Showing 1 - 6 of 6 Research Library Publications
Posted: | King Yiu Suen, Victoria Yaneva, Le An Ha, Janet Mee, Yiyun Zhou, Polina Harik

Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), Pages 443-447

 

This paper presents the ACTA system, which performs automated short-answer grading in the domain of high-stakes medical exams. The system builds upon previous work on neural similarity-based grading approaches by applying these to the medical domain and utilizing contrastive learning as a means to optimize the similarity metric. 

Posted: | Victoria Yaneva, Peter Baldwin, Le An Ha, Christopher Runyon

Advancing Natural Language Processing in Educational Assessment: Pages 167-182

 

This chapter discusses the evolution of natural language processing (NLP) approaches to text representation and how different ways of representing text can be utilized for a relatively understudied task in educational assessment – that of predicting item characteristics from item text.

Posted: | Polina Harik, Janet Mee, Christopher Runyon, Brian E. Clauser

Advancing Natural Language Processing in Educational Assessment: Pages 58-73

 

This chapter describes INCITE, an NLP-based system for scoring free-text responses. It emphasizes the importance of context and the system’s intended use and explains how each component of the system contributed to its accuracy.

Posted: | Victoria Yaneva, Le An Ha, Sukru Eraslan, Yeliz Yesilada, Ruslan Mitkov

Neural Engineering Techniques for Autism Spectrum Disorder: Volume 2, Pages 63-79

 

Automated detection of high-functioning autism in adults is a highly challenging and understudied problem. In search of a way to automatically detect the condition, this chapter explores how eye-tracking data from reading tasks can be used.

Posted: | Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva, Simon Harper

ACM SIGACCESS Accessibility and Computing

 

In this article, we first summarise STA (Scanpath Trend Analysis) with its application in autism detection, and then discuss future directions for this research.

Posted: | M. J. Margolis, B. E. Clauser

Handbook of Automated Scoring

 

In this chapter we describe the historical background that led to development of the simulations and the subsequent refinement of the construct that occurred as the interface was being developed. We then describe the evolution of the automated scoring procedures from linear regression modeling to rule-based procedures.