25 papers · ranked by Valyu relevance
Shengnan Bai
This research focuses on developing a learning progression of probability for middle school students, and it applies the GDINA model in cognitive diagnosis models to data analysis. GDINA model analysis firstly extracted nine cognitive attributes and constructed their attribute hierarchy and the hypothesized learning…
Fei Wang, Zhaosheng Luo, Ying Miao, Shuting Zhou + 1 more
To meet the growing demands for competency-based and personalized instruction in high school English reading, this study investigates a quantitative approach to modeling learning pathways and progressions. Traditional assessments often fail to capture students’ fine-grained cognitive differences and provide limited…
Younyoung Choi, Robert J. Mislevy
An overarching mission of the educational assessment community today is strengthening the connection between assessment and learning. To support this effort, researchers draw variously on developments across technology, analytic methods, assessment design frameworks, research in learning domains, and cognitive, social…
Andrea Bassich, Francesco Foglino, Matteo Leonetti, Daniel Kudenko⋆
Curriculum Learning for Reinforcement Learning is an increasingly popular technique that involves training an agent on a sequence of intermediate tasks, called a Curriculum, to increase the agent's performance and learning speed. This paper introduces a novel paradigm for curriculum generation based on progression and…
Maria Shujah, Suyash Joshi, Mari Nakamura, Tania Rinaldi Barkat
Curriculum Learning (CL) is a strategy where concepts with increasing complexity are acquired sequentially. Despite its widespread application, its putative neural mechanisms are poorly understood. In this study, using a multi-staged Go/No-Go auditory discrimination paradigm for mice, we show that CL improves and…
Neva Howard, Roger Edwards, Kathy Boutis, Seth Alexander + 1 more
'Martin Pusic'] Learning curves can be used to design, implement, and evaluate educational interventions. Attention to key aspects of the method can improve the fidelity of this representation of learning as well as its suitability for education and research purposes. This paper addresses when to use a learning curve…
Alex Graves, Marc G. Bellemare, Jacob Menick, Rémi Munos + 1 more
'Koray Kavukcuoglu'] We introduce a method for automatically selecting the path, or syllabus, that a neural network follows through a curriculum so as to maximise learning efficiency. A measure of the amount that the network learns from each data sample is provided as a reward signal to a nonstationary multiarmed…
George Leu, Jiangjun Tang
Machine education is an emerging research field that focuses on the problem which is inverse to machine learning. To date, the literature on educating machines is still in its infancy. A fairly low number of methodology and method papers are scattered throughout various formal and informal publication avenues, mainly…
Daniel A. Parker, Elizabeth A. Roumell
Along with technological progress, vocational education and training (VET) is consistently changing. Workforce disruption has serious consequences for workers and international economies, often requiring adults to transition into different occupations or to upskill to maintain employment. We review recent literature…
Mark Collier, Joeran Beel
Syllabuses for curriculum learning have been developed on an ad-hoc, per task basis and little is known about the relative performance of different syllabuses. We identify a number of syllabuses used in the literature. We compare the identified syllabuses based on their effect on the speed of learning and…
Hua-Dong Xiong, Li Ji-An, Robert C. Wilson, Marcelo G. Mattar
A hallmark of intelligence is the ability to adapt behavior to changing environments, which requires adapting one’s own learning strategies. This phenomenon is known as learning to learn or meta-learning. Although well established in humans and animals, a computational framework that characterizes how biological agents…
Ryan Campbell, Jun-Sang Yoon
This study1 explores an approach to Automatic Curriculum Learning (ACL) in reinforcement learning (RL), focusing on the integration of gradient norm reward signals. Traditional ACL methods primarily rely on predefined metrics that may not adequately capture the intricacies of learning dynamics. Our work proposes a…
Charlotte Volk, Christopher C. Pack, Shahab Bakhtiari
Generalization of visual perceptual learning (VPL) to unseen conditions varies across tasks. Previous work suggests that training curriculum may be integral to generalization, yet a theoretical explanation is lacking. We propose an explanatory theory of visual learning generalization and curriculum effects by…
Hua-Dong Xiong, Li Ji-An, Robert C. Wilson, Marcelo G. Mattar
A hallmark of intelligence is the ability to adapt behavior to changing environments, which requires adapting one’s own learning strategies. This phenomenon is known as learning to learn in cognitive science and meta-learning in artificial intelligence. While this phenomenon is well-established in humans and animals…
Jeff Guo, Vendy Fialková, Juan Diego Arango, Christian Margreitter + 4 more
Reinforcement learning (RL) is a powerful paradigm that has gained popularity across multiple domains. However, applying RL may come at a cost of multiple interactions between the agent and the environment. This cost can be especially pronounced when the single feedback from the environment is slow or computationally…
Vipul K. Satone, Rachneet Kaur, Anant Dadu, Hampton Leonard + 9 more
Alzheimer’s disease (AD) is a common, age-related, neurodegenerative disease that impairs a person’s ability to perform day-to-day activities. Diagnosing AD is challenging, especially in the early stages. Many patients still go undiagnosed, partly due to the complex heterogeneity in disease progression. This highlights…
Joshua Rule, Eric Schulz, Steven T. Piantadosi, Joshua B. Tenenbaum
Humans master complex systems of interrelated concepts like mathematics and natural language. Previous work suggests learning these systems relies on iteratively and directly revising a language-like conceptual representation. We introduce and assess a novel concept learning paradigm called Martha’s Magical Machines…
Ahmed Zaidi, Russell Moore, Ted Briscoe
The structure of curriculum plays a vital role in our learning process, both as children and adults. Presenting material in ascending order of difficulty that also exploits prior knowledge can have a significant impact on the rate of learning. However, the notion of difficulty and prior knowledge differs from person to…
Xiangbo Shu, Jinhui Tang, Zechao Li, Hanjiang Lai + 2 more
'Shuicheng Yan'] Abstract—Age progression is defined as aesthetically re-rendering the aging face at any future age for an individual face. In this work, we aim to automatically render aging faces in a personalized way. Basically, for each age group, we learn an aging dictionary to reveal its aging characteristics…
Meir Meshulam, Liat Hasenfratz, Hanna Hillman, Yun-Fei Liu + 3 more
How do students understand and remember new information? Despite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural measure for predicting and…
Authors not listed
Large Language Models (LLMs) based on transformer architectures excel at internet-scale tasks. However, real-world scientific scenarios—such as synthetic chemistry laboratories and autonomous experimental setups—typically involve incremental data generation in batches as new chemical reactions are conducted, unlike…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Abootaleb Sedighi, Tudor Radu, Qirat Ashraf, Balmiki Kumar + 3 more
We developed the Interdisciplinary Science Program in Research and Entrepreneurship (INSPIRE) to address the changing career landscape that students with an interest in Physical Chemistry, Biophysics and Biochemistry face. Third and fourth-year undergraduate Chemistry and Physics students participated in a 4-week…
Timothy Gould
This study examined factors influencing student confidence and their perception of learning in the context of undergraduate chemistry and biochemistry courses. Anonymous online surveys were used to measure the extent to which small group work influenced student confidence in solving problems compared to working…
Szu Szu Ling, Fabrice Saffre, Deborah L. Gater, Lilia Halim + 1 more
Computer quiz games are introduced to improve teaching and learning in a freshman engineering chemistry course in an English-as-a-Second-Language (ESL) environment. These quiz games are developed and implemented as a supplemental and augmentative tool to enhance traditionally delivered lectures. The paper shows an…