Abstract
Schoolchildren’s academic progress is known to be affected by the classroom environment. It is important for teachers and administrators to understand their pupils’ status and how various factors in the classroom may affect them, as it can help them adjust pedagogical interventions and management styles. In this study, we expand a novel agent-based model of classroom interactions of our design, towards a more efficient model, enriched with further parameters of peers and teacher’s characteristics, which we believe renders a more realistic setting. Specifically, we explore the effect of disruptive neighbours and teacher control. The dataset used for the design of our model consists of 65,385 records, which represent 3,315 classes in 2007, from 2,040 schools in the UK.
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Notes
- 1.
RR344_-_Performance_Indicators_in_Primary_Schools.pdf (publishing.service.gov.uk).
- 2.
Please note however that PIPS data is only available for Start Math and End Math, thus only the start and end of the simulation process.
References
Alharbi, K., et al.: Agent-based simulation of the classroom environment to gauge the effect of inattentive or disruptive students. In: 17th International Conference on Intelligent Tutoring Systems (2021)
Braun, S.S., et al.: Effects of a seating chart intervention for target and nontarget students. J. Exp. Child Psychol. 191, 104742 (2020). https://doi.org/10.1016/j.jecp.2019.104742
Cardoso, A.P., et al.: Personal and pedagogical interaction factors as determinants of academic achievement. Procedia - Soc. Behav. Sci. 29, 1596–1605 (2011). https://doi.org/10.1016/j.sbspro.2011.11.402
Cobb, J.A.: Relationship of discrete classroom behaviors to fourth-grade academic achievement. J. Educ. Psychol. 63(1), 74–80 (1972). https://doi.org/10.1037/h0032247
Cohen, J.: Statistical Power Analysis for the Behavioral Sciences. Academic Press (2013)
Esturgó-Deu, M.E., Sala-Roca, J.: Disruptive behaviour of students in primary education and emotional intelligence. Teach. Teach. Educ. 26(4), 830–837 (2010). https://doi.org/10.1016/j.tate.2009.10.020
Houghton, S., et al.: Classroom behaviour problems which secondary school teachers say they find most troublesome. Br. Educ. Res. J. 14(3), 297–312 (1988). https://doi.org/10.1080/0141192880140306
Ingram, F.J., Brooks, R.J.: Simulating classroom lessons: an agent-based attempt. In: Proceedings of the Operational Research Society Simulation Workshop 2018, SW 2018, pp. 230–240 (2018)
Jafari, S., Asgari, A.: Predicting students’ academic achievement based on the classroom climate, mediating role of teacher-student interaction and academic motivation. Integr. Educ. 24(1), 62–74 (2020). https://doi.org/10.15507/1991-9468.098.024.202001.062-074
Koster, A., Koch, F., Assumpção, N., Primo, T.: The role of agent-based simulation in education. In: Koch, F., Koster, A., Primo, T., Guttmann, C. (eds.) CARE/SOCIALEDU 2016. CCIS, vol. 677, pp. 156–167. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-52039-1_10
Kristoffersen, J.H.G., et al.: Disruptive school peers and student outcomes. Econ. Educ. Rev. 45, 1–13 (2015). https://doi.org/10.1016/j.econedurev.2015.01.004
Kuyper, H., et al.: Motivation, meta-cognition and self-regulation as predictors of long term educational attainment. Educ. Res. Eval. 6(3), 181–205 (2000). https://doi.org/10.1076/1380-3611(200009)6:3;1-a;ft181
Lavasani, M.G., Khandan, F.: Maintaining the balance: teacher control and pupil disruption in the classroom. Cypriot J. Educ. 2, 61–74 (2011)
Little, E.: Secondary school teachers’ perceptions of students’ problem behaviours. Educ. Psychol. 25(4), 369–377 (2005). https://doi.org/10.1080/01443410500041516
Macal, C., North, M.: Introductory tutorial: agent-based modeling and simulation, pp. 6–20 (2014)
Mauricio, S., et al.: Analysing differential school effectiveness through multilevel and agent-based modelling multilevel modelling and school effectiveness research. 17, 1–13 (2014)
Merrell, C., et al.: A longitudinal study of the association between inattention, hyperactivity and impulsivity and children’s academic attainment at age 11. Learn. Individ. Differ. 53, 156–161 (2017). https://doi.org/10.1016/j.lindif.2016.04.003
Müller, C.M., et al.: Peer influence on disruptive classroom behavior depends on teachers’ instructional practice. J. Appl. Dev. Psychol. 56, 99–108 (2018). https://doi.org/10.1016/j.appdev.2018.04.001
Ponticorvo, M., et al.: An agent-based modelling approach to build up educational digital games for kindergarten and primary schools. Expert Syst. 34(4), 1–9 (2017). https://doi.org/10.1111/exsy.12196
Smith, D.P., et al.: Who goes where? The importance of peer groups on attainment and the student use of the lecture theatre teaching space. FEBS Open Bio 8(9), 1368–1378 (2018). https://doi.org/10.1002/2211-5463.12494
Subramainan, L., et al.: A conceptual emotion-based model to improve students engagement in a classroom using agent-based social simulation. In: Proceeding of the - 2016 4th International Conference on User Science and Engineering, i-USEr 2016, pp. 149–154 (2017). https://doi.org/10.1109/IUSER.2016.7857951
Subramainan, L., Mahmoud, M., Ahmad, M., Yusoff, M.: A simulator’s specifications for studying students’ engagement in a classroom. In: Omatu, S., Rodríguez, S., Villarrubia, G., Faria, P., Sitek, P., Prieto, J. (eds.) DCAI 2017. AISC, pp. 206–214. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-62410-5_25
Tymms, P.: Baseline Assessment and Monitoring in Primary Schools. David Fulton Publisher, London (1999)
Tymms, P., Albone, S.: Performance indicators in primary schools. In: School Improvement through Performance Feedback, pp. 191–218 (2002)
World Health Organization: The ICD-10 classification of mental and behavioural disorders. World Heal. Organ. 55, 135–139 (1993). https://doi.org/10.4103/0019
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Alharbi, K., Cristea, A.I., Shi, L., Tymms, P., Brown, C. (2021). Agent-Based Classroom Environment Simulation: The Effect of Disruptive Schoolchildren’s Behaviour Versus Teacher Control over Neighbours. In: Roll, I., McNamara, D., Sosnovsky, S., Luckin, R., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science(), vol 12749. Springer, Cham. https://doi.org/10.1007/978-3-030-78270-2_8
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