Innovation in Language Learning
Educators & AI: Research, Reflections, and the Design of an Advanced Academic Course
Oksana Nakonechmaya, ITMO University (Information Technologies, Mechanics and Optics University), Saint-Petersburg (Russian Federation)
Abstract
Despite the overwhelming presence of AI-related topics everywhere with academia not being an exception, we believe the idea of effective integration of AI-based tools in educational process has not been sufficiently analyzed and researched. Leading by this thought we assumed it was better to investigate the attitude of educators towards AI-driven teaching from different angles, collect, analyze and synthesize data and thus, having obtained reliable statistics, start developing a professional course for ITMO university colleagues which could meet their demands and expectations.
Research aimed at achieving three major goals: to identify and summarize AI-driven practices popular among educators, collect and analyze data to further measure degree of trust experienced by educators towards AI-generated output and their ability to manage AI-based learning performed by students. Within this research university educators did several polls and their answers formed database which was further processed via correlation analysis which was applied to identify clusters of AI tool preferences and their relation to the types of educational practices. The findings of this experiment became foundation of the educational development course which in turn comprised relevant classroom practices and educational objectives of our respondents.
The findings showed that 90% of faculty members are regularly integrating AI-based practices in all stages of teaching process with major interest towards materials design and automatization of formative assessment. Taking into account this information, we developed a comprehensive course on effective integration of AI-based practices into classroom for advanced AI users. The course consists of four practice-oriented modules: profound prompt engineering, crafting academic chatbots, productive incorporation of AI-driven collaborative platforms and ethical guidelines.
Course feedback survey showed increasing confidence in the necessity of effective and responsible integration of AI based tools in academia but at the same time highlighted concerns related to insufficient number of ethical guidelines and documentation.
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Keywords |
AI, AI-driven Education, Academia, Course Design, Research |
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REFERENCES |
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