AIMC Topic: Learning

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Judgments of learning distinguish humans from large language models in predicting memory.

Scientific reports
Large language models (LLMs) increasingly mimic human cognition in various language-based tasks. However, their capacity for metacognition-particularly in predicting memory performance-remains unexplored. Here, we introduce a cross-agent prediction m...

Integrating AI in Pakistani ESL classrooms: Teachers' practices, perspectives, and impact on student performance.

PloS one
The global rise of Artificial Intelligence (AI) in English as a Second Language (ESL) education has shown promise, yet its application in resource-constrained contexts like Pakistan remains underexplored. This study examines the integration of AI too...

AI acceptance and Chinese EFL learners' behavioral engagement with mediating effects of motivation.

Scientific reports
As artificial intelligence (AI) technologies become increasingly integrated into education, understanding how they influence learners' engagement is essential for effective pedagogy. This study examines the motivational mechanisms by which Chinese EF...

Route-centric ant-inspired memories enable panoramic route-following in a car-like robot.

Nature communications
Solitary foraging ants excel at route following using minimal neural resources, Robots don't. Recent biological studies proposed lateralized, nest-centric memories to explain ants' direct visual homing but did not address how ants follow curved visua...

Online reinforcement learning of state representation in recurrent network supported by the power of random feedback and biological constraints.

eLife
Representation of external and internal states in the brain plays a critical role in enabling suitable behavior. Recent studies suggest that state representation and state value can be simultaneously learned through Temporal-Difference-Reinforcement-...

Learning and spiking dynamics in brain-like nanoscale networks.

Nanoscale horizons
Neuromorphic approaches to computation are driven by both the low-power operation of the biological brain and ever-increasing energy consumption of modern computing systems. Percolating networks of nanoparticles are promising candidates for self-asse...

Analysis and optimization of student learning paths based on CRNN and sequential data.

PloS one
The analysis and optimization of student learning paths have become increasingly critical in modern education, as they enable personalized learning experiences and improved academic outcomes. However, existing approaches often struggle to effectively...

Perception of Medical Undergraduates on Artificial Intelligence in Medical Education: Qualitative Exploration.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) has revolutionized medical education by delivering tools that enhance and optimize learning. However, there is limited research on the medical students' perceptions regarding the effectiveness of AI as a learn...

Observing a robot peer's failures facilitates students' classroom learning.

Science robotics
According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students' knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain t...

Kinship verification via correlation calculation-based multi-task learning.

PloS one
Previous studies have demonstrated that metric learning approaches yield remarkable performance in the field of kinship verification. Nevertheless, a prevalent limitation of most existing methods lies in their over-reliance on learning exclusively fr...