• Arthur, W., Woehr, D. J., & Maldegen, R. (2000). Convergent and discriminant validity of assessment center dimensions: A conceptual and empirical reexamination of the assessment center construct-related validity paradox. Journal of Management, 26(4), 813-835. https://doi.org/10.1177/014920630002600410.
• Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327.
• Basturkmen, H., East, M., & Bitchener, J. (2014). Supervisors’ on-script feedback comments on drafts of dissertations: socialising students into the academic discourse community. Teaching in Higher Education, 19(4), 432-445. https://doi.org/10.1080/13562517.2012.752728.
• Berson, Y., Halevy, N., Shamir, B., & Erez, M. (2015). Leading from different psychological distances : A construal-level perspective on vision communication, goal setting, and follower motivation. The Leadership Quarterly, 26(2), 143-155. https://doi.org/10.1016/j.leaqua.2014.07.011.
• Bishop, K., & International, S. A. (2002). New Roles, Skills and Capabilities for the Knowledge-focused Organisation: Standards Australia International.
• Bodenheimer, T., & Handley, M. A. (2009). Goal-setting for behavior change in primary care : An exploration and status report. Patient Education and Counseling, 76(2), 174-180. https://doi.org/10.1016/j.pec.2009.06.001.
• Byrne, B. M. (2009). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Second Edition: Taylor & Francis.
• Cassuto, L. (2010). Advising the Struggling Dissertation Student. Chronicle of Higher Education, 57(11), A51-A53.
• Catania, G. (2014). The unintended consequences of motivational techniques : Goal setting and unethical behavior in the Maltese financial services Industry. Procedia-Social and Behavioral Sciences, 109, 1375-1385. https://doi.org/10.1016/j.sbspro.2013.12.640.
• Chatti, M. A. (2012). Knowledge management: a personal knowledge network perspective. Journal of Knowledge Management, 16(5), 829–844. https://doi.org/10.1108/13673271211262835.
• Chen, K.-C., & Jang, S.-J. (2010). Motivation in online learning : Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741-752. https://doi.org/10.1016/j.chb.2010.01.011.
• Chin, W. W. (1998). The partial least squares approach for structural equation modeling Modern methods for business research (pp. 295-336). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.
• Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, UK: Lawrence Erlbaum Associates.
• Debowski, S. (2007). Knowledge Management: Wiley India Pvt. Limited.
• Fang, E., Evans, K. R., & Zou, S. (2005). The moderating effect of goal-setting characteristics on the sales control systems–job performance relationship. Journal of Business Research, 58(9), 1214-1222. https://doi.org/10.1016/j.jbusres.2004.03.006.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research (JMR), 18(1), 39-50. https://doi.org/10.1177/002224378101800104.
• Fried, Y., & Slowik, L. H. (2004). Enriching goal-setting theory with time: An integrated approach. Academy of Management Review, 29(3), 404–422. https://doi.org/10.5465/amr.2004.13670973.
• George, J. M., & Jones, G. R. (2000). The role of time in theory and theory building. Journal of Management, 26(4), 657-684. https://doi.org/10.1177/014920630002600404.
• Grolnick, W. S. (2015). Mothers’ motivation for involvement in their children’s schooling : mechanisms and outcomes. Motivation and Emotion, 39(1), 63-73. https://doi.org/10.1007/s11031-014-9423-4.
• Hagström, E., & Lindberg, O. (2013). Three theses on teaching and learning in higher education. Teaching in Higher Education, 18(2), 119-128. https://doi.org/10.1080/13562517.2012.694097.
• Hair, J. F. (2013). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM): SAGE Publications.
• Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM).
• Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory & Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202.
• Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565-580. https://doi.org/10.1007/s00180-012-0317-1.
• Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., . . . Calantone, R. J. (2014). Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182-209. https://doi.org/10.1177/1094428114526928.
• Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8.
• Hildreth, P. M., & Kimble, C. (2004). Knowledge Networks: Innovation Through Communities of Practice: Idea Group Pub. https://doi.org/10.4018/978-1-59140-200-8.
• Huang, T.-C., Jeng, Y.-L., Hsiao, K.-L., & Tsai, B.-R. (2016). SNS collaborative learning design: enhancing critical thinking for human–computer interface design. Universal Access in the Information Society, 1-10. https://doi.org/10.1007/s10209-016-0458-z.
• Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20(2), 195-204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7.
• Hunt, C. (2001). Climbing Out of the Void: Moving from chaos to concepts in the presentation of a thesis. Teaching in Higher Education, 6(3), 351-367. https://doi.org/10.1080/13562510120061214.
• Kimble, C., Hildreth, P. M., & Bourdon, I. (2008). Communities of Practice: Creating Learning Environments for Educators: Information Age Pub.
• Landers, R. N., Bauer, K. N., & Callan, R. C. (2017). Gamification of task performance with leaderboards: A goal setting experiment. Computers in Human Behavior, 71, 508-515. https://doi.org/10.1016/j.chb.2015.08.008.
• Latham, G. P., & Locke, E. A. (1991). Self-regulation through goal setting. Organizational Behavior and Human Decision Processes, 50(2), 212-247. https://doi.org/10.1016/0749-5978(91)90021-k.
• Lin, S., Hung, T.-C., & Lee, C.-T. (2015). Revalidate forms of presence in training effectiveness: Mediating effect of self-efficacy. Journal of Educational Computing Research, 53(1), 32-54. https://doi.org/10.1177/0735633115588772.
• Lindsay, S. (2015). What works for doctoral students in completing their thesis? Teaching in Higher Education, 20(2), 183-196. https://doi.org/10.1080/13562517.2014.974025.
• Locke, E. A. (1968). Toward a theory of task motivation and incentives. Organizational Behavior and Human Performance, 3(2), 157-189. https://doi.org/10.1016/0030-5073(68)90004-4.
• Locke, E. A., & Latham, G. P. (1990). A Theory of Goal Setting & Task Performance: Prentice-Hall, Inc.
• Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation : A 35-year odyssey. American Psychologist, 57(9), 705-717. https://doi.org/10.1037/0003-066X.57.9.705.
• Locke, E. A., & Latham, G. P. (2006). New directions in Goal-Setting Theory. Current Directions in Psychological Science, 15(5), 265-268. https://doi.org/10.1111/j.1467-8721.2006.00449.x.
• Locke, E. A., & Latham, G. P. (2015). Chapter Four - Breaking the Rules: A Historical Overview of Goal-Setting Theory. In J. E. Andrew (Ed.), Advances in Motivation Science (Vol. Volume 2, pp. 99-126): Elsevier. https://doi.org/10.1016/bs.adms.2015.05.001.
• Locke, E. A., Cartledge, N., & Knerr, C. S. (1970). Studies of the relationship between satisfaction, goal-setting, and performance. Organizational Behavior and Human Performance, 5(2), 135-158. https://doi.org/10.1016/0030-5073(70)90011-5.
• O’Leary-Kelly, S. W., & Vokurka, R., J. (1998). The empirical assessment of construct validity. Journal of Operations Management, 16(4), 387-405. https://doi.org/10.1016/s0272-6963(98)00020-5.
• Roberts, C. M. (2004). The Dissertation Journey: A Practical and Comprehensive Guide to Planning, Writing, and Defending Your Dissertation: SAGE Publications.
• Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67. https://doi.org/10.1006/ceps.1999.1020.
• Shea, P., & Bidjerano, T. (2008). Measures of quality in online education: an investigation of the community of inquiry model and the net generation. Journal of Educational Computing Research, 39(4), 339-361. https://doi.org/10.2190/EC.39.4.b.
• Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in Structural Equation Models. Sociological Methodology, 13, 290-312. https://doi.org/10.2307/270723.
• Sonnentag, S. (2012). Time in organizational research: Catching up on a long neglected topic in order to improve theory. Organizational Psychology Review, 2(4), 361-368. https://doi.org/10.1177/2041386612442079.
• Stößlein, M., & Kanet, J. J. (2016). Undergraduate research experiences: Identifying lessons learned and challenges for business schools. The International Journal of Management Education, 14(3), 349-367. https://doi.org/10.1016/j.ijme.2016.07.004.
• Thomas, R. M., & Brubaker, D. L. (2000). Theses and Dissertations: A Guide to Planning, Research, and Writing: Bergin & Garvey.
• Vinzi, V. E. (2010). Handbook of Partial Least Squares: Concepts, Methods and Applications: Springer Berlin Heidelberg.
• Wenger, E., McDermott, R. A., & Snyder, W. (2002). Cultivating Communities of Practice: A Guide to Managing Knowledge: Harvard Business Press.
• Zhao, L., Lu, Y., Wang, B., & Huang, W. (2011). What makes them happy and curious online? An empirical study on high school students’ Internet use from a self-determination theory perspective. Computers & Education, 56(2), 346-356. https://doi.org/10.1016/j.compedu.2010.08.006.

