An Investigation on Social Relations between University Students from Seat Position Data

Minami, Toshiro; Ohura, Yoko

doi:10.1109/icict50521.2020.00037

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…Analyzing the distribution of students' seating in the classroom, along with SNA, can help capture their social relationships. This approach sets the foundation for parsing complex student social behaviors (Minami & Ohura, 2020;Pei et al, 2018).…”

Section: Related Workmentioning

confidence: 99%

The NEDC-GTOPSIS Node Influence Evaluation Algorithm Based on Multi-Layer Heterogeneous Classroom Networks

Shou,

Xie,

Wen

et al. 2024

International Journal of Information and Communication Technology Education

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To address the deficiency in the analysis of individual students within existing research on in-classroom social networks and the constraints of traditional centrality metrics in identifying influential nodes, this paper presents the NEDC-GTOPSIS evaluation method for evaluating node influence in multi-layer heterogeneous networks. Initially, students' friendship, interaction, and attribute information are leveraged to compute neighborhood overlap and attribute similarity between nodes, to construct the Composite Relationship Network. Subsequently, the Seat Similarity Network is constructed by applying the Nearest-Neighbor Effective Distance Criterion to compute seat similarity across various class sessions among nodes. Finally, the structure characteristics of two networks serve as influence decision indicators, and the GRA-TOPSIS algorithm, based on the combined weight method, evaluates nodes' influence. Experiments demonstrate that, compared to traditional single-layer relational networks and classical algorithms, this method can more effectively assess influential student nodes.

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Section: Related Workmentioning

confidence: 99%

The NEDC-GTOPSIS Node Influence Evaluation Algorithm Based on Multi-Layer Heterogeneous Classroom Networks

Shou,

Xie,

Wen

et al. 2024

International Journal of Information and Communication Technology Education

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“…Sebagai makhluk sosial, tentunya manusia tidak dapat menjalani kehidupan sendiri. Dalam rangka menyempurnakan kebutuhan sehari-harinya, manusia membutuhkan manusia lain untuk menjalin hubungan antar individu, antar individu dan kelompok, atau antar kelompok dalam kehidupan sosial (Hadar-Shoval, Alon-Tirosh, & Morag, 2019;Li, Zhong, & Xu, 2020;Minami & Ohura, 2020). Akan tetapi, tidak jarang ditemukan perbedaan dalam kehidupan sosial yang menimbulkan perbedaan dalam perilaku hubungan sosia (Bakadorova, Hoferichter, & Raufelder, 2020)l.…”

Section: Pendahuluanunclassified

Hubungan Sosial Mahasiswa Papua dengan Mahasiswa Non Papua di Universitas Sriwijaya Kampus Indralaya

Yolanda

Susanto

Yanti

2021

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Hubungan sosial terjadi antara mahasiswa Papua dengan mahasiswa non Papua yang sama-sama sedang menempuh pendidikan di Universitas Sriwijaya kampus Indralaya. Objek dalam penelitian ini adalah mahasiswa Papua dan mahasiswa non- Papua Universitas Sriwijaya yang memenuhi kriteria informan dalam penelitian ini. Penelitian ini bertujuan untuk mengkaji mengenai hubungan sosial mahasiswa Papua dengan mahasiswa non Papua di Universitas Sriwijaya kampus Indralaya dengan melihat bentuk-bentuk hubungan sosial serta faktor pendorong dan penghambat hubungan sosial. Konsep yang digunakan untuk mengkaji permasalahan mengenai hubungan sosial ini adalah konsep hubungan sosial dari Wardiyatmoko. Metode yang digunakan di dalam penelitian ini adalah deskriptif kualitatif dengan mahasiswa Papua dan mahasiswa non Papua yang menjadi informan utama serta penjaga asrama mahasiswi yang menjadi informan pendukung dalam penelitian ini. Teknik pengumpulan data dalam penelitian ini adalah observasi, wawancara semi struktur kepada informan utama dan informan pendukung, serta dokumentasi. Hasil dari penelitian ini menunjukkan bahwa hubungan sosial asosiatif dalam bentuk kerjasama terjadi dalam kegiatan berupa kerja kelompok dan aksi solidaritas penggalangan dana. Akomodasi terjadi dalam bentuk toleransi dalam bidang keagamaan, diskusi untuk meredakan ketegangan, dan kompromi saat mengerjakan tugas kelompok yang dilakukan oleh mahasiswa Papua dan mahasiswa non Papua. Kemudian hubungan sosial disosiatif terjadi dalam bentuk kontravensi yang berupa ejekan dan sindiran yang sering diterima oleh mahasiswa Papua. Faktor pendorong hubungan sosial mahasiswa Papua dengan mahasiswa non Papua adalah kesadaran bahwa mereka sedang menempuh pendidikan, untuk menjaga rasa aman, menambah relasi pertemanan, dan keperdulian. Sedangkan faktor penghambat hubungan sosial mahasiswa Papua dengan mahasiswa non Papua adalah kesulitan adaptasi, sifat mahasiswa Papua yang cenderung tertutup, dan prasangka negatif yang sering muncul.Kata kunci: Hubungan Sosial, Mahasiswa Papua, Universitas Sriwijaya.

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“…Gao et al (2022) used wearable physiological sensors to research how individual and group classroom seating affects students' engagement and found that students who sit together tend to have a high degree of physiological synchrony and are more likely to have similar learning engagement. Minami and Ohura (2020) used the distance between students' seats as a measure of their friendship relationships and found student groups. Dokuka et al (2015) used a stochastic actor-oriented model (SAOM) to analyze students' social networks and found that students tend to choose classmates with similar academic achievements as their friends.…”

Section: Introductionmentioning

confidence: 99%

Key Student Nodes Mining in the In-Class Social Network Based on Combined Weighted GRA-TOPSIS Method

Shou

Tang

Wen

et al. 2023

International Journal of Information and Communication Technology Education

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In this paper, a key node mining algorithm of entropy-CRITIC combined weighted GRA-TOPSIS method is proposed, which is based on the network structure features. First, the method obtained multi-dimensional data of students' identities, seating relationships, social relationships, and so on to build a database. Then, the seating similarity among students was used to construct the in-class social networks and analyze the structural characteristics of them. Finally, the CRITIC and entropy weight method was introduced for obtaining the combined weight values and the GRA-TOPSIS multi-decision fusion algorithm to mine the key student nodes that have negative impact. The experiments showed that the algorithm of this paper can evaluate students objectively based on their classroom social networks, providing technical support for process-oriented comprehensive quality education evaluation.

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An Investigation on Social Relations between University Students from Seat Position Data

Cited by 4 publications

References 9 publications

The NEDC-GTOPSIS Node Influence Evaluation Algorithm Based on Multi-Layer Heterogeneous Classroom Networks

The NEDC-GTOPSIS Node Influence Evaluation Algorithm Based on Multi-Layer Heterogeneous Classroom Networks

Hubungan Sosial Mahasiswa Papua dengan Mahasiswa Non Papua di Universitas Sriwijaya Kampus Indralaya

Key Student Nodes Mining in the In-Class Social Network Based on Combined Weighted GRA-TOPSIS Method

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