26 papers · ranked by Valyu relevance
Eugenia Smyrnova-Trybulska, Nataliia Morze, Lilia Varchenko-Trotsenko
Contemporary education is often based on using e-learning courses, which have become a popular means of delivering didactic material to students. Among the main advantages mentioned is the potential possibility of creating individual ways of learning and teaching. The purpose of this article is to provide a description…
Paulette Vincent-Ruz, Nathan R. B. Boase, Kristopher V. Waynant
In tertiary science education, students are encouraged to engage in discipline specific thinking, to learn their chosen subject. The challenge for educators is engaging all students equitably, despite their educational backgrounds and depth of discipline specific knowledge. Personalising learning in the context of…
Hwa-Young Jeong, Gangman Yi
In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while…
Cedric Foucault, Florent Meyniel
Humans face a dynamic world that requires them to constantly update their knowledge. Each observation should influence their knowledge to a varying degree depending on whether it arises from a stochastic fluctuation or an environmental change. Thus, humans should dynamically adapt their learning rate based on each…
Qin He, Daniel N. Scott, Michael J. Frank, Cristian B. Calderon + 1 more
People adjust their use of feedback over time through a process referred to as adaptive learning. We have recently proposed that the underlying mechanisms of adaptive learning are rooted in how the brain organizes time into similarly credited units, which we refer to as latent states. Here we develop a…
Niloufar Razmi, Matthew R. Nassar
People adjust their learning rate rationally according to local environmental statistics and calibrate such adjustments based on the broader statistical context. To date, no theory has captured the observed range of adaptive learning behaviors or the complexity of its neural correlates. Here, we attempt to do so using…
Sebastian Kucharski, Iris Braun, Gregor Damnik, Matthias Wählisch
Objective: We conducted a systematic review of the literature addressing the following research questions. How are adaptive learning mechanisms integrated into LMSs systemindependently? How are they provided, how are they specified, and on which database do they operate? A priori, we proposed three hypotheses. First…
Xiao Li, Hanchen Xu, Jinming Zhang, Hua Hua Chang
In this paper, we formulate the adaptive learning problem—the problem of how to find an individualized learning plan (called policy) that chooses the most appropriate learning materials based on learner's latent traits—faced in adaptive learning systems as a Markov decision process (MDP). We assume latent traits to be…
Hang Li, Tianlong Xu, Chaoli Zhang, Eason Chen + 5 more
'Xing Fan' 'Haoyang Li' 'Jiliang Tang' 'Qingsong Wen'] The recent surge in generative AI technologies, such as large language models and diffusion models, have boosted the development of AI applications in various domains, including science, finance, and education. Concurrently, adaptive learning, a concept that has…
Manuel Ninaus, Michael Sailer
Recent advancements in artificial intelligence make its use in education more likely. In fact, existing learning systems already utilize it for supporting students’ learning or teachers’ judgments. In this perspective article, we want to elaborate on the role of humans in making decisions in the design and…
Helene Ackermann, Anna L. Lange, Verena V. Hafner, Rebecca Lazarides
As educational environments become more diverse, adaptive technologies like social robots hold promise for providing individual support to learners. This study investigated the role of adaptive teaching of a robot on students’ learning outcomes, emotions, and self-regulated learning (SRL). A total of 120 participants…
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…
Antonio Bucchiarone, Tommaso Martorella, Diego Colombo
The digital age is changing the role of educators and pushing for a paradigm shift in the education system as a whole. Growing demand for general and specialized education inside and outside classrooms is at the heart of this rising trend. In modern, heterogeneous learning environments, the one-size-fits-all approach…
Nongkhai, Lalita Na, Wang, Jingyun + 2 more
This paper introduces an ontology-based approach within an adaptive learning support system for computer programming. This system (named ADVENTURE) is designed to deliver personalized programming exercises that are tailored to individual learners' skill levels. ADVENTURE utilizes an ontology, named CONTINUOUS, which…
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…
Teófilo Félix Valentín Melgarejo, Gastón Jeremías Oscátegui Nájera, Dora Marina Hachoque Aguirre, Ulises Espinoza Apolinario + 10 more
Reading comprehension is a critical cognitive competency in higher education, although learners demonstrate substantial variability in responsiveness to metacognitive instructional interventions. The study focused on individual cognitive-response processes within the framework of the adaptive metacognitive reading…
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…
Christos Troussas, Akrivi Krouska, Cleo Sgouropoulou, Salim Lahmiri
This paper describes an innovative and sophisticated approach for improving learner-computer interaction in the tutoring of Java programming through the delivery of adequate learning material to learners. To achieve this, an instructional theory and intelligent techniques are combined, namely the Component Display…
Alexis Ross, Jacob Andreas
Misconceptions Authors: ['Alexis Ross' 'Jacob Andreas'] When a teacher provides examples for a student to study, these examples must be informative, enabling a student to progress from their current state toward a target concept or skill. Good teachers must therefore simultaneously infer what students already know and…
Ilya Musabirov, Angela Zavaleta Bernuy, Pan Chen, Michael Liut + 1 more
'Joseph Jay Williams'] Randomized A/B comparisons of alternative pedagogical strategies or other course improvements could provide useful empirical evidence for instructor decision-making. However, traditional experiments do not provide a straightforward pathway to rapidly utilize data, increasing the chances that…
Erdem Pulcu
We are living in a dynamic world in which stochastic relationships between cues and outcome events create different sources of uncertainty^1^ (e.g. the fact that not all grey clouds bring rain). Living in an uncertain world continuously probes learning systems in the brain, guiding agents to make better decisions. This…
Authors not listed
For applications in gas sensing, purification, and capture, we often wish to search a large set of metal-organic frameworks (MOFs) for the top-K in terms of their Henry coefficient of an adsorbate. A molecular simulation to predict the Henry coefficient of a MOF constitutes a Monte Carlo integration where each sample…
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
The integration of machine learning methods is transforming many areas of research by, for instance, accelerating molecular dynamics simulations and enabling improved prediction and optimization of chemical reactions. However, despite this progress, the adoption of data-driven approaches in atomic layer deposition…
Etinosa Osaro, Yamil Colón
The application of machine learning (ML) techniques in materials science has revolutionized the pace and scope of materials research and design. In the case of metal-organic frameworks (MOFs), a promising class of materials due to their tunable properties and versatile applications in gas adsorption and separation, ML…
Finlay Clark, Graeme Robb, Daniel Cole, Julien Michel
Alchemical absolute binding free energy (ABFE) calculations have substantial potential in drug discovery, but are often prohibitively computationally expensive. To unlock their potential, efficient automated ABFE workflows are required to reduce both computational cost and human intervention. We present a…