Funded Ph.D. position in machnine learning and e-learning at Polytechnique Montreal

Creating opportunities for deep learning and supporting student engagement in large online or blended classrooms and MOOCs presents a particular challenge. Central to this challenge are the restrictions of current automated assessment techniques and limited opportunity for individualized formative feedback from teachers. In this project, we seek to harness the power of computational techniques to address these limitations. In particular, we focus on discourse-centric analytics to explore the language that students and teachers use as they engage in learning and teaching.
In this project, we have three aims. First, to characterize the language constructs of students and teachers across a number of disciplines. Second, to explore whether understanding disciplinary literacy development can support the provision of effective and formative feedback to learners and the enhance the quality of their skill development. Finally, we address the challenge of automated evaluation of students' written responses to questions.
Description of the Ph.D. project:
The Ph.D. project concerns the third objective. Learners test data will be analyzed to obtain mappings of disciplinary features to questions and provide fine-grained assessment of learners’ disciplinary proficiency.
Model answers and learners responses will be compared for the evaluation of each individual question using features of disciplinary literacy. The assessment of learner answers will be supported by semantic similarity methods (with model answers) and readability metrics such as coherence and paraphrases. Machine learning models will also be built for each question to automatically grade learners answers based on these features.
Description of the institution:
Polytechnique Montréal, a flagship of engineering in Québec, is also one of Canada’s leading engineering teaching and research institutions. In keeping with its mission since 1873, it has trained nearly 46,000 engineers, specialists and researchers. The activities of its professors, employees and students have led Polytechnique to major discoveries in all areas of engineering and technology, and its accomplishments are known worldwide.
Polytechnique is a key player in Québec’s engineering and innovation sector, as well as the partner of choice for a number of innovative businesses in Québec, elsewhere in Canada and all over the world.
Application:
The candidate must send the following documents:
- Letter of motivation
- C.V.
- Two letters of recommendation
- School report (bachelor and master degrees) and GPA
Send the documents to Dr. Michel Gagnon, at the following email:
michel.gagnon-AT-polymtl.ca
The studies are expected to start in January 2018, and financial support is provided following the NSERC guidelines for Ph.D. students.