Artificial Intelligence and Education

2011 ◽  
pp. 138-143
Author(s):  
Eduardo Sánchez ◽  
Manuel Lama
Keyword(s):  
Artificial Intelligence ◽  
Work Environment ◽  
Learning Strategies ◽  
Learning Processes ◽  
Educational Systems ◽  
Graduate Degrees ◽  
Life Long Learning ◽  
Key Factor ◽  
State Of Art ◽  
Educational Costs

Governments and institutions are facing the new demands of a rapidly changing society. Among many significant trends, some facts should be considered (Silverstein, 2006): (1) the increment of number and type of students; and (2) the limitations imposed by educational costs and course schedules. About the former, the need of a continuous update of knowledge and competences in an evolving work environment requires life-long learning solutions. An increasing number of young adults are returning to classrooms in order to finish their graduate degrees or attend postgraduate programs to achieve an specialization on a certain domain. About the later, due to the emergence of new types of students, budget constraints and schedule conflicts appear. Workers and immigrants, for instance, are relevant groups for which educational costs and job incompatible schedules could be the key factor to register into a course or to give up a program after investing time and effort on it. In order to solve the needs derived from this social context, new educational approaches should be proposed: (1) to improve and extend the online learning courses, which would reduce student costs and allows to cover the educational needs of a higher number of students, and (2) to automate learning processes, then reducing teacher costs and providing a more personalized educational experience anytime, anywhere. As a result of this context, in the last decade an increasing interest on applying computer technologies in the field of Education has been observed. On this regard, the paradigms of the Artificial Intelligence (AI) field are attracting an special attention to solve the issues derived from the introduction of computers as supporting resources of different learning strategies. In this paper we review the state-of-art of the application of Artificial Intelligence techniques in the field of Education, focusing on (1) the most popular educational tools based on AI, and (2) the most relevant AI techniques applied on the development of intelligent educational systems.

scholarly journals Artificial Intelligence and the Internet of Things in Industry 4.0

2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Razvan Nicolescu ◽  
Michael Huth ◽  
Omar Santos
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Leading Industry ◽  
Key Technologies ◽  
The Internet Of Things ◽  
State Of Art ◽  
Social Level

AbstractThis paper presents a new design for artificial intelligence in cyber-physical systems. We present a survey of principles, policies, design actions and key technologies for CPS, and discusses the state of art of the technology in a qualitative perspective. First, literature published between 2010 and 2021 is reviewed, and compared with the results of a qualitative empirical study that correlates world leading Industry 4.0 frameworks. Second, the study establishes the present and future techniques for increased automation in cyber-physical systems. We present the cybersecurity requirements as they are changing with the integration of artificial intelligence and internet of things in cyber-physical systems. The grounded theory methodology is applied for analysis and modelling the connections and interdependencies between edge components and automation in cyber-physical systems. In addition, the hierarchical cascading methodology is used in combination with the taxonomic classifications, to design a new integrated framework for future cyber-physical systems. The study looks at increased automation in cyber-physical systems from a technical and social level.

scholarly journals Conceiving Socioscientific Issues in STEM Lessons from Science Education Research and Practice

2021 ◽  
Vol 11 (5) ◽  
pp. 238
Author(s):  
Silvia Alcaraz-Dominguez ◽  
Mario Barajas
Keyword(s):  
Science Education ◽  
Learning Strategies ◽  
Teaching And Learning ◽  
Socioscientific Issues ◽  
Educational Systems ◽  
Group Discussions ◽  
Inquiry Based Learning ◽  
Teaching And Learning Strategies ◽  
Assessment Of Student Learning ◽  
Method Of Assessment

This paper aims to elicit the different conceptions of Socioscientific Issues (SSI) in formal, non-tertiary STEM lessons. An examination of recent publications in the field of science education was conducted to elicit the most common conceptions of SSI as per the components of STEM lessons, namely: purpose, contents, teaching and learning strategies and assessment. As for purpose, the conceptions elicited have been organized in terms of contributing to citizenship goals, or to scientific competence. As for contents, it was found that SSI are related both to knowledge of science and knowledge about science and linked to skills such as argumentation. In terms of teaching and learning strategies, SSI are mainly associated with Inquiry-Based Learning; and with student engagement techniques such as dilemmas and group discussions. Lastly, performance assessment of student learning processes and results is typical when SSI are conceived as a method of assessment of STEM lessons. This conception sets up strong foundations for the design and evaluation of innovative SSI teaching. It shall also help to open new lines of research establishing connections among applications of SSI in different subjects, cultural contexts and educational systems.

