The Innovative Educational Computing Lab is hiring a few graduate students (MS and PhD) as research and software engineering interns on the following projects. The appointment will be either as GRA (at a contracted monthly stipend with tuition benefit), research intern (at a per-hour rate payment without a tuition benefit), or volunteer (no pay). Interested candidates should email Dr. Matsuda (Noboru.Matsuda@ncsu.edu) a current CV and a statement of research indicating the project of interest.
AI applications for Educationl
Project 1: NLP research for scalable online course engineering [Deep Learning on NLP]
We are looking for MS students for various research projects on the PASTEL project (www.ieclab.org) with a particular focus on application of NLP-based ML techniques. Potential projects include (but not limited to) automatic question generation, automatic evaluation of assessment questions to predict their pedagogical validity, and analysis of courseware contents for latent skill discovery. The actual project task will be identified based on the skills and interests of the candidates.
Ideal candidates should have in-depth experience and theoretical understanding in artificial intelligence, machine learning, and natural language processing beyond course projects. In-depth experience with NLP and ML techniques (e.g., prompt engineering) is required. Please use this form to apply.
Project 2: Studying the effect of learning by teaching a synthetic peer [Machine Learning for Science of Learning]
The Innovative Educational Computing Lab (www.ieclab.org) is looking for a PhD student to conduct a research on an externally funded project, called SimStudent, where we study how students learn by teaching (www.SimStudent.org). We apply an interactive machine-learning technology to deploy a pedagogical agent that serves as a synthetic peer for a student to teach. Potential thesis projects include (but not limited to) developing a dialogue model to facilitate the effect of learning by teaching, extending the built-in machine learning model of the synthetic peer to deal with multimodal instructions (e.g., written texts and diagrams), conducting school study to advance a theory of learning by teaching. This is an NSF/IES funded project called SimStudent. Visit our web for details: www.SimStudent.org
An ideal candidate should have a decent experience on a research project with strong theoretical background in artificial intelligence, machine learning, and learning science. Please email Dr. Matsuda to apply as instructed above.
Project 3: Video analysis for anomaly behavior detection [Deep Learning on Video Analysis]
There is growing demand for automated surveillance in broad domains. One of the critical tasks is to detect anomalous behavior captured in video recordings. We apply deep neural network technology to build a highly reliable model for anomaly detection. Although, the technology is (or should be) task independent, we are currently interested in animal behavior, in particular bred animals in a farm (e.g., detecting sick animal).
Ideal candidates should have in-depth experience and theoretical understanding in deep learning beyond course projects. Please email Dr. Matsuda to apply as instructed above.
Software Engineers
Project 4: Adaptive Online Courseware Project [Full-stack programmer]
The goal of the project is to develop a web-based platform to create and host adaptive online courseware. The adaptive online courseware has been deployed on existing open-source system, Open edX. We have extended Open edX to a great extent by integrating several AI techniques (e.g., integration of intelligent tutoring systems, analysis of courseware contexts to optimize assessment sequencing, etc), and will continue our effort further.
An ideal candidate should have a solid record in full-stack Web developer with expertise in Python, Java, Django, REST, JavaScript, JSP, HTML, CSS, and Tomcat. Knowledge and experience on Linux OS, Git and Github, and Docker would be ideal. Spell out your experience as a full-stack Web developer when you apply. Please use this form to apply.
Project 5: Online Platform for Learning by Teaching [Full-stack programmer]
The goal of the project is to develop a web-based app for learning by teaching (www.SimStudent.org). The primary task is to convert a Java applet version using Java Swing our research intervention, called APLUS, into a web app. APLUS allows students to interactively teach a synthetic peer, called SimStudent, how to solve linear equations, but the theory conjectures that it is actually the student who learns by teaching. In other words, using the APLUS app, we investigate how and when students learn by teaching.
An ideal candidate for the full-stack programmer should have a solid record in full-stack Web developer with expertise in Java (programming and debugging for an existing large project), REST, MVC pattern, Spring Boot, Angular, SQL, JavaScript, HTML, and CSS. Knowledge and experience on the Linux OS would be ideal. Knowledge on Docker technologies would be plus.
Project 6: Interactive Map for History Education Project [Full-stack programmer]
The goal of the project is to develop an interactive map comparison tool that allows students to compare modern and ancient maps. We hypothesize that the interactive map comparison tool will help students understand how individual countries developed their perception of other countries, which in turn facilitate student's learning to understand how the concept of nation and modern international relationships have evolved.
An ideal candidate would have at least one year of industry experience as a full-stack programmer with the following skill set: React, Express, Node.js, MongoDB or some other Database (can be SQL). Experience working with Geographic Information Systems would be preferred. Please email Dr. Matsuda to apply as instructed above.