The Effect of Peer Tutoring on the Process of Learning Mathematical Proofs

Rahman, Nurul Ashikin Abdul; Razak, Fatimah Abdul; Dzul-Kifli, Syahida Che

doi:10.37418/amsj.9.9.84

Cited by 3 publications

(10 citation statements)

References 2 publications

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“…If the tutor has a strong academic record, the benefits of peer tutoring can be immense. The chosen peer tutors, however, are occasionally not high achievers [16], which may indicate less or sometimes incorrect understanding of the educational content.…”

Section: Related Workmentioning

confidence: 99%

“…This inevitably impacts the structure of a learning community [15]. Previously, in [16,17], we studied the relationship between peer tutoring and student performance. Ref.…”

Section: Introductionmentioning

confidence: 99%

“…A practical solution can be recommended to educators to help monitor and create a healthier learning environment. This study is a continuation of [16,17], further using centrality measures to understand the learning community of Malaysian students. Due to the dearth of studies related to online learning communities, particularly in Malaysia, it is a field that requires attention, especially when dealing with crises such as the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

“…Social network analysis is an approach that utilizes data mining to investigate the social structure of a community via graph theory. This strategy has been successfully applied in a variety of disciplines, including finance [18,19], scientific collaboration [20,21], and education [16,17]. In the context of education, this approach can be utilized as a benchmark for monitoring student association through networks and developing solutions that are pertinent to concerns and challenges [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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Comparing Friends and Peer Tutors Amidst COVID-19 Using Social Network Analysis

et al. 2023

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COVID-19 has drastically changed the teaching patterns of higher education from face-to-face to online learning, and it has also affected students’ engagement socially and academically. Understanding the nature of students’ engagement during online learning can help in identifying related issues so that various initiatives can be implemented in adapting to this situation. In this study, social network analysis is conducted to gain insights on students’ engagement during COVID-19. Directed and weighted networks were used to visualize and analyze friendship as well as peer tutor networks obtained from online questionnaires answered by all students in the class. Contrasting friends and peer tutors reveals some hidden interactions between students and shines some light on dynamics of the online learning community. The results indicate that, popular and important peer tutors may not be high achievers and thus possibly contributing to the spread of misinformation in the online learning community. By comparing weighted indegree and betweenness centrality values, we suggest approaches to cultivate a healthy online learning community. This study highlights the use of social network analysis to assist and monitor students’ engagement and further formulate strategies in order to make the class a conducive online learning community, particularly in the advent of online learning in higher education institutions.

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Section: Related Workmentioning

confidence: 99%

“…This inevitably impacts the structure of a learning community [15]. Previously, in [16,17], we studied the relationship between peer tutoring and student performance. Ref.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparing Friends and Peer Tutors Amidst COVID-19 Using Social Network Analysis

et al. 2023

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“…Many studies related to learning models to develop an understanding of proof and students' mathematical argumentation abilities. Rahman et al (2020) analyzed the learning of peer tutors in identifying gaps and improving student performance in learning proof and understanding of mathematics. Maya & Sumarmo (2011) applied a modified Moore learning approach to improve students' mathematical understanding and proof abilities.…”

Section: A Introductionmentioning

confidence: 99%

Implementation of Inquiry Learning Model in Collaboration with PBL to Improve Student Understanding in Number Theory Course

Tristanti,

Nusantara,

Maf’ulah

2024

JTAM

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The purpose of this study was to describe the presence or absence of the influence of the infusion learning model collaboration with Problem-Based Learning (PBL) to develop students' understanding of proof and mathematical argumentation in number theory courses. This research is an experimental study with a randomized control group pretest-posttest design, two groups namely the experimental group and the control group. The experimental group is the group that uses the infusion learning model in collaboration with PBL, while the control group is the group that uses conventional learning. The subjects of this study consisted of 40 students at a university in Jombang, Indonesia. Data collection techniques through observation sheets, proof understanding tests and observation sheets of students' mathematical argumentation abilities. The results of the research show that the significant difference between the average proof of understanding of students in the experimental group and the control group. The difference between the average proof of understanding in the experimental group and the average proof of understanding of students in the control group was 21.75. Furthermore, the significant difference between the average argumentation ability of students in the experimental group and the control group. The difference between the average argumentation ability of students in the experimental group and the average argumentation ability of students in the control group is 5.25. Therefore, the implementasion of infusion learning in collaboration with PBL is more effective than conventional learning models for developing students' ability to understand mathematical proof and argumentation. This learning model promotes the development of critical thinking skills, problem-solving, conceptual and different understanding needed to construct a formal proof, and strong and valid arguments.

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Modelling Heterogeneity and Super Spreaders of the COVID-19 Spread through Malaysian Networks

Razak

Zamzuri

2021

Symmetry

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Malaysia is multi-ethnic and diverse country. Heterogeneity, in terms of population interactions, is ingrained in the foundation of the country. Malaysian policies and social distancing measures are based on daily infections and R0 (average number of infections per infected person), estimated from the data. Models of the Malaysian COVID-19 spread are mostly based on the established SIR compartmental model and its variants. These models usually assume homogeneity and symmetrical full mixing in the population; thus, they are unable to capture super-spreading events which naturally occur due to heterogeneity. Moreover, studies have shown that when heterogeneity is present, R0 may be very different and even possibly misleading. The underlying spreading network is a crucial element, as it introduces heterogeneity for a more representative and realistic model of the spread through specific populations. Heterogeneity introduces more complexities in the modelling due to its asymmetrical nature of infection compared to the relatively symmetrical SIR compartmental model. This leads to a different way of calculating R0 and defining super-spreaders. Quantifying a super-spreader individual is related to the idea of importance in a network. The definition of a super-spreading individual depends on how super-spreading is defined. Even when the spreading is defined, it may not be clear that a single centrality always correlates with super-spreading, since centralities are network dependent. We proposed using a measure of super-spreading directly related to R0 and that will give a measure of ‘spreading’ regardless of the underlying network. We captured the vulnerability for varying degrees of heterogeneity and initial conditions by defining a measure to quantify the chances of epidemic spread in the simulations. We simulated the SIR spread on a real Malaysian network to illustrate the effects of this measure and heterogeneity on the number of infections. We also simulated super-spreading events (based on our definition) within the bounds of heterogeneity to demonstrate the effectiveness of the newly defined measure. We found that heterogeneity serves as a natural curve-flattening mechanism; therefore, the number of infections and R0 may be lower than expected. This may lead to a false sense of security, especially since heterogeneity makes the population vulnerable to super-spreading events.

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The Effect of Peer Tutoring on the Process of Learning Mathematical Proofs

Cited by 3 publications

References 2 publications

Comparing Friends and Peer Tutors Amidst COVID-19 Using Social Network Analysis

Comparing Friends and Peer Tutors Amidst COVID-19 Using Social Network Analysis

Implementation of Inquiry Learning Model in Collaboration with PBL to Improve Student Understanding in Number Theory Course

Modelling Heterogeneity and Super Spreaders of the COVID-19 Spread through Malaysian Networks

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