6 citations · 15 across the 6 of their papers we have counts for
6 papers
Gradient-Based Neuroplastic Adaptation for Concurrent Optimization of Neuro-Fuzzy Networks
John Wesley Hostetter, Min Chi
Neuro-fuzzy networks (NFNs) are transparent, symbolic, and universal function approximations that perform as well as conventional neural architectures, but their knowledge is expre…
A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategies
Md Mirajul Islam, Xi Yang, John Hostetter +2
A key challenge in e-learning environments like Intelligent Tutoring Systems (ITSs) is to induce effective pedagogical policies efficiently. While Deep Reinforcement Learning (DRL)…
Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learning
Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes +1
In deductive domains, three metacognitive knowledge types in ascending order are declarative, procedural, and conditional learning. This work leverages Deep Reinforcement Learning…
Leveraging Deep Reinforcement Learning for Metacognitive Interventions across Intelligent Tutoring Systems
Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes +1
This work compares two approaches to provide metacognitive interventions and their impact on preparing students for future learning across Intelligent Tutoring Systems (ITSs). In t…
Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer
Mark Abdelshiheed, John Wesley Hostetter, Xi Yang +2
Metacognitive skills have been commonly associated with preparation for future learning in deductive domains. Many researchers have regarded strategy- and time-awareness as two met…
The Power of Nudging: Exploring Three Interventions for Metacognitive Skills Instruction across Intelligent Tutoring Systems
Mark Abdelshiheed, John Wesley Hostetter, Preya Shabrina +2
Deductive domains are typical of many cognitive skills in that no single problem-solving strategy is always optimal for solving all problems. It was shown that students who know ho…