1 |
Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological methods, 1(1), 16.
DOI
|
2 |
Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training. Journal of Computer Assisted Learning, 24(3), 260-270.
DOI
|
3 |
Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of social and clinical psychology, 4(3), 359-373.
DOI
|
4 |
Bong, M., Kim, S., Reeve, J., Lim, H., Li, W., Jiang, Y., & Pack, S. (2012). SMILES (Student Motivation in the Learning Environment Scales): Measurement of Student Motivation in Learning Environment. korea.ac.kr/korean/research/assessment_scales/list.html
|
5 |
Caprara, G. V., Fida, R., Vecchione, M., Del Bove, G., Vecchio, G. M., Barbaranelli, C., & Bandura, A. (2008). Longitudinal analysis of the role of perceived self-efficacy for self-regulated learning in academic continuance and achievement. Journal of educational psychology, 100(3), 525-534.
DOI
|
6 |
Cho, J., & Do, H. (2020). Relationships among Teaching Presence, Learning Engagement, and Learners' Satisfaction in K-MOOC. The Journal of Learner-Centered Curriculum and Instruction, 20(15), 551-572.
|
7 |
Choi, S. (2016). A Study on Teaching-learning for Enhancing Computational Thinking Skill in terms of Problem Solving. The Journal of Korean Association of Computer Education, 19(1), 53-62.
DOI
|
8 |
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of educational research, 74(1), 59-109.
DOI
|
9 |
Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of distance education, 15(1), 7-23.
DOI
|
10 |
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman. New York: NY.
|
11 |
Garrison, D. R. (2003). Cognitive presence for effective asynchronous online learning: The role of reflective inquiry, self-direction and metacognition. Elements of quality online education: P ractice and direction, 4(1), 47-58.
|
12 |
Handelsman, M. M., Briggs, W. L., Sullivan, N., & Towler, A. (2005). A measure of college student course engagement. The Journal of Educational Research, 98(3), 184-192.
DOI
|
13 |
Han, J., & Lee, S. (2019). Investigating Online Learning Types Based on self-regulated learning in Online Software Education: Applying Hierarchical Cluster Analysis. The Journal of Korean Association of Computer Education, 22(5), 51-65.
|
14 |
Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling.
|
15 |
Junco, R. (2012). In-class multitasking and academic performance. Computers in Human Behavior, 28(6), 2236-2243.
DOI
|
16 |
Heeter, C. (1992). Being there: The subjective experience of presence. Presence: Teleoperators & Virtual Environments, 1(2), 262-271.
DOI
|
17 |
Joo, Y., Ha, Y., Yoo, J., & Kim, E. (2010). The Structural Relationship among Teaching Presence, Cognitive Presence, Social Presence, and Learning Outcome in Cyber University. Journal of The Korean Association of Information Education, 14(2), 175-187.
|
18 |
Joo, Y., Kim, N., & Cho, H. (2008). Relationship between Self-Efficacy, Online Task Value and Self-Regulated Learning, and Satisfaction and Achievement in Cyber Education. Journal of Korean Association for Educational Information and Media, 14(3), 115-135.
|
19 |
Jeong, S., Kim, B., Koo, I., & Park, J. (2010). Effects on Scientific Inquiry, Scientific Attitudes, and Scientific Achievements of Experimental Classes for Kinetics Unit using Self-Regulated Learning Strategy. Journal of the Korean Association for Science Education, 30(6), 681-692.
DOI
|
20 |
Burford, V. N., & Gross, D. D. (2000). Caring on-line: On-line empathy, self-disclosure, emotional expression and nurturing. Paper presented at the Annual Meeting of the National Communication Association. Seattle, WA.
|
21 |
Cheong, Y. (2015). A Study on types of self-regulated learning and change in the type over time. Doctoral dissertation, Graduate School of Kyung Hee University.
|
22 |
Zimmerman, B. J. (2000). 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 Press.
|
23 |
Sun, J. C. Y., & Rueda, R. (2012). Situational interest, computer self-efficacy and self-regulation: Their impact on student engagement in distance education. British Journal of Educational Technology, 43(2), 191-204.
DOI
|
24 |
Swan, K., Shea, P., Richardson, J., Ice, P., Garrison, D. R., Cleveland-Innes, M., & Arbaugh, J. B. (2008). Validating a measurement tool of presence in online communities of inquiry. E-mentor, 2(24), 1-12.
|
25 |
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
DOI
|
26 |
Kim, S., Moon, E., & Park, I. (2015). Investigation on the Relationships among Students' Elearning Readiness, Teaching Presence and Learning Effects in an Online Learning Environment. Journal of Korean Association for Educational Information and Media, 21(4), 687-710.
