17 papers · ranked by Valyu relevance
Yanjiao Wang, Jieru Han, Ziming Teng
This paper proposes an improved group teaching optimization algorithm (IGTOA) to improve the convergence speed and accuracy of the group teaching optimization algorithm. It assigns teachers independently for each individual, replacing the original way of sharing the same teacher, increasing the evolutionary direction…
Sumer Kohli, Neelesh Ramachandran, Ana Tudor, Gloria Tumushabe + 2 more
'Olivia Hsu' 'Gireeja Ranade'] Underrepresented students face many significant challenges in their education. In particular, they often have a harder time than their peers from majority groups in building long-term high-quality study groups. This challenge is exacerbated in remote-learning scenarios, where students are…
Jayashree Rajesh Prasad, Shashikant V. Athawale, Roshani Raut, Sonali Patil + 2 more
The current work describes a blockchain-based optimization approach that mimics the psychological mental illness evaluation procedure and evaluates mental fitness. Combining lightweight models with blockchains can give a variety of benefits in the healthcare business. This study aims to offer an improved review and…
Wenjing Yin
The future pedagogical systems need anthropocentric inclusive educational programs in which the goal should be adjustable according to the knowledge requirements, intelligence, and learning objective of each student. Prioritizing these needs, innovative AI methods are required to assist and ensure the making of…
Toni Vallès-Català, Ramon Palau, Olga Scrivner
For some decades now, theories on learning methodologies have advocated collaborative learning due to its good results in terms of effectiveness and learning types and its promotion of educational and social values. This means that teachers need to be able to apply different criteria when forming heterogeneous groups…
Jiafeng Li, Lixia Cao, Guoliang Zhang, Ka-Chun Wong
The teaching of the optimization algorithm is a new kind of swarm intelligence optimization technique, which is superior in optimizing many simple functions. Still, it is not evident in processing some complex problems (group and teaching classification). Achieving automatic matching and knowledge transfer in online…
Aynur Aliyeva, Ali Abbasov
The article discusses the problem concept maps are crucial tools for visualizing informatics knowledge in adaptive learning systems. In computer science education, concept maps are essential for visualizing complex knowledge structures and supporting adaptive learning. This study presents a learning path generation…
Tong Wu, Tang Xiao-hang, Sam Wong, Xi Chen + 2 more
Experience Report in a Large CS1 Course Authors: ['Tong Wu' 'Tang Xiao-hang' 'Sam Wong' 'Xi Chen' 'Clifford A. Shaffer' 'Chen Yan'] Programming instructors often conduct collaborative learning activities, such as Peer Instruction (PI), to enhance student motivation, engagement, and learning gains. However, the impact…
Emre Arslan, Atilla Özkaymak, Nesrin Özdener
The aim of this study is clustering students according to their gamification user types and learning styles with the purpose of providing instructors with a new perspective of grouping students in case of clustering which cannot be done by hand when there are multiple scales in data. The data used consists of 251…
Mohammadreza Amiri, Gholamali Montazer, Ebrahim Mousavi
their Learning Styles Authors: ['Mohammadreza Amiri' 'Gholamali Montazer' 'Ebrahim Mousavi'] The E-learning environment offers greater flexibility compared to face-to-face interactions, allowing for adapting educational content to meet learners' individual needs and abilities through personalization and customization…
Wei Peng, Zhibin Tang
With the establishment and perfection of social market economy, China has made changes to the disadvantages of farmers' vocational education system, such as singleness, backward educational means, and backward levels. Compared to traditional forms of farming, problems related to lack of farming expertise, poor…
Bowen Yu, Penghai Li, Haoze Xu, Yueming Wang + 2 more
Mice are among the most prevalent animal models used in neuroscience, benefiting from the extensive physiological, imaging and genetic tools available to study their brain. However, the development of novel and optimized behavioral paradigms for mice has been laborious and inconsistent, impeding the investigation of…
Swier Garst, Julian Dekker, Marcel Reinders
Federated learning is an upcoming machine learning paradigm which allows data from multiple sources to be used for training of classifiers without the data leaving the source it originally resides. This can be highly valuable for use cases such as medical research, where gathering data at a central location can be…
Nick Rittler, Kamalika Chaudhuri
Inspired by the problem of improving classification accuracy on rare or hard subsets of a population, there has been recent interest in models of learning where the goal is to generalize to a collection of distributions, each representing a "group". We consider a variant of this problem from the perspective of active…
Authors not listed
The Hidden Subgroup Problem (HSP) unifies several landmark quantum algorithms, yet systematic exploration of its variants and modern applications has slowed. This paper revives HSP-based algorithm design by examining new group structures with direct relevance to post-quantum cryptography, lattice problems, and…
Authors not listed
Generative artificial intelligence (AI) tools such as large language models (LLMs) have become ubiquitous in everyday life, and are also increasingly finding applications in the chemical sciences. Although LLMs have achieved impressive performance on many chemistry tasks, optimal performance requires proper use…
Authors not listed
This document presents a comprehensive heuristic algorithm for the teaching and practice of fundamental inorganic chemistry in representative elements. A logical-deductive method is proposed, starting from the electronic configuration and Hund’s Maximum Multiplicity Principle to determine valence by counting unpaired…