most citedPreparing Unprepared Students For Future Learning

7 citations · 27 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CY2023★ 6 cited

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…

cs.CY2023★ 2 cited

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…

cs.HC2023

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…

cs.HC2023★ 5 cited

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…

cs.HC2023★ 7 cited

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…

cs.HC2023★ 7 cited

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…

cs.CY2022

Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning towards Improved Problem Solving

Preya Shabrina, Behrooz Mostafavi, Mark Abdelshiheed +2

Learning to derive subgoals reduces the gap between experts and students and makes students prepared for future problem solving. Researchers have explored subgoal labeled instructi…