Course Structure Overview
The B.Tech in Education program at The Assam Royal Global University Guwahati spans four years and consists of eight semesters. Each semester is designed to build upon the previous one, ensuring a comprehensive understanding of educational principles and practices.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | MATH101 | Mathematics for Engineers | 3-0-0-3 | - |
| 1 | PHYS101 | Physics for Engineering | 3-0-0-3 | - |
| 1 | CHEM101 | Chemistry for Engineers | 3-0-0-3 | - |
| 1 | CS101 | Introduction to Computer Science | 2-0-2-4 | - |
| 1 | ENG101 | English for Engineers | 3-0-0-3 | - |
| 1 | EDU101 | Introduction to Education | 2-0-0-2 | - |
| 2 | MATH201 | Advanced Mathematics | 3-0-0-3 | MATH101 |
| 2 | PHYS201 | Thermodynamics and Heat Transfer | 3-0-0-3 | PHYS101 |
| 2 | CHEM201 | Organic Chemistry | 3-0-0-3 | CHEM101 |
| 2 | CS201 | Data Structures and Algorithms | 2-0-2-4 | CS101 |
| 2 | EDU201 | Educational Psychology | 2-0-0-2 | EDU101 |
| 3 | MATH301 | Statistics and Probability | 3-0-0-3 | MATH201 |
| 3 | PHYS301 | Electromagnetic Fields | 3-0-0-3 | PHYS201 |
| 3 | CHEM301 | Analytical Chemistry | 3-0-0-3 | CHEM201 |
| 3 | CS301 | Database Systems | 2-0-2-4 | CS201 |
| 3 | EDU301 | Curriculum Planning and Design | 2-0-0-2 | EDU201 |
| 4 | MATH401 | Numerical Methods | 3-0-0-3 | MATH301 |
| 4 | PHYS401 | Quantum Mechanics | 3-0-0-3 | PHYS301 |
| 4 | CHEM401 | Physical Chemistry | 3-0-0-3 | CHEM301 |
| 4 | CS401 | Software Engineering | 2-0-2-4 | CS301 |
| 4 | EDU401 | Educational Technology | 2-0-0-2 | EDU301 |
| 5 | MATH501 | Operations Research | 3-0-0-3 | MATH401 |
| 5 | PHYS501 | Optics and Lasers | 3-0-0-3 | PHYS401 |
| 5 | CHEM501 | Industrial Chemistry | 3-0-0-3 | CHEM401 |
| 5 | CS501 | Machine Learning | 2-0-2-4 | CS401 |
| 5 | EDU501 | Assessment and Evaluation Techniques | 2-0-0-2 | EDU401 |
| 6 | MATH601 | Mathematical Modeling | 3-0-0-3 | MATH501 |
| 6 | PHYS601 | Plasma Physics | 3-0-0-3 | PHYS501 |
| 6 | CHEM601 | Biochemistry | 3-0-0-3 | CHEM501 |
| 6 | CS601 | Big Data Analytics | 2-0-2-4 | CS501 |
| 6 | EDU601 | Educational Leadership and Management | 2-0-0-2 | EDU501 |
| 7 | MATH701 | Advanced Calculus | 3-0-0-3 | MATH601 |
| 7 | PHYS701 | Condensed Matter Physics | 3-0-0-3 | PHYS601 |
| 7 | CHEM701 | Environmental Chemistry | 3-0-0-3 | CHEM601 |
| 7 | CS701 | Artificial Intelligence | 2-0-2-4 | CS601 |
| 7 | EDU701 | Special Education and Inclusive Practices | 2-0-0-2 | EDU601 |
| 8 | MATH801 | Research Methodology | 3-0-0-3 | MATH701 |
| 8 | PHYS801 | Nuclear Physics | 3-0-0-3 | PHYS701 |
| 8 | CHEM801 | Materials Science | 3-0-0-3 | CHEM701 |
| 8 | CS801 | Capstone Project in Educational Technology | 2-0-4-6 | CS701 |
| 8 | EDU801 | Final Thesis in Education | 2-0-0-4 | EDU701 |
Advanced Departmental Elective Courses
AI in Education: This course explores how artificial intelligence can revolutionize teaching and learning processes. Students learn to design AI-driven educational tools, analyze student behavior using machine learning algorithms, and create personalized learning experiences tailored to individual needs.
Design Thinking for Educators: Focused on applying human-centered design principles in educational settings, this course teaches students how to identify problems, ideate solutions, prototype concepts, and implement changes that improve the learning experience. The curriculum includes real-world case studies from schools and universities around the world.
Learning Analytics: This course delves into the use of data analytics in education, enabling students to interpret large datasets related to student performance, engagement, and retention. Students gain hands-on experience with tools like Tableau, Power BI, and Python-based libraries such as Pandas and NumPy.
EdTech Startup Ecosystem: Designed for aspiring entrepreneurs, this elective provides insights into building successful startups in the education technology space. Topics include business models, funding strategies, legal frameworks, and marketing techniques specific to EdTech ventures.
Cognitive Science of Learning: Combining psychology, neuroscience, and computer science, this course examines how the brain processes information during learning. Students explore theories of memory, attention, and problem-solving while developing practical applications for classroom instruction.
Global Educational Policy: This course analyzes international educational policies and their impact on local systems. Students study comparative frameworks from countries like Finland, Singapore, and South Korea, understanding how policy decisions shape access, equity, and quality in education.
Mobile Learning Technologies: With the proliferation of smartphones and tablets, this elective focuses on developing mobile applications for educational purposes. Students learn about responsive design, user interface (UI) principles, and content delivery strategies tailored for mobile environments.
Virtual Reality in Education: Exploring immersive technologies, this course introduces students to VR development platforms and their applications in education. From virtual field trips to simulations of complex scientific phenomena, students create interactive learning experiences that enhance comprehension.
Open Educational Resources (OER): This course teaches how to develop, curate, and share open educational materials. Students learn about licensing frameworks, digital repositories, and community-driven initiatives that promote free access to quality education resources.
Parental Engagement Strategies: Understanding the role of parents in student success, this elective provides strategies for building effective partnerships between educators and families. Students explore communication techniques, cultural sensitivity, and collaborative planning methods that support learning outcomes.
Project-Based Learning Philosophy
The department emphasizes project-based learning as a core pedagogical approach. Projects are designed to be interdisciplinary, allowing students to integrate knowledge from various domains while solving real-world challenges. Mini-projects begin in the second year and culminate in a final-year thesis or capstone project.
Mini-projects are typically completed over one semester and involve small teams of 3-5 students working under faculty supervision. These projects focus on developing specific skills such as research methodology, data analysis, presentation techniques, and teamwork. Evaluation criteria include innovation, feasibility, impact assessment, and peer feedback.
The final-year thesis is a substantial piece of original research that allows students to explore a topic in depth. Students select their topics in consultation with faculty advisors, ensuring alignment with current trends and research needs. The thesis must demonstrate critical thinking, scholarly rigor, and practical relevance. Faculty mentors guide students through the entire process, from literature review to data collection, analysis, and writing.
Project selection is done through a formal process involving proposal submission, faculty review, and approval. Students are encouraged to propose projects that align with their interests and career goals, ensuring maximum engagement and motivation throughout the research journey.