The curriculum of the B.Tech in Education program at Nayanta University Pune is designed to provide a holistic and progressive learning experience that balances theoretical knowledge with practical application. The program spans eight semesters, with each semester building upon previous learnings and introducing new concepts.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | EDU101 | Introduction to Education | 3-0-0-3 | - |
| 1 | EDU102 | Foundations of Human Development | 3-0-0-3 | - |
| 1 | MAT101 | Mathematics for Educators | 4-0-0-4 | - |
| 1 | PHY101 | Physics for Education | 3-0-0-3 | - |
| 1 | CHE101 | Chemistry for Education | 3-0-0-3 | - |
| 1 | BIO101 | Biology for Education | 3-0-0-3 | - |
| 1 | EDU103 | Psychology of Learning | 3-0-0-3 | - |
| 2 | EDU201 | Curriculum Design and Planning | 3-0-0-3 | EDU101 |
| 2 | EDU202 | Educational Assessment Techniques | 3-0-0-3 | EDU101 |
| 2 | MAT201 | Statistics for Education | 4-0-0-4 | MAT101 |
| 2 | PHY201 | Advanced Physics Concepts | 3-0-0-3 | PHY101 |
| 2 | CHE201 | Organic Chemistry for Education | 3-0-0-3 | CHE101 |
| 2 | BIO201 | Genetics and Evolution | 3-0-0-3 | BIO101 |
| 2 | EDU203 | Instructional Strategies in Education | 3-0-0-3 | EDU101 |
| 3 | EDU301 | Educational Technology Integration | 3-0-0-3 | EDU201 |
| 3 | EDU302 | Research Methods in Education | 3-0-0-3 | EDU202 |
| 3 | MAT301 | Calculus for Educational Analytics | 4-0-0-4 | MAT201 |
| 3 | PHY301 | Quantum Mechanics in Learning | 3-0-0-3 | PHY201 |
| 3 | CHE301 | Chemical Applications in Education | 3-0-0-3 | CHE201 |
| 3 | BIO301 | Biological Foundations of Learning | 3-0-0-3 | BIO201 |
| 3 | EDU303 | Classroom Management Techniques | 3-0-0-3 | EDU203 |
| 4 | EDU401 | Digital Learning Platforms | 3-0-0-3 | EDU301 |
| 4 | EDU402 | Educational Policy and Governance | 3-0-0-3 | EDU302 |
| 4 | MAT401 | Data Science for Education | 4-0-0-4 | MAT301 |
| 4 | PHY401 | Modern Physics in Educational Contexts | 3-0-0-3 | PHY301 |
| 4 | CHE401 | Environmental Chemistry and Sustainability | 3-0-0-3 | CHE301 |
| 4 | BIO401 | Neuroscience of Learning | 3-0-0-3 | BIO301 |
| 4 | EDU403 | Leadership in Education | 3-0-0-3 | EDU303 |
| 5 | EDU501 | Advanced Curriculum Design | 3-0-0-3 | EDU401 |
| 5 | EDU502 | Educational Research Projects | 3-0-0-3 | EDU402 |
| 5 | MAT501 | Machine Learning in Education | 4-0-0-4 | MAT401 |
| 5 | PHY501 | Applied Physics in Teaching | 3-0-0-3 | PHY401 |
| 5 | CHE501 | Nanochemistry and Educational Applications | 3-0-0-3 | CHE401 |
| 5 | BIO501 | Bioinformatics in Learning | 3-0-0-3 | BIO401 |
| 5 | EDU503 | Global Education Perspectives | 3-0-0-3 | EDU403 |
| 6 | EDU601 | Specialized Educational Interventions | 3-0-0-3 | EDU501 |
| 6 | EDU602 | Educational Innovation Labs | 3-0-0-3 | EDU502 |
| 6 | MAT601 | Advanced Analytics for Education | 4-0-0-4 | MAT501 |
| 6 | PHY601 | Optics and Visual Learning | 3-0-0-3 | PHY501 |
| 6 | CHE601 | Green Chemistry in Education | 3-0-0-3 | CHE501 |
| 6 | BIO601 | Systems Biology in Learning | 3-0-0-3 | BIO501 |
| 6 | EDU603 | Entrepreneurship in Education | 3-0-0-3 | EDU503 |
| 7 | EDU701 | Capstone Research Project | 3-0-0-3 | EDU601 |
| 7 | EDU702 | Internship and Fieldwork | 3-0-0-3 | EDU602 |
| 7 | MAT701 | Advanced Statistical Modeling | 4-0-0-4 | MAT601 |
| 7 | PHY701 | Advanced Physics Applications | 3-0-0-3 | PHY601 |
| 7 | CHE701 | Chemical Processes in Education | 3-0-0-3 | CHE601 |
| 7 | BIO701 | Neuroplasticity and Learning | 3-0-0-3 | BIO601 |
| 7 | EDU703 | Educational Policy Analysis | 3-0-0-3 | EDU603 |
| 8 | EDU801 | Final Year Thesis Project | 3-0-0-3 | EDU701 |
| 8 | EDU802 | Professional Portfolio Development | 3-0-0-3 | EDU702 |
| 8 | MAT801 | Educational Data Science Capstone | 4-0-0-4 | MAT701 |
| 8 | PHY801 | Physics of Modern Teaching | 3-0-0-3 | PHY701 |
| 8 | CHE801 | Chemistry in Educational Environments | 3-0-0-3 | CHE701 |
| 8 | BIO801 | Biology of Learning and Memory | 3-0-0-3 | BIO701 |
| 8 | EDU803 | Leadership in Educational Innovation | 3-0-0-3 | EDU703 |
