Mitigating the Base-Rate Neglect Cognitive Bias in Data Science Education
Orit Hazzan
How can machine learning educators help learners cope with the base rate neglect cognitive bias?
Computational Thinking in the Era of Data Science
Incorporating data thinking into computer science education.
The Base-Rate Neglect Cognitive Bias in Data Science
Using Bayes' Theorem, the correct answer to both the medical diagnosis problem and to the lion classification question, can be calculated.
Machine Learning: Out! Data Science: In!
We propose to stop teaching machine learning courses to populations whose core discipline is neither computer science nor mathematics and statistics.
Validity and Reliability in Data Science: An Interdisciplinary Perspective
We examine the essence of the components of data science, as well as their interrelations, from the educational perspective.
The Expression of the Rhetorical Triangle in Data Science
In data science, good storytelling means that data-driven solutions are communicated clearly, concisely, and directly to each relevant target audience group.
Reflection Pre-learning in Computer Science Courses
Our experience with reflection pre-learning in a MOOC on computational thinking that we developed and currently teach.
Changes in the Technion’s Teaching Strategies During the Pandemic
This post describes three significant changes that took place during the pandemic in the instructional strategies at the Technion – Israel Institute of Technology.
Framing the Description of the Shrinking Pipeline
The shrinking pipeline refers to the low percentages of women earning computer science academic degrees and holding faculty positions.
Shape the Future of Computing
ACM encourages its members to take a direct hand in shaping the future of the association. There are more ways than ever to get involved.
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