Analysis and Improvement of Classroom Teaching Based on Artificial Intelligence

Sun, Zhong; Yu, Zi Chun; Xu, Fei

doi:10.1007/978-3-031-09687-7_7

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Step 1, obtain the gating signal, calculate the reset gate signal Rt by formula (1), and calculate the update gating signal Zt by formula (2), [xt,ht-1] which indicates that the input Xt of the current state is vectorially spliced with the previous hidden state ht-1 ; and σdenotes the sigmoid function, which indicates that the range of values of the reset gate and the update gate is (0,1).…”

Section: Expression Time Feature Extractionmentioning

confidence: 99%

“…In recent years, with the continuous development and maturity of computer vision related technology, through the monitoring camera system, real-time tracking of student learning can be carried out to help teachers understand the learning status of students and improve teaching efficiency [1].The learning status of students can also reflect the teaching situation of teachers, by analyzing the changes in students' expressions can assist in evaluating the teaching effect of teachers, help teachers find the problems of teaching in a timely manner, and assist teachers in formulating targeted teaching plans, so as to enhance the teaching Effect [2]. Therefore, there is an urgent need for a reliable algorithm to classroom expression recognition to evaluate students' learning status and provide a certain reference for classroom teaching evaluation.…”

Section: Introductionmentioning

confidence: 99%

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Improved MobileNetv3 lightweight dynamic expression recognition algorithm for classroom scenarios

顾,

丁,

冯

2024

Preprint

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Aiming at the proplem of high difficulty and low real-time in dynamic expressions recognition under classroom scenes, a lightweight dynamic expression recognition algorithm based on improved MobileNetv3 is proposed. Firstly, through embedding a feature extraction module of GRU (Gate Recurrent Unit) in the MobileNetv3 network, the corresponding space vector of each expression image is processed, the temporal feature among expression image sequences is extracted, and the expression characteristics over time are fully explored. Then, a new hybrid loss LMCF (Large Margin Cosine Focal Loss) is proposed to build the hypersphere of facial expression features, and the inter-class distance of expressions is increased by enlarging the cosine distance, while the blurring problem of inter-class feature boundaries caused by unbalanced expression data is alleviated. Finally, a sparsely connected Pointwise Group Convolution is adopted to optimize the depthwise separable convolution in MobileNetv3 network, the model complexity is reduced, and the model speed is improved. The experimental results show that the accuracy and speed of the proposed algorithm are better than those of the other algorithms in the classroom scene test set, the mean average precision (mAP) can be improved by up to 2.88%, and the recognition rate can be improved by up to 12 FPS.

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Section: Expression Time Feature Extractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved MobileNetv3 lightweight dynamic expression recognition algorithm for classroom scenarios

顾,

丁,

冯

2024

Preprint

View full text Add to dashboard Cite

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Enriching the Teaching-Learning Experience by Using AI Tools in the L2 Classroom

Barrios-Beltran

2024

AI in Language Teaching, Learning, and Assessment

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Artificial intelligence (AI) has emerged as a transformative force in second language (L2) education, reshaping teaching and learning methodologies. This chapter explores AI's impact on L2 educators and learners through insights from questionnaires and a follow-up conversation. Initial apprehension towards AI is counterbalanced by curiosity about its potential to enhance educational practices. The chapter provides practical guidance, showcasing how AI tools can be aligned with key language learning skills and offering structured examples of activities to enhance these skills. It highlights AI's role in providing immediate feedback, simplifying complex concepts, and creating inclusive classrooms tailored to individual learning styles and needs. The discussion also addresses educators' recognition of AI's potential and underscores the need for clear guidelines and training in ethical AI implementation. As AI technology evolves, it promises a more personalized, dynamic educational journey, enriching the L2 learning process.

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Artificial Intelligence

Ahmad,

Shokeen,

Raj

2024

Advances in Educational Technologies and Instructional Design

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The evolution of Artificial Intelligence (AI) has significantly transformed various fields, including education, by introducing advanced techniques and algorithms. This transformation encompasses tasks such as convergence, classification, identification, recognition, and beyond, integrating knowledge from sociology, psychology, ethics, computer science and pedagogy. The historical milestones of AI, from the early works of Turning and McCarthy to the recent advancements in Large Language Models (LLMs) like ChatGPT, demonstrate AI's progression and its impact on education. Recent advancements in AI, including Internet of Thing, Machine Learning, Augmented Reality, and Virtual Reality, have transformed the educational landscape, making it more inclusive and accessible for individuals with disabilities. This chapter proposes AI as solution to the field of special education particularly while addressing the needs of CwSN in mainstream settings. The research conducted in the past suggests that the use AI has greater advantages over traditional methods of teaching to the CwSN.

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Analysis and Improvement of Classroom Teaching Based on Artificial Intelligence

Cited by 3 publications

References 25 publications

Improved MobileNetv3 lightweight dynamic expression recognition algorithm for classroom scenarios

Improved MobileNetv3 lightweight dynamic expression recognition algorithm for classroom scenarios

Enriching the Teaching-Learning Experience by Using AI Tools in the L2 Classroom

Artificial Intelligence

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