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Artificial intelligence (AI) is becoming slowly but permanently a vital component at all levels of education: i.e. with the help of modern ICT-technology and easily accessible multiple internet-based devises, the AIs assist school-children, students and working adults in developing their knowledge in a “personalised way”. New technologies and solutions that have already emerged during the pandemic are making the educational process easier.
However, teaching remains complex social interaction that requires authentic human skills (such as empathy); these and other skills would hardly be substituted by a PC in a near future. Hence, teachers are not going to be replaced by AIs; they would be just assisted to make the whole education process more effective and sustainable. Emergence of online schools, start-up colleges and numerous online platforms is impossible without AIs.
More and more university audiences and classes are connected to internet and ICT devices: students can be linked-on from homes while administrators cooperate with students through various apps and new software. Hence, after two years of the pandemic, innovators in education have learned to combine ICTs with the learning schemes.
Some experts have shown at least three outcomes of such “adaptations”: first, the quick adaption to constantly changing market and technological conditions is the best way to meet students’ needs over the long term. The key elements of a new “academic model” can include experiential learning, entrepreneurship, integration of theory and practice in the courses and digitalisation.
Second, flexible educators’ skills shall be preferable in delivering various education/training courses to enable universities to survive at exponential challenges in educational blocks to concentrate on most urgent problem-solving issues, adaptability, creativity and sustainable growth. Third, utilizing “robust technology toolsets” and advanced ICTs (including AI) is aimed at delivering optimal educational experience to students, as well as “implanting” in the education process such technologies that assist design-thinking for the next-generation’s problem-solving, as well as “augmented and virtual reality for immersive learning and advances in neuroscience to fuel better understanding when it comes to rapid skills development”.
Source and citation: https://www.universityworldnews.com/post.php?story=20220614100738763
European initiatives
The European Digital Education Action Plan (2021-2027) represents an EU-wide policy to support the sustainable and effective adaptation of the member states’ education and training systems to the digital age. Thus, the Action Plan sets out 13 actions in 2 priority areas: a) fostering the development of a high-performing digital education ecosystem, and b) enhancing digital skills and competences for the digital transformation in the education sector.
For example, under priority 1(action 6), an expert group was developing AIs ethical guidelines and data-usage in education and training (based on the Ethics Guidelines for Trustworthy Artificial Intelligence, presented by the High-Level Expert Group on AI in 2019). Under priority 2 (action 7), an expert group has been developing common guidelines for teachers and educators to foster digital literacy and tackle disinformation through education and training. The guidelines’ total set is expected to be ready in September 2022. The European Commission has also adopted in 2017 a Communication on strengthening European identity through education and culture; the communication was a contribution to the EU leaders’ meeting on education and culture at the Gothenburg summit; some practical actions have to be adopted by 2025.
Source: https://digital-strategy.ec.europa.eu/en/policies/digital-learning.
In June 2021, the European Commission published a report analysing national AI strategies and providing suggestions for future developments; the report was commissioned in tandem between the OECD and the European Commission Joint Research Centre. The report titled “National Strategies on Artificial Intelligence: A European Perspective” focuses on areas of cooperation in: – strengthening AI education and skills; – supporting research and innovation to drive AI developments into successful products and services, improving collaboration and networking; – creating a regulatory framework to address the ethics and trustworthiness of AI systems; and – establishing a cutting-edge data ecosystem and ICT infrastructure.
Additionally, an important aspect of the report dealt with the post-pandemic sustainability issues, including environmental protection and climate change to be included in the updated national strategies. The report also provides an overview of the national competence centers in AI research and presents policies to promote data access and sharing as well as actions to stimulate the use of AI in public services.
Reference to: https://digital-strategy.ec.europa.eu/en/news/new-report-looks-ai-national-strategies-progress-and-future-steps.
In August 2021, Commission proposed for the Council a recommendation on “blended learning” to support high quality and inclusive primary and secondary education; the term “blended learning” in formal education and training is used to describe a process when a school, educator or student takes more than one approach to learning. It can be a blend of school site and other physical environments (companies, training centers, distance learning, outdoor, cultural sites, etc.), or blending different learning tools that can be digital and non-digital.
Thus, blended learning can help to improve the inclusiveness of education, particularly due to its flexibility; it can also mean better education provision in remote and rural areas, for travelers and/or for those in residential areas, in hospitals and care-centers, as well as those in high-performance training.
