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Maria Korochkina; Kathleen Rastle – npj Science of Learning, 2025
Breaking down complex words into smaller meaningful units (e.g., "unhappy = un- + happy"), known as morphemes, is vital for skilled reading as it allows readers to rapidly compute word meanings. There is agreement that children rely on reading experience to acquire morphological knowledge in English; however, the nature of this…
Descriptors: Childrens Literature, Morphemes, Morphology (Languages), Reading Skills
Pablo Flores Romero; Kin Nok Nicholas Fung; Guang Rong; Benjamin Ultan Cowley – npj Science of Learning, 2025
Large Language Models (LLMs) present a radically new paradigm for the study of "information foraging behavior." We study how LLM technology is used for pedagogical content creation by a sample of 25 participants in a doctoral-level Artificial Intelligence (AI) in Education course, and the role of computational-thinking skills in shaping…
Descriptors: Man Machine Systems, Artificial Intelligence, Natural Language Processing, Interaction
Chanyuan Gu; Samuel A. Nastase; Zaid Zada; Ping Li – npj Science of Learning, 2025
While evidence has accumulated to support the argument of shared computational mechanisms underlying language comprehension between humans and large language models (LLMs), few studies have examined this argument beyond native-speaker populations. This study examines whether and how alignment between LLMs and human brains captures the homogeneity…
Descriptors: Reading Comprehension, Native Language, Second Language Learning, Brain Hemisphere Functions