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Artificial intelligence will support future of learning and education

As technology races ahead, skill gaps have appeared, widened and morphed.  In addition, automation may displace 85 million jobs by 2025, whereas time now spent on tasks will be equally divided between people and machines. For these reasons, workforce roles will change, and so will the skills needed to perform them. Learning and work go hand in hand — therefore, the future of learning is deeply entwined with the future of work. To prepare people for the anticipated changes to their lives, we must ensure that our education and training is tuned to the new demands of the workplace and society

 

In March 2018, The Future of Education and Skills 2030 OECD project published a position paper in which it proposed an initial framework designed to help countries address two key questions: What knowledge, skills, attitudes and values will today’s students need to thrive and shape their world; and How can instructional systems develop these knowledge, skills, attitudes and values effectively?

 

Technology is shaping learning for the future artificial intelligence and developing digital technologies are performing tasks in the workplace and education settings, changing the jobs we do and naturally transforming the future landscape of work and study. In thinking about how AI will impact on education and what sorts of knowledge and skills future citizens will need, we, therefore, need to look beyond the current trends towards trying to identify the jobs and skills that the world will require to the core issue of what it means to be intelligent in an AI-augmented world.

 

Now is the time when we must agree on what we want from our Human Intelligence (HI), how best this HI can work with AI, how AI and HI should complement each other and as a consequence what new knowledge and skills we must focus our attention upon.

 

In another NESTA report, Schneider and Bakhshi (2017) discuss future skills and argue that the future of work is not only influenced by automation, but also by key trends in environmental sustainability, urbanisation, increasing inequality, political uncertainty, technological change, globalisation and demographic change. They say there will be a strong emphasis on interpersonal skills, higher order cognitive skills and systems skills. Originality, fluency of ideas and active learning are very important. A future workforce will need broad-based knowledge as well as a specialist feature for specific occupations.

 

Authors like Gardner (2007) and Luckin (2018) have offered alternative ways of conceptualising Intelligence to suit the modern world. Gardner suggests that we need five sorts of intelligence, or mental capacities: The Disciplinary Mind: to master academic subject knowledge, such as science, mathematics, and history, as well as at least one professional craft; The Synthesizing Mind: to enable us to integrate ideas from different disciplines into a coherent whole and to communicate this synthesized, integrated understanding to others; The Creating Mind: which imbues us with the capability to uncover and clarify new problems, questions, and phenomena; The Respectful Mind: that ensure that we are aware of and appreciate the differences among and between humans (and possibly AIs in the future); The Ethical Mind: vital components to ensure that we
fulfil our responsibilities as both a worker and a citizen. These five minds offer thought
provocations for how education needs to be revised.

 

In another WEF report, “New Vision for Education: Fostering social and Emotional Learning through Technology”, 2015, the authors discuss the sorts of skills that students will need in the future and argue for the importance of social and emotional learning: “To thrive in the 21st century, students need more than traditional academic learning. They must be adept at collaboration, communication and problem solving, which are some of the skills developed through social and emotional learning (SEL). Coupled with mastery of traditional skills, social and emotional proficiency will equip students to succeed in the swiftly evolving digital economy.’

 

Artificial Intelligence (AI) is currently the most transformative field of technology in the world, and the education industry is no exception. AI platforms can be divided into two types: weak AI/narrow AI, which is designed for a specific task, and strong AI, also known as artificial general intelligence, which can solve unfamiliar problems.

 

When a machine mimics cognitive functions that humans associate with other human minds, such as problem-solving, reasoning, planning, learning, natural language processing, perception, moving and manipulating objects, social intelligence, and general intelligence, it is referred to as general Artificial intelligence (AI).

 

AI is any software technology with at least one of the following capabilities: perception—including audio, visual, textual, and tactile (e.g., face recognition), decision-making (e.g., medical diagnosis systems), prediction (e.g., weather forecast), automatic knowledge extraction and pattern recognition from data (e.g., discovery of fake news circles in social media), interactive communication (e.g., social robots or chat bots), and logical reasoning (e.g., theory development from premises). This view encompasses a large variety of subfields, including machine learning.

