Task-Driven Approach and Knowledge Transfer in Practical Courses Teaching
Liangliang Kong, Lin Chen
Available Online June 2017.
- https://doi.org/10.2991/icmess-17.2017.126How to use a DOI?
- task-driven; knowledge transfer; simulator; neural networks
- This paper analyzes the task-driven teaching and knowledge transfer at first, and then proposes a combined teaching approach based on both of them according to the characteristics of practical courses. Taking the course of computer architecture practice as an example, it explains the application of the proposed approach in teaching. Firstly, teaching content breaks down into tasks by teachers and students prepare related documents. Secondly, teachers make questions with the aim of achieving each task, and students are divided into several groups to solve the questions with the guidance of teachers. In this step, teachers may need to discuss with students or operate how to solve a problem in classroom. Finally, teachers make knowledge transfer to extend students' knowledge and enhance their interests of learning. Teachers tell students how to use the experimental data obtained before to implement and train a neural network to solve the problems of computer architecture, e.g. the estimation of performance of a target architecture or task scheduling in distributed systems. The feedback from teachers and students has shown the combined teaching approaching is an effective way to improve teaching effect for practical courses.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Liangliang Kong AU - Lin Chen PY - 2017/06 DA - 2017/06 TI - Task-Driven Approach and Knowledge Transfer in Practical Courses Teaching BT - 2017 International Conference on Management, Education and Social Science (ICMESS 2017) PB - Atlantis Press SP - 540 EP - 543 SN - 2352-5398 UR - https://doi.org/10.2991/icmess-17.2017.126 DO - https://doi.org/10.2991/icmess-17.2017.126 ID - Kong2017/06 ER -