JACIII Vol.27 No.2 pp. 215-222
doi: 10.20965/jaciii.2023.p0215

Research Paper:

Relations Among Curriculum Governance Model, Teacher Work Settings, and Teacher Perceptions on the Professional Learning Community

Hsiao-Chi Juan

Department of Education, National Taichung University of Education
No.140 Minsheng Road, West District, Taichung City 40306, Taiwan

Corresponding author

August 10, 2022
November 22, 2022
March 20, 2023
LASSO regression, ridge regression, professional learning community, curriculum governance, R
Relations Among Curriculum Governance Model, Teacher Work Settings, and Teacher Perceptions on the Professional Learning Community

Coefficient estimates for ridge regression

Following the education reform occurring worldwide, the professional learning community has been seen as a crucial factor in changing the teaching practice on site. However, empirical research has failed to deal with multicollinearity under a social context. This study examines the effect of curriculum development policy and leadership on the professional learning community of teachers. The regularized linear regression method is used to identify the precise effect on the professional learning community in two ways, i.e., ridge and least absolute shrinkage and selection operator regressions. The results show that the main variance comes from teacher actions at the school level and that the collaborative sense of teachers has the most significant effect. This study contributes to existing knowledge on the professional learning of teachers by providing distinguished view of governance model.

Cite this article as:
H. Juan, “Relations Among Curriculum Governance Model, Teacher Work Settings, and Teacher Perceptions on the Professional Learning Community,” J. Adv. Comput. Intell. Intell. Inform., Vol.27, No.2, pp. 215-222, 2023.
Data files:
  1. [1] R. DuFour, R. Eaker, and R. DuFour, “Recurring themes of professional learning communities and the assumptions they challenge,” R. DuFour, R. Eaker, and R. DuFour (Eds.), “On common ground: The power of professional learning communities,” pp. 7-29, Solution Tree, 2005.
  2. [2] A. Hogan et al., “Teachers’ and school leaders’ perceptions of commercialisation in Australian public schools,” The Australian Educational Researcher, Vol.45, No.2, pp. 141-160, 2018.
  3. [3] K. Leithwood and D. Jantzi, “Transformational school leadership for large-scale reform: Effects on students, teachers, and their classroom practices,” School Effectiveness and School Improvement, Vol.17, No.2, pp. 201-227, 2006.
  4. [4] P. Hallinger, “Leadership for learning: Lessons from 40 years of empirical research,” J. of Educational Administration, Vol.49, No.2, pp. 125-142, 2011.
  5. [5] E. Sørensen and J. Torfing, “The democratic anchorage of governance networks,” Scandinavian Political Studies, Vol.28, No.3, pp. 195-218, 2005.
  6. [6] T. Greany and R. Higham, “Hierarchy, markets and networks: Analysing the ‘self-improving school-led system’ agenda in England and the implications for schools,” UCL Institute of Education Press, 2018.
  7. [7] F. Bektaş, A. Ç. Kılınç, and S. Gümüş, “The effects of distributed leadership on teacher professional learning: Mediating roles of teacher trust in principal and teacher motivation,” Educational Studies, Vol.48, No.5, pp. 602-624, 2022.
  8. [8] S. C. Tipping, “Understanding professional learning communities in a middle years setting: A case study,” Ph.D. thesis, University of Calgary, 2020.
  9. [9] Y. Liu and S. Watson, “Whose leadership role is more substantial for teacher professional collaboration, job satisfaction and organizational commitment: A lens of distributed leadership,” Int. J. of Leadership in Education, 2020.
  10. [10] S. Liu, P. Hallinger, and D. Feng, “Supporting the professional learning of teachers in China: Does principal leadership make a difference?,” Teaching and Teacher Education, Vol.59, pp. 79-91, 2016.
