scholarly journals Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education

Information ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Petros Lameras ◽  
Sylvester Arnab
Keyword(s):  
Artificial Intelligence ◽  
Data Analysis ◽  
Teaching And Learning ◽  
Data Driven ◽  
Synthesis Process ◽  
Analysis And Synthesis ◽  
Analysis Strategy ◽  
Artificial Intelligence In Education ◽  
The Impact ◽  
Meaningful Data

This exploratory review attempted to gather evidence from the literature by shedding light on the emerging phenomenon of conceptualising the impact of artificial intelligence in education. The review utilised the PRISMA framework to review the analysis and synthesis process encompassing the search, screening, coding, and data analysis strategy of 141 items included in the corpus. Key findings extracted from the review incorporate a taxonomy of artificial intelligence applications with associated teaching and learning practice and a framework for helping teachers to develop and self-reflect on the skills and capabilities envisioned for employing artificial intelligence in education. Implications for ethical use and a set of propositions for enacting teaching and learning using artificial intelligence are demarcated. The findings of this review contribute to developing a better understanding of how artificial intelligence may enhance teachers’ roles as catalysts in designing, visualising, and orchestrating AI-enabled teaching and learning, and this will, in turn, help to proliferate AI-systems that render computational representations based on meaningful data-driven inferences of the pedagogy, domain, and learner models.

scholarly journals Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education

2021 ◽  
Vol 13 (14) ◽  
pp. 7941
Author(s):  
Seungsu Paek ◽  
Namhyoung Kim
Keyword(s):  
Artificial Intelligence ◽  
Evaluation System ◽  
Teaching And Learning ◽  
Latent Dirichlet Allocation ◽  
Research Trends ◽  
Dramatic Rise ◽  
Artificial Intelligence In Education ◽  
Current Impact ◽  
Future Direction ◽  
The Impact

In today’s world, artificial intelligence (AI) and human intelligence coexist, and no field is free from the impact of AI. At present, education cannot be discussed without mentioning AI, which has an omnidirectional impact on all its areas, including the purpose, content, method, and evaluation system. This study aimed to explore the future direction of education by examining the current impact and predicting future impacts of AI. It also examined research trends and collaboration status by country through network analysis, topic modeling and global research trends in AI in education (AIED), by applying the Latent Dirichlet Allocation algorithm. Over the past 20 years, the number of papers on AIED has steadily increased, with a dramatic rise since 2015. The research can be broadly classified into eight topics, including “changes in the content of teaching and learning.” Using a linear regression model, three hot topics, two cold topics and trend changes for each research topic were identified. The study found that AIED research should be more thematically diversified and in-depth; this directly applies AI algorithms and technologies to education, which should be further promoted. This study provides a reference for exploring the direction of future AIED research.

Teaching and Learning With Artificial Intelligence

2021 ◽  
pp. 73-98
Author(s):  
Libi Shen ◽  
Irene Chen ◽  
Anne Grey ◽  
Anchi Su
Keyword(s):  
Artificial Intelligence ◽  
Teaching And Learning ◽  
Learning Assessment ◽  
Modern World ◽  
Learning And Teaching ◽  
Curriculum Assessment ◽  
Education Major ◽  
Fast Speed ◽  
Artificial Intelligence In Education ◽  
Teaching Learning

Artificial intelligence (AI) is developing at a fast speed and has incessantly impacted the modern world for decades. AI technologies are beneficial for all kinds of industries, including businesses, economics, transportation, hospitals, schools, universities, and so forth. Many researchers have investigated the development of artificial intelligence in education (AIEd), specifically on how AI assists teaching, learning, assessment, references, and collaboration. Several questions arise. What impact do AI technologies have on education? How do AI technologies assist teaching (e.g., curriculum, assessment, student learning, and teaching practices)? How do teachers cope with AI Technologies in education? What are the ethical concerns of AI technologies? What are the barriers of AI-based learning in education? The purpose of this chapter is to explore the evolution and the challenges of AI technologies in education. Major research on AI from 1999 to 2019 will be reviewed. Problems with AI in education will be raised and solutions for solving the issues will be recommended.

