Undergraduate time-use: a comparison of US, Chinese, and Russian students at highly selective universities

References

• Andrietti, V. (2014). Does lecture attendance affect academic performance? Panel data evidence for introductory macroeconomics. International Review of Economics Education, 15, 1–16.
   Google Scholar
• Arulampalam, W., Naylor, R. A., & Smith, J. (2012). Am I missing something? The effects of absence from class on student performance. Economics of Education Review, 31(4), 363–375.
   Web of Science ®Google Scholar
• Bennett, D. L., Edwards, E., & Ngai, C. (2019). Homeschool background, time use and academic performance at a private religious college. Educational Studies, 45(3), 305–325.
   Web of Science ®Google Scholar
• Bie, D. R., & Yi, M. C. (2014). The context of higher education development and policy response in China. Studies in Higher Education, 39(8), 1499–1510.
   Web of Science ®Google Scholar
• Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2009). Introduction to meta-analysis. Chichester: John Wiley & Sons.
   Google Scholar
• Bratti, M., & Staffolani, S. (2002). Student time allocation and educational production functions. HEW 0207001. In Economics working paper archive at WUSTL (pp. 1–27). Washington: Washington University.
   Google Scholar
• Chi, X., Liu, J., & Bai, Y. (2017). College environment, student involvement, and intellectual development: Evidence in China. Higher Education, 74(1), 81–99.
   Web of Science ®Google Scholar
• Chinn, S. (2000). A simple method for converting an odds ratio to effect size for use in meta-analysis. Statistics in Medicine, 19(22), 3127–3131.
   PubMed Web of Science ®Google Scholar
• Coccia, C., & Darling, C. A. (2016). Having the time of their life: College student stress, dating and satisfaction with life. Stress and Health, 32(1), 28–35.
   PubMed Web of Science ®Google Scholar
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum.
   Google Scholar
• De Vita, G. (2001). Learning styles, culture and inclusive instruction in the multicultural classroom: A business and management perspective. Innovations in Education and Teaching International, 38(2), 165–174.
   Web of Science ®Google Scholar
• DesJardins, S. L., McCall, B. P., Ott, M., & Kim, J. (2010). A quasi-experimental investigation of how the Gates Millennium Scholars program is related to college students’ time use and activities. Educational Evaluation and Policy Analysis, 32(4), 456–475.
   Web of Science ®Google Scholar
• Devlin, M., & Gray, K. (2007). In their own words: A qualitative study of the reasons Australian university students plagiarize. Higher Education Research & Development, 26(2), 181–198.
   Google Scholar
• Dobkin, C., Gil, R., & Marion, J. (2010). Skipping class in college and exam performance: Evidence from a regression discontinuity classroom experiment. Economics of Education Review, 29(4), 566–575.
   Web of Science ®Google Scholar
• Dollinger, S. J., Matyja, A. M., & Huber, J. L. (2008). Which factors best account for academic success: Those which college students can control or those they cannot? Journal of Research in Personality, 42(4), 872–885.
   Web of Science ®Google Scholar
• Dolton, P., Marcenaro, O. D., & Navarro, L. (2003). The effective use of student time: A stochastic frontier production function case study. Economics of Education Review, 22, 547–560.
   Web of Science ®Google Scholar
• Fosnacht, K., McCormick, A. C., & Lerma, R. (2018). First-year students’ time use in college: A latent profile analysis. Research in Higher Education, 59(7), 958–978.
   Web of Science ®Google Scholar
• Froumin, I., & Platonova, D. (2017). Higher education expansion in Brazil, Russia, India, and China. In Encyclopedia of international higher education systems and institutions (pp. 1–7). Dordrecht: Springer.
   Google Scholar
• Grave, B. S. (2011). The effect of student time allocation on academic achievement. Education Economics, 19(3), 291–310.
   Google Scholar
• Hensley, L. C., Wolters, C. A., Won, S., & Brady, A. C. (2018). Academic probation, time management, and time use in a college success course. Journal of College Reading and Learning, 48(2), 105–123.
   Google Scholar
• Hu, S., & McCormick, A. C. (2012). An engagement-based student typology and its relationship to college outcomes. Research in Higher Education, 53(7), 738–754.
   Web of Science ®Google Scholar
• Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31(8), 651–666.
   Web of Science ®Google Scholar
• Jaju, A., Kwak, H., & Zinkhan, G. M. (2002). Learning styles of undergraduate business students: A cross-cultural comparison between the US, India, and Korea. Marketing Education Review, 12(2), 49–60.
