   Google Scholar
• 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. https://doi.org/10.1037/0022-0663.82.1.51
   Google Scholar