Research Article

Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis

Volume: 10 Number: 1 January 30, 2023
EN

Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis

Abstract

Classroom rules are a fundamental aspect of classroom management and ensuring compliance with established rules is crucial. Previous research has shown that students often pay little attention to the development of classroom rules. This quantitative study aims to investigate the expectations that students have concerning classroom rules. To this end, a 4-point Likert scale questionnaire consisting of 30 items was administered to 356 secondary school students. The Bayesian Search method and expert opinion were used to obtain a Bayesian Network model. The findings of the study indicate that students expect rules to be determined at the beginning of the academic year, wish to be involved in the determination process, and prefer minimal changes to the rules. They also expect a limited number of rules and reinforcement from teachers for displaying desirable behavior. Additionally, the study found that students are more likely to adhere to classroom rules in a clean and uncrowded environment, and prefer that their parents are not informed about these rules. The results also suggest that increased adherence to classroom rules leads to increased class inclusion, while decreased adherence results in decreased class inclusion. Furthermore, the study found that adoption of classroom rules leads to increased in-class cohesion, while non-adoption results in decreased cohesion. These findings contribute to the existing body of knowledge concerning student expectations of classroom rules.

Keywords

Bayesian network, classroom rules, classroom management, disruptive behavior, student expectations

References

  1. Aelterman, N., Vansteenkiste, M., & Haerens, L. (2019). Correlates of students’ internalization and defiance of classroom rules: A self‐determination theory perspective. British journal of educational psychology, 89(1), 22-40. doi: 10.1111/bjep.12213
  2. Alberto, P. A., & Troutman, A. C. (2013). Applied behavior analysis for teachers (9th ed.). Pearson.
  3. Algozzine, B., Wang, C., & Violette, A. S. (2011). Reexamining the relationship between academic achievement and social behavior. Journal of Positive Behavior Interventions, 13(1), 3-16. doi:10.1177/1098300709359
  4. Almond, R., Mislevy, R., Steinberg, L., Yan, D., & Williamson, D. (2015). Critiquing and learning model structure. In: Bayesian networks in educational assessment. Statistics for social and behavioral sciences. Springer, New York, NY. doi:10.1007/978-1-4939-2125-6_10084
  5. Alter, P., & Haydon, T. (2017). Characteristics of effective classroom rules: A review of the literature. Teacher Education and Special Education: The Journal of the Teacher Education Division of the Council for Exceptional Children, 40(2), 114-127. doi:10.1177/0888406417700962
  6. Alter, P., Walker, J., & Landers, E. (2013). Teachers’ perceptions of students’ challenging behavior and the impact of teacher demographics. Education and Treatment of Children, 36(4), 51-69. doi:10.1353/etc.2013.0040
  7. Billingsley, G. M., McKenzie, J. M., & Scheuermann, B. K. (2018). The effects of a structured classroom management system in secondary resource classrooms, Exceptionality, 28(5), 317-332. doi:10.1080/09362835.2018.1522257
  8. Brophy, J. (1999). Perspectives of classroom management: Yesterday, today, and tomorrow. In H. J. Freiberg, & J. E. Brophy (Eds.), Beyond behaviorism: Changing the class management paradigm (pp. 43-56). Boston: Allyn and Bacon.
  9. Browers, A., & Tomic, W. (2000). A longitudinal study of teacher burnout and perceived self‐efficacy in classroom management. Teaching and Teacher Education, 16(2), 239- 253. doi:10.1016/S0742-051X(99)00057-8
  10. Botsios, S., Georgiou, D. A., & Safouris, N. F. (2007). Learning style estimation using Bayesian Networks. In International Conference on Web Information Systems and Technologies, 2, 415-418.
APA
Demir, İ., Şener, E., Karaboğa, H. A., & Başal, A. (2023). Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis. Participatory Educational Research, 10(1), 424-442. https://doi.org/10.17275/per.23.23.10.1
AMA
1.Demir İ, Şener E, Karaboğa HA, Başal A. Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis. PER. 2023;10(1):424-442. doi:10.17275/per.23.23.10.1
Chicago
Demir, İbrahim, Ersin Şener, Hasan Aykut Karaboğa, and Ahmet Başal. 2023. “Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis”. Participatory Educational Research 10 (1): 424-42. https://doi.org/10.17275/per.23.23.10.1.
EndNote
Demir İ, Şener E, Karaboğa HA, Başal A (January 1, 2023) Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis. Participatory Educational Research 10 1 424–442.
IEEE
[1]İ. Demir, E. Şener, H. A. Karaboğa, and A. Başal, “Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis”, PER, vol. 10, no. 1, pp. 424–442, Jan. 2023, doi: 10.17275/per.23.23.10.1.
ISNAD
Demir, İbrahim - Şener, Ersin - Karaboğa, Hasan Aykut - Başal, Ahmet. “Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis”. Participatory Educational Research 10/1 (January 1, 2023): 424-442. https://doi.org/10.17275/per.23.23.10.1.
JAMA
1.Demir İ, Şener E, Karaboğa HA, Başal A. Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis. PER. 2023;10:424–442.
MLA
Demir, İbrahim, et al. “Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis”. Participatory Educational Research, vol. 10, no. 1, Jan. 2023, pp. 424-42, doi:10.17275/per.23.23.10.1.
Vancouver
1.İbrahim Demir, Ersin Şener, Hasan Aykut Karaboğa, Ahmet Başal. Expectations of Students from Classroom Rules: A Scenario Based Bayesian Network Analysis. PER. 2023 Jan. 1;10(1):424-42. doi:10.17275/per.23.23.10.1