Mei Hua Piao; Jeong Eun Kim

doi:10.16952/pns.2016.13.1.29

Journal List > Perspect Nurs Sci > v.13(1) > 1060418

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Piao and Kim: The Effect of Problem Based Learning on Nursing Students’ Interaction and Self-directed Learning: A Social Network Analysis

Original Article

Perspectives in Nursing Science 2016;13(1):29-35.

Published online: 19 April 2016

DOI: https://doi.org/10.16952/pns.2016.13.1.29

The Effect of Problem Based Learning on Nursing Students’ Interaction and Self-directed Learning: A Social Network Analysis

Mei Hua Piao¹, Jeong Eun Kim^2,

¹Assistant Professor, Department of Nursing, Cheju Halla University, Jeju

²Professor, College of Nursing, Seoul National University, Seoul, Korea

Corresponding author: Kim, Jeong Eun College of Nursing, Seoul National University, 103 Daehak-ro, Jongro-gu, Seoul 03080, Korea. Tel: +82-2-740-8483, Fax: +82-2-766-1852, E-mail: kim0424@snu.ac.kr

Received 26 February 2016 Revised 3 March 2016 Accepted 3 March 2016

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose:

This study aimed to explore the underlying structures of students’ interaction networks to monitor network changes during the year, to verify the relationship with self-directed learning, and to identify the effect of problem-based learning on interaction and self-directed learning. Methods: A longitudinal study was designed which included 3 parts (A=25, B=27, C=26) with a total of 78 second-year nursing students from 2013 to 2014. Interaction indicators used group network centralization and density, and individual in-degree centrality. Results: Group network centralization showed mean reversion patterns, however, centralization and density showed a slight increase from 2013 to 2014 (Centralization of A part from 52.78 to 36.96, B part from 20.56 to 32.20, C part from 34.40 to 37.24; Density of A part from 0.122 to 0.123, B part from 0.111 to 0.121, C part from 0.109 to 0.121). The individual in-degree centrality is significantly correlated with self-directed learning and the correlation coefficient increased during the year (r=.274 in 2013, r=.356 in 2014, p<.001). Conclusion: Students share information more interactively during the year and the more they share the higher the scores of self-directed learning.

Keywords: Problem-based learning, Social network analysis, Self-directed learning, Social network centrality

REFERENCES

1.Barrows HS. A taxonomy of problem-based learning methods. J Med Educ. 1986. 20(6):481–6. http://dx.doi.org/10.1111/j.1365-2923.1986.tb01386.x.

2.Hong GC. A meta-analysis on the effects of problem-based learning. J Educ Stud. 2008. 39(3):79–110.

3.Kang MH., Kang JH., Choi HS., Um SY. The effects of learners' perceived roles of a tutor on interactions and learning outcomes of problem-based learning in medical education. J Educ Stud. 2008. 39(3):1–25.

4.Moore MG., Kearsley G. Distance education: a systems view. Belmont: Wads Worth;1996.

5.Cho H., Stefanone M., Gay G. Social network analysis of information sharing networks in a CSCL community. Proceeding of the Conference on Computer Support for Collaborative Learning: Foundation for a CSCL Community. 2002 Jan 7-11; Boulder, USA. Mahwah: Lawrence Erlbaum Associates;. 2002.

6.Kim DS., Kang YG. The effects of the social network data presentation on interaction processes and products in computer supported collaborative learning environment. J Educ Technol. 2004. 20(1):89–115.

7.Chang DJ. Classroom networks and study performance. J Soc Stud Educ. 2000. 4:161–85.

8.Kim YH. Social network theory. Seoul: Pakyoungsa;2007.

9.Shin IS., Kim JH. The effect of problem-based learning in nursing education: a meta-analysis. Adv Health Sci Educ Theory Pract. 2013. 18(5):1103–20.

10.Kim YH. Social network analysis. Seoul: Parkyoungsa;2011.

11.Park JY. A study on the development and the effects of self-directed learning model by project method [dissertation]. Gang-neung: Catholic Kwandong University;2008.

12.Kim DH., Park JY., Lee NY. Factors influencing problem solving ability among nursing students. J Korean Data Anal Soc. 2012. 14(3):1551–63.

