Powergrading: a Clustering Approach to Amplify Human Effort for Short Answer Grading
Sumit Basu,Charles E. Jacobs,Lucy Vanderwende +2 more
- Vol. 1, pp 391-402
TLDR
This paper used a similarity metric between student responses, and then used this metric to group responses into clusters and subclusters, which allowed teachers to grade multiple responses with a single action, provide rich feedback to groups of similar answers, and discover modalities of misunderstanding among students.Abstract:
We introduce a new approach to the machine-assisted grading of short answer questions. We follow past work in automated grading by first training a similarity metric between student responses, but then go on to use this metric to group responses into clusters and subclusters. The resulting groupings allow teachers to grade multiple responses with a single action, provide rich feedback to groups of similar answers, and discover modalities of misunderstanding among students; we refer to this amplification of grader effort as “powergrading.” We develop the means to further reduce teacher effort by automatically performing actions when an answer key is available. We show results in terms of grading progress with a small “budget” of human actions, both from our method and an LDA-based approach, on a test corpus of 10 questions answered by 698 respondents.read more
Citations
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Book ChapterDOI
Balancing Human Efforts and Performance of Student Response Analyzer in Dialog-Based Tutors
TL;DR: It is shown that data collection efforts can be significantly reduced by predicting question difficulty and by collecting answers from a focused set of students, and grades can be reduced by filtering student answers that may not be helpful in training Student Response Analyzer.
Proceedings ArticleDOI
Cross-Lingual Content Scoring.
TL;DR: This work investigates the feasibility of cross-lingual content scoring, a scenario where training and test data in an automatic scoring task are from two different languages, and creates a comparable bi-lingUAL corpus by extending the English ASAP dataset with German answers.
Journal ArticleDOI
Going deeper: Automatic short-answer grading by combining student and question models
Yuan Zhang,Chen Lin,Min Chi +2 more
TL;DR: Overall, the results on a real-world corpus demonstrate that 1) leveraging student and question models to the conventional answer-based approach can greatly enhance the performance of ASAG, and 2) deep learning models such as DBN can be productively applied to the task of ASAGs.
Proceedings ArticleDOI
Evaluation Dataset (DT-Grade) and Word Weighting Approach towards Constructed Short Answers Assessment in Tutorial Dialogue Context
TL;DR: The DT-Grade corpus consists of short constructed answers extracted from tutorial dialogues between students and an Intelligent Tutoring System and annotated for their correctness in the given context and whether the contextual information was useful.
References
More filters
Journal ArticleDOI
Latent dirichlet allocation
TL;DR: This work proposes a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hofmann's aspect model.
Proceedings Article
Latent Dirichlet Allocation
TL;DR: This paper proposed a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hof-mann's aspect model, also known as probabilistic latent semantic indexing (pLSI).
Book
Finding Groups in Data: An Introduction to Cluster Analysis
TL;DR: An electrical signal transmission system, applicable to the transmission of signals from trackside hot box detector equipment for railroad locomotives and rolling stock, wherein a basic pulse train is transmitted whereof the pulses are of a selected first amplitude and represent a train axle count.
Journal ArticleDOI
An algorithm for suffix stripping
TL;DR: An algorithm for suffix stripping is described, which has been implemented as a short, fast program in BCPL, and performs slightly better than a much more elaborate system with which it has been compared.
Journal ArticleDOI
Finding Groups in Data: An Introduction to Chster Analysis
TL;DR: This book make understandable the cluster analysis is based notion of starsmodern treatment, which efficiently finds accurate clusters in data and discusses various types of study the user set explicitly but also proposes another.