The Department of Computer Science Organised FDP [Faculty Development Program]
Date : 18/06/2026
At: Auditorium SBMJFGC-KGF
Organized by: Department of Computer Science, SBMJFGC, KGF in association with IQAC
Total Faculty Participants : 55
Resource Person :
Dr. Ilango
FIETE (Fellow of the Institution of Electronics and Telecommunication Engineers) SMIEEE (Senior Member, Institute of Electrical and Electronics Engineers)
Internationally Recognized and Certified Mentor & Coach – UNESCO Agency, USA International Member – American Psychological Association (APA), USA Project Director and Coordinator – ICSSR-ICSSR Research Project-GoI-MoE Founder & Director – Warriors Consulting Services and Solutions Pvt. Ltd. (DPIIT)
Title of FDP : “AI in Education: A Need for IPR Generation”
The Principal is addresed a Faculty Development Programme (FDP) on “AI in Education: A Need for IPR Generation”,
1. AI-Driven Knowledge Creation and Intellectual Property
Artificial Intelligence is transforming higher education from knowledge consumption to knowledge generation. Faculty and researchers must leverage AI tools to create patentable innovations, copyrighted content, and proprietary educational technologies.
2. Integration of AI in Research and Innovation Ecosystems
AI-powered analytics, machine learning models, and data-driven decision-making can accelerate research outcomes, leading to increased patent filings, technology transfers, and commercialization opportunities.
3. Intellectual Property Rights (IPR) as a Measure of Academic Excellence
Modern accreditation frameworks such as NAAC and NIRF increasingly recognize patents, copyrights, and innovation outputs as indicators of institutional quality and global competitiveness.
4. AI-Assisted Patent Discovery and Prior-Art Analysis
Advanced Natural Language Processing (NLP) systems can automate patent searches, identify research gaps, and support novelty assessment, reducing the time required for innovation validation.
5. Generative AI for Educational Content Development
Generative AI technologies enable faculty members to create original digital learning resources, virtual laboratories, simulations, and adaptive educational materials that can be protected through copyrights and licensing mechanisms.
6. Building an Innovation-Centric Academic Culture
Educational institutions must establish AI Innovation Cells, Incubation Centers, and IPR Facilitation Units to encourage faculty and students to convert research outcomes into intellectual assets.
7. Ethical AI and Ownership of AI-Generated Content
As AI contributes to research and content creation, institutions must develop clear policies regarding authorship, inventorship, copyright ownership, and ethical use of AI-generated outputs.
8. AI-Based Multidisciplinary Research for Patent Generation
The convergence of AI with domains such as healthcare, agriculture, cybersecurity, biotechnology, and environmental science creates opportunities for high-impact patents and industry collaborations.
9. Commercialization of Academic Innovations
The true value of IPR lies not only in obtaining patents but also in technology transfer, startup creation, licensing agreements, and industry partnerships that contribute to economic development.
10. Vision for AI-Enabled Universities and Future Readiness
Institutions must transition toward AI-enabled smart campuses where research, innovation, entrepreneurship, and IPR generation become integral components of teaching and learning, preparing students for the Fourth Industrial Revolution and the emerging knowledge economy.
Session 1: AI in Education – Key Technical Points (As Delivered by Resource Person Dr. Ilangoo)
- Artificial Intelligence as a Transformative Educational Technology
- AI is revolutionizing teaching-learning processes through intelligent automation, adaptive learning systems, and personalized education pathways.
- Machine Learning-Based Personalized Learning
- AI algorithms analyze student performance data to customize content delivery, learning pace, and assessment strategies according to individual learner needs.
- Natural Language Processing (NLP) in Education
- NLP technologies power chatbots, virtual tutors, automated essay evaluation systems, and multilingual educational platforms to enhance learner engagement.
- Predictive Analytics for Student Performance Monitoring
- AI models can identify at-risk students through behavioral and academic data analysis, enabling early intervention and improved retention rates.
- Intelligent Tutoring Systems (ITS)
- AI-driven tutoring systems provide real-time feedback, personalized guidance, and adaptive instruction similar to one-on-one teaching environments.
- Generative AI for Content Creation
- Advanced AI models can generate lesson plans, question banks, case studies, laboratory manuals, and interactive learning materials, reducing faculty workload.
- AI-Powered Assessment and Evaluation
- Automated grading systems, plagiarism detection tools, and competency-based evaluation frameworks improve assessment efficiency and transparency.
- Learning Analytics and Educational Data Mining
- AI extracts actionable insights from large educational datasets, helping institutions improve curriculum design, teaching effectiveness, and student outcomes.
- Ethical AI and Responsible Usage in Academia
- Educational institutions must address concerns related to data privacy, algorithmic bias, academic integrity, transparency, and responsible AI governance.
- Future of AI-Enabled Smart Education Ecosystems
- The integration of AI with IoT, Cloud Computing, AR/VR, Digital Twins, and Learning Management Systems (LMS) will create intelligent, data-driven educational environments supporting lifelong learning.
Session 2: Patent Filing and Copyright Protection – 10 Technical Points
1. Importance of Intellectual Property Rights (IPR) in Academia
- Intellectual Property Rights protect innovations, research outcomes, software, educational content, and creative works generated by faculty and students.
2. Patentability Criteria
- An invention must satisfy three essential requirements:
- Novelty (new and not disclosed previously)
- Inventive Step (non-obvious advancement)
- Industrial Applicability (practical utility)
3. Prior Art Search Before Patent Filing
- Researchers should conduct a comprehensive patent search using databases such as the World Intellectual Property Organization PATENTSCOPE and the Indian Patent Office databases to ensure originality.
4. Types of Patent Applications
- Provisional Patent Application
- Complete Specification Patent
- National Patent Filing
- International Patent Filing through the Patent Cooperation Treaty mechanism
5. Patent Drafting Methodology
- A patent document must include:
- Title of Invention
- Abstract
- Technical Field
- Background
- Detailed Description
- Drawings/Flowcharts
- Claims (most critical section)
6. Copyright Protection for Academic Works
- Copyright safeguards:
- Research papers
- Books and study materials
- Software source code
- Multimedia educational content
- E-learning modules and digital resources
7. Copyright Registration Process
- Copyright protection exists upon creation, but registration provides stronger legal evidence of ownership and facilitates dispute resolution.
8. AI-Generated Content and Ownership Challenges
- The emergence of Generative AI raises questions regarding authorship, originality, ownership rights, and legal protection of AI-assisted works.
9. Technology Transfer and Commercialization
- Patents and copyrights can be monetized through:
- Licensing agreements
- Industry collaborations
- Startups and spin-off companies
- Royalty-based commercialization
10. Role of Faculty in IPR Generation
- Faculty members should transform research projects, innovative teaching methodologies, software applications, and product prototypes into protected intellectual assets, thereby enhancing institutional innovation rankings.
