Daily Arxiv

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CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

Ada-TransGNN: An Air Quality Prediction Model Based On Adaptive Graph Convolutional Networks

Unlearning as Ablation: Toward a Falsifiable Benchmark for Generative Scientific Discovery

Consistent Opponent Modeling of Static Opponents in Imperfect-Information Games

Finding Outliers in a Haystack: Anomaly Detection for Large Pointcloud Scenes

Agentic AI for Software: thoughts from Software Engineering community

Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs

Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning

Dream to Chat: Model-based Reinforcement Learning on Dialogues with User Belief Modeling

A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems

Generative Artificial Intelligence and Agents in Research and Teaching

CALR: Corrective Adaptive Low-Rank Decomposition for Efficient Large Language Model Layer Compression

Comparative Analysis of UAV Path Planning Algorithms for Efficient Navigation in Urban 3D Environments

Retrieval Enhanced Feedback via In-context Neural Error-book

From Confidence to Collapse in LLM Factual Robustness

On Task Vectors and Gradients

Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model

DLLMQuant: Quantizing Diffusion-based Large Language Models

LLM-Enhanced Linear Autoencoders for Recommendation

Leveraging GNN to Enhance MEF Method in Predicting ENSO

Uncertainty-Guided Face Matting for Occlusion-Aware Face Transformation

New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants

Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems

SKA-Bench: A Fine-Grained Benchmark for Evaluating Structured Knowledge Understanding of LLMs

Apple Intelligence Foundation Language Models: Tech Report 2025

SE-VLN: A Self-Evolving Vision-Language Navigation Framework Based on Multimodal Large Language Models

Demographic-aware fine-grained classification of pediatric wrist fractures

Krul: Efficient State Restoration for Multi-turn Conversations with Dynamic Cross-layer KV Sharing

Solar Altitude Guided Scene Illumination

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning

Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models

EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion

RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection

Revisiting SSL for sound event detection: complementary fusion and adaptive post-processing

Concept-Guided Interpretability via Neural Chunking

Unveiling the Landscape of LLM Deployment in the Wild: An Empirical Study

An Ontology-Driven Graph RAG for Legal Norms: A Hierarchical, Temporal, and Deterministic Approach

Prefill-level Jailbreak: A Black-Box Risk Analysis of Large Language Models

Video CLIP Model for Multi-View Echocardiography Interpretation

A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Disease Detection from Retinal Fundus Images

M$^2$IV: Towards Efficient and Fine-grained Multimodal In-Context Learning via Representation Engineering

Noise-based reward-modulated learning

Faster Parameter-Efficient Tuning with Token Redundancy Reduction

UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials

Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems

Large Language Models Badly Generalize across Option Length, Problem Types, and Irrelevant Noun Replacements

TableTalk: Scaffolding Spreadsheet Development with a Language Agent

StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis

Generative Artificial Intelligence-Supported Pentesting: A Comparison between Claude Opus, GPT-4, and Copilot

Safe Multiagent Coordination via Entropic Exploration

TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use

Cultural Dimensions of AI Perception: Charting Expectations, Risks, Benefits, Tradeoffs, and Value in Germany and China

CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers

Perception Gaps in Risk, Benefit, and Value Between Experts and Public Challenge Socially Accepted AI

Hierarchical Object-Oriented POMDP Planning for Object Rearrangement

From Intents to Conversations: Generating Intent-Driven Dialogues with Contrastive Learning for Multi-Turn Classification

Secure Reinforcement Learning via Shuffle Privacy Model

Overcoming label shift with target-aware federated learning

Benchmarking XAI Explanations with Human-Aligned Evaluations

HonestCyberEval: An AI Cyber Risk Benchmark for Automated Software Exploitation

Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning

GeNet: A Multimodal LLM-Based Co-Pilot for Network Topology and Configuration

ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context

Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL

Exploring the Robustness of Language Models for Tabular Question Answering via Attention Analysis

Learning county from pixels: corn yield prediction with attention-weighted multiple instance learning

Memory augment is All You Need for image restoration

Rethinking Distribution Shifts: Empirical Analysis and Inductive Modeling for Tabular Data

DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models

Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

ST-Raptor: LLM-Powered Semi-Structured Table Question Answering

Route-and-Execute: Auditable Model-Card Matching and Specialty-Level Deployment

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

Response and Prompt Evaluation to Prevent Parasocial Relationships with Chatbots

Profile-Aware Maneuvering: A Dynamic Multi-Agent System for Robust GAIA Problem Solving by AWorld

Multi-Agent LLMs as Ethics Advocates for AI-Based Systems

Feature-Guided Neighbor Selection for Non-Expert Evaluation of Model Predictions

Architecting Clinical Collaboration: Multi-Agent Reasoning Systems for Multimodal Medical VQA

mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation

Jigsaw-Puzzles: From Seeing to Understanding to Reasoning in Vision-Language Models

The Influence of Human-inspired Agentic Sophistication in LLM-driven Strategic Reasoners

YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models

Consensus in Motion: A Case of Dynamic Rationality of Sequential Learning in Probability Aggregation

Can Large Language Models Act as Ensembler for Multi-GNNs?

Pessimistic Iterative Planning with RNNs for Robust POMDPs

Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding

Integrating Large Language Model for Improved Causal Discovery

A Survey on Causal Discovery: Theory and Practice

Generative Interfaces for Language Models

Interpolating Speaker Identities in Embedding Space for Data Expansion

VibeVoice Technical Report

LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding

Understanding Tool-Integrated Reasoning

Emotions as Ambiguity-aware Ordinal Representations

Real-Time Model Checking for Closed-Loop Robot Reactive Planning

New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants

Created by

Haebom

저자

Sergio Rojas-Galeano

개요

본 연구는 교육 환경에서 AI 코딩 보조 도구의 도입이 초보 프로그래머들에게 미치는 영향을 탐구하는 탐색적 연구입니다. 20명의 학생들을 대상으로 AI 지원을 받는 프로그래밍 과제와 AI 지원 없이 문제를 확장하는 과제를 통해 학생들의 인식을 조사했습니다. 결과적으로 학생들은 초기 단계에서 AI 도구가 코드 개념 이해와 자신감 향상에 도움이 된다고 인식했지만, AI 지원 없이 작업하도록 했을 때 어려움을 겪었고, 기본적인 지식 전달의 부족과 AI 도구에 대한 과도한 의존성을 보였습니다.

시사점, 한계점

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시사점: AI 코딩 보조 도구는 초보 프로그래머의 코드 이해와 자신감 향상에 도움이 될 수 있지만, 과도한 의존으로 인해 기본 프로그래밍 능력 향상에 방해가 될 수 있음을 시사합니다. 따라서 AI 도구를 효과적으로 통합하여 핵심 프로그래밍 기술을 향상시키는 새로운 교육 방식이 필요합니다.

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한계점: 20명의 학생을 대상으로 한 소규모 연구이므로 결과의 일반화에는 제한이 있습니다. 또한, 특정 AI 코딩 보조 도구와 교육 환경에 국한된 결과이므로 다른 도구나 환경에서는 결과가 다를 수 있습니다.

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