2022 Fiscal Year Research-status Report
The impact of AI-teachers on the human teachers who use them in schools
| Project/Area Number |
20K13900
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| Research Institution | Ochanomizu University |
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Principal Investigator |
ヤマモト.ラヴェナー ロクサナ お茶の水女子大学, リーディング大学院推進センター, 特任講師 (60794675)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | AI in education; / AI tools for teachers; / Affective domain |
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| Outline of Annual Research Achievements |
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.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Although there are still several obstacles to overcome in the process of collecting primary data from teachers, which largely depends on the level of cooperativeness of education boards, the research progress is not significantly delayed.
In the absence of means to test our FER application in formal educational settings, mainly due to the setbacks in the process of obtaining agreements for recording classes, experiments have recently commenced using synthetic data, which provides flexibility, scalability and realism.
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| Strategy for Future Research Activity |
The plan is to continue interviewing teachers on the impact, usefulness and necessity of AI tools for teaching. The investigation related to speech application used by Japanese teachers of English language will resume in summer, as requested by the city education board in charge.
Data collection from teachers about the educational value of appraising student affect, as well as the testing of our FER application are ongoing and will conclude when significant results have been obtained. Research findings will be published in due course.
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| Causes of Carryover |
To improve the developed AI application, further collaborations are needed with scientists, on the one hand to refine the code, and on the other, to assist with the mathematics of change for detecting significant deviation from student default behaviour. Softwares and devices for experiments and improvement of the application may be needed too.
Continuous self-study requires purchasing books and/or taking online courses or the help of specialists.
Assistance with analysis of interview results, translations and travel fees may also be incurred.
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