The impact of AI-teachers on the human teachers who use them in schools

该项目继续调查教师采用或为教师设计的人工智能工具的有用性。报告成果的研究有三个方面：1。该研究调查了日本英语教师，他们在教学发音的范围内，采用了人工智能工具，使用机器学习算法进行分析，并使用自然语言处理技术来理解用户的语音。研究结果表明，这种教学工具不仅提供了更好的教学体验，而且可能使传统的英语发音教学技术过时。对教师评价学生情感的需求和使用面部情感识别（FER）人工智能来补充其自然方法的愿望的调查取得了积极的结果。开发的FER应用程序经过改进，可以检测到学生默认情绪状态的偏差。现在，通过训练一个多任务卷积神经网络，以效价（情绪的积极/消极本质）和唤醒（情绪强度）为基础，对情绪进行建模，以创造一个连续的情绪体验频谱，而不是像以前那样简单地将情绪分为离散的类别（快乐、中性、悲伤等）。

The project continued with investigations on the usefulness of AI tools adopted by or designed for teachers. There are three lines of research which report achievements:1. The study surveyed Japanese schoolteachers of English language who, with the scope of teaching pronunciation, adopted an AI tool which uses machine learning algorithms to analyse, and natural language processing techniques to understand users' speech. Findings show that such teaching tool not only provides a better teaching-learning experience, but may render traditional English pronunciation teaching techniques obsolete.2. Investigation on teachers' need to appraise student affect and their desire to use facial emotion recognition (FER) AI to complement their natural methods yielded positive results.3. The developed FER application was improved to allow detection of deviations from default student emotional state. Emotions are now modelled in terms of valence (positive/negative nature of emotion) and arousal (emotion intensity) by training a multi-task convolutional neural network, in order to create a continuous spectrum of emotional experiences, rather than simply categorising emotions into discrete classes (happy, neutral, sad etc.), as it did before.