  11. [11] E. Santana-Monagas et al., “Teachers’ engaging messages: The role of perceived autonomy, competence and relatedness,” Teaching and Teacher Education, Vol.109, Article No.103556, 2022.
  12. [12] J. Zhang, Q. Huang, and J. Xu, “The relationships among transformational leadership, professional learning communities and teachers’ job satisfaction in China: What do the principals think?,” Sustainability, Vol.14, No.4, Article No.2362, 2022.
  13. [13] N. Kock and G. S. Lynn, “Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations,” J. of the Association for Information Systems, Vol.13, No.7, pp. 546-580, 2012.
  14. [14] M. Yuan and Y. Lin, “Model selection and estimation in regression with grouped variables,” J. of the Royal Statistical Society: Series B (Statistical Methodology), Vol.68, No.1, pp. 49-67, 2006.
  15. [15] L. E. Melkumova and S. Y. Shatskikh, “Comparing ridge and LASSO estimators for data analysis,” Procedia Engineering, Vol.201, pp. 746-755, 2017.
  16. [16] J. O. Ogutu, T. Schulz-Streeck, and H.-P. Piepho, “Genomic selection using regularized linear regression models: Ridge regression, lasso, elastic net and their extensions,” BMC Proc., Vol.6, Article No.S10, 2012.
  17. [17] A. F. Haynos et al., “Machine learning enhances prediction of illness course: A longitudinal study in eating disorders,” Psychological Medicine, Vol.51, No.8, pp. 1392-1402, 2021.
  18. [18] S. Demirci, “A Closer look to Turkish students’ scientific literacy: What do pisa 2015 results tell us?,” M.S. thesis, Middle East Technical University, 2018. [Accessed July 25, 2022]
  19. [19] T.-F. Lee et al., “Using multivariate regression model with least absolute shrinkage and selection operator (LASSO) to predict the incidence of xerostomia after intensity-modulated radiotherapy for head and neck cancer,” PLoS ONE, Vol.9, No.2, Article No.e89700, 2014.
  20. [20] C. Wells and L. Feun, “Implementation of learning community principles: A study of six high schools,” NASSP Bulletin, Vol.91, No.2, pp. 141-160, 2007.
  21. [21] C. Philpott and C. Oates, “Professional learning communities as drivers of educational change: The case of learning rounds,” J. of Educational Change, Vol.18, No.2, pp. 209-234, 2016.
  22. [22] M. Considine and J. M. Lewis, “Bureaucracy, network, or enterprise? Comparing models of governance in Australia, Britain, the Netherlands, and New Zealand,” Public Administration Review, Vol.63, No.2, pp. 131-140, 2003.
  23. [23] L. B. E. Sawyer and S. E. Rimm-Kaufman, “Teacher collaboration in the context of the Responsive Classroom approach,” Teachers and Teaching, Vol.13, No.3, pp. 211-245, 2007.
  24. [24] J. Parsons, “Work less, party more: A review essay about collaborative teacher professional learning,” Northwest J. of Teacher Education, Vol.11, No.2, Article No.1, 2013.
  25. [25] M. R. Bonces, “Organizing a Professional Learning Community – A strategy to enhance professional development,” Íkala, Revista de Lenguaje y Cultura, Vol.19, No.3, pp. 307-319, 2015.
  26. [26] A. M. Thomson, J. L. Perry, and T. K. Miller, “Conceptualizing and measuring collaboration,” J. of Public Administration Research and Theory, Vol.19, No.1, pp. 23-56, 2009.
  27. [27] M. Tavakol and R. Dennick, “Making sense of Cronbach’s Alpha,” Int. J. of Medical Education, Vol.2, pp. 53-55, 2011.
  28. [28] L. R. James, “Aggregation bias in estimates of perceptual agreement,” J. of Applied Psychology, Vol.67, No.2, pp. 219-229, 1982.
  29. [29] S. Menard, “Applied logistic regression analysis,” 2nd Edition, SAGE, 2002.
  30. [30] R. d. Vlaming, “Linear mixed models in statistical genetics,” Ph.D. thesis, Erasmus University Rotterdam, 2017. [Accessed July 25, 2022]

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 19, 2023