In the era of ICT, every sphere of human life, especially the education sector, is being influenced and regulated by technology. Future societies will require more engaging, effective, and efficient educational experiences by leveraging digital tools and resources. Educational technology (EdTech) is a rapidly growing field that offers a range of career opportunities for individuals with a passion for education and technology. The 4th and 5th industrial revolutions is having a profound impact on education, and EdTech is playing a key role in shaping its future.
The Department of Educational Technology and Engineering (EdTE) under the Faculty of Digital Transformation Engineering prepares students on how to integrate technology into the curriculum, educational system, or workplace to increase learning and productivity. These programs typically cover topics such as instructional design and technology, digital media, educational psychology, assessment, administration and e-management, blended learning, programming languages, cloud computing, cyber security, mobile and web application development, and ICT. Rather, it supports evaluating existing and emerging innovative technologies that allow students to integrate pedagogical practices into the workplace. The curriculum is meant to provide students of the 21st century with the abilities necessary for success in both education and developing innovative technology industries.
Educational technology and Engineering has the potential to revolutionize education by making learning more accessible, personalized, and interactive. Additionally, EdTE can support collaboration and communication among students and teachers, as well as provide new ways to assess and evaluate student learning. In addition, AI and other advanced technologies are being used to support the development and delivery of more effective and efficient educational content and resources. This is an emerging sector with excellent employment prospects, which are expected to improve further in the short-to-medium term.
This program's scope includes finding answers to interdisciplinary issues with an emphasis on overall engineering and management approaches, as well as establishing learning concepts for education and technology and implementing them in real-world settings. Overall, an undergraduate program in Educational Technology and Engineering provides students with a solid foundation in technology and education. It prepares them for a variety of careers in the rapidly growing field of educational technology. The department has state-of-the-art infrastructure and facilities in its labs. With the assistance, collaboration, and criticism from academics and industry professionals, the curriculum has been developed based on the needs of the future world.
To know more on EdTE BDU, please navigate through the links.
» Vision and Mission
» History
» Contact
» Message From Chairman
» Why EdTE@BDU?
» Facilities
Date | Title | View/Download |
---|---|---|
29/12/2024 | সংশোধিত বিজ্ঞপ্তি | View |
17/12/2024 | Thesis/Project Notice | View |
27/11/2024 | Notice | View |
19/11/2024 | ২০১৯-২০ সেশনের প্রি-ডিফেন্সেরবিজ্ঞপ্তি | View |
No available data found
1 | Enhanced thyroid disease prediction using ensemble machine learning: a high‑accuracy approach with feature selection and class balancing in Discover Artificial Intelligence ,Volume 5 , Issue article number 9,2025 [Paper Link] |
2 | Query Expansion for Bangla Search Engine Pipilika in 2020 IEEE Region 10 Symposium (TENSYMP) ,2020 [Paper Link] |
3 | Bangla text normalization for text-to-speech synthesizer using machine learning algorithms in Journal of King Saud University - Computer and Information Sciences ,Volume 36 , Issue 1,2024 [Paper Link] |
4 | Evaluation of THz Wave Transmission Performance in TOPAS-based Heptagonal Photonic Crystal Fiber (He-PCF) in Heliyon ,2024 |
5 | A comprehensive analysis of feature ranking-based fish disease recognition in ARRAY ,2023 |
6 | Addressing agricultural challenges: An identification of best feature selection techniques for dragon fruit disease recognition. in ARRAY ,2023 |
7 | A Transfer Learning Approach to the Development of an Automation System for Recognizing Guava Disease Using CNN Models for Feasible Fruit Production. in In International Conference on Hybrid Intelligent Systems ,2022 |
8 | RoseNet: Rose leave dataset for the development of an automation system to recognize the diseases of rose. in Data in Brief ,Volume 44 ,2022 |
9 | VegNet: An organized dataset of cauliflower disease for a sustainable agro-based automation system in Data in Brief ,Volume 43 ,2022 |
10 | Feature Ranking Based Carrot Disease Recognition Using MIFS Method in Hybrid Intelligent Systems: 21st International Conference on Hybrid Intelligent Systems (HIS 2021) ,2021 |
11 | A Machine Learning Approach to Detect the Brain Stroke Disease in 4th International Conference on Smart Systems and Inventive Technology (ICSSIT) ,2022 |
12 | Sunflower Diseases Recognition Using Computer Vision-Based Approach in 2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) ,2021 |
13 | A comprehensive guava leaves and fruits dataset for guava disease recognition in Data in Brief ,Volume 42 ,2022 |
14 | An extensive sunflower dataset representation for successful identification and classification of sunflower diseases in Data in Brief ,Volume 42 ,2022 |
No available data found
No available data found