 

“Learning engineering” is a relatively new term, Indeed, some believe that learning engineering is the same as saying “data-driven instructional design.” The main aim is to use data to improve learning and teaching. Learning engineers use technologies, standards, and science to propose, test, and implement solutions. One of the most useful things learning engineering can do is to take some of the guesswork out of education. In the past, educators have largely been in the dark about how well different instructional tools and resources are working.

Artificial Intelligence (AI) for numerous applications within the education sector to reinforce teachers’ and students’ experience and improve their knowledge and the growing want for multilingual translators integrated with the AI technology are expected to drive the expansion of the AI in education market.

 

AI to support knowledge and skill development

According to Forbes, AI allows businesses to better understand a customer and their learning journey. With AI in learning and development, employees can arrange their personalized learning material, decide on their objectives, and gain information based on their learning styles and preferences.

 

Students: Helping everyone to know

Education software, machine learning, and artificial intelligence are a number of the Innovative learning models and Technologies amendment the principles and making tremendous shift from the teaching ways. These technologies have fully remodeled with a room.

AI systems can readily acquire and process knowledge. They can rapidly build up vast representations of bodies of knowledge and these can be harnessed to help us to develop our knowledge and to learn facts. This is easiest in well-defined subject areas, such as science and maths but can also be harnessed in other disciplines which require knowledge of non-contextualised facts.

The bodies of knowledge embedded in AI systems can then be used to help students. They can be presented to students in a variety of modes for example as text augmented with pictures or audio or video. The AI system can time the presentation of the knowledge and therefore pace the learners experience as well as vary the order that the resources are presented to learners in order to maximise learning or meet some other criteria which is embedded in the design of the system.

Diminishing gaps between different socioeconomic groups

Ensuring equity of access to knowledge for different subgroups of our population is a major
goal for education. AI systems can help to bridge this gap by providing access to knowledge
as described above for those who may not have the resources either in their homes or their
communities or their schools.

Providing Access to knowledge and information for disabled students and those with additional educational needs

Sophisticated AI systems have been developed to provide a range of interfaces to
knowledge for students who have disabilities. For example, natural language processing
software enable students with physical disabilities to use voice activation to access devices.
Specialised systems have been designed to help learners with additional educational needs
for example, Grammarly is an AI-powered browser plug-in designed to support people with
dyslexia when writing.

Personalised learning

AI can compute and combine big data sources and identify the gaps in an individual’s knowledge. Then, depending on these disparate data, learner profiles can be created, which can enhance the overall learning experience and teach new skills to an employee. AI-backed L&D programs can automate the learning process while improving the engagement and reinforcement of the training program.

AI systems are designed to not only store knowledge about the domain they are teaching but also have representations of the learners who use the system. This includes the knowledge and information that has been presented to them as well as information about what the AI system thinks the learner knows (this data is gathered by the system as it records the actions of the learner in response to the system). By reasoning with the information, the system has about the learner and the information it has about the knowledge, the system can provide personalised experiences for learners which aim to help them develop the knowledge that the system knows they do not have.

When AI in L&D training courses are used, programs can be developed keeping in mind the different learning styles of the employees. This will allow them to learn the personalized content at their own pace and meet the criteria set by the company. It helps the learners and the company save time.

You can easily provide personalized and just-in-time training to your learners using artificial intelligence technology. AI will assist in tracking individual learners’ previous results, making one-size-fits-all training a breeze. Also, within an online training course, AI can help to monitor the employees’ progress, making it easier to recognize their learning gaps. Through doing so, you will be able to provide top-notch training that makes them more profitable for the company.

Individualised feedback

AI systems store information about learners and can give feedback to learners about how they are doing both in terms of whether they have got something correct or not.

Machine learning algorithms predict results, allowing you to tailor content to a learner’s experience and personal objectives. For example, online learners who articulate a specific ability gap receive tailored recommendations that help them fill in the gaps in their experience in a more personalized way. This may involve situations where the system recognizes that a learner might be able to skip a few modules to take a more extensive and less sequential learning journey than someone who lacks the fundamental skills needed for that subject.

Freeing up human teachers to work with learners on other things

As AI systems are used increasingly to provide personalised learning experiences for students about academic knowledge, teachers time will be freed up as they do not need to use their time to teach this type of knowledge.

Repetition, drill and practice

Learning often requires repetition in order to consolidate knowledge or skills. AI systems
can readily supply endless examples (without losing patience!) and therefore be used to
consolidate knowledge and skills both for learners who are struggling and have not yet
consolidated their knowledge or mastered a skill and for those who wish to practice.

