Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Algorithms | 1 |
| Artificial Intelligence | 1 |
| Bias | 1 |
| Cognitive Psychology | 1 |
| Comprehension | 1 |
| Computer Science Education | 1 |
| Data Science | 1 |
| Difficulty Level | 1 |
| Engineering Education | 1 |
| Ethics | 1 |
| Introductory Courses | 1 |
| More ▼ | |
Source
| IEEE Transactions on Education | 1 |
Author
| Hazzan, Orit | 1 |
| Mike, Koby | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkMike, Koby; Hazzan, Orit – IEEE Transactions on Education, 2023
Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect…
Descriptors: Engineering Education, Computer Science Education, Data Science, Introductory Courses
