Students‘ well-being and teaching-learning efficiency during and post-pandemic period
Alina Monica Costin (Volume editor)
Henrietta Torkos (Volume editor)
Editha COȘARBĂ (Volume editor)
Summary
Excerpt
Table Of Contents
- Cover
- Title
- Copyright
- About the author
- About the book
- This eBook can be cited
- Table of Contents
- Artificial intelligence (AI) – retrospectives and prospectives: A multidimensional analysis
- Well-being and happiness of children, adolescents, and young people in post-pandemic period
- The relationship between learning and well-being: An integrative framework process approach
- Developing the well-being of students by using ludic and dramatic methods in the teaching-learning-assessment process
- The influence of student participation on nonformal activities at school performance
- The Romanian students’ perceptions of digital learning and its consequences on learning efficiency: A qualitative study
- Technology acceptance theories in students’ learning contexts
- Achieving well-being in primary school, by enrolling in outdoor learning situations
- Experiences and attitudes of teenage gamers in relation to school results, seen through the eyes of eighth-grade students in Bihor County, during the COVID-19 pandemic: A qualitative study
- From classical assessment to formative assessment in academic education
- A reflective view to quality in early education today
- Loneliness and well-being on social networks
- An analysis of the impact the pandemic had on children with disabilities
- A network analysis on the students’ sense of belonging on grit: Implications for student’s well-being
- Grandparents–grandchildren relationships
- Assessment of motor skills by jump tests: A comparative analysis
Mușata-Dacia BOCOȘ PhD University Professor and Ciprian BACIU PhD University Lecturer
Babeș-Bolyai University of Cluj-Napoca
musata.bocos@yahoo.com, ciprian.baciu@ubbcluj.ro
Artificial intelligence (AI) – retrospectives and prospectives: A multidimensional analysis
Keywords: artificial intelligencemultidimensional analysisAbstract: Currently, AI is a scientific branch centered on a complex, dynamic, and evolving concept with applications in all areas of human activity. In the technological field, the implementation of AI in computer systems aims to develop intelligent machines that can think like humans and imitate human cognitive and noncognitive behaviors as much as possible, and even appropriate these behaviors.
Introduction
Artificial intelligence (AI) represents a field of research in computer science, regarding the study of ideas that allow computers to be intelligent through the development of specific programs (Bocoş (coord.) et al., 2020). This branch of computer science deals with the implementation of computer systems/programs with capabilities specific to human intelligence, for example, recognition of speech, objects, text, and human faces.
Artificial intelligence is a feature of an artificial system, which allows it to learn, with or without external help, with the aim of constantly improving itself, in order to more faithfully reproduce the behavior of naturally intelligent systems.
Currently, there are two major distinguishable directions in the development of artificial intelligence, with different objectives and methodologies:
- Designing computer systems that perform well in problem-solving, by any means possible. According to this direction, the study of human (expert) behavior in problem-solving situations can be a source of inspiration for finding good heuristics and for creating effective programs;
- Designing systems to model human behavior (expert or not) in relation to cognitive psychology studies. The motivations of this direction refer to the test of psychological models or the realization of interactive support systems in solving problems and education support systems (Doron & Parot, 2007/2008).
Currently, AI is a scientific branch centered on a complex, dynamic, and evolving concept with applications in all areas of human activity. In the technological field, the implementation of AI in computer systems aims to develop intelligent machines that can think like humans and imitate human cognitive and noncognitive behaviors as much as possible, and even appropriate these behaviors.
The concept of AI in multidimensional analysis
We aim to carry out an analysis of the concept of AI taking into account several dimensions and analytical criteria, including criteria specific to the educational field. Through this analysis, we aim to support the transposition of the concept in educational sciences, the realization of specific applications, as well as prospecting in the field.
We opted for a tabular presentation of the ideas, with the aim of organizing, structuring, and correlating the information, in order to facilitate reading, understanding, and active retrieval.
