Design and Realization of Interactive Learning System for Art Teaching in Pre-school Education of Artificial Intelligence Equipment

2021 ◽  
pp. 540-548
Author(s):  
Lijuan Zhong
Keyword(s):  
Artificial Intelligence ◽  
Interactive Learning ◽  
School Education ◽  
Learning System ◽  
Art Teaching

Awareness Based Recommendation

2019 ◽  
pp. 167-186
Author(s):  
Tomohiro Yamaguchi ◽  
Takuma Nishimura ◽  
Keiki Takadama
Keyword(s):  
Artificial Intelligence ◽  
Interaction Design ◽  
Interactive Learning ◽  
Learning System ◽  
Experimental Results ◽  
Human Intelligence ◽  
Human Interface ◽  
True Preference ◽  
Heavy Users ◽  
And Robotics

In Artificial Intelligence and Robotics, one of the important issues is to design Human interface. There are two issues, one is the machine-centered interaction design to adapt humans for operating the robots or systems. Another one is the human-centered interaction design to make it adaptable for humans. This research aims at latter issue. This paper presents the interactive learning system to assist positive change in the preference of a human toward the true preference, then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors' system improves the efficiency for deciding the most preferred plan for both heavy users and light users.

Awareness Based Recommendation

2016 ◽  
Vol 4 (1) ◽  
pp. 83-99
Author(s):  
Tomohiro Yamaguchi ◽  
Takuma Nishimura ◽  
Keiki Takadama
Keyword(s):  
Artificial Intelligence ◽  
Interaction Design ◽  
Interactive Learning ◽  
Learning System ◽  
Experimental Results ◽  
Human Intelligence ◽  
Human Interface ◽  
True Preference ◽  
Heavy Users ◽  
And Robotics

In Artificial Intelligence and Robotics, one of the important issues is to design Human interface. There are two issues, one is the machine-centered interaction design to adapt humans for operating the robots or systems. Another one is the human-centered interaction design to make it adaptable for humans. This research aims at latter issue. This paper presents the interactive learning system to assist positive change in the preference of a human toward the true preference, then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors' system improves the efficiency for deciding the most preferred plan for both heavy users and light users.

scholarly journals Artificial intelligence-based education assists medical students’ interpretation of hip fracture

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Chi-Tung Cheng ◽  
Chih-Chi Chen ◽  
Chih-Yuan Fu ◽  
Chung-Hsien Chaou ◽  
Yu-Tung Wu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Education ◽  
Hip Fracture ◽  
Medical Students ◽  
Medical Image ◽  
Learning System ◽  
Significant Difference ◽  
Dynamic Collaboration ◽  
Increase In Accuracy ◽  
Image Learning

Abstract Background With recent transformations in medical education, the integration of technology to improve medical students’ abilities has become feasible. Artificial intelligence (AI) has impacted several aspects of healthcare. However, few studies have focused on medical education. We performed an AI-assisted education study and confirmed that AI can accelerate trainees’ medical image learning. Materials We developed an AI-based medical image learning system to highlight hip fracture on a plain pelvic film. Thirty medical students were divided into a conventional (CL) group and an AI-assisted learning (AIL) group. In the CL group, the participants received a prelearning test and a postlearning test. In the AIL group, the participants received another test with AI-assisted education before the postlearning test. Then, we analyzed changes in diagnostic accuracy. Results The prelearning performance was comparable in both groups. In the CL group, postlearning accuracy (78.66 ± 14.53) was higher than prelearning accuracy (75.86 ± 11.36) with no significant difference (p = .264). The AIL group showed remarkable improvement. The WithAI score (88.87 ± 5.51) was significantly higher than the prelearning score (75.73 ± 10.58, p < 0.01). Moreover, the postlearning score (84.93 ± 14.53) was better than the prelearning score (p < 0.01). The increase in accuracy was significantly higher in the AIL group than in the CL group. Conclusion The study demonstrated the viability of AI for augmenting medical education. Integrating AI into medical education requires dynamic collaboration from research, clinical, and educational perspectives.

