Artificial Intelligence (AI): A Force Multiplier in Higher Education

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Artificial Intelligence

In generic terms, Artificial Intelligence (AI) is the process of creating machines and programs that can easily do specific tasks independently, which were possible earlier only through human cognition. For emulating human knowledge in specific fields, technologists program algorithms and extensive rules for computers, which support AI value chain. Such systems with machine language bring out quick correlations and patterns in available vast data, which are not immediately comprehensible or intuitive to humans. Some of the recent visible applications include creating GPS systems, auto language translations, voice recognitions, face recognition, recommending books by companies like Amazon, and shaping academic trajectories for students. Some solutions provided by AI technologies are at Fig. 1.

Available AI Tools

Some of the AI tools currently being used in higher education sector for supplementing pedagogy, establishing systems, and decision-making process across stakeholders and administrative levels are as under:

  1. Intelligent and interactive tutoring systems: It helps in assessing student’s comprehension level and design remedial action. Tools like GradeGuardian uses visualizations and predictive models for student performance along with interactive dashboard indicating anticipated effects.
  2. Predictive tools to inform pre-emptive action for students: By analyzing available student data, the probable student activities like dropping out, motivation etc. could be predicted and remedial actions could be taken.
  3. Adaptive learning tools for customized learning: At the level of individual students, it helps to judge learning levels and allow development of customized educational content. It also provides feedback to instructors for appropriate guidance.
  4. Automated rationalization of teachers: This helps in effective distribution and posting of instructors based on supply gaps, candidate preferences etc.
  5. Professional development courses: Training content for instructors based on their performance can be developed using adaptive AI tools. These tools design and develop professional development training content, and could be used for understanding concepts and instructor’s skill development

Based on the objectives and higher education needs, organizational AI tools can be customized and developed for use and efficiency. The concerns like intellectual property rights, data security and content security need appropriate consideration.

Role of AI in higher education

AI, as an emerging disruptive technology, demands response from higher education system. AI provides higher education services more scalable in different areas. Some of the immediate and future applications of AI in four key areas of higher education are given below.

  • Student acquisition:
    Studies indicate that more than 41 per cent of the potential students use Edu websites as a primary source for making decisions. AI enabled websites can be used for scaling enrolment work. Students can text for answers to FAQ Chatbots for their common questions, which ultimately frees counselors to take other priority jobs. AI can assist in identifying students who can succeed in certain majors and the institutions can make effective and target enrolments.
  • Learning enhancement:
    AI can help instructors to supply resources to struggling students as required. AI can help instructors for grading students and free themselves to attend lager class issues and engage students. Creating AI enabled adaptive courseware can enhance learning. AI enabled online multi lingual translation tools, besides promoting different languages, would enhance learning from different streams with least intervention of instructors.
  • Student affairs:
    Based on predictive data and past performance, AI can provide personalized degree planning. It also helps to create hyper learning in which institutions can use data to maximize complex decisions. For eg. Building maintenance can be linked to class schedules under various campuses.
  • Institutional efficiency maximization:
    AI can be used to integrate information from multiple campus systems. AI helps to understand local hiring needs of employers and prepare students to fill the needs. AI tools can optimize the course platforms and provide uniform feedback and exam mechanism for large multidisciplinary colleges, universities and HEI (Higher Education Institutions) clusters with 3000 or more students to be created at the national level.

Forward looking vision

Higher education, as a sector, may be late to adopt AI as compared to corporate sector. Further research on AI adoption and developing requisite AI tools for different spheres of higher education is of immense importance at this stage. NITI Aayog has already rolled out a discussion paper on National Strategy for Artificial intelligence, bringing out various concerns and probabilities.  For quality output, leading western institutions like MIT, Carnegie Mellon etc. have made huge investments to incorporate AI into all diversified programs through their college of computer science and institutions. Recent National Education Policy aims to provide access to highest-quality education for all learners by 2030. At the educational system level, AI can facilitate as a force multiplier to achieve this objective. At the level of individual institutions, and among existing more than 50,000 higher education institutions in India, pioneer institutions and early adopters of AI techniques can provide high quality value outputs in their respective field, in addition to reaping financial benefits for their institutional growth.

References:

  • Artificial Intelligence in Higher Education, Learning House, December 2018.
  • Government Artificial Intelligence Readiness Index 2019, Oxford Insights, 2019.
  • National Education Policy, Ministry of HRD, 2019.
  • National Strategy for Artificial Intelligence: Discussion Paper, NITI Aayog, June 2018.
  • Rewire for Growth: Accelerating India’s Economic Growth with Artificial Intelligence, Accenture, 2017.

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