Communications of the ACM
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From BLOG@CACM
Why Is It Hard to Define Data Science?
Data science can be described as a science, as a research paradigm, as a research method, as a discipline, as a workflow, and as a profession.
From BLOG@CACM
The Process-Object Duality in Computer Science and Data Science Education
The process-object duality has several educational implications for the design of teaching and learning processes.
From BLOG@CACM
Three Risks Facing Higher Education
The implications of COVID-19 for risk management in higher education.
From BLOG@CACM
Opportunities of Data Science Education
Considering the six new and exciting opportunities that data science presents.
From BLOG@CACM
Mitigating the Base-Rate Neglect Cognitive Bias in Data Science Education
How can machine learning educators help learners cope with the base rate neglect cognitive bias?
From BLOG@CACM
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.
From BLOG@CACM
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.
From BLOG@CACM
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.
From BLOG@CACM
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.
From BLOG@CACM
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.
From BLOG@CACM
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...
From BLOG@CACM
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.
From BLOG@CACM
Computational Thinking: The Discussion Continues
Perspectives on computational thinking.
From BLOG@CACM
Supervising a Doctoral Thesis: Lessons and Guidelines
Presenting 10 guidelines for supervising graduate students, focusing on the supervision process of doctoral students.
From BLOG@CACM
The Solar System from the Computational Thinking Perspective
We describe our choice of the solar system as one of the main illustrative examples used in our MOOC on computational thinking.
From BLOG@CACM
The Triad of Graduate Studies
The Research Community, Research Subject, and Research Process.
From BLOG@CACM
10 Tips for Implementing Executable Exams
The focus is on executable exams for an Introduction to Computer Science course.
From BLOG@CACM
A MERge Analysis of an Organizational Change: The Case of Internalization at Home
How the Technion assimilated its international activities into its other units’ activities and, at the same time, reduced operational costs related to its international...
From BLOG@CACM
New Social-Economic Trends in Computer Science Education
Considering new social-economic trends in Computer Science, Software Engineering, and Data Science education.
From BLOG@CACM