A Practice-Oriented Computational Thinking Framework for Teaching Neural Networks to Working Professionals
Background: Conventional machine learning courses are usually designed for academic learners, instead of working professionals. This study addresses this gap by proposing a new instructional framework that builds practical computational thinking skills for developing neural network models on busines...
Saved in:
| Main Author: | Jing Tian |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | AI |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-2688/6/7/140 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
PROFESSIONAL SPECIFICITY OF CONCEPTUAL THINKING
by: S. A. Gilmanov
Published: (2017-12-01) -
Teaching design students machine learning to enhance motivation for learning computational thinking skills
by: Hung-Hsiang Wang, et al.
Published: (2024-11-01) -
AI Thinking: a framework for rethinking artificial intelligence in practice
by: Denis Newman-Griffis
Published: (2025-01-01) -
Bringing computational thinking into classrooms: a systematic review on supporting teachers in integrating computational thinking into K-12 classrooms
by: Zhichun Liu, et al.
Published: (2024-10-01) -
Implementation of personalized frameworks in computational thinking development: implications for teaching in software engineering
by: Josué Guevara-Reyes, et al.
Published: (2025-06-01)