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Home Opinion

Importance of Amalgamation of AI with Outcome-Based Education (OBE)in Higher Education

Lagatar News by Lagatar News
May 17, 2023
in Opinion
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DEVASIS PRADHAN

OBE places an emphasis on the desired learning outcomes that students should have attained by the time they complete their education. It ensures that students acquire the necessary knowledge, skills, and competencies relevant to their field of study rather than just providing content. Improves graduates’ employ-ability and aligns education with real-world requirements through this strategy. It also places understudies at the focal point of the educational experience. It allows for individualized and tailored learning experiences because it takes into account the various requirements, interests, and learning styles of students. OBE encourages active engagement, motivation, and deep learning by tailoring educational experiences to each student’s individual objectives and aspirations. The advanced education programs line up with the requirements of enterprises and callings. OBE programs are better able to produce graduates with the skills and competencies required by the job market by involving industry experts in the creation of learning outcomes, curriculum design, and assessment procedures. This arrangement upgrades graduates’ employ-ability and adds to monetary development. Outcome-Based Education (OBE) relies heavily on artificial intelligence (AI) because it provides a wide range of capabilities and tools that improve instruction, assessment, and overall educational outcomes.

The following are important roles that AI helps OBE:

  1. Individualized Instruction: AI is capable of adapting to the specific requirements and preferences of each student, resulting in individualized learning experiences. AI systems are able to identify knowledge gaps and provide individualized content, resources, and activities to address those gaps by analyzing data on students’ performance.
  2. Systems for Intelligent Teaching: Students can receive support, direction, and feedback in real-time from intelligent tutoring systems powered by AI. These systems are capable of simulating one-on-one tutoring sessions, determining the strengths and weaknesses of students, and providing specific interventions to help students improve their comprehension and skills.
  3. Adaptive Evaluations: Man-made intelligence empowers versatile appraisals that change the trouble and content of inquiries in light of the student’s exhibition. This strategy enables educators to collect precise and comprehensive data on students’ progress and competencies while also ensuring that students are appropriately challenged.
  4. Information Investigation and Prescient Examination: Man-made intelligence can dissect huge measures of instructive information to recognize examples, patterns, and relationships. This information can assist educators in making decisions based on data, such as predicting learning outcomes based on specific interventions or instructional approaches or identifying areas where students may struggle.
  5. Processing Natural Languages: The creation of intelligent chat bots, virtual assistants, and language processing tools is made easier by AI-powered natural language processing capabilities. These tools can help students right away, answer their questions, make discussions easier, and make it easier for teachers and students to talk to each other.
  6. Optimizing and designing a curriculum: Computer-based intelligence can add to the plan and streamlining of educational programs by dissecting learning goals, understudy execution information, and input. AI can suggest curriculum changes and new instructional resources improve learning outcomes by identifying areas for improvement.
  7. Detection of Plagiarism: Simulated intelligence-based counterfeiting discovery instruments can assist teachers with recognizing examples of scholastic contemptibly. AI algorithms can provide evidence-based reports for further investigation by comparing student work with a vast database of resources.
  8. Learning Examination and Understudy Achievement: Learning analytics can be collected and analyzed with AI, revealing student engagement, progress, and success rates. These investigations can assist instructors with distinguishing in danger understudies, mediate when essential, and execute methodologies to further develop by and large understudy achievement.

It is essential to keep in mind that, despite the fact that AI possesses useful capabilities, it should only be utilized in conjunction with knowledgeable educators who are capable of interpreting and acting upon the data and insights provided. When it comes to guiding and supporting students’ learning journeys, educators continue to play a crucial role. Institutions can better prepare students for the challenges of the future and contribute to the overall development of society by adopting an OBE approach.

(Devasis Pradhan is an Assistant Professor Grade -1 and Research Coordinator of Department of Electronics & Communication Engineering at Acharya Institute of Technology, Bangalore)

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