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Jaimie Drozdal

Researcher at Rensselaer Polytechnic Institute

Publications -  17
Citations -  182

Jaimie Drozdal is an academic researcher from Rensselaer Polytechnic Institute. The author has contributed to research in topics: Brainstorming & Computer science. The author has an hindex of 4, co-authored 16 publications receiving 72 citations. Previous affiliations of Jaimie Drozdal include IBM.

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Proceedings ArticleDOI

Trust in AutoML: exploring information needs for establishing trust in automated machine learning systems

TL;DR: It is found that including transparency features in an AutoML tool increased user trust and understandability in the tool; and out of all proposed features, model performance metrics and visualizations are the most important information to data scientists when establishing their trust with an Auto ML tool.
Journal ArticleDOI

Foreign language acquisition via artificial intelligence and extended reality: design and evaluation

TL;DR: Artificial Intelligence (AI) and Extended Reality (XR) have been employed in several foreign language education applications to increase the availability of experiential learning methods akin to in-situ learning methods.
Journal ArticleDOI

The Rensselaer Mandarin Project — A Cognitive and Immersive Language Learning Environment

TL;DR: The Rensselaer Mandarin Project enables a group of foreign language students to improve functional understanding, pronunciation and vocabulary in Mandarin Chinese through authentic speaking situations in a virtual visit to China.
Proceedings ArticleDOI

What Makes a Well-Documented Notebook? A Case Study of Data Scientists’ Documentation Practices in Kaggle

TL;DR: In this paper, a qualitative analysis at both the notebook level and the markdown-cell level was conducted to find that Kaggle notebooks are indeed well documented in reference to previous literature, and also revealed nine categories of content that data scientists write in their documentation cells.
Proceedings ArticleDOI

Interaction Challenges in AI Equipped Environments Built to Teach Foreign Languages Through Dialogue and Task-Completion

TL;DR: A human-scale, immersive room with a virtual AI agent that aids foreign language learning through task-completion exercises using multi-modal dialogue and enhanced the AI agent, virtual environment, and the on-boarding process for new users to mitigate these challenges.