A Study on Experts’ Perception Survey on Elementary AI Education Platform

Lee, Jae-Ho; 컴퓨터교육과, 경인교육대학교; Lee, Seung‐Hoon

doi:10.14352/jkaie.2020.24.5.483

Cited by 2 publications

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“…The key technical features of the smart learning environment are mainly reflected in the recording process, situational perception, adaptive interaction, etc., emphasizing the perception and recording of learners' knowledge acquisition and other aspects through motion capture, emotional computing, eye tracking, etc., in order to facilitate learning. Compared with ordinary digital learning environments, smart learning environments focus on cultivating learners' innovative ability, problem-solving ability, decision-making ability, and critical thinking ability, while cognitive activities play an important role in cultivating learners' higher-order thinking ability [ 2 , 3 ].…”

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confidence: 99%

Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data

Zhang

2022

Occupational Therapy International

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At present, most of the research on academic emotions focuses on the concept, current situation, and relevance. There are not many researches on the application of artificial intelligence-based neural network facial expression recognition technology in practical teaching. With reference to image-based big data, this research integrates the application of artificial intelligence facial expression recognition technology with the research on educational theory and applies information technology to the actual teaching process, in order to promote the optimization of the teaching process and improve the learning effect. Method. A Hadoop cluster consisting of 3 nodes is built on the Linux system, and the environment required for Opencv execution is compiled for each node, which provides support for subsequent parallel optimization, feature extraction, feature fusion, and recognition of student facial images. The image data type and input and output format based on MapReduce framework are designed, and the image data is optimized by means of serialized files. The color features, texture features, and Sift features of students’ facial images and common distractors were analyzed. A parallel extraction framework of student facial image features is designed, and based on this, the student facial image feature extraction under Hadoop platform is implemented. This paper proposes a dynamic sequential facial expression recognition method that combines shallow and deep features with an attention mechanism. The relative position of facial landmarks and local area texture features based on FACS represent shallow-level features. At the same time, the structure of ALexNet is improved to extract the deep features of sequence images to express high-level semantic features. The effectiveness of the facial expression recognition system is improved by introducing three attention mechanisms: self-attention, weight-attention, and convolutional attention. Results/Discussion. Through the analysis of the teaching effect, we found that when teachers can obtain the correct student’s academic mood, they can intervene on the students’ positive academic mood. The purpose of the intervention is to improve the positive academic emotions of students. After the students receive the intervention, their academic emotions are also improved and are positively correlated with their academic performance. Through the analysis of teaching effect, the research can achieve the predetermined goal. From the specific teaching effect of this study, it is concluded that in classroom teaching, teachers should devote energy to intervene in students’ positive academic emotions, in order to improve students’ positive academic emotions, which will improve students’ academic performance and teaching.

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Section: Introductionmentioning

confidence: 99%

Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data

Zhang

2022

Occupational Therapy International

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“…Using a drag-and-drop method, young students could quickly encounter BD and AI. In addition, there are numerous programming environments that K-12 students can use to learn the fundamentals of BD and AI, as per Park and Shin [100] and other authors [101][102][103][104]. These settings enable basic BD and AI projects to be implemented by young students.…”

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The Potential of Big Data Application in Mathematics Education in Malaysia

et al. 2022

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The world is facing rapid changes after the emergence of innovative technologies. These changes aim to ensure that a country keeps track of current world developments, strengthens its economy, and reduces its dependence on imports. Hence, every country is now amid technological transformation in the industrial sector by replacing manpower with machines to increase production and efficiency, allowing for mass production. Technology advancements in control, information technology, and automation that are applied to business and industry production processes are referred to as ‘Industry 4.0’. The objective is to increase the autonomy, adaptability, and effectiveness of decision-making and production processes utilizing cyber-physical systems (CPS), Big Data (BD), artificial intelligence (AI), and the industrial Internet of Things (IoT). Specifically, this article first introduces Industry Revolution (IR) 4.0, followed by a delineation of the concept of BD. Correspondingly, we discuss BD in education and relate mathematics education with BD. The article concludes with the implications of BD for Malaysian teaching and learning practices.

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A Study on Experts’ Perception Survey on Elementary AI Education Platform

Cited by 2 publications

References 0 publications

Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data

Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data

The Potential of Big Data Application in Mathematics Education in Malaysia

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