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Found 19 papers, 11 papers with code
Transforming Question Answering Datasets Into Natural Language Inference Datasets
Existing datasets for natural language inference (NLI) have propelled research on language understanding.
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings
We provide an NLP framework to uncover four linguistic dimensions of political polarization in social media: topic choice, framing, affect and illocutionary force.
GoEmotions: A Dataset of Fine-Grained Emotions
Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior.
Ranked #1 on
Emotion Classification
on GoEmotions
P\'art\'elet: A Hungarian Corpus of Propaganda Texts from the Hungarian Socialist Era
P{\'a}rt{\'e}let was the official journal of the governing party during the Hungarian socialism from 1956 to 1989, hence it represents the direct political agitation and propaganda of the dictatorial system in question.
The Role of Verb Semantics in Hungarian Verb-Object Order
We test the effect of lexical semantics on the ordering of verbs and their objects by grouping verbs into 11 semantic classes.
Analyzing the Framing of 2020 Presidential Candidates in the News
In this study, we apply NLP methods to learn about the framing of the 2020 Democratic Presidential candidates in news media.
Learning to Recognize Dialect Features
Evaluation on a test set of 22 dialect features of Indian English demonstrates that these models learn to recognize many features with high accuracy, and that a few minimal pairs can be as effective for training as thousands of labeled examples.
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
In conversation, uptake happens when a speaker builds on the contribution of their interlocutor by, for example, acknowledging, repeating or reformulating what they have said.
Computationally Identifying Funneling and Focusing Questions in Classroom Discourse
Responsive teaching is a highly effective strategy that promotes student learning.
The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts
Classroom discourse is a core medium of instruction - analyzing it can provide a window into teaching and learning as well as driving the development of new tools for improving instruction.
MD3: The Multi-Dialect Dataset of Dialogues
We introduce a new dataset of conversational speech representing English from India, Nigeria, and the United States.
Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction
In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript segments based on classroom observation instruments, (B) identifying highlights and missed opportunities for good instructional strategies, and (C) providing actionable suggestions for eliciting more student reasoning.
SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts
To overcome this challenge, we propose a set of best practices for using large language models (LLMs) to cheaply classify the comments at scale.
Kid-Whisper: Towards Bridging the Performance Gap in Automatic Speech Recognition for Children VS. Adults
Recent advancements in Automatic Speech Recognition (ASR) systems, exemplified by Whisper, have demonstrated the potential of these systems to approach human-level performance given sufficient data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
"Mistakes Help Us Grow": Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms
Teachers' growth mindset supportive language (GMSL)--rhetoric emphasizing that one's skills can be improved over time--has been shown to significantly reduce disparities in academic achievement and enhance students' learning outcomes.
Bridging the Novice-Expert Gap via Models of Decision-Making: A Case Study on Remediating Math Mistakes
We evaluate state-of-the-art LLMs on our dataset and find that the expert's decision-making model is critical for LLMs to close the gap: responses from GPT4 with expert decisions (e. g., "simplify the problem") are +76% more preferred than without.
Measuring Five Accountable Talk Moves to Improve Instruction at Scale
To build scalable measures of instruction, we fine-tune RoBERTa and GPT models to identify five instructional talk moves inspired by accountable talk theory: adding on, connecting, eliciting, probing and revoicing students' ideas.
Edu-ConvoKit: An Open-Source Library for Education Conversation Data
We introduce Edu-ConvoKit, an open-source library designed to handle pre-processing, annotation and analysis of conversation data in education.
Backtracing: Retrieving the Cause of the Query
While information retrieval (IR) systems may provide answers for such user queries, they do not directly assist content creators -- such as lecturers who want to improve their content -- identify segments that _caused_ a user to ask those questions.