DOI
|
27 |
Kim, J., & Kang, M. (2010). Structural Relationship among Teaching Presence, Learning Presence, and Effectiveness of e-Learning in the corporate setting. Asian Journal of Education, 11(2), 29-56.
DOI
|
28 |
Kim, M., & Kim, H. (2018). Effectiveness analysis based on computational thinking of a computing course for non-computer majors. The Journal of Korean Association of Computer Education, 21(1), 11-21.
DOI
|
29 |
Kim, S., & Lim, K. (2017). The Moderating Effects of Perceived Usefulness and Self-Regulated Learning Skills on the Relationship between Participative Motivation and Learning Satisfaction in Online Continuing Education Programs. Journal of Lifelong Learning Society, 13(3), 85-107.
DOI
|
30 |
Kang, M., & Lim, K. (2013). Structural Analyses on the Effects of Self-regulated Learning and Learning Motivation on Learner-instructor Interactions and Academic Performance in College Learning Environments with e-Learning Contents. Journal of The Korea Contents Society, 13(11), 1014-1023.
DOI
|
31 |
Lee, J., Yoo, J., & Lee, M. (2018). Predictability of Elementary Students' Self-Regulated Learning, GRIT and Parents Support on Computational Thinking and Learning Satisfaction in Online Software Education. Journal of The Korean Association of Information Education, 22(6), 689-699.
DOI
|
32 |
Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational psychology review, 16(4), 385-407.
DOI
|
33 |
Lee, S., & Ann, S. (2020). Analysis of student perception of learning block-type educational programming tools in online learning environment. Journal of The Korean Association of Information Educaton, 24(6), 519-528.
DOI
|
34 |
Korkmaz, O., Cakir, R., & Ozden, M. Y. (2015). Computational thinking levels scale (ctls) adaptation for secondary school level. Gazi. Journal of Education Sciences, 1(2), 143-162.
|
35 |
Lee, J., & Yoon, S. (2011). The Effects of Task Value, Perceived Usefulness, and Teaching Presence on Learning Outcomes in Cyber University. Journal of The Korean Association of Information Education, 15(3), 449-458.
|
36 |
Kim, S. (2019). Teaching presence strengthening strategy based on correlation analysis between perception of teaching presence and learning satisfaction in online Spanish education. Latin American and Caribbean Studies, 38(3), 69-98.
DOI
|
37 |
Lim, Y., & Lee, O. (2008). A Study on Relations Among the Learning Participation, Learning Satisfaction and Academic Achievement of Cyber Learners. The Journal of Yeolin Education, 16(2), 177-200.
|
38 |
Ministry of Education, Korea (2015). Software Education Instructional Guidance.
|
39 |
Mosholder, R. S. (2007). Evaluating engagement with, and determining the direct effects of, a curriculum teaching students learning and motivation strategies. Doctoral dissertation, The Ohio State University.
|
40 |
Oh, M., & Kim, M. (2018). Analysis of Effects of Scratch Programing Education to Improve Computational Thinking. Journal of Korean Association for Educational Information and Media, 24(2), 255-275.
DOI
|
41 |
Robinson, P. E., & Caroll, J. (2017). An online learning platform for teaching, learning, and assessment of programming. 2017 IEEE Global Engineering Education Conference (EDUCON), 547-556.
|
42 |
Marks, H. M. (2000). Student engagement in instructional activity: Patterns in the elementary, middle, and high school years. American educational research journal, 37(1), 153-184.
DOI
|
43 |
Skinner, E. A., & Belmont, M. J. (1993). Motivation in the classroom: Reciprocal effects of teacher behavior and student engagement across the school year. Journal of educational psychology, 85(4), 571-581.
DOI
|
44 |
Spanjers, D. M. (2007). Cognitive engagement as a predictor of achievement. University of Minnesota.
|
45 |
Surya, E., Syahputra, E., & Jumiati, N. (2018). Effect of Problem Based Learning Toward Mathematical Communication Ability and Self-Regulated Learning. Journal of Education and P ractice, 9(6), 14-23.
|
46 |
Newmann, F. M. (Ed.). (1992). Student engagement and achievement in American secondary schools. New York: Teacher College Press Columbia University.
|