Design of English reading and learning management system in college education based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Fen Zhang ◽  
Min She
Keyword(s):  
Artificial Intelligence ◽  
Model Performance ◽  
College Education ◽  
Personalized Learning ◽  
Learning System ◽  
Model Function ◽  
English Reading ◽  
Function Modules ◽  
Learning Platforms ◽  
Learning Management

English reading learning in college education is an efficient means of English learning. However, most of the current English reading learning platforms in colleges and universities only put different English books on the platform in electronic form for students to read, which leads to blindness of reading. Based on artificial intelligence algorithms, this paper builds model function modules according to the needs of English reading and learning management in college education and implements system functions based on artificial intelligence algorithms. Moreover, according to the above design principles of personalized learning model and the characteristics of personalized network learning, this paper designs a personalized learning system based on meaningful learning theory. In addition, this article verifies and analyzes the model performance. The research results show that the model proposed in this paper has a certain effect.

Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of Artificial Intelligence: A pilot Study

Endoscopy ◽  
2020 ◽  
Author(s):  
Alanna Ebigbo ◽  
Robert Mendel ◽  
Tobias Rückert ◽  
Laurin Schuster ◽  
Andreas Probst ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Pilot Study ◽  
White Light ◽  
Submucosal Invasion ◽  
Learning System ◽  
Endoscopic Images ◽  
Barrett’S Cancer ◽  
Significant Difference ◽  
Sensitivity Specificity

Background and aims: The accurate differentiation between T1a and T1b Barrett’s cancer has both therapeutic and prognostic implications but is challenging even for experienced physicians. We trained an Artificial Intelligence (AI) system on the basis of deep artificial neural networks (deep learning) to differentiate between T1a and T1b Barrett’s cancer white-light images. Methods: Endoscopic images from three tertiary care centres in Germany were collected retrospectively. A deep learning system was trained and tested using the principles of cross-validation. A total of 230 white-light endoscopic images (108 T1a and 122 T1b) was evaluated with the AI-system. For comparison, the images were also classified by experts specialized in endoscopic diagnosis and treatment of Barrett’s cancer. Results: The sensitivity, specificity, F1 and accuracy of the AI-system in the differentiation between T1a and T1b cancer lesions was 0.77, 0.64, 0.73 and 0.71, respectively. There was no statistically significant difference between the performance of the AI-system and that of human experts with sensitivity, specificity, F1 and accuracy of 0.63, 0.78, 0.67 and 0.70 respectively. Conclusion: This pilot study demonstrates the first multicenter application of an AI-based system in the prediction of submucosal invasion in endoscopic images of Barrett’s cancer. AI scored equal to international experts in the field, but more work is necessary to improve the system and apply it to video sequences and in a real-life setting. Nevertheless, the correct prediction of submucosal invasion in Barret´s cancer remains challenging for both experts and AI.

The Effects of an Interactive Learning System on PANCE Performance

2008 ◽  
Vol 19 (3) ◽  
pp. 30-34
Author(s):  
Scott Massey ◽  
Mona Sedrak ◽  
Louise Lee
Keyword(s):  
Interactive Learning ◽  
Learning System

scholarly journals Orienteering in Geography Education in Japanese High School

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Taketo Kobayashi
Keyword(s):  
High School ◽  
Learning Effect ◽  
Geography Education ◽  
School Education ◽  
Learning System ◽  
Map Learning ◽  
The Core ◽  
Learning Outdoors ◽  
Good Learning ◽  
Map Scale

<p><strong>Abstract.</strong> Orienteering, a map activity, has been described as effective in learning geography in school education. When dealing with orienteering in school education, it is learning outdoors different from ordinary classroom lessons. Also, the environment surrounding school education differs from country to country. From this, it is important to show the practice of orienteering in school education in each country. In this research, I described the practice of orienteering in geography education of Japanese high schools in the following three viewpoints. The three viewpoints are the significance of orienteering in geography education, learning system of orienteering in geography education, examples of orienteering in geography education at school. The main points are as follows. <ol> <li>The skills given by orienteering are the basis of map learning and field learning in geography education.</li> <li>Learning system of orienteering is related to the map learning and field learning perspective, such as related to the map-scale linked with place.</li> <li>Orienteering practice in regular geography class at school grounds is the core, and good learning effect can be obtained. After this, orienteering can be expanded in a wide variety of directions.</li> </ol></p>

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