A Simulator’s Specifications for Studying Students’ Engagement in a Classroom

Subramainan, Latha; Mahmoud, Moamin A.; Ahmad, Mohd Sharifuddin; Yusoff, Mohd Zamri

doi:10.1007/978-3-319-62410-5_25

Cited by 5 publications

(3 citation statements)

References 26 publications

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“…Different teachers have various levels of understanding of what engages and interests' students in classroom settings, usually based on experience years and gender (Zepke, Leach, & Butler, 2014;Trowler, 2015). Subramainan, Mahmoud, Ahmad, and Yusoff (2017) highlighted the reasons for poor students' engagement in classrooms by studying the attributes of environmental factors, such as the number of students, lecture length, type of subject, and the year of study. They also included emotional factors, such as the negative emotional states of student, including anger, anxiety, or boredom, and the emotional states of lecturers (Subramainan et al, 2017).…”

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confidence: 99%

“…Subramainan, Mahmoud, Ahmad, and Yusoff (2017) highlighted the reasons for poor students' engagement in classrooms by studying the attributes of environmental factors, such as the number of students, lecture length, type of subject, and the year of study. They also included emotional factors, such as the negative emotional states of student, including anger, anxiety, or boredom, and the emotional states of lecturers (Subramainan et al, 2017). The simulation outcome showed that an experienced lecturer may have ideas on new strategies and can inculcate them during lectures to promote student engagement.…”

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confidence: 99%

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Student Engagment and Math Teachers Support

Alrajeh

Shindel

2020

J. Math. Educ.

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This study aimed to investigate the factors that influence student engagement in mathematics classes. It explored the relationship among emotional, organizational, and instructional support and the impacts of characteristics of teacher, such as years of experience, and sexual orientation, on student engagement. Data were taken from the Consortium for Political and Social Research. The study was involved mathematics teachers and encompassed three years of data collection and observation. Data were collected first hand through classroom observations and student–teacher surveys. In this study, ANOVA, t-test, and partial correlation were employed to evaluate the relationships among the study variables based on participants’ responses. The relationship between student engagement and instructional support weakened after controlling for emotional and organizational support. However, instructional support continued to significantly influence student engagement. In addition, results showed a significant difference in student engagement attributed to the teacher’s gender. Results revealed the interaction between gender and years of experience significantly influenced student engagement, which was in favor of female teachers.

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Student Engagment and Math Teachers Support

Alrajeh

Shindel

2020

J. Math. Educ.

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“…Modelling and simulation study plays an important role in the selection of a particular configuration and system evaluation prior implementation [21]- [23], [49], [50]. To ensure the efficient achievement of Smart Manufacturing realization, Mittal et al [21] includes a simulation in their action roadmap.…”

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confidence: 99%

Towards the Adoption of Smart Manufacturing Systems: A Development Framework

Mahmoud¹,

Grace

2019

IJACSA

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Today, a new era of manufacturing innovation is introduced as Smart Manufacturing Systems (SMS) or Industry 4.0. Many studies have discussed the different characteristics and technologies associated with SMS, however, little attention has been devoted to study the development process when establishing new SMS. The study's objective is to propose a development framework that increases the adoption and awareness of Industry 4.0 among manufacturers and aids decision-makers in designing better SMS capabilities. The framework consists of three phases, iterative process of application modelling; evaluation to ensure optimal configuration and adoption; and finally implementation. The proposed framework is hoped to assist the industries' management in planning for the adoption of technology, in establishing SMS or assessing the need in existing ones. Indirectly, more industry will gain the benefits as a support for their initiatives to transform into Industry 4.0.

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Agent-Based Classroom Environment Simulation: The Effect of Disruptive Schoolchildren’s Behaviour Versus Teacher Control over Neighbours

Alharbi

Cristea

Shi

et al. 2021

Lecture Notes in Computer Science

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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 paramwhich 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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A Simulator’s Specifications for Studying Students’ Engagement in a Classroom

Cited by 5 publications

References 26 publications

Student Engagment and Math Teachers Support

Student Engagment and Math Teachers Support

Towards the Adoption of Smart Manufacturing Systems: A Development Framework

Agent-Based Classroom Environment Simulation: The Effect of Disruptive Schoolchildren’s Behaviour Versus Teacher Control over Neighbours

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