We propose and implement a novel intelligent tutoring system, called RadarMath, to support personalized learning for math education. The system provides the services including automatic grading guidance. Specifically, two models are designed accomplish tasks scoring text-answer formula-answer questions respectively. An education-oriented knowledge graph with individual learner’s state is used a...

A new Z-basis for the space of quasisymmetric functions (QSym, for short) is presented. It is shown to have nonnegative structure constants, and several interesting properties relative to the quasisymmetric functions associated to matroids by the Hopf algebra morphism F of Billera, Jia, and Reiner [3]. In particular, for loopless matroids, this basis reflects the grading by matroid rank, as wel...

Automated assessment of student learning has become the subject of increasing attention. Students’ textual responses to short answer questions offer a rich source of data for assessment. However, automatically analyzing textual constructed responses poses significant computational challenges, exacerbated by the disfluencies that occur prominently in elementary students’ writing. With robust tex...

Abstract Autograding short textual answers has become much more feasible due to the rise of NLP and increased availability question-answer pairs brought about by a shift online education. performance is still inferior human grading. The statistical black-box nature state-of-the-art machine learning models makes them untrustworthy, raising ethical concerns limiting their practical utility. Furth...

Study Tips Hints to help you review more effectively. Answer Sheets Write the letter of the correct answer for the questions in the review tests. Although only one set of answer sheets are included, you can take these tests as often as you want. Review Session A 100-multiple-choice question Review Session to help you determine where you need more study emphasis. However, be aware that none of t...

Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The STS shared task is a venue for assessing the current state-of-the-art. The 2017 task focuses on multilingual and cross-lingual pairs with on...

A limitation to the accurate study of muscle injuries and their management has been the lack of a uniform approach to the categorisation and grading of muscle injuries. The goal of this narrative review was to provide a framework from which to understand the historical progression of the classification and grading of