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Found 10 papers, 4 papers with code
Representation Learning from Limited Educational Data with Crowdsourced Labels
Extensive experiments conducted on three real-world data sets demonstrate the superiority of our framework on learning representations from limited data with crowdsourced labels, comparing with various state-of-the-art baselines.
Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms
Asking questions is one of the most crucial pedagogical techniques used by teachers in class.
Learning Multi-level Dependencies for Robust Word Recognition
Robust language processing systems are becoming increasingly important given the recent awareness of dangerous situations where brittle machine learning models can be easily broken with the presence of noises.
Multimodal Learning For Classroom Activity Detection
The experimental results demonstrate the benefits of our approach on learning attention based neural network from classroom data with different modalities, and show our approach is able to outperform state-of-the-art baselines in terms of various evaluation metrics.
Automatic Short Answer Grading via Multiway Attention Networks
Automatic short answer grading (ASAG), which autonomously score student answers according to reference answers, provides a cost-effective and consistent approach to teaching professionals and can reduce their monotonous and tedious grading workloads.
A Multimodal Alerting System for Online Class Quality Assurance
To warn the unqualified instructors and ensure the overall education quality, we build a monitoring and alerting system by utilizing multimodal information from the online environment.
Deep Knowledge Tracing with Side Information
Monitoring student knowledge states or skill acquisition levels known as knowledge tracing, is a fundamental part of intelligent tutoring systems.
Dolphin: A Spoken Language Proficiency Assessment System for Elementary Education
In our offline experiments, we show that Dolphin improves both phonological fluency and semantic relevance evaluation performance when compared to state-of-the-art baselines on real-world educational data sets.
Recommender Systems with Heterogeneous Side Information
In modern recommender systems, both users and items are associated with rich side information, which can help understand users and items.
Learning Effective Embeddings From Crowdsourced Labels: An Educational Case Study
In practice, the crowdsourced labels are usually inconsistent among crowd workers given their diverse expertise and the number of crowdsourced labels is very limited.