Commission press release in: https://ec.europa.eu/commission/presscorner/detail/en/ip_21_3908
The Commission’s AI-Watch platform was set up by the Commission to monitor the implementation of the Coordinated Plan on AI, proposed already in 2018, as a joint initiative between the Commission and the EU member states; recent Commission AI Package (April 2021) included a review of the plan, as well as a proposal for a regulatory framework on AI.
On AI package, see: https://ec.europa.eu/commission/presscorner/detail/en/ip_21_1682
The Commission proposed that the EU invests in AI at least €1 billion per year from the Horizon Europe and Digital Europe programs; EU-level funding on AI should attract and pool investment to foster collaboration among the states to maximise impact by joining forces. By mid-2021, 19 countries out of 27 EU states, as well as Norway, have adopted national strategies.
The plan sets four key policy objectives, supported by concrete actions and indicating possible funding mechanism and timeline to: a) set enabling conditions for AI development and uptake in the EU; b) make Europe the place where excellence thrives from the lab to market; c) ensure that AI works for people and is a force for wellbeing in society, and d) build strategic leadership in high-impact sectors.
Source: the 2021 Coordinated Plan’s key message in: https://digital-strategy.ec.europa.eu/en/policies/plan-ai
As technology and society continue to evolve and develop, the way people learn and acquire knowledge will also continue to change, for children and adults alike. Some experts in the AI and digital algorithms predict greater AI’s influence on society, on computer scientists and engineers, scholars in the social sciences and humanities (including anthropologists, economists, historians, media scholars, philosophers, psychologists, and sociologists), law and public policy decision-makers, as well as on business management and private sectors.
More in:https://ai100.stanford.edu/gathering-strength-gathering-storms-one-hundred-year-study-artificial-intelligence-ai100-2021-study
AI in education: “lifelong learning companion”
AI has been regarded as one of the most disruptive technologies, even in educational spheres, i.e. in schools and universities. Artificial intelligence will be able to make the educational experience more efficient and engaging, both for teachers and students. With the use of technologies powered by Artificial Intelligence, the problem of a “one-size-fits-all” approach to teaching will be finally solved. Thanks to Machine Learning algorithms, teachers will be able to identify the educational needs of their students, and find the gaps in their methods, pointing where students are struggling the most.
On the other hand, students will be able to move through their education more effectively, and talented students who are often bored by easy tasks will finally find new motivation and challenges. use of AI-based tutors helps students adopt productive learning behaviors, such as self-regulation and self-explanation. “Collaborating with a human-computer could help students to learn using new approaches we can’t yet imagine”.
The AI algorithms will also help to provide an enhanced experience to users, with personalised features: each student can get access to specific purposes and learning needs. In the future, that means that a student won’t have to learn the same exact thing at the same exact pace as 30 of their classmates. Instead, we will be able to hone in on the areas where a student struggles, and tailor their lessons to help them through difficult topics”.
Source: https://acerforeducation.acer.com/education-trends/education-technology/is-artificial-intelligence-transforming-education/?gclid=EAIaIQobChMImeyk3NWs-AIVFp3VCh2biw5kEAAYBCAAEgIEDvD_BwE
AI roles in education: complex effect
= AIs can be used in colleges for grading homework and tests for lecture courses: although existing AIs still unable to truly replace educators’ grading, it is presently possible for teachers to automate grading for nearly all kinds of multiple choice and fill-in-the-blank testing. Today’s essay-grading software is still in its infancy, but it is constantly improving to allowing teachers to focus more on in-class activities and student interaction than grading.
= AIs help to adapt educational software to students needs: some are already impacting education through applications on individualized learning: these apps respond to the students’ needs by putting emphasis on certain topics and repeating subjects that students mastered; thus, “adaptive learning, AL” programs will likely be improved and expanded with time. E.g. presently, Oxford AL program is available at €2,743; it is designed for managers in industries and business leaders in different sectors to increase the AI’s possibilities.
Source: https://www.getsmarter.com/products/oxford-artificial-intelligence-programme
= AI program can define places in courses to be improved: thus, students can get immediate feedback that helps them to understand a concept and remember how to do it correctly next time. E.g. Coursera, a massive open online course provider, is already widely used in practice. When a large number of students submit the wrong answer to a homework assignment, the system alerts the teacher and gives students a customized message with hints to correct answer.