Self-efficacy experiences in day care and primary school from the children’s perspective: A starting point for the reflection of didactic and methodological competences of adult educators

2021 ◽  
pp. 1476718X2110511
Author(s):  
Katrin Velten
Keyword(s):  
Primary School ◽  
Self Efficacy ◽  
Day Care ◽  
Formal Education ◽  
Learning Processes ◽  
Adult Educators ◽  
Pedagogical Practice ◽  
Children’S Perspectives ◽  
Starting Point ◽  
Key Factor

This paper discusses self-efficacy as a key factor in children managing the transition to primary school, the threshold to formal education and further learning processes. In presenting results of a qualitative-longitudinal interview study of German preschool and primary school children’s perspectives on their self-efficacy experiences, it furnishes evidence for enhancing self-efficacy in pedagogical practice in a so-called mastery climate. Co-determined or self-determined opportunities for playing without adult intervention prove to be central in this to children’s self-efficacy. Following on from this, the discussion will make references to the pedagogical relevance of child-led or unsupervised play for the promotion of self-efficacy in both settings. In addition, based on the reflection of the concept of generational order, the study points to concrete starting points to focus on necessary didactic and methodological competences of adult educators for the appropriate design of child-oriented co-determined or self-determined learning settings.

Techniques, Technologies and Patents Related to Intelligent Educational Systems

2011 ◽  
pp. 1-28
Author(s):  
Jim Prentzas ◽  
Ioannis Hatzilygeroudis
Keyword(s):  
Artificial Intelligence ◽  
Learning Systems ◽  
Future Research ◽  
Educational Systems ◽  
Learner Characteristics ◽  
Tutoring Systems ◽  
Artificial Intelligence Methods ◽  
E Learning ◽  
Future Research Directions ◽  
Intelligent Methods

E-learning systems play an increasingly important role in lifelong learning. Tailoring the learning process to individual needs is a key issue in such systems. Intelligent Educational Systems (IESs) are e-learning systems employing Artificial Intelligence methods to effectively adapt to learner characteristics. Main types of IESs are Intelligent Tutoring Systems (ITSs) and Adaptive Educational Hypermedia Systems (AEHSs) incorporating intelligent methods. In this chapter, the authors present technologies and techniques used in the primary modules of IESs and survey corresponding patents. They present issues and problems involving specific IES modules as well as the overall IES. The authors discuss solutions offered for such issues by Artificial Intelligence methods and patents. They also discuss categorization aspects of patents related to IESs and briefly present the work described in some representative patents. Lastly, the authors outline future research directions regarding IESs.

The Impact of the Work Environment on Innovation and Business Sustainability in SMEs

2021 ◽  
pp. 133-156
Author(s):  
Rafael Ignacio Pérez-Uribe ◽  
Solange Dianira Jordan Bustamante ◽  
Carlos Salcedo -Perez
Keyword(s):  
Organizational Climate ◽  
Work Environment ◽  
Interpersonal Relationships ◽  
Business Sustainability ◽  
Key Factor ◽  
The Face ◽  
The Impact ◽  
The Relationship ◽  
The City ◽  
Innovation Processes

Innovation is a process, where the interpersonal relationships of employees are key to the creation of ideas that will contribute to the generation of value for organizations in the face of disruptive environments. This chapter analyzes the relationship between the work environment as a key factor and its impact on the development of innovation processes and business sustainability, taking as a sample 182 SMEs, from commercial, footwear, and textile sectors from the city of Cúcuta. The results showed an interrelation between the organizational climate and the culture of innovation as an agent that generates change that contributes to business sustainability.

scholarly journals A technologist view of the next decade evolution of the librarian work environment

2018 ◽  
Vol 186 ◽  
pp. 09004
Author(s):  
André Schaaff ◽  
Marc Wenger
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Work Environment ◽  
New Technologies ◽  
State Of The Art ◽  
Working Environment ◽  
Online Resources ◽  
Mining Machine ◽  
Daily Work

The work environment has deeply evolved in recent decades with the generalisation of IT in terms of hardware, online resources and software. Librarians do not escape this movement and their working environment is becoming essentially digital (databases, online publications, Wikis, specialised software, etc.). With the Big Data era, new tools will be available, implementing artificial intelligence, text mining, machine learning, etc. Most of these technologies already exist but they will become widespread and strongly impact our ways of working. The development of social networks that are "business" oriented will also have an increasing influence. In this context, it is interesting to reflect on how the work environment of librarians will evolve. Maintaining interest in the daily work is fundamental and over-automation is not desirable. It is imperative to keep the human-driven factor. We draw on state of the art new technologies which impact their work, and initiate a discussion about how to integrate them while preserving their expertise.