Supporting Collaboration

When students work collaboratively, Ai systems can be used to monitor some indicators of
collaboration and can therefore be used to both monitor and manage collaborative working
and learning.

 

Teachers

Automating administrative tasks

AI has been used in different industries to automate tasks and the same is happening in the education sector. Professors and teachers usually have to manage the classroom environment alongside numerous organizational and administrative tasks. According to a report in research paper writing services, teachers don’t just teach. They also spend time grading tests, evaluating homework, filing the necessary paperwork, making a progress report, organizing resources and materials for lectures, managing teaching materials, etc.  Artificial Intelligence will automate these tasks to have more time to do their primary work of teaching without being bothered with administrative tasks.

Create Smart content

One of the advantages of AI technology is that it can assist in the creation of new content. As a result, you can always get refreshing content that meets your students’ requirements by using AI for personalized learning. This not only saves time and resources but also relieves the instructional designers of a significant amount of work.

AI can help teachers create smart content that makes teaching and learning more comfortable for them and the students, respectively. According to Paul Barry, lab report writer at assignment writing service, AI can help teachers create different content types.

  • Digital lessons: AI can help generate bite-sized learning, study guides, digital textbooks, all within the framework of digital learning.
  • Information visualization: Simulation, visualization, and web-based study environments are different ways to perceive information that AI can power.
  • Learning content updates: Learning content can be generated and updated regularly with AI. This ensures that information is up-to-date.

Content Distribution and Appropriate Scheduling

Another advantage of using AI for personalized learning is that you can properly schedule and deliver information. You can conveniently plan your coursework through your learning portal using AI technology. You may also deliver learning tools based on an individual’s performance and evaluation results. Moreover, AI allows you to predict course maps for your students and make appropriate changes as required.

Changing the nature of what is taught by teachers.

As AI systems are developed that store wider bodies of knowledge and enable students to practice a range of skills, teachers’ time can be freed up to work with learners on other aspects of their development to enable them to become active and engaged citizens. Teachers will be able to work with learners to develop the six other types of inter related intelligence, secure in the knowledge that AI will ensure that all their students have the academic knowledge and skills that they need.

Assessing and monitoring student progress

AI systems store information about what students know and can do and what information and resources have been presented to students as well as the skills they have practiced and mastered. Teachers can readily have access to this information which can be presented for individuals, particular groups and the whole cohort. It can be used for a variety of purposes which can save time if used effectively.

Teachers need to know what their students know and can do. It is important for teachers to
monitor their students’ progress in order to ensure that their teaching is effective.
The information can be used for reporting purposes – to parents and school leaders, as the
basis for conversations with learners to motivate them and engage them in their learning as
well as developing their confidence in their own knowledge and skills.

Take, for example, a new study titled “Language as Thought: Using Natural Language Processing to Model Noncognitive Traits that Predict College Success.” Released in 2022, the researchers, including grit expert Angela Duckworth, studied how language can help to predict a student’s future by studying noncognitive traits.

The researchers built off of years of studies that suggest that thought and language are inextricably coupled. As part of the work, the team used natural language processing, machine learning, and manual coding to analyze college application essays and infer writers’ noncognitive traits, such as goal orientation and perseverance.

The study concluded that language can indeed reveal noncognitive traits and help gauge a student’s learning potential. To be more exact, a student’s college essay predicted their success in college.

Planning future teaching and interventions

On the basis of the information that teachers have about individuals and groups of learners,
teachers can plan their future teaching, for example, to address gaps in knowledge or skills for an entire cohort of students or to plan interventions for individual children. They can also plan their teaching so as to move onto different areas when their students are ready.

 

Educating People about AI and Digital Technology

The basic AI concepts

It is crucial that citizens of the future have a basic understanding of AI concepts so that they can engage both effectively and critically with AI systems which are becoming increasingly pervasive in our daily lives. Although there are concerns that the curriculum is overcrowded, in the future AI will become part of the existing computing/ICT/computer science curricula as they evolve.

The sophistication level has raised enormously with the increasing adoption of artificial intelligence and machine learning algorithms. These Technologies have become extraordinarily helpful for developing easy call support systems and utilized in data acquisition applications, language translation, and data retrieval.

