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Submitted by Jayshree on
Overview / Summary

The AI Centre at BITS Pilani Campus is a cutting-edge hub dedicated to advancing the integration of artificial intelligence in education through innovative research and development. It focuses on creating AI-powered teaching aids and instruments to assess the efficacy of instruction, including automated grading and feedback systems for student contributions, known as assessment automation. The centre employs AI to generate diverse yet equivalent question papers to uphold assessment integrity and uses AI models to evaluate and provide commentary on student dissertations. Supporting this initiative is the AI for Education Innovation Lab—a dedicated space for designing, testing, and evaluating AI applications tailored to educational contexts, fostering collaboration among researchers, educators, and students.

Vision

To use artificial intelligence (AI) to improve research, education, and practical applications in order to make learning more effective, impactful, and individualized.

Mission

To create and apply AI-powered solutions that enhance instructional strategies, expedite evaluation procedures, and promote creativity across a range of fields, including business and education.

Aim & Objectives
  • Improve Learning Experiences: Make use of AI to develop individualized learning programs and give students immediate assistance.
  • Simplify Assessments: Create AI tools to help professors assess students' work, dissertations, and effectiveness as teachers.
  • Encourage Fair Evaluations: To guarantee fairness and lessen academic dishonesty, create several copies of the test questions.
  • Advance Research: Take part in innovative AI studies that tackle practical issues.
Campus
Pilani Campus
Focus areas or Specializations of Center
AI in Education: Creating AI-powered teaching aids and instruments to assess the efficacy of instruction.
Establishing mechanisms for automated grading and feedback on student contributions is known as assessment automation.
Question Paper Generation: To preserve the integrity of assessments, AI is used to generate diverse but comparable question papers.
Evaluation of Dissertations: Using AI models to evaluate and comment on student dissertations
Key facilities or Resources provided by the Center
High-performance computing: outfitted with an HPE DL380 Gen10 server that has an NVIDIA A100 80GB GPU and Intel Xeon Gold CPUs for effective AI model training.
Software Tools: TensorFlow, PyTorch, Scikit-learn, and other cutting-edge AI and machine learning frameworks are available.
An area specifically designed for creating and evaluating AI applications in educational contexts is the AI for Education Innovation Lab.
Services
  • AI-Based Teaching Assistants: Resources that help teachers grade assignments and answer questions from students.
  • AI algorithms that assess the efficacy of instruction based on a variety of data inputs are known as instructor performance analysis.
  • Automated Question Paper Generation: To maintain fairness, systems generate several exam versions.
  • Dissertation feedback systems are artificial intelligence (AI) platforms that offer thorough assessments of student dissertations.
Training & Workshops
Workshops on AI and machine learning: Practical sessions addressing subjects including deep learning, data analysis, and neural networks.
Monthly Talks: Consistent webinars with professionals talking about how AI is affecting education and other fields.
Certification Programs: To help working professionals expand their knowledge of artificial intelligence, courses such as the Post Graduate Programme in Artificial Intelligence and Machine Learning are offered.