The Use of a WhatsApp Record for Communication With Students

2021 ◽  
pp. 310-325
Author(s):  
Leslie Chiuswa ◽  
Alex Sibanda
Keyword(s):  
Data Analysis ◽  
Teaching And Learning ◽  
The Other ◽  
Mixed Methodology ◽  
Internet Connectivity ◽  
Qualitative And Quantitative ◽  
Regional Campus ◽  
The University ◽  
The Impact ◽  
Quantitative Approaches

The purpose of this study was to explore the impact of WhatsApp usage in disseminating information to students at the Management, Zimbabwe Open University's Mashonaland West Regional Campus. This study employed a mixed methodology wherein both the qualitative and quantitative approaches were used. Data was collected using questionnaires and interviews. The questionnaires were distributed to students through WhatsApp groups for all faculties. A total of 255 questionnaires were distributed to students through the existing WhatsApp groups. Of the distributed questionnaires, 128 were returned, and of these, 69 were usable for data analysis. The study revealed that the majority of students utilize WhatsApp for communication with the university. The other finding was that WhatsApp communication was characterized by data bundle costs and internet connectivity challenges. The study recommended that there be a WhatsApp policy and widening of the use for teaching and learning.

THE IMPACT OF ARTIFICIAL INTELLIGENCE IN THE LEGISLATIVE PROCESS ON HUMAN RIGHTS

2020 ◽  
Vol 10 (4) ◽  
pp. 70-75
Author(s):  
TOMAS MOLODTSOV ◽  
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
Legislative Process ◽  
Additional Measure ◽  
Human Rights Protection ◽  
Methods Of Analysis ◽  
Analysis And Synthesis ◽  
Definition Of ◽  
Automation Tools ◽  
The Impact

The article is devoted to the definition of artificial intelligence and its impact on human rights in the context of lawmaking activity. Purpose of the article: this paper aims to investigate the main approaches to understanding artificial intelligence and the consequences of its integration into the legislative process, as well as to assess the impact of artificial intelligence on human rights. The purpose of the article is also to identify the risks of such influence and ways to level them. Methodology and methods: this article uses general scientific methods of analysis, especially empirical and dialectical, which allow to consider raised issues comprehensively. The author also uses methods of analysis and synthesis, induction and deduction. Conclusions: as the result of this research, the author comes to the conclusion that artificial intelligence, understood as both an exclusively automated tool and a pure consciousness, can significantly optimize the current lawmaking system. However, its impact on human rights in this context may be negative, limiting the freedom of choice, privacy and secrecy of correspondence. To protect human rights, the author recommends using automation tools only as additional measure, but not as substitute. The conclusion raises the question of what consequences can occur for people if artificial intelligence, integrated into law-making activities, can become aware of itself. Scope of the results: this work can be interested to both lawmakers and society as a whole, as it raises basic issues of human rights protection in the context of global digitalization.

Artificial Intelligence in Education

2020 ◽  
Vol 8 (3) ◽  
pp. 49-56
Author(s):  
Vassya Likova-Arsenova
Keyword(s):  
Artificial Intelligence ◽  
Policy Development ◽  
High Technology ◽  
Educational Programs ◽  
Point Of View ◽  
Ethical Challenges ◽  
Artificial Intelligence In Education ◽  
Effective Policy ◽  
The Impact ◽  
And Training

The article examines the impact of Information Technology (IT) and Artificial Intelligence (AI) in education, the joint design of working with high technology and the need for effective policy development. The use of AI in education is an important topic for teachers from both a conceptual and a practical point of view. Ethical challenges in the training and working with AI are on the agenda. It is necessary to adapt the educational programs for future pedagogues in regards to implementing AI in teaching and training.

scholarly journals Demystification of Artificial Intelligence in Education – How much AI is really in the Educational Technology?

2020 ◽  
Vol 2 (1) ◽  
pp. 14 ◽  
Author(s):  
André Renz ◽  
Swathi Krishnaraja ◽  
Elisa Gronau
Keyword(s):  
Artificial Intelligence ◽  
Educational Technology ◽  
Learning Analytics ◽  
Public Discourse ◽  
Business Models ◽  
Data Driven ◽  
Current Status ◽  
Causal Connection ◽  
Artificial Intelligence In Education ◽  
The Relationship

<span lang="EN-US">The data-driven development of education through Learning Analytics in combination with Artificial Intelligence is an emerging field in the education sector. In the field of Artificial Intelligence in Education, numerous studies and research have been carried out over the past 60 years, and since then drastic changes have taken place. In the first part of this paper we present a brief overview of the current status of Learning Analytics and Artificial Intelligence in education. In order to develop a better understanding of the relationship between Learning Analytics and Artificial Intelligence in education, we outline the relationship between the two phenomena. The results show that the previous studies only vaguely distinguish between them: the terms are often used synonymously. In the second part of the paper we focus on the question why the European market currently has hardly any real applications for Artificial Intelligence in education. The research is based on a meta-investigation of data-driven business models, in particular the so-called Educational Technology providers. The core of the analysis is the question of how data-driven these companies really are, how much Learning Analytics and Artificial Intelligence is applied and whether there is a causal connection between the growth of the Educational Technology market and the application relevance of Artificial Intelligence in Education. In the scientific and public discourse, we can observe a distortion between the theoretical-conjunctive understanding of the application of Artificial Intelligence in Education and the current practical relevance.</span>

scholarly journals eBook Technology Facilitating University Education During COVID-19: Japanese Experience

