乌克兰高等教育人工智能教学的创新方法和途径

{"title":"乌克兰高等教育人工智能教学的创新方法和途径","authors":"","doi":"10.57125/fed.2024.03.25.02","DOIUrl":null,"url":null,"abstract":"The aim of the research was to evaluate innovative methodology and approaches to teaching with AI in Ukrainian higher education and to outline the effective delivery practices. The research objectives were to explain AI-based teaching approaches and methods used in the Ukrainian institutions of higher education, to find the most effective teaching approaches and methods in the system of training of future specialists, and to develop the methodological recommendations for instructors involved in the training of future AI experts. Within the framework of the given research, a number of pedagogical articles and key documents devoted to the analysis of used artificial intelligence in teaching, and implementation of AI-based methodology were studied . Over 50 scientific that were published during the recent five years to understand the problem and to evaluate the improvements brought by AI were selected. A mixed methodology that combined descriptive, association, and intervention methods was applied. Descriptive methods included literature review, narrative, content analysis of educational and professional programs, as well as the phenomenological approach. Associational methods included predictive analysis aimed at forecasting of the probability of innovative methodology and approaches that impact the AI education. The intervention suggested using a survey and an assessment. The research included 42 instructors of Ukrainian institutions of higher education that were involved in the training of future AI experts. They represented graduating departments that were responsible for the development of educational and professional program, formulated the training objectives, and designed the conceptual framework for the creation of innovative educational environment with the use of AI. The research resulted in the development of methodical recommendations on using teaching methods and approaches in AI-powered higher education. The recommendations can be suggested by instructors at higher education institutions that are involved specifically in training future AI experts . Also, the recommendations are applicable for scientific and pedagogical stuff working on digitalisation of educational process.","PeriodicalId":427861,"journal":{"name":"Futurity Education","volume":"26 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Innovative Methodologies and Approaches to Teaching with Artificial Intelligence in Ukrainian Higher Education\",\"authors\":\"\",\"doi\":\"10.57125/fed.2024.03.25.02\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of the research was to evaluate innovative methodology and approaches to teaching with AI in Ukrainian higher education and to outline the effective delivery practices. The research objectives were to explain AI-based teaching approaches and methods used in the Ukrainian institutions of higher education, to find the most effective teaching approaches and methods in the system of training of future specialists, and to develop the methodological recommendations for instructors involved in the training of future AI experts. Within the framework of the given research, a number of pedagogical articles and key documents devoted to the analysis of used artificial intelligence in teaching, and implementation of AI-based methodology were studied . Over 50 scientific that were published during the recent five years to understand the problem and to evaluate the improvements brought by AI were selected. A mixed methodology that combined descriptive, association, and intervention methods was applied. Descriptive methods included literature review, narrative, content analysis of educational and professional programs, as well as the phenomenological approach. Associational methods included predictive analysis aimed at forecasting of the probability of innovative methodology and approaches that impact the AI education. The intervention suggested using a survey and an assessment. The research included 42 instructors of Ukrainian institutions of higher education that were involved in the training of future AI experts. They represented graduating departments that were responsible for the development of educational and professional program, formulated the training objectives, and designed the conceptual framework for the creation of innovative educational environment with the use of AI. The research resulted in the development of methodical recommendations on using teaching methods and approaches in AI-powered higher education. The recommendations can be suggested by instructors at higher education institutions that are involved specifically in training future AI experts . Also, the recommendations are applicable for scientific and pedagogical stuff working on digitalisation of educational process.\",\"PeriodicalId\":427861,\"journal\":{\"name\":\"Futurity Education\",\"volume\":\"26 13\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Futurity Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.57125/fed.2024.03.25.02\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Futurity Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.57125/fed.2024.03.25.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

研究的目的是评估乌克兰高等教育中使用人工智能进行教学的创新方法和途径,并概述有效的教学实践。研究目标是解释乌克兰高等教育机构使用的基于人工智能的教学方法和手段,找到未来专家培训系统中最有效的教学方法和手段,并为参与未来人工智能专家培训的教师制定方法建议。在既定研究框架内,研究了大量教学文章和重要文件,这些文章和文件专门分析了人工智能在教学中的应用,以及基于人工智能的教学方法的实施情况。选取了最近五年发表的 50 多篇科学文章,以了解问题并评估人工智能带来的改进。研究采用了描述、关联和干预相结合的混合方法。描述性方法包括文献综述、叙述、教育和专业项目内容分析以及现象学方法。关联方法包括预测分析,旨在预测影响人工智能教育的创新方法和途径的可能性。干预建议使用调查和评估。研究对象包括乌克兰高等教育机构中参与未来人工智能专家培训的 42 名教师。他们代表负责制定教育和专业计划的毕业部门,制定了培训目标,并设计了利用人工智能创建创新教育环境的概念框架。通过研究,提出了在人工智能推动的高等教育中使用教学方法和手段的方法建议。这些建议可供专门培养未来人工智能专家的高等院校教师参考。此外,这些建议也适用于从事教育过程数字化工作的科学和教学人员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Innovative Methodologies and Approaches to Teaching with Artificial Intelligence in Ukrainian Higher Education
The aim of the research was to evaluate innovative methodology and approaches to teaching with AI in Ukrainian higher education and to outline the effective delivery practices. The research objectives were to explain AI-based teaching approaches and methods used in the Ukrainian institutions of higher education, to find the most effective teaching approaches and methods in the system of training of future specialists, and to develop the methodological recommendations for instructors involved in the training of future AI experts. Within the framework of the given research, a number of pedagogical articles and key documents devoted to the analysis of used artificial intelligence in teaching, and implementation of AI-based methodology were studied . Over 50 scientific that were published during the recent five years to understand the problem and to evaluate the improvements brought by AI were selected. A mixed methodology that combined descriptive, association, and intervention methods was applied. Descriptive methods included literature review, narrative, content analysis of educational and professional programs, as well as the phenomenological approach. Associational methods included predictive analysis aimed at forecasting of the probability of innovative methodology and approaches that impact the AI education. The intervention suggested using a survey and an assessment. The research included 42 instructors of Ukrainian institutions of higher education that were involved in the training of future AI experts. They represented graduating departments that were responsible for the development of educational and professional program, formulated the training objectives, and designed the conceptual framework for the creation of innovative educational environment with the use of AI. The research resulted in the development of methodical recommendations on using teaching methods and approaches in AI-powered higher education. The recommendations can be suggested by instructors at higher education institutions that are involved specifically in training future AI experts . Also, the recommendations are applicable for scientific and pedagogical stuff working on digitalisation of educational process.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信