arXiv Machine Learning July 2, 2026 By Manuel Alonso-Carracedo (Universidade de Vigo, Spain, IFCAE, Universidade de Vigo, Spain), Ruben Fernandez-Boullon (Universidade de Vigo, Spain, IFCAE, Universidade de Vigo, Spain), Pedro Celard (Universidade de Vigo, Spain, IFCAE, Universidade de Vigo, Spain), Francisco J. Rodriguez-Martinez (Universidade de Vigo, Spain, IFCAE, Universidade de Vigo, Spain), Lorena Otero-Cerdeira (Universidade de Vigo, Spain, IFCAE, Universidade de Vigo, Spain)

CogTax: A Four-Level Cognitive Taxonomy for Command-Line Computing Education

Read the original on arXiv Machine Learning →

arXiv:2607. 00140v1 Announce Type: cross Abstract: As computing education expands beyond traditional programming into operational domains such as systems administration and command-line environments, existing pedagogical frameworks struggle to capture a dimension that is critical in these contexts: the real-world consequences of learner actions.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

Jul 3

Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach

arXiv:2607. 02432v1 Announce Type: new Abstract: Scalable and reliable grading of command-line examinations remains a challenge in computing education, where rising enrolments make manual marking difficult and rule-based autograders cannot handle partial credit, equivalent solutions, or syntactic variation.

By Manuel Alonso-Carracedo, Ruben Fernandez-Boullon, Pedro Celard, Francisco J. Rodriguez-Martinez, Lorena Otero-Cerdeira

llms robotics safety

arXiv AI

Aug 5

TACT: Taxonomy-Aligned Post-Training for Pedagogically Adaptive English Tutoring

arXiv:2608. 03952v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to provide conversational practice for English-as-a-second-language (ESL) learners.

By Dongjie Yang, Siyan Lin, Leixian Shen, Rui Sheng, Huamin Qu, Zixin Chen

llms fine-tuning benchmarks

arXiv AI

Jun 19

Measuring Curriculum Alignment across Topical Coverage, Competency, and Cognitive Depth: A Longitudinal Framework Applied to CS2013 and CS2023

arXiv:2606. 19469v1 Announce Type: new Abstract: Undergraduate computer science is governed by international curricular guidelines revised about once a decade, yet programs lack a reliable, reproducible way to measure how completely they cover the current guidelines and how that coverage shifts when the guidelines are restructured.

By Sherzod Turaev, Mary John, Saja Aldabet, Mamoun Awad, Nazar Zaki, Khaled Shuaib

safety

arXiv AI

Jun 18

From Memorization to Creation: Evaluating the Cognitive Depth of LLM-Generated Educational Questions

arXiv:2606. 18257v1 Announce Type: cross Abstract: While LLMs show promise in automating educational content creation, their ability to generate questions that stimulate higher-order thinking remains understudied.

By Xiaolong Wang, Zhe Zhao, Song Lai, Chaoli Zhang, Zijie Geng, Yu Tong, Ye Wei, Qingsong Wen

llms benchmarks safety

arXiv AI

Jun 17

LLM-as-Judge in Education: A Curriculum-Grounded Marking Pipeline

arXiv:2606. 17507v1 Announce Type: new Abstract: Generative AI and large language models (LLMs) are increasingly applied to question generation and automated assessment.

By Xiwei Xu, Chen Wang, Jacky Jiang, Phil Yang, Qian Fu, Mohan Dhall, Wenjie Zhang, Liming Zhu

llms safety

arXiv AI

Jun 9

Lost in the Flow with Code Talkers: Unveiling the Instruction-Tuning Tax of Large Language Models in Code Tasks

arXiv:2606. 08676v1 Announce Type: cross Abstract: AI coding assistants have significantly improved developer productivity by automatically suggesting code that aligns with user intent, and many of these tools are now integrated directly into Integrated Development Environments (IDEs).

By Shi Ying Chang, Chiok Yew Ho, Yichen Li, Yintong Huo

llms fine-tuning

Related stories

Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach

TACT: Taxonomy-Aligned Post-Training for Pedagogically Adaptive English Tutoring

Measuring Curriculum Alignment across Topical Coverage, Competency, and Cognitive Depth: A Longitudinal Framework Applied to CS2013 and CS2023

From Memorization to Creation: Evaluating the Cognitive Depth of LLM-Generated Educational Questions

LLM-as-Judge in Education: A Curriculum-Grounded Marking Pipeline

Lost in the Flow with Code Talkers: Unveiling the Instruction-Tuning Tax of Large Language Models in Code Tasks