2021 ◽  
Vol 47 (4) ◽  
Author(s):  
Rwitajit Majumdar ◽  
Brendan Flanagan ◽  
Hiroaki Ogata
Keyword(s):  
Artificial Intelligence ◽  
Management System ◽  
Teaching And Learning ◽  
University Education ◽  
Learning Materials ◽  
Japanese Experience ◽  
Reading Materials ◽  
National University ◽  
Artificial Intelligence In Education ◽  
University Level

UNESCO reported that 90% of students are affected in some way by COVID-19 pandemic. Like many countries, Japan too imposed emergency remote teaching and learning at both school and university level. In this study, we focus on a national university in Japan, and investigate how teaching and learning were facilitated during this pandemic period using an ebook platform, BookRoll, which was linked as an external tool to the university’s learning management system. Such an endeavor also reinforced the Japanese national thrust regarding explorations of e-book-based technologies and using Artificial Intelligence in education. Teachers could upload reading materials for instance their course notes and associate an audio of their lecture. While students who registered in their course accessed the learning materials, the system collected their interaction logs in a learning record store. Across the spring semesters from April - July 2020, BookRoll system collected nearly 1.5 million reading interaction logs from more than 6300 students across 243 courses in 6 domains. The analysis highlighted that during emergency remote teaching and learning BookRoll maintained a weekly average traffic above 1,900 learners creating more than 78,000 reading logs and teachers perceived it as useful for orchestrating their course.

scholarly journals A Review on Artificial Intelligence in Education

2021 ◽  
Vol 10 (3) ◽  
pp. 206
Author(s):  
Jiahui Huang ◽  
Salmiza Saleh ◽  
Yufei Liu
Keyword(s):  
Artificial Intelligence ◽  
Education Reform ◽  
Adaptive Learning ◽  
Teaching And Learning ◽  
Rapid Development ◽  
Virtual Classroom ◽  
Teaching Evaluation ◽  
Innovative Technologies ◽  
Artificial Intelligence In Education ◽  
Positive Meaning

The emergence of innovative technologies has an impact on the methods of teaching and learning. With the rapid development of artificial intelligence (AI) technology in recent years, using AI in education has become more and more apparent. This article first outlines the application of AI in the field of education, such as adaptive learning, teaching evaluation, virtual classroom, etc. And then analyzes its impact on teaching and learning, which has a positive meaning for improving teachers' teaching level and students' learning quality. Finally, it puts forward the challenges that AI applications may face in education in the future and provides references for AI to promote education reform.   Received: 16 January 2021 / Accepted: 24 March 2021 / Published: 10 May 2021

scholarly journals Artificial Intelligence Based Structural Assessment for Regional Short- and Medium-Span Concrete Beam Bridges with Inspection Information

2021 ◽  
Vol 13 (18) ◽  
pp. 3687
Author(s):  
Ye Xia ◽  
Xiaoming Lei ◽  
Peng Wang ◽  
Limin Sun
Keyword(s):  
Artificial Intelligence ◽  
Structural Characteristics ◽  
Highway Bridges ◽  
Condition Assessment ◽  
Transport Infrastructure ◽  
Data Driven ◽  
Bridge Inspection ◽  
Structural Deterioration ◽  
Data Driven Approach ◽  
The Impact

The functional and structural characteristics of civil engineering works, in particular bridges, influence the performance of transport infrastructure. Remote sensing technology and other advanced technologies could help bridge managers review structural conditions and deteriorations through bridge inspection. This paper proposes an artificial intelligence-based methodology to solve the condition assessment of regional bridges and optimize their maintenance schemes. It includes data integration, condition assessment, and maintenance optimization. Data from bridge inspection reports is the main source of this data-driven approach, which could provide a substantial amount og condition-related information to reveal the time-variant bridge condition deterioration and effect of maintenance behaviors. The regional bridge condition deterioration model is established by neural networks, and the impact of the maintenance scheme on the future condition of bridges is quantified. Given the need to manage limited resources and ensure safety and functionality, adequate maintenance schemes for regional bridges are optimized with genetic algorithms. The proposed data-driven methodology is applied to real regional highway bridges. The regional inspection information is obtained with the help of emerging technologies. The established structural deterioration models achieve up to 85% prediction accuracy. The obtained optimal maintenance schemes could be chosen according to actual structural conditions, maintenance requirements, and total budget. Data-driven decision support can substantially aid in smart and efficient maintenance planning of road bridges.

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