Retracted: Evaluation of user concentration in ubiquitous and cognitive artificial intelligence‐assisted English online guiding system integrating face and eye movement detection

Liu, Lu; Peng, Nan

doi:10.1002/dac.4580

Cited by 7 publications

(7 citation statements)

References 18 publications

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“…In the context of the Internet of Things, we examine how facial recognition and eye tracking may work together, as well as the theory behind evaluating user attentiveness. We propose an online English teaching focus assessment system based on the aforesaid technologies in the context of AI [14].…”

Section: Literature Surveymentioning

confidence: 99%

Research on English Hybrid Assisted Teaching System Using Contextual Support of R-CNN

Yuan

2022

Wireless Communications and Mobile Computing

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The developing countries and developed countries are depending on major as well as single language, i.e., English. The software tool level English teaching assistance models are available but those are not that user-friendly and also unable to support current technology. The earlier English teaching assistance techniques like RFO (Random Forest Optimization) machine learning, Xboosting machine learning, and SVM (Support Vector Machine) cannot support background provision. English teachers must find a way to coordinate the relationships between students, teachers, the learning environment, and learning strategies. A modern user-friendly building technique and an advanced ecobalancing of education are suggested and executed, which may increase the hybrid education characteristics and request skills of English. Therefore, an advanced ANN-(artificial neural network-) based hybrid English teaching assistance model is inevitability necessary. In this research work, R-CNN-based ANN model is imported to make applications for hybrid English teaching assistants. The performance measures like accuracy 97.89%, sensitivity 98.34%, recall 94.83%, and throughput 92.89% had attained. The implemented design is competing with present technology and outstrips the methodology. The process is outstripped by the realized design, which competes with current technology.

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Section: Literature Surveymentioning

confidence: 99%

Research on English Hybrid Assisted Teaching System Using Contextual Support of R-CNN

Yuan

2022

Wireless Communications and Mobile Computing

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“…Wen et al [ 38 ] presented chaos optimization cognitive learning model, where the learning process of distance learning has been formulated into a multi-objective optimization problem. Liu and Peng [ 23 ] proposed an online user focus evaluation system, where eye tracking and face recognition technologies were combined with the cognitive theory to evaluate the concentration of students.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of e-learners’ concentration using recurrent neural networks

Jeong

Cho

2022

J Supercomput

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Recently, interest in e-learning has increased rapidly owing to the lockdowns imposed by COVID-19. A major disadvantage of e-learning is the difficulty in maintaining concentration because of the limited interaction between teachers and students. The objective of this paper is to develop a methodology to predict e-learners’ concentration by applying recurrent neural network models to eye gaze and facial landmark data extracted from e-learners’ video data. One hundred eighty-four video data of ninety-two e-learners were obtained, and their frame data were extracted using the OpenFace 2.0 toolkit. Recurrent neural networks, long short-term memory, and gated recurrent units were utilized to predict the concentration of e-learners. A set of comparative experiments was conducted. As a result, gated recurrent units exhibited the best performance. The main contribution of this paper is to present a methodology to predict e-learners’ concentration in a natural e-learning environment.

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“…Examination and model proposition studies measure, observe, or locally control physical conditions using different methods [1,[31][32][33]. Furthermore, experimental studies conducted in classroom environments ignored the effect of physical classroom conditions [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48]. In learning environments, the main purpose is learning efficiency.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of an IoT-Based Smart Classroom Incubator

Burunkaya

Duraklar

2022

Applied Sciences

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Ambient conditions influence human health, emotions, and mental power. Therefore, numerous studies have been conducted in different disciplines on the measurement and control of ambient conditions in classrooms. Moreover, a number of studies identify some physical and mental performances of students simultaneously or for informative purposes by utilizing various hardware and software. However, these studies did not consider automatic control processes and individuality in fulfilling classroom ambient conditions, which influence students’ behavior. This study aims to reduce the adverse impacts of environmental factors on learning and control more necessary physical parameters with higher accuracy using the latest technology and methods. Thus, a new smart classroom incubator (SCI) algorithm, including hardware, software, and experimental studies, in which individual differences could be considered even in the same classroom environment, and its implementation were presented. The system enables access and monitoring of data wherever there is Internet connection. Moreover, it was designed based on IoT because it allows for data transfer over web services or data-dependent operations. All the necessary equipment was placed in the classroom without affecting the learning environment and distracting the class. Cronbach’s α coefficient, which indicates the reliability of the implemented model, was 0.891.

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Retracted: Evaluation of user concentration in ubiquitous and cognitive artificial intelligence‐assisted English online guiding system integrating face and eye movement detection

Cited by 7 publications

References 18 publications

Research on English Hybrid Assisted Teaching System Using Contextual Support of R-CNN

Research on English Hybrid Assisted Teaching System Using Contextual Support of R-CNN

Evaluation of e-learners’ concentration using recurrent neural networks

Design and Implementation of an IoT-Based Smart Classroom Incubator

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