13.Mehra A., Kilduff M., Brass D. The social network of high and low self-monitors: implications for workplace performance. Adm Sci Q. 2001. 46(1):121–46. http://dx.doi.org/10.2307/2667127.

14.Lee SS. An analysis of interaction patterns in face-to-face and online synchronous/asynchronous learning environments. J Educ Technol. 2004. 20(1):63–88.

15.Cho H., Gay G., Davidson B., Ingraffea A. Social networks, communication styles and learning performance in a CSCL community. Comput Educ. 2007. 49(2):309–29. http://dx.doi.org/10.1016/j.compedu.2005.07.003.

16.Aviv R., Erlich Z., Ravid G., Geva A. Network analysis of knowledge construction in asynchronous learning networks. J Asynchronous Learn Netw. 2003. 7(3):1–23.

17.Park ES., Choi MS. The effect of learners' social network centralities on knowledge construction in online debating learning. J Educ Inf Media. 2011. 17(3):353–77.

18.Nam CW. The effects of students' centrality of social network on their academic achievement and attitude toward online cooperative learning. J Yeolin Educ. 2012. 20(2):51–73.

19.De Laat M. Network and content analysis in an online community discourse. Proceeding of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community; 2002 Jan 7-11; Boulder, USA. Mahwah: Lawrence Erlbaum Associates;. 2002.

20.Shin HS. The case studies about communication education, applying problem-based learning. J Korean Educ Forum. 2011. 10(3):137–69.

21.Jo YS. The Theory and practice of problem based learning. Seoul: Hakjisa;2006.

22.Chae SJ., Lim GY. An analysis of the relationship between intragroup peer assessment results and self-directed learning readiness in a leadership curriculum. Korean J Med Educ. 2008. 20(4):363–6.

23.Lee HJ., Kim MJ., Chung SK. The relationship between critical thinking disposition and lifelong core competency of college students. J Korean Data Anal Soc. 2012. 14(3B):1535–49.

24.Kim CH. Study on the relationships between participation in sport activities, social network and school life adjustment among the adolescents [dissertation]. Incheon: Inha University;2010.

25.Lim KY., Heo HO., Kim YS. Team leaders' interaction patterns in online team project. J Educ Inf Media. 2009. 15(4):295–317.

26.Palonen T., Hakkarainen K. Patterns of interaction in computer-supported learning: a social network analysis. Proceedings of the Fourth International Conference of the Learning Sciences. 2000. June 14-17; Ann Arbor, USA. Mahwah: Lawrence Erlbaum Associate; 2000.

27.Kang MJ., Piao MH., Park CS. The effects of students' interaction on self-directed learning and learner satisfaction in PBL class-a social network analysis. J Korean Data Anal Soc. 2014. 16(5):2807–18.

28.Cho YS., Chae JS., Baek EJ., Lim HH. A theoretic study on the teaching-learning process for problem-based learning (PBL) in elementary school classrooms. Korean J Educ Methodol Stud. 2004. 16(2):1–28.

Figure 1.

Study interaction network sociogram (Class A)

Figure 2.

Study interaction network sociogram (Class B).

Figure 3.

Study interaction network sociogram (Class C)

Table 1.

Study Interaction Network Characteristics by Classes

Classes	2013		2014
Classes	Centralization	Density	Centralization	Density
A	52.78	0.122	36.96	0.123
B	20.56	0.111	32.20	0.121
C	34.40	0.109	37.24	0.121

Table 2.

Individual in-degree Centrality and Self-directed Learning

Variables	2013	2014	t^∗ (p)
Variables	M±SD	M±SD	t^∗ (p)
Self-directed learning	3.31±0.33	3.06±0.52	3.838
Self-directed learning			(＜.001)
Individual in-degree centrality∗	0.12±0.12	0.14±0.11	1.447
			(.153)

^∗ Paired t test.

Table 3.

The Relationship between Individual In-degree Centrality & Self-Directed Learning

Variable	Individual in-degree centrality
Variable	2013	2014
Self-directed learning	.274^∗	.356^∗

^∗ p＜.001

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