The deep learning technologies define the technology that follows the concept of DL. The deep neural network (e.g., DNN), recurrent neural network (e.g., RNN), convolutional neural network (e.g., CNN) are some examples of the DL technologies.
Published in Chapter:
Deep Learning in Instructional Analysis, Design, Development, Implementation, and Evaluation (ADDIE)
Mahbubur Rahman (North American University, USA) and Mustafa Duran (North American University, USA)
Copyright: © 2022
|Pages: 16
DOI: 10.4018/978-1-7998-7776-9.ch005
Abstract
The authors emphasize the application scope of the deep learning (DL) technologies in the instructional analysis, design, development, implementation, and evaluation of the educational tools that can enhance the 21st-century modes and models of learning and instruction. The latest trend in the remote learning systems opens a wonderful opportunity for the DL technologies to be integrated with these systems that can impact the way of learning, teaching, design, and development of such systems. The DL technologies provide the data driven decisions and analytical outcomes that can be integrated with the educational technologies. The existing educational technologies and remote learning systems lack in such integrated DL services that can impact the overall education learning systems of the 21st century. The learners and instructors can also benefit from such DL-integrated educational tools. The authors expand further details on the application and implication of the DL services mentioned above in the chapter.