 

Inclusion and equity.

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and accelerate progress towards SDG 4. However, rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. UNESCO is committed to supporting Member States to harness the potential of AI technologies for achieving the Education 2030 Agenda, while ensuring that its application in educational contexts is guided by the core principles of inclusion and equity.

UNESCO’s mandate calls inherently for a human-centred approach to AI. It aims to shift the conversation to include AI’s role in addressing current inequalities regarding access to knowledge, research and the diversity of cultural expressions and to ensure AI does not widen the technological divides within and between countries. The promise of “AI for all” must be that everyone can take advantage of the technological revolution under way and access its fruits, notably in terms of innovation and knowledge.

 

AI-based tools

Although there has been an explosion in the number of digital learning platforms, not enough attention is paid to learning science in their design and implementation. These platforms should be built so that they can both provide data and experimental environments for learning scientists, and accommodate research-based insights in future updates to the platform.

In other words, too little has been done to take advantage of the data created by learning platforms. By implementing learning engineering principles, these systems can create feedback loops that promote our knowledge of learning while improving the platforms themselves.

To perform these AI operations, we require a few tools where we can allow the AI-based software to run. Versions of search and mathematical optimization, logic, probability, and economics methods would all be included in these tools. These are called AI-based platforms

Artificial Intelligence in Education Market

In recent years, experts have predicted that between 2017 and 2021, the use of artificial intelligence in education in the US will grow by 47.5 percent. This is according to a report on the Artificial Intelligence Market in the education sector in the US.

The global Artificial Intelligence in Education market is expected to be around US$ 12 Billion by 2027 at CAGR of 45% in the given forecast period.

The high adoption of cloud services among education institutes nowadays is additionally making good surroundings for the artificial intelligence in education market. Higher education institutes, faculties, facilitators, Educators, and students in colleges area unit more and more creating use of computing and education so on improve the learning expertise similarly as productivity. The utilization of cloud services helps in the reduction of value of possession for academic Institutes and this helps them to supply high-quality Education without much value. Universities and colleges are able to adopt cloud computing without having the necessity to upgrade the prevailing infrastructure with Advanced Technologies.

 

On the other hand, there are some factors which will restrain the market from reaching its truest potential. One of the key challenges faced by the AI in education market is that the resistance towards adopting latest technology by various colleges. Several faculties and colleges merely stick with orthodox ways of teaching. This can act as a challenge for the market.

 

The global Artificial Intelligence in Education market is segregated on the basis of Model as Learner model, Pedagogical model, and Domain model.

Based on Technology the global Artificial Intelligence in Education market is segmented in Machine Learning, Natural Language Processing (NLP), Deep learning, and Others.

Based on End-User Industry the global Artificial Intelligence in Education market is segmented in Higher education, K-12 education, and corporate learning.

Based on Application, the global Artificial Intelligence in Education market is segmented in Virtual Facilitators and Learning Environments, Intelligent Tutoring Systems, Student-initiated learning, Content Delivery Systems, Student-initiated learning, and Others.

The report also bifurcates the global Artificial Intelligence in Education market based on Component in Solutions, 1 Software Tools, .2 Platforms, Services, 1 Professional Services, and 2 Managed Services. The report also bifurcates the global Artificial Intelligence in Education the global Deployment Mode market is segmented in Cloud and On-premises.

 

Key players in the market are Pearson, IBM, AWS, Nuance Communications, Cognizant, Quantum Adaptive Learning, Google Inc., Third Space Learning, Microsoft Co, Blackboard, and others are among the major players in the global Artificial Intelligence in Education market. The companies are involved in several growth and expansion strategies to gain a competitive advantage. Industry participants also follow value chain integration with business operations in multiple stages of the value chain.

 

References and Resources also include:

https://www.marketresearchengine.com/artificial-intelligence-in-education-market?mod=article_inline

https://www.the-learning-agency.com/insights/a-game-changer-lets-talk-about-learning-engineering/

https://trainingmag.com/top-7-ways-artificial-intelligence-is-used-in-education/

https://www.evelynlearning.com/using-ai-for-personalized-learning/#:~:text=Using%20AI%20for%20personalized%20learning%20is%20a%20method%20that%20focuses,individual%20needs%20of%20each%20student.

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