Collaborative activities recommendation based on students’ collaborative learning styles using ANN and WSM

Troussas, Christos; Giannakas, Filippos; Sgouropoulou, Cleo; Voyiatzis, Ioannis

doi:10.1080/10494820.2020.1761835

Cited by 44 publications

(28 citation statements)

References 35 publications

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“…Therefore, artificial neural networks (ANN) can be conceived as a machine learning methodology for defining the function (metamodel) that connects a set of inputs to a set of outputs. In the relevant literature [12,13], ANNs have been used in a number of studies.…”

Section: Metamodel Of Interpreting Students' Satisfactionmentioning

confidence: 99%

Creating a Metamodel for Predicting Learners’ Satisfaction by Utilizing an Educational Information System During COVID-19 Pandemic

Kanetaki

Stergiou

Bekas

et al. 2021

Frontiers in Artificial Intelligence and Applications

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Faced with the disruption generated by the COVID-19 pandemic, the advent of enforced and exclusive online learning presented a challenging opportunity for researchers worldwide, to quickly adapt curricula to this new reality and gather electronic data by tracking students’ satisfaction after attending online modules. Many researchers have looked into the subject of student satisfaction to discover if there is a link between personal satisfaction and academic achievement. Using a set of data, filtered out of a statistical analysis applied on an online survey, with 129 variables, this study investigates students’ satisfaction prediction in a first-semester Mechanical Engineering CAD module combined with the evaluation and the effectiveness of specific curriculum reforms. A hybrid machine learning model that has been created, initially consists of a Generalized Linear Model (GLAR), based on critical variables that have been filtered out after a correlation analysis. Its fitting errors are utilized as an extra predictor, that is used as an input to an artificial neural network. The model has been trained using as a basis the 70% of the population (consisting of 165 observations) to predict the satisfaction of the remaining 30%. After several trials and gradual improvement, the metamodel’s architecture is produced. The trained hybrid model’s final form had a coefficient of determination equal to 1 (R = 1). This indicates that the data fitting method was successful in linking the independent variables with the dependent variable 100 percent of the time (satisfaction prediction).

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Section: Metamodel Of Interpreting Students' Satisfactionmentioning

confidence: 99%

Creating a Metamodel for Predicting Learners’ Satisfaction by Utilizing an Educational Information System During COVID-19 Pandemic

Kanetaki

Stergiou

Bekas

et al. 2021

Frontiers in Artificial Intelligence and Applications

Self Cite

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“…Kegiatan dirancang sesuai dengan minat dan ketertarikan pembelajar, misalnya mencari game yang milenial dan menyenangkan sehingga ini akan membuat mereka tidak bosan dan senang mengikuti pembelajaran sampai akhir. Troussas et al (2020) merekomendasikan kegiatan kolaborasi diterapkan pada pembelajaran dengan mempertimbangkan kebutuhan dan pilihan pembelajar sebagai upaya untuk meningkatkan daya tarik mereka untuk terlibat dalam kegiatan tersebut. Sepadan dengan pendapat Bernard, Rubalcava, & St-Pierre (2000) dan So & Brush ( 2008) dalam (Kuo & Kuo, 2020) menuliskan bahwa collaborative learning telah dipertimbangkan menjadi salah satu metode yang paling efektif dari berbagai jenis setting pembelajaran, baik pembelajaran konvensional maupun pembelajaran yang dicampur (hybrid) sehingga ini dapat menjadi salah satu acuan yang dapat digunakan oleh pengajar untuk diimplementasikan di dalam kelas.…”

Section: Gambar 2: Belajar Sambil Bermain Gamesunclassified

Pemberdayaan Anak Dan Remaja Perempuan Melalui Pembelajaran Bahasa Inggris Di Desa Golong, Kec. Narmada Menggunakan Pendekatan Collaborative Learning

et al. 2021

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Various issues in villages become one of the obligations of academicians or lecturers to solve the problems faced by society. Golong is a village that has the uniqueness and opportunity to be a developed village both for natural resources and human resources. Even though the society has low income but the spirit of the society is high. Therefore, community service team initiates to guide in learning English for children and women teenagers in Golong, Narmada, and West Lombok. Collaborative learning is one of the methods used in this community service activity because it involves and provides plenty opportunity to the learners for sharing and discussing of the materials and to solve the matters. Consequently, by applying the collaborative learning approach, the learners are expected to be more active in learning and cooperating so that their habits of learning and collaboration to be implemented by the learners in workplaces. The community service results show that guidance and empowerment in learning English have a positive impact and have a good response from the learners and community. The empowerment has a pivotal role in encouraging the learners’ motivation and improves the learners’ achievements. The community service activity is expected to be able to be sustainable and become one of cooperation between institutions and villages so that the institution contributes to shape the society to be smart, wise, and prosperous.

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“…In Smart Cities people with disabilities as motor disabled people have solutions to their problems through the Internet of Things (IoT) which connects the physical objects with the people, the Internet, information systems and among themselves [22]. There are researchers showing the assisting technology providing solutions to everyday life of disabled people as people with motor disability that help them to escape of their problem.…”

Section: Smart Cities Augmented Reality and Internet Of Things Improve Accessibilitymentioning

confidence: 99%

Ambient Intelligence and Smart Environments: A Preliminary Overview

Poli

2021

Frontiers in Artificial Intelligence and Applications

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Nowadays human activities are incoming at a digitalization stage. The introduction of information technology along with new forms of communication, influence a variety of forms of human action and focus mainly on the integration and the convergence of the digital and physical worlds. The use of more intelligent – electronic solutions, improves the lives of people around the world, according to studies carried out on the ingress of new smart technologies. Artificial and Ambient intelligence nowadays getting more and more attention about the development of smart, digital environments. The Smart Cities designed for All must aim to arrange the disparity in cities through smart technology, making cities both smart and accessible to a range of users regardless of their abilities or disabilities. The birth of “Artificial Intelligence” (AI) has facilitated the complex computations for reality simulation the new communication era of wireless 5G, all combined have given the hope for a new and better future, to reverse disability to empower the humans with more capabilities, to be faster than they can ever be, stronger than they can ever dream. This paper provides an overview of Ambient Intelligence and smart environments, as well as how technological advancements will benefit everyday usage by devices in common spaces such as homes or offices, and how they will interact and serve as a part of an intelligent ecosystem by bringing together resources such as networks, sensors, human-computer interfaces, pervasive computing, and so on.

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Collaborative activities recommendation based on students’ collaborative learning styles using ANN and WSM

Cited by 44 publications

References 35 publications

Creating a Metamodel for Predicting Learners’ Satisfaction by Utilizing an Educational Information System During COVID-19 Pandemic

Creating a Metamodel for Predicting Learners’ Satisfaction by Utilizing an Educational Information System During COVID-19 Pandemic

Pemberdayaan Anak Dan Remaja Perempuan Melalui Pembelajaran Bahasa Inggris Di Desa Golong, Kec. Narmada Menggunakan Pendekatan Collaborative Learning

Ambient Intelligence and Smart Environments: A Preliminary Overview

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