APA

Lin, S., & Chiu, C.-K. (2020). Heuristic Projects in Open Learning Environments: Time Phase in Individual and Collective Determinants. Eurasia Journal of Mathematics, Science and Technology Education, 16(1), em1797. https://doi.org/10.29333/ejmste/112247

Vancouver

Lin S, Chiu CK. Heuristic Projects in Open Learning Environments: Time Phase in Individual and Collective Determinants. EURASIA J Math Sci Tech Ed. 2020;16(1):em1797. https://doi.org/10.29333/ejmste/112247

AMA

Lin S, Chiu CK. Heuristic Projects in Open Learning Environments: Time Phase in Individual and Collective Determinants. EURASIA J Math Sci Tech Ed. 2020;16(1), em1797. https://doi.org/10.29333/ejmste/112247

Chicago

Lin, Shinyi, and Chou-Kang Chiu. "Heuristic Projects in Open Learning Environments: Time Phase in Individual and Collective Determinants". Eurasia Journal of Mathematics, Science and Technology Education 2020 16 no. 1 (2020): em1797. https://doi.org/10.29333/ejmste/112247

Harvard

Lin, S., and Chiu, C.-K. (2020). Heuristic Projects in Open Learning Environments: Time Phase in Individual and Collective Determinants. Eurasia Journal of Mathematics, Science and Technology Education, 16(1), em1797. https://doi.org/10.29333/ejmste/112247

MLA

Lin, Shinyi et al. "Heuristic Projects in Open Learning Environments: Time Phase in Individual and Collective Determinants". Eurasia Journal of Mathematics, Science and Technology Education, vol. 16, no. 1, 2020, em1797. https://doi.org/10.29333/ejmste/112247