arXiv AI By Neha Rani, Vu Minh Anh Le, Austin M. Spangler, Erta Cenko

Cognitive Skills in the Age of AI: Computing Students and Experts Perceptions

Read the original on arXiv AI →

The study examines how AI’s growing presence in computing affects the perceived importance of cognitive skills among students and experts. Findings suggest that most cognitive skills will become less critical in an AI‑rich future, while critical thinking remains essential. Interviews provide reasons for these shifts and offer guidance for preparing future computing students.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

Hugging Face Trending Papers
Sep 2

Addressing Trust in AI Systems through Education: A Didactic Perspective

The paper identifies two main challenges in machine learning education: opaque tools that give learners only a superficial grasp of ML and hinder the development of calibrated trust in AI systems. It introduces ICE‑T, a didactic framework that combines intermodal transfer, computational thinking, and explanatory thinking to provide representational richness, graduated process control, and error contextualization. By linking these facets to trust‑calibration literature, the authors argue that trust should be an explicit educational goal and that ICE‑T offers a scalable method to achieve it.

arXiv AI
Sep 3

Addressing Trust in AI Systems through Education: A Didactic Perspective

The paper introduces ICE-T, a didactic framework designed to improve trust in AI systems through education. It combines intermodal transfer, computational thinking, and explanatory thinking to address the opacity of machine learning tools. By linking these facets to research on algorithm aversion and AI literacy, the authors argue that trust calibration should be an explicit educational goal.

By Pierre Haritz, Hendrik Krone, Thomas Liebig