| Criterion | AI |
|---|---|
| The nature of the scientific branch | – it is a creative field, referential for the progress of mankind, by which it is desired to give the ability of rational thinking to machines and the ability to reproduce cognitive and noncognitive behaviors – involves (re)building a system of human values (social, educational, ethical, moral, etc.), assimilating and promoting them – it is an opportunity for our societies to become more socially, legally, and environmentally fair and sustainable through regulatory systems of public scrutiny and control (Voss, 2020) |
| Development rationale (finalist perspective) | – is to build systems that reason/think and feel (have emotions, feelings, states) and that become capable of learning as they evolve and interact with the external environment, constantly adapting; thus, these systems become aware of their own existence, to the point of having their own consciousness and developing their own decisions, independently |
| Development rationale (action perspective) | – is to build systems that act and become capable of learning and adapting, ever better – which may give birth to bioinspired artificial neural networks |
| Way of thinking and acting | – is coherent, logical, and rational, that is, close to the efficient human way of thinking, based on efficient computing algorithms |
| From a structural point of view | – it involves building systems based on intelligent agents as structural elements – structural components to meet certain standards: (a) in terms of thinking to (at least) match the performance of human thinking (the desire is to create systems that exceed the level of human thinking – also see superintelligence) (b) in terms of the efficiency of actions, to exceed the capabilities of human actions, both in terms of efficiency, real-time adaptability, durability, but also in terms of accuracy |
| The behavioral perspective | – it aims to automate intelligent action behaviors so that they can be reproduced, multiplied, and made more efficient, permanently |
| The quality of behaviors perspective | – tends toward – the formation and development of desirable, perfectly rational, and coherent action behaviors – reducing or excluding undesirable action behaviors |
| Time perspective | – possess the ability to reason, act and react correctly, quasi-instantaneously – in real time |
| The central ability for intelligence | – reading, which ensures the knowledge base: (a) heteronomous (systems acquire knowledge and learn by coding and inserting/entering it manually by humans) (b) autonomous (systems acquire knowledge and learn, without external human support, with the help of sensors, from the outside, by scanning a certain environment, by using self-feedback in order to improve the learning process) |
| “Two points deserve to be made about machine reading. First, it may not be clear to all readers that reading is an ability that is central to intelligence. The centrality derives from the fact that intelligence requires vast knowledge.” (Selmer & Govindarajulu, 2022) | |
| The computer ideal | – consists in the development of super-evolved systems, called superintelligent systems (ASI), reaching those that are aware of their own existence, as well as of others (humans or other machines), with their own cognitive and noncognitive behaviors (Bostrom, 2019; Bostrom & Bosted, 2020, Vinge, 1993) – AI and ASI systems must ensure a high level of individual and collective well-being, through ways of developing, implementing, and using them reliably, respecting the following principles (Grupul independent de experți la nivel înalt privind inteligența artificială, 2019): (a) respect for people’s autonomy – respect for fundamental rights, freedom, privacy, etc. of people (b) damage prevention – avoiding negative impact on humans and the environment; not to cause damage and danger to people, other beings, and machines (c) fairness: – the concrete dimension – involves a commitment to ensure the equal and fair distribution of both benefits and costs; to avoid unfairly biased judgments, discrimination, and stigmatization; – the procedural dimension – involves the ability to effectively challenge and challenge decisions made by AI systems and users (d) explainability – processes and decisions must be transparent, and the purpose, behaviors, capabilities, and risks of AI systems must be openly communicated to avoid undesirable situations. The idea of the emergence of ultra-intelligent machines was formulated by Good in 1965. “Let an ultra-intelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever.” (Good, 1966, p. 33) |
| The educational/pedagogical ideal | – to ensure human training under the conditions of the rational exploitation of AI (with, through, and for AI), with respect and responsibility toward man and toward the social and natural environment, in the perspective of sustainable development of society – to offer the possibility of collaborative learning mediated by agents of artificial intelligence, by intelligent guidance systems – to provide the possibility of personalized learning, mediated by artificial intelligence agents, which design learning paths – provide disadvantaged individuals and communities, people with disabilities, refugees, those in schools, and those living in isolated communities with equitable and inclusive access to appropriate learning and educational opportunities (Grupul independent de experți la nivel înalt privind inteligența artificială, 2019). |
| The aesthetic ideal | (a) from the point of view of the development of machines: the development of machines that can perceive, evaluate, and create artistic, social, and natural beauty (b) from the point of view of the design of equipment, and systems: ensuring aesthetic requirements and ergonomic requirements |
| Ethical ideal | – a formal regulatory framework is needed to define the principles and ethical requirements that must be taken into account in the design, development, implementation, and operation of AI-based technologies – from access to data to strict control of results: (a) from the point of view of the development of machines: – the creation of machines that respect the principles, standards, and moral norms of society – connecting all design phases within the life cycle of AI-based systems to moral and ethical principles |
