arXiv:2601. 18685v4 Announce Type: replace-cross Abstract: The capabilities of generative AI in mathematics education are rapidly evolving, posing significant challenges for research to keep pace.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.
arXiv:2605. 21629v2 Announce Type: replace-cross Abstract: How much have students' ordinary learning processes shifted in response to generative AI, and how does that affect their durable learning outcomes?
arXiv:2606. 12441v1 Announce Type: cross Abstract: The four dominant learning theories of behaviorism, cognitivism, constructivism, and connectivism show significant conceptual limitations as generative artificial intelligence (AI) proliferates in educational settings.
arXiv:2604. 27618v2 Announce Type: replace-cross Abstract: Understanding the impact of large language models (LLMs) on mathematics education requires data on LLMs' mathematical performance and biases.
arXiv:2606. 24104v1 Announce Type: cross Abstract: Generative artificial intelligence(GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and social sciences(HSS), where learning outcomes are commonly expressed through written and interpretive forms that align closely with GenAI's capabilities.
arXiv:2607. 15247v1 Announce Type: new Abstract: Evidence synthesis is crucial for turning primary research into reliable knowledge for science, medicine, education, and policy.
arXiv:2608. 16118v1 Announce Type: new Abstract: How should we assess whether large language models can perform mathematical invention?