Applications of artificial intelligence in the apparel industry: a review

2011 ◽  
Vol 81 (18) ◽  
pp. 1871-1892 ◽  
Author(s):  
ZX Guo ◽  
WK Wong ◽  
SYS Leung ◽  
Min Li
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Apparel Industry ◽  
Apparel Design ◽  
Research Issues ◽  
Chain Management ◽  
Research Challenges ◽  
State Of Art

This paper presents a systematic review on the state-of-art of artificial intelligence (AI) applications in the apparel industry. The existing literature is reviewed based on different research issues and AI-based methodologies. The research issues are categorized into four categories on the basis of the operation processes of the apparel industry, including apparel design, manufacturing, retailing, and supply chain management. This paper shows that research on AI applications in the apparel industry is still limited by analyzing the limitations of previous studies and research challenges. Finally, suggestions for further studies are offered.

scholarly journals Artificial Intelligence-Enhanced Predictive Insights for Advancing Financial Inclusion: A Human-Centric AI-Thinking Approach

2020 ◽  
Vol 4 (2) ◽  
pp. 8 ◽  
Author(s):  
Meng-Leong How ◽  
Sin-Mei Cheah ◽  
Aik Cheow Khor ◽  
Yong Jiet Chan
Keyword(s):  
Artificial Intelligence ◽  
World Bank ◽  
Poverty Reduction ◽  
Service Providers ◽  
Financial Inclusion ◽  
Social Good ◽  
Financial Products ◽  
The World Bank ◽  
Key Factor ◽  
Legacy Data

According to the World Bank, a key factor to poverty reduction and improving prosperity is financial inclusion. Financial service providers (FSPs) offering financially-inclusive solutions need to understand how to approach the underserved successfully. The application of artificial intelligence (AI) on legacy data can help FSPs to anticipate how prospective customers may respond when they are approached. However, it remains challenging for FSPs who are not well-versed in computer programming to implement AI projects. This paper proffers a no-coding human-centric AI-based approach to simulate the possible dynamics between the financial profiles of prospective customers collected from 45,211 contact encounters and predict their intentions toward the financial products being offered. This approach contributes to the literature by illustrating how AI for social good can also be accessible for people who are not well-versed in computer science. A rudimentary AI-based predictive modeling approach that does not require programming skills will be illustrated in this paper. In these AI-generated multi-criteria optimizations, analysts in FSPs can simulate scenarios to better understand their prospective customers. In conjunction with the usage of AI, this paper also suggests how AI-Thinking could be utilized as a cognitive scaffold for educing (drawing out) actionable insights to advance financial inclusion.

Employees’ perceptions of barriers to participation in training and development in small engineering businesses

2015 ◽  
Vol 27 (7) ◽  
pp. 561-578 ◽  
Author(s):  
Pattanee Susomrith ◽  
Alan Coetzer
Keyword(s):  
Work Environment ◽  
Learning Strategies ◽  
Small Businesses ◽  
Employee Participation ◽  
Training And Development ◽  
Future Research ◽  
Formal Training ◽  
Content Type ◽  
Industry Sector ◽  
Proactive Behaviour

Purpose – This paper aims to investigate barriers to employee participation in voluntary formal training and development opportunities from the perspective of employees in small engineering businesses. Design/methodology/approach – An exploratory qualitative methodology involving data collection via site visits and in-depth semi-structured interviews with 20 employees in five small engineering businesses was used. Interviews explored the role of developmental proactivity and employees’ perceptions of conditions in the immediate work environment and industry sector that represent barriers to their participation in formal training and development. Interview transcripts were analysed using thematic analysis. Findings – Three key findings are as follows. First, proactive behaviour regarding access to external training and development is muted in small business settings because of strong resource allocation norms. Second, factors in the internal work environment rather than the industry sector constitute the major barriers to training and development. Third, owner-managers and employees appear to have significantly differing perspectives of barriers to training and development. Research limitations/implications – The findings suggest avenues for future research. These include examining how workplace norms influence employee behaviour with regard to accessing formal training and development and investigating the learning strategies that employees use to compensate for a lack of access to training and development. Originality/value – Research into relatively low levels of employee participation in formal training and development in small businesses is deficient because it predominantly involves surveys of owner-managers’ opinions. This study is novel because it seeks to generate new insights not previously articulated by employees. The study yielded four propositions that have practical and research implications.

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