= AIs provide additional support for tutors: some programs based on AI already exist and can help students through basics in mathematics, writing, etc. With the rapid pace of technological advancement the advanced tutoring systems have a better future.
= AIs are giving students and educators a helpful feedback: thus, universities with online courses are using AI systems to monitor student progress and to alert professors in case of problems in student’s performance. Such AIs allow students to get the needed support and professors to find areas where they can improve instructions; some AI programs are offering both advices on individual courses and on developing systems that assist to deliver on majors.
= AIs are already vital for peoples’ ability to process personal and professional information; they are able to change students’ management with the needed information in universities. Presently, the AI-based education systems have already radically changed the way students interact with information to help prepare for courses and doing research.
= AIs are making trial-and-error learning less intimidating: some apps help students to learn and deal with trial and error; AI could offer students a way to experiment and learn in a relatively judgment-free environment. When AI tutors offer solutions for improvement, the AI is supporting an optimal kind of learning through “learning” by a trial-and-error method.
= AI can help future students find the “right” university: some AI systems are already assisting colleges in interacting with prospective and current students – from recruiting to helping students choose the best courses. AIs are also helping make more closely tailor future students’ needs.
= Changing almost everything that is taken presently for granted in education. AIs can make the whole education process look a whole lot different by using “smart AIs”. Using AI systems, software, and support, students can learn from anywhere in the world at any time, and with these kinds of programs taking the place of certain types of classroom instruction, AI may just replace teachers in some instances (for better or worse). Educational programs powered by AI are already helping students to learn basic skills, but as these programs grow and as developers learn more, they will likely offer students a much wider range of services.
References and citations from: https://www.teachthought.com/the-future-of-learning/roles-for-artificial-intelligence-in-education/
Computer science and AI in the US
The number of new computer science (CS) graduates both at doctoral and undergraduate level in the US educational institutions has grown 3.5 times during decade 2010 to 2020; more than 31,000 undergraduates completed CS degrees in 2020, i.e. 11.6% increase from 2019.
In the US however, most AI-related courses are offered as part of the CS curriculum at the undergraduate level; but the higher education level is catching up: in 2020, one in every five CS students who graduated with PhD degrees specialized in AI and machine learning (ML), the most popular specialty in the past decade; it is also a speciality that exhibits the most significant growth during 2010-20, relative to 18 other specializations. Robotics/vision is also among the most popular CS specialties of PhD graduates in 2020, registering just one percent change in the share of total new CS PhDs in the past 11 years.
Historically, AI research has been the domain of computer scientists and researchers studying cognitive processes; it has become clear recently that all areas of human activity – especially the social sciences – could be included in a broader involvement with the perspective AIs. By minimizing the negative impacts on society and enhancing the positive aspects, modern ICT solutions can facilitate AIs’ use for outcomes relevant to ongoing society’s requirements.
Source and references to: https://ai100.stanford.edu/2021-report/conclusions
In 2020, the share of new PhD graduates in AI/ML specialization PhD in the US who chose to work in the industry dipped slightly, with its share dropping from 65.7% in 2019 to 60.2% in 2020. The share of new AI PhDs who went into academia changed during present decade (2010-20) from 40 to 24 percent and for government has been almost constant during the decade at about two percent; the 2020 data may be impacted by the increasing number of new AI PhDs who went abroad upon graduation, a number that grew from 19 in 2019 to 32 in 2020. In the US, the number of international students in AI has reached by about 60-65 percent.
Reference to: https://aiindex.stanford.edu/wp-content/uploads/2022/03/2022-AI-Index-Report_Chapter-4.pdf. p.30.
It has to be said in conclusion, that progressive AI-development has to be incorporated into a nation-wide education and training system, with a clear and newly-established lines of communication between teachers’ and AI-type education-providers. Only in this way, the success of the AI in education can be achieved by empowering education community and researchers by efficient algorithms to assist educational revolution’s process. It is quite feasible that universities and high-education institutions in the near future shall inaugurate a quick transformation of existing slowly outdated facilities. New adaptive hybrid education models shall be not only computer-based but include a liaison of the learning content, crowd-sourcing platforms and other “educational shifts”. Traditional education/teaching models shall be oriented to modern dynamic labor market: the secondary, tertiary and adult education will be different to answer disruptive global challenges.