A Vision of Teaching and Learning with AI

Petros Lameras

doi:10.1109/EDUCON52537.2022.9766718

A Vision of Teaching and Learning with AI

Petros Lameras

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

8 Citations (Scopus)

545 Downloads (Pure)

Abstract

Rapid development of AI technologies with breakthroughs in algorithmic machine learning and autonomous decision making have generated unprecedented opportunities for technological innovation. There is consensus from policy report that in the next years AI could revolutionise the way teaching and learning is designed and delivered to students leading to seamless intelligent services that are more tailored to student’s needs and interests. Current impetus on AI-based research in education has mainly focused on a knowledge-based approach inherently prevalent in Intelligent Tutoring Systems employed in specific domains. The aim of this paper is to proliferate a compendious framework that classifies teaching practice with a spectrum of AIED applications and tools. The framework acts as a point of departure for teachers that envisage to use AI for enhancing the way learning and teaching is manifested. It may also serve as a blueprint for AIED developers to design AIED systems that focus on specific teaching and learning instances.

Original language	English
Title of host publication	2022 IEEE Global Engineering Education Conference (EDUCON)
Publisher	IEEE
Pages	1796-1803
Number of pages	8
ISBN (Electronic)	978-1-6654-4434-7
ISBN (Print)	978-1-6654-4435-4
DOIs	https://doi.org/10.1109/EDUCON52537.2022.9766718
Publication status	Published - 11 May 2022
Event	2022 IEEE Education Engineering - Tunis, Tunisia Duration: 28 Mar 2022 → 31 Mar 2022

Publication series

Name	IEEE Global Engineering Education Conference, EDUCON
Volume	2022-March
ISSN (Print)	2165-9559
ISSN (Electronic)	2165-9567

Conference

Conference	2022 IEEE Education Engineering
Abbreviated title	(EDUCON)
Country/Territory	Tunisia
City	Tunis
Period	28/03/22 → 31/03/22

Keywords

Artificial intelligence
Education
technology-enhanced learning

Access to Document

10.1109/EDUCON52537.2022.9766718

Post-PrintAccepted author manuscript, 851 KB

Cite this

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title = "A Vision of Teaching and Learning with AI",

abstract = "Rapid development of AI technologies with breakthroughs in algorithmic machine learning and autonomous decision making have generated unprecedented opportunities for technological innovation. There is consensus from policy report that in the next years AI could revolutionise the way teaching and learning is designed and delivered to students leading to seamless intelligent services that are more tailored to student{\textquoteright}s needs and interests. Current impetus on AI-based research in education has mainly focused on a knowledge-based approach inherently prevalent in Intelligent Tutoring Systems employed in specific domains. The aim of this paper is to proliferate a compendious framework that classifies teaching practice with a spectrum of AIED applications and tools. The framework acts as a point of departure for teachers that envisage to use AI for enhancing the way learning and teaching is manifested. It may also serve as a blueprint for AIED developers to design AIED systems that focus on specific teaching and learning instances.",

keywords = "Artificial intelligence, Education, technology-enhanced learning",

author = "Petros Lameras",

year = "2022",

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isbn = "978-1-6654-4435-4",

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publisher = "IEEE",

pages = "1796--1803",

booktitle = "2022 IEEE Global Engineering Education Conference (EDUCON)",

address = "United States",

note = "2022 IEEE Education Engineering , (EDUCON) ; Conference date: 28-03-2022 Through 31-03-2022",

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AB - Rapid development of AI technologies with breakthroughs in algorithmic machine learning and autonomous decision making have generated unprecedented opportunities for technological innovation. There is consensus from policy report that in the next years AI could revolutionise the way teaching and learning is designed and delivered to students leading to seamless intelligent services that are more tailored to student’s needs and interests. Current impetus on AI-based research in education has mainly focused on a knowledge-based approach inherently prevalent in Intelligent Tutoring Systems employed in specific domains. The aim of this paper is to proliferate a compendious framework that classifies teaching practice with a spectrum of AIED applications and tools. The framework acts as a point of departure for teachers that envisage to use AI for enhancing the way learning and teaching is manifested. It may also serve as a blueprint for AIED developers to design AIED systems that focus on specific teaching and learning instances.

KW - Artificial intelligence

KW - Education

KW - technology-enhanced learning

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U2 - 10.1109/EDUCON52537.2022.9766718

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ER -

A Vision of Teaching and Learning with AI

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

XFORMS: XFORMS: Navigating Societal Adaptation Through Cultural Spaces and Cyberspaces for Democratic Expression

Teachers’ experiences of how artificial intelligence impacts teaching and learning

Reframing Digital Capabilities in Higher Education

Cite this

A Vision of Teaching and Learning with AI

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

XFORMS: XFORMS: Navigating Societal Adaptation Through Cultural Spaces and Cyberspaces for Democratic Expression

Teachers’ experiences of how artificial intelligence impacts teaching and learning

Research output

Reframing Digital Capabilities in Higher Education

Cite this