20 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…
Sanaz Bahargam, Dóra Erdös, Azer Bestavros, Evimaria Terzi
Whether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective; (1.) group students so that they can maximally benefit from peer interaction and (2.) find an optimal…
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…
Suresh Kumaar Jayaraman, Reid Simmons, Aaron Steinfeld, Henny Admoni
Human-Robot Collaboration Across Diverse Groups Authors: ['Suresh Kumaar Jayaraman' 'Reid Simmons' 'Aaron Steinfeld' 'Henny Admoni'] Abstract—In this work, we aim to improve transparency and efficacy in human-robot collaboration by developing machine teaching algorithms suitable for groups with varied learning…
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…
Manuel Lopes, Francisco S. Melo
In this paper we propose the first machine teaching algorithm for multiple inverse reinforcement learners. Specifically, our contributions are: (i) we formally introduce the problem of teaching a sequential task to a heterogeneous group of learners; (ii) we identify conditions under which it is possible to conduct such…
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…
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…
Zhibo Zhai, Guoping Jia, Kai Wang
Teaching-learning-based optimization (TLBO) algorithm is a novel heuristic method which simulates the teaching-learning phenomenon of a classroom. However, in the later period of evolution of the TLBO algorithm, the lower exploitation ability and the smaller scope of solutions led to the poor results. To address this…
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…
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…
Elinor Jones, Tom Palmer
The teaching of statistics in higher education in the UK is still largely lecture-based. This is despite recommendations such as those given by the American Statistical Association's GAISE report that more emphasis should be placed on active learning strategies where students take more responsibility for their own…
Minji Kim, Yeonsung Kim, Lei Qian, Jun S. Song
Bioinformatics is a rapidly growing field that has emerged from the synergy of computer science, statistics, and biology. Given the interdisciplinary nature of bioinformatics, many students from diverse fields struggle with grasping bioinformatic concepts only from classroom lectures. Interactive tools for helping…
Erin A. Becker, Erin J. Easlon, Sarah C. Potter, Alberto Guzman-Alvarez + 5 more
Evidence-based teaching is a highly complex skill, requiring repeated cycles of deliberate practice and feedback to master. Despite existing well characterized frameworks for practice-based training in K-12 teacher education, the major principles of these frameworks have not yet been transferred to instructor…
Tanya Y. Tan, Megan K. Barker
Undergraduate science students spend a substantial amount of time working in their laboratory groups, and instructors want to make evidence-based decisions on how to best set up these groups. Despite several studies on group composition, the evidence appears to be quite context-specific, and very little has been…
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
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…
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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…