| – the design should be carried out in such a way as to enhance, complement, and enable the development of people’s cognitive, social, and cultural competences – to respect design principles in allocating functions for humans and AI systems: – human centeredness – providing a significant choice of system facilities (by human factor) – ensuring human supervision – ensuring human control regarding work processes in AI systems for their safe management – the justified support of people in the work environment through necessary and significant activities to help them – the imposition of performance standards that provide certain guarantees that future developments can be kept under control by the human factor (b) from the point of view of the use of machines by humans: – not to be irresponsible from the point of view of the development, use, and exploitation of AI – not to violate human privacy – not to discriminate based on any criteria (c) from the point of view of the autonomous operation of the machines: – not to cause or exacerbate damage, and not to adversely affect people – not to violate human privacy – not to endanger humans and society – to maintain human control over the machine | |
| Moral/civic-moral ideal | – promoting the “man-centered approach,” in which the person benefits from a unique and inalienable moral status of supremacy in the civil, political, economic, and social sphere – respect for fundamental human rights, which “are described in the EU Charter by reference to dignity, freedoms, equality and solidarity, citizens’ rights and justice.” |
| – “respect for human dignity implies that all people are treated with the respect they deserve as moral subjects and not just objects to be selected, sorted, graded, herded, conditioned, or manipulated. So, AI systems should be developed in a way that respects, serves, and protects people’s physical and mental integrity, their personal and cultural sense of identity, and the satisfaction of their essential needs.” (Grupul independent de experți la nivel înalt privind inteligența artificială, 2019, p. 12) | |
| Life ideal | – AI systems should be put at the service of human well-being (individual and social), respectively of a positive, desirable state of health, on the following dimensions: physical, material, social, psychological, and emotional – the state of well-being as well as the state of health are directly related to the quality of life, which is an index of human development – the awareness that well-being is, to a large extent, in our control and that it can be improved with the support of AI systems |
Such qualitative and quantitative analyses, with the aim of description, clarification, explanation, and above all prediction, will shortly become increasingly necessary to ensure progress in the various fields of human activity, as shown by the authors of a survey carried out recently (2022 Expert Survey on Progress in AI, 2022).
Predictions, developments, perspectives, possible outcomes, and questions
Specialists ask themselves questions related to the technological singularity (Baciu et al., 2015; Bostrom, 2019; Bostrom & Bosted, 2020; Schwab, 2016; Vikulov, 2021; Vinge, 1993) – a concept from the field of futurology, which appeared due to rapid technological progress, digitalization and numerous paradigmatic social changes.
It is predicted that there will be a fusion of artificial intelligence with human intelligence, hence the term singularity (common influences). Advanced and accessible artificial intelligence will be a partner, a friend, and an extension of human intelligence.
We are facing a new revolution – the fourth industrial revolution (4IR). This concept was enshrined in 2016 by the engineer, professor, and economist Klaus Schwab, founder and executive chairman of the World Economic Forum, at the Davos forum, as well as in the book entitled “The Fourth Industrial Revolution.” Even if some of the specific technologies of 4IR were invented before the consecration of this new concept, the year 2016 can be considered the birth year of the fourth industrial revolution.
“I believe that today we are at the beginning of a fourth industrial revolution.” (Schwab, 2016, pp. 11–12)
Details
- Pages
- 272
- Publication Year
- 2023
- ISBN (PDF)
- 9783631901946
- ISBN (ePUB)
- 9783631901953
- ISBN (Softcover)
- 9783631899663
- DOI
- 10.3726/b20818
- Language
- English
- Publication date
- 2023 (August)
- Keywords
- Educational Sciences Psychology Technology acceptance Sustainable wellbeing Outdoor learning
- Published
- Berlin, Bern, Bruxelles, New York, Oxford, Warszawa, Wien, 2023. 272 pp., 30 fig. b/w, 18 table.
Biographical notes
Alina Roman (Volume editor)
Evelina Balaș (Volume editor)
Tiberiu Dughi (Volume editor)
Dana Rad (Volume editor)
Alina Monica Costin (Volume editor)
Henrietta Torkos (Volume editor)
Editha COȘARBĂ (Volume editor)
Evelina Balas, Ph.D., is an associate professor at the Faculty of Educational Sciences, Psychology and Social Sciences at Aurel Vlaicu University of Arad, Romania and Head of the Sociopsychopedagogical Research Center for Promoting Excellence in the Profession. Evelina is an educational and pedagogy specialist and a principal investigator in multiple European Union-funded projects on the topic of education for all ages. Alina Roman, Ph.D., is a professor habil. at Faculty of Educational Sciences, Psychology and Social Sciences at Aurel Vlaicu University of Arad, Romania and Dean of the Faculty of Educational Sciences, Psychology and Social Sciences. Her areas of interest include digital wellbeing, educational assessment, interactive strategies in the teaching and learning process and the efficiency of didactic activities outdoor. Dana Rad, Ph.D., is an associate professor at Aurel Vlaicu University of Arad, Romania and the head of the Center of Research, Development and Innovation in Psychology. Her areas of interest include digital wellbeing, organizational psychology, psychoinformatics and cognitive systems engineering.