   Google Scholar
• Joy, S., & Kolb, D. A. (2009). Are there cultural differences in learning style? International Journal of Intercultural Relations, 33(1), 69–85.
   Web of Science ®Google Scholar
• Katz, N. (1988). Individual learning style. Journal of Cross-Cultural Psychology, 19(3), 361–379.
   Web of Science ®Google Scholar
• Kember, D., Jamieson, Q. W., Pomfret, M., & Wong, E. T. (1995). Learning approaches, study time and academic performance. Higher Education, 29(3), 329–343.
   Web of Science ®Google Scholar
• Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Kolb, A. Y., & Kolb, D. A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning & Education, 4(2), 193–212.
   Web of Science ®Google Scholar
• Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development. New Jersey: FT press.
   Google Scholar
• Landin, M., & Pérez, J. (2015). Class attendance and academic achievement of pharmacy students in a European university. Currents in Pharmacy Teaching and Learning, 7(1), 78–83.
   Web of Science ®Google Scholar
• Lukkarinen, A., Koivukangas, P., & Seppälä, T. (2016). Relationship between class attendance and student performance. Procedia - Social and Behavioral Sciences, 228, 341–347.
   Google Scholar
• Marshall, S. J. (2018). Student time choices and success. Higher Education Research & Development, 37(6), 1216–1230.
   Web of Science ®Google Scholar
• Mearman, A., Pacheco, G., Webber, D., Ivlevs, A., & Rahman, T. (2014). Understanding student attendance in business schools: An exploratory study. International Review of Economics Education, 17, 120–136.
   Google Scholar
• Mehta, N., Stinebrickner, R., & Stinebrickner, T. (2017). Detecting academic peer effects: Exploring the role of time-use. Paper presented on AREA Conferences, Munich, 1–2 September.
   Google Scholar
• Meng, C., & Heijke, H. (2005). Student time allocation, the learning environment and the acquisition of competencies, ROA Research Memorandum 2005/1E. University of Maastricht.
   Google Scholar
• Neves, J., & Hillman, N. (2017). Student academic experience survey. York: Higher Education Academy.
   Google Scholar
• Nonis, S. A., & Hudson, G. I. (2010). Performance of college students: Impact of study time and study habits. Journal of Education for Business, 85(4), 229–238.
   Google Scholar
• Pace, C. R. (1980). Measuring the quality of student effort. Current Issues in Higher Education, 2, 10–16.
   Google Scholar
• Plant, E. A., Ericsson, K. A., Hill, L., & Asberg, K. (2005). Why study time does not predict grade point average across college students: Implications of deliberate practice for academic performance. Contemporary Educational Psychology, 30(1), 96–116.
   Web of Science ®Google Scholar
• Pratt, D. D. (1991). Conceptions of self within China and the United States: Contrasting foundations for adult education. International Journal of Intercultural Relations, 15(3), 285–310.
   Web of Science ®Google Scholar
• Quadlin, N. Y. (2016). Gender and time use in college: Converging or diverging pathways? Gender & Society, 30(2), 361–385.
   Web of Science ®Google Scholar
• Quadlin, N. Y., & Rudel, D. (2015). Responsibility or liability? Student loan debt and time use in college. Social Forces, 94, 589–614.
   Web of Science ®Google Scholar
• Sawilowsky, S. S. (2009). New effect size rules of thumb. Journal of Modern Applied Statistical Methods, 8(2), 26.
   Google Scholar
• Scheja, M. (2006). Delayed understanding and staying in phase: Students’ perceptions of their study situation. Higher Education, 52(3), 421–445.
   Web of Science ®Google Scholar
• Schmidt, R. M. (1983). Who maximizes what? A study in student time allocation. The American Economic Review, 73(2), 23–28.
   Web of Science ®Google Scholar
• Thibodeaux, J., Deutsch, A., Kitsantas, A., & Winsler, A. (2017). First-year college students' time use: Relations with self-regulation and GPA. Journal of Advanced Academics, 28(1), 5–27.
   Web of Science ®Google Scholar
• Trow, M. (1972). The expansion and transformation of higher education. International Review of Education, 18(1), 61–84.
   Web of Science ®Google Scholar
• Yamazaki, Y. (2005). Learning styles and typologies of cultural differences: A theoretical and empirical comparison. International Journal of Intercultural Relations, 29(5), 521–548.
   Web of Science ®Google Scholar
• Yamazaki, Y., & Kayes, D. C. (2005). Expatriate learning: Exploring how Japanese managers adapt in the United States. Paper presented at the Annual Meeting of the Academy of Management, Honolulu, HI.
   Google Scholar