Edutopia

Scaffolding Deeper Learning With Recall Activities

When students are asked to remember and explain relevant knowledge just before applying it, they arrive at a more concrete ...
IEEE

Enhancing Task-Incremental Learning via a Prompt-Based Hybrid Convolutional Neural Networks (CNNs)-Vision Transformer (ViT) Framework

Abstract: Artificial neural network (ANN) models are widely used in various fields such as image classification, multi-object detection, intent prediction, military applications, and natural language ...
Frontiers

Are S.M.A.R.T goals really smart? The psychological effects of goal-setting in a learning task

Aim: Specific, Measurable, Achievable, Realistic, Time-bound (SMART) goals are commonly used in educational settings as a strategy to optimise learning. However, research and theory suggest that such ...
GitHub

Scaling Agentic Reinforcement Learning with a Multi-Turn, Multi-Task Framework

For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see AgentBench FC. For reproducing the ...
Scientific Research Publishing

Research on the Optimization Strategy of Integrating VR into Ideological and Political Courses in Colleges and Universities from the Perspective of College Students

Traditional VR instruction often places students directly into immersive experiences without preparation, resulting in a cognitive “cold start”. To resolve this issue, the first step in the ...

How curriculum, assessment, and policy are reshaping school learning

Explore how curriculum, assessment, and policy changes are fostering independent learning in schools worldwide.
IEEE

Multi-UAV Dynamic Task Assignment Based on Event-Triggered Graph Reinforcement Learning Under Weak Communication

Abstract: This paper addresses the dynamic task assignment problem for multiple uncrewed aerial vehicles (UAVs) operating under weak communication. Existing learning-based methods face two primary ...