Curriculum learning for reinforcement learning domains: A framework and survey
Reinforcement learning (RL) is a popular paradigm for addressing sequential decision tasks
in which the agent has only limited environmental feedback. Despite many advances over …
in which the agent has only limited environmental feedback. Despite many advances over …
A theoretical and evidence-based conceptual design of metadash: An intelligent teacher dashboard to support teachers' decision making and students' self-regulated …
Teachers' ability to self-regulate their own learning is closely related to their competency to
enhance self-regulated learning (SRL) in their students. Accordingly, there is emerging …
enhance self-regulated learning (SRL) in their students. Accordingly, there is emerging …
Flexible learning with semantic visual exploration and sequence-based recommendation of MOOC videos
Massive Open Online Course (MOOC) platforms have scaled online education to
unprecedented enrollments, but remain limited by their rigid, predetermined curricula. To …
unprecedented enrollments, but remain limited by their rigid, predetermined curricula. To …
Deep Reinforcement Learning With Curriculum Design for Quantum State Classification
H Yu, X Zhao - IEEE Transactions on Emerging Topics in …, 2024 - ieeexplore.ieee.org
In quantum information science, one of the ambitious goals is to look for an efficient
technique for classifying multiple quantum states. To solve the binary classification problem …
technique for classifying multiple quantum states. To solve the binary classification problem …
SeqSense: Video Recommendation Using Topic Sequence Mining
This paper examines content-based recommendation in domains exhibiting sequential
topical structure. An example is educational video, including Massive Open Online Courses …
topical structure. An example is educational video, including Massive Open Online Courses …
Using serious game analytics to inform digital curricular sequencing: What math objective should students play next?
Z Peddycord-Liu, C Cody, S Kessler, T Barnes… - Proceedings of the …, 2017 - dl.acm.org
This paper applied serious game analytics to inform digital curricular sequencing in a
longitude, curriculum-integrated math game, ST Math. When integrating serious games into …
longitude, curriculum-integrated math game, ST Math. When integrating serious games into …
Opening up an intelligent tutoring system development environment for extensible student modeling
K Holstein, Z Yu, J Sewall, O Popescu… - Artificial Intelligence in …, 2018 - Springer
ITS authoring tools make creating intelligent tutoring systems more cost effective, but few
authoring tools make it easy to flexibly incorporate an open-ended range of student …
authoring tools make it easy to flexibly incorporate an open-ended range of student …
Re-Designing the Structure of Online Courses to Empower Educational Data Mining.
The amount of information contained in any educational data set is fundamentally
constrained by the instructional conditions under which the data are collected. In this study …
constrained by the instructional conditions under which the data are collected. In this study …
[PDF][PDF] Designing real-time teacher augmentation to combine strengths of human and AI instruction
K Holstein - Unpublished doctoral dissertation …, 2019 - reports-archive.adm.cs.cmu.edu
When used in K-12 classrooms, AI-based educational software such as intelligent tutoring
systems (ITSs) allows students to work at their own pace, while also freeing up the teacher to …
systems (ITSs) allows students to work at their own pace, while also freeing up the teacher to …
Can we take advantage of time-interval pattern mining to model students activity?
Analyzing students' activities in their learning process is an issue that has received
significant attention in the educational data mining research field. Many approaches have …
significant attention in the educational data mining research field. Many approaches have …