16 citations · 67 across the 21 of their papers we have counts for
8 papers · 1 filter
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…
Preparing Unprepared Students For Future Learning
Mark Abdelshiheed, Mehak Maniktala, Song Ju +3
Based on strategy-awareness (knowing which problem-solving strategy to use) and time-awareness (knowing when to use it), students are categorized into Rote (neither type of awarene…
Assessing Competency Using Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning
Mark Abdelshiheed, Mehak Maniktala, Tiffany Barnes +1
One fundamental goal of learning is preparation for future learning (PFL) and being able to extend acquired skills and problem-solving strategies to different domains and environme…
Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning
Mark Abdelshiheed, Guojing Zhou, Mehak Maniktala +2
In this work, we investigate how two factors, metacognitive skills and motivation, would impact student learning across domains. More specifically, our primary goal is to identify…
HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare
Ge Gao, Song Ju, Markel Sanz Ausin +1
Reinforcement learning (RL) has been extensively researched for enhancing human-environment interactions in various human-centric tasks, including e-learning and healthcare. Since…