Home   »   Artificial Intelligence in Education

Artificial Intelligence in Education

Context: Recently, a meeting of the education ministers of G20 countries held in Pune agreed to equitable and inclusive use of ‘Artificial Intelligence’ in education and skilling that respects human rights.

About Artificial Intelligence

  • Artificial Intelligence (AI) is a simulation of human intelligence into a computer machine so that it can think and act like a human.
  • AI systems are designed to simulate or replicate human cognitive abilities, such as perception, reasoning, learning, and problem-solving.
  • AI rely on algorithms and computational models to process and analyze large amounts of data, extracting patterns and making predictions or decisions based on that information.
  • AI has various uses and applications in different sectors, including education.

Artificial Intelligence in Education (AIED)

  • AIED refers to the application of AI technologies and techniques in the field of education.
  • In the 1970s, AIED has occurred as a specialist area to cover new technology to teaching & learning, specifically for higher education.
  • The main aim of AIED is to facilitate the learners with flexible, personalized, and engaging learning along with the basic automated task.
  • Some popular trends in AIED include Intelligent tutor systems, smart classroom technologies, adaptive learning, and pedagogical agents.
Artificial Intelligence in Education
Artificial Intelligence in Education

Various applications of AI in Education

  • Intelligent Tutoring Systems: These systems analyze learner data, adapt the curriculum to individual needs, and offer interactive and engaging learning experiences.
  • Adaptive Learning: AI algorithms analyze student performance data to create personalized learning paths. It can identify knowledge gaps, suggest appropriate learning materials, and adjust the difficulty level of content to optimize the learning process for each student.
  • Automated Grading and Feedback: AI can automate the grading process for objective assessments, such as multiple-choice questions. It can also provide instant feedback to students, allowing them to identify areas for improvement and adjust their learning strategies accordingly.
  • Natural Language Processing (NLP): NLP can be used in language learning applications, automated essay grading, and intelligent chatbots that provide answers to student queries.
  • Intelligent Content Creation: AI can generate educational content, such as quizzes, exercises, and instructional materials.
  • Virtual Reality (VR) and Augmented Reality (AR): AI technologies, combined with VR and AR, can create immersive learning environments. These technologies provide interactive simulations, virtual field trips, and 3D visualizations, enhancing understanding and engagement in various subjects.
  • Data Analytics and Predictive Modeling: AI can analyze large volumes of educational data, such as student performance, attendance, and behavior, to identify patterns and trends. Predictive models can help educators identify students at risk of falling behind and provide timely interventions.
  • Intelligent Learning Management Systems (LMS): These systems can automate administrative tasks, such as scheduling and grading, allowing teachers to focus more on instruction.
Various applications of AI in Education
Various applications of AI in Education

Risks and Challenges with AI in Education

  • Overreliance on AI: Overreliance on AI systems may neglect the importance of human guidance, mentorship, and the social aspects of education. AI should be seen as a complementary tool rather than a substitute for human teachers.
  • Ethical Use and Transparency: Transparency in how AI algorithms make decisions and provide recommendations is crucial to build trust among students, educators, and stakeholders.
  • Lack of Universal Access and Equity: Disparities in access to technology, reliable internet, and training can create a digital divide, leaving some students behind.
  • Data Privacy and Security: AI systems in education collect and analyze substantial amounts of student data. Robust data protection measures and compliance with privacy regulations are crucial.
  • Algorithmic Bias and Fairness: AI systems can inadvertently perpetuate biases present in the data they are trained on. If these biases are not addressed, it can lead to unfair treatment and discrimination in educational outcomes.

Challenges in the Implementation of AI in Education in India

A report by the UNESCO titled ‘‘Status of Education Report 2022 for India’ ‘Artificial Intelligence (AI) in Education’ has highlighted the following challenges:

  • There is a lack of policies on the role of AI in education and a lack of resources and infrastructure affects the spread of AI in education.
  • There is a dearth of training data for AI in education systems in India.
  • Barriers to digital learning in India
    • Inadequate technology infrastructure: Only around 41.3% of schools had access to computers and 24.5% to the internet in 2020-2021.
    • Inability of teachers: In addition to technology infrastructure, the inability of most teachers to use technology effectively to assist their students’ learning is a significant barrier.
    • Digital divide:
      • Rural –urban divide: Only 68% of adolescents in urban areas were found to use technology-enabled learning tools, and only 47% in rural areas.
      • Gender divide: 67 percent of the male population are using internet in India, while it is only 33 percent for female population.
      • Children with disabilities, from migrant families, living in remote areas, from scheduled tribes and scheduled castes, and girls in particular experience these inequalities most acutely.

Efforts by the Government of India towards AI in Education

  • NEP 2020: The National Education Policy, introduced in 2020, has recommended introducing contemporary subjects like Artificial Intelligence in the curriculum.
    • In accordance with the NEP, 2020, the NCERT has started the process of developing a new National Curriculum Framework for School Education, during which the potential for adding an introductory course on artificial intelligence (AI) at the secondary level.
  • National Strategy for AI: NITI Aayog has published the National Strategy for Artificial Intelligence wherein it has identified five core areas for the application of AI that includes Education, Healthcare, Agriculture, Smart Cities and Infrastructure, and Smart Mobility and Transportation.
  • Education 4.0 India initiative: The initiative was jointly launched in May 2020 by the World Economic Forum (WEF), the United Nations Children’s Fund (UNICEF) and YuWaah (Generation Unlimited India).
    • It focuses on how digital technologies can enhance learning and reduce inequalities in access to education among children in India, with the overreaching aim of making Indian students ready for 21st century jobs, and India ready to benefit from the fourth industrial revolution.
    • It serves as a call to action for all stakeholders in the ed-tech space to come together to transform the sector.
  • National Programme on Responsible Use of AI for Youth: With the objective to empower the youth to become AI ready and help reduce the skill gap, government along with Industry partner has started this initiative to promote AI awareness among Government school going children.
  • National Digital Education Architecture (NDEAR): Union Budget 2021-22 has announced setting up of NDEAR within the context of a Digital First Mindset.
    • It is meant to enable a common set of principles and approaches to be followed in building, using and re-using technology for education.
    • NDEAR is under the aegis of the Ministry of Education in collaboration with Ministry of Electronics and IT (MeitY).

Way Forward

  • Recommendations by the UNESCO report: The report has suggested the following for effective implementation of AI in Indian educational system:
    • AI ethics in education should be given top priority. All students and teachers should be ensured access to the latest technology.
    • Providing a comprehensive regulatory framework for AI in education should be accelerated.
    • Effective public-private partnership should be created.
    • Efforts should be made to remove the biases associated with algorithms and the discrimination arising out of it.
    • Necessary reforms are necessary to increase public confidence in AI.
    • The private sector can be consulted to better utilize the knowledge of students and academics in developing AI products.
  • Beijing Consensus: UNESCO has published the Beijing Consensus on Artificial Intelligence (AI) and Education, the first ever document to offer guidance and recommendations on how best to harness AI technologies for achieving the Education 2030 Agenda.
    • The Education 2030 Agenda aims to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all by the year 2030, forms a part of UN SDG 4.
    • The Beijing Consensus recommends the UNESCO’s Member States to:
      • Plan AI in education policies in response to the opportunities and challenges AI technologies bring, from a whole-government, multi-stakeholder, and inter-sectoral approach, that also allow for setting up local strategic priorities to achieve SDG 4 targets.
      • Support the development of new models enabled by AI technologies for delivering education and training where the benefits clearly outweigh the risks, and use AI tools to offer lifelong learning systems which enable personalized learning anytime, anywhere, for anyone.
      • Consider the use of relevant data where appropriate to drive the development of evidence-based policy planning.
      • Ensure AI technologies are used to empower teachers rather than replace them and develop appropriate capacity-building programmes for teachers to work alongside AI systems.
      • Prepare the next generation of existing workforce with the values and skills for life and work most relevant in the AI era.
      • Promote equitable and inclusive use of AI irrespective of disability, social or economic status, ethnic or cultural background or geographical location, with a strong emphasis on gender equality, as well as ensure ethical, transparent and auditable uses of educational data.

Sharing is caring!