Titlebook: Innovative Technologies and Learning; 4th International Co Yueh-Min Huang,Chin-Feng Lai,Tania Rocha Conference proceedings 2021 Springer Na

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書目名稱Innovative Technologies and Learning影響因子(影響力)




書目名稱Innovative Technologies and Learning影響因子(影響力)學(xué)科排名




書目名稱Innovative Technologies and Learning網(wǎng)絡(luò)公開度




書目名稱Innovative Technologies and Learning網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Innovative Technologies and Learning被引頻次




書目名稱Innovative Technologies and Learning被引頻次學(xué)科排名




書目名稱Innovative Technologies and Learning年度引用




書目名稱Innovative Technologies and Learning年度引用學(xué)科排名




書目名稱Innovative Technologies and Learning讀者反饋




書目名稱Innovative Technologies and Learning讀者反饋學(xué)科排名

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Lightening Up a New AI Cognitions and Performances for Engineering Students’ Problem-Based Learning vation ability, and improve the cognitive levels of problem-solving by quantitative analysis of learning achievements; (4) to show that the factor of students disposition AI courses is the most important for their impact on learning attitudes by one-way ANOVA.

inquisitive

Use Object-Detection to Identify Materials and Tools for STEAM Hands-on Activity tools through recording the videos of learners in STEAM hands-on activities. This report can be used as the basic prototype of the application of computer vision in STEAM education. The ultimate goal is to identify and judge learners’ participation in STEAM activities.

Delirium

Regarding the Virtual Reality Environment Design and Evaluation Based on STEAM Learningy”. In terms of the practicability evaluation of STEAM VR learning environment establishment, the highest scoring element is “Interactivity”, followed by “Engagement”, with “Imagination” being the lowest. This study serves as a reference for future educators and researchers in establishing a STEAM VR learning environment.

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Conference proceedings 2021er/December 2021. Due to COVID-19 pandemic the conference was held virtually.. The 59 full papers presented together with 2 short papers were carefully reviewed and selected from 110 submissions. The papers are organized in the following topical sections: Artificial Intelligence in Education; Augmen

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Oral Practice Language Learning Companion Implementation on Voice Assistant Platformit can always be with you to practice English conversation. It uses natural language processing and voice recognition technology to tell if you are repeating the same sentence, help students can practice conversation by themselves.

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Developing an AR Tutoring System to Support Maker Educationucation. In addition, we conducted a series of analyses. Based on the results of the analysis, we boldly assume that the system is helpful to students’ learning in maker education. Finally, we have listed the problems and solutions encountered during the development process for future developers’ reference.