21 papers · ranked by Valyu relevance
Joseph-Omer Dyer, Anne Hudon, Katherine Montpetit-Tourangeau, Bernard Charlin + 2 more
Background Example-based learning using worked examples can foster clinical reasoning. Worked examples are instructional tools that learners can use to study the steps needed to solve a problem. Studying worked examples paired with completion examples promotes acquisition of problem-solving skills more than studying…
Tiago P. Bonetti, Williamson Silva, Thelma E. Colanzi
Background and Context: The discipline of Software Engineering (SE) allows students to understand specific concepts or problems while designing software. Empowering students with the necessary knowledge and skills for the software industry is challenging for universities. One key problem is that traditional…
Eric C. Wong
In this hypothesis paper we argue that when driven by example behavior, a simple Hebbian learning mechanism can form the core of a computational theory of learning that can support both low level learning and the development of human level intelligence. We show that when driven by example behavior Hebbian learning…
A. K. Chatterjee, Suman Kundu
Learning is most effective when it's connected to relevant, relatable examples that resonate with learners on a personal level. However, existing educational AI tools don't focus on generating examples or adapting to learners' changing understanding, struggles, or growing skills. We've developed ExaCraft, an AI system…
Chengwei Wang, Junyi Li, Haiyan Li, Yijing Xia + 3 more
'Yufei Xie' 'Jinyang Wu'] Background Constructivism theory has suggested that constructing students’ own meaning is essential to successful learning. The erroneous example can easily trigger learners’ confusion and metacognition, which may “force” students to process the learning material and construct meaning deeply.…
Lukas Wesenberg, Felix Krieglstein, Sebastian Jansen, Günter Daniel Rey + 2 more
'Günter Daniel Rey' 'Maik Beege' 'Sascha Schneider'] Several studies highlight the importance of the order of different instructional methods when designing learning environments. Correct but also erroneous worked examples are frequently used methods to foster students’ learning performance, especially in…
Yu Qi Qiao, Jun Shen, Xiao Liang, Song Ding + 4 more
'Li Shao' 'Qing Zheng' 'Zhi Hua Ran'] Background Educators continue to search for better strategies for medical education. Although the unifying theme of reforms was “increasing interest in, attention to, and understanding of the knowledge base structures”, it is difficult to achieve all these aspects via a single type…
Jeffrey N. Love, Anne M. Messman, Chris Merritt
In an effort to create a more compelling presentation, one of us took a previously well-received presentation on anterior segment ophthalmologic trauma and used educational theory and best practices to redesign it. This was done with the goals of improving participants’ learning and retention. Successful treatment of…
Michael J. Lee, James J. DiCarlo
A core problem in visual object learning is using a finite number of images of a new object to accurately identify that object in future, novel images. One longstanding, conceptual hypothesis asserts that this core problem is solved by adult brains through two connected mechanisms: 1) the re-representation of incoming…
Ben Sorscher, Surya Ganguli, Haim Sompolinsky
Understanding the neural basis of our remarkable cognitive capacity to accurately learn novel high-dimensional naturalistic concepts from just one or a few sensory experiences constitutes a fundamental problem. We propose a simple, biologically plausible, mathematically tractable, and computationally powerful neural…
Naomi Steenhof, Jon Schommer
Pharmacy educators are grappling with concerns around curriculum overload and core pharmacist competencies in a rapidly changing and increasingly complex healthcare landscape. Adaptive expertise provides a conceptual framework to guide educators as they design instructional activities that can support students on their…
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…
Teodora Popordanoska, Mahesh Kumar, Stefano Teso
We introduce explanatory guided learning (XGL), a novel interactive learning strategy in which a machine guides a human supervisor toward selecting informative examples for a classifier. The guidance is provided by means of global explanations, which summarize the classifier's behavior on different regions of the…
Reema Ajmera, Dinesh Kumar Dharamdasani
- As IT grows the impact of new technology reflects in more or less every field. Education also gets new dimensions with the advancement in IT sector. Nowadays education is not limited to books and black boards only it gets a new way i.e. electronic media. Although with e-learning, the education having broader…
William L. Tong, Anisha Iyer, Venkatesh N. Murthy, Gautam Reddy
Dogs and laboratory mice are commonly trained to perform complex tasks by guiding them through a curriculum of simpler tasks (‘shaping’). What are the principles behind effective shaping strategies? Here, we propose a machine learning framework for shaping animal behavior, where an autonomous teacher agent decides its…
Yannick Ureel, Maarten R. Dobbelaere, Yi Ouyang, Kevin De Ras + 3 more
By combining machine learning with design of experiments, so-called active machine learning, more efficient and cheaper research can be conducted. Machine learning algorithms are more flexible, and are better at investigating the processes spanning all length scales of chemical engineering. While the active machine…
Yao Zhou, Arun Reddy Nelakurthi, Jingrui He
With the increasing demand for large amount of labeled data, crowdsourcing has been used in many large-scale data mining applications. However, most existing works in crowdsourcing mainly focus on label inference and incentive design. In this paper, we address a different problem of adaptive crowd teaching, which is a…
Authors not listed
In philosophy and science, a first principle is a basic proposition or assumption that cannot be deduced from any other proposition or assumption. Ancient Greek philosophy Aristotle defined the first principle as “the first basis from which a thing is known.” First principles thinking (or reasoning from first…
Ah Jung Jeon, David Kellogg, Mohammed Asif Khan, Greg Tucker-Kellogg
Laboratory pedagogy is moving away from step-by-step instructions and toward inquiry-based learning (IBL), but only now developing methods for integrating inquiry-based writing (IBW) practices into the laboratory course. Based on an earlier proposal (Science 332:919 (2011)), we designed and implemented an IBW sequence…
Lucie Denisart, Diana Zapata-Dominguez, Xavier David, Aubin Leclere + 5 more
The manufacturing process of batteries can be complex and time-consuming. We introduce a new version of the digital twin of our lithium ion battery pilot line, Simubat 4.0 Gen-2, based on a new combination of Virtual Reality and Mixed Reality. This digital twin is designed to deliver training on the lithium-ion battery…
Authors not listed
Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…