Advanced departmental electives form a significant part of the curriculum, offering students opportunities to specialize in areas that align with their interests and career goals. Below are detailed descriptions of some of these courses:
Educational Technology Integration (EDU501)
This course explores how modern educational technologies such as virtual reality, augmented reality, and AI can be effectively integrated into traditional classroom settings. Students will learn to develop interactive learning modules, design digital curricula, and evaluate the impact of technological tools on student engagement and performance.
Educational Research Methods (EDU502)
This course provides students with a comprehensive understanding of both qualitative and quantitative research methodologies in education. It covers literature review techniques, experimental design, data collection methods, and statistical analysis. Students will complete an independent research project that contributes to the field of educational science.
Machine Learning in Education (MAT501)
This course introduces students to machine learning concepts and their applications in education. Topics include predictive analytics, personalized learning algorithms, natural language processing for educational content, and automated assessment systems. Students will work with real datasets to build models that improve learning outcomes.
Global Education Perspectives (EDU503)
This course examines the diversity of educational systems around the world, focusing on cultural influences, policy frameworks, and best practices from different countries. Students will engage in comparative case studies, cross-cultural research projects, and international collaboration initiatives.
Educational Innovation Labs (EDU602)
This hands-on course encourages students to experiment with emerging educational tools and methodologies. Through lab sessions, students will prototype new learning technologies, test innovative teaching strategies, and collaborate with industry partners on real-world projects that address current challenges in education.
Advanced Analytics for Education (MAT601)
This course teaches advanced statistical techniques used in educational research and practice. Students will learn to analyze large datasets using Python and R, interpret results from complex models, and apply findings to improve educational outcomes across various contexts.
Neuroscience of Learning (BIO401)
This interdisciplinary course bridges the gap between biology and education by exploring how brain function affects learning processes. Students will study neuroplasticity, cognitive development, and neural correlates of memory and attention, applying this knowledge to enhance teaching effectiveness.
Educational Policy Analysis (EDU703)
This course equips students with the skills needed to analyze and critique educational policies at local, national, and international levels. Students will examine policy documents, conduct impact assessments, and propose evidence-based solutions for improving educational equity and access.
Leadership in Educational Innovation (EDU803)
This capstone course prepares students for leadership roles in educational organizations by focusing on strategic planning, change management, innovation implementation, and stakeholder engagement. Students will complete a final project that demonstrates their ability to lead transformative initiatives in the field of education.
Project-based learning is central to the curriculum, with students engaging in both mini-projects throughout their academic journey and a comprehensive final-year thesis or capstone project. These projects are designed to be relevant, impactful, and aligned with current educational challenges and trends.
The structure of these projects includes planning phases, execution periods, peer review sessions, and presentations to faculty and industry partners. Evaluation criteria emphasize creativity, rigor, relevance, and potential for real-world application. Students work closely with assigned mentors who guide them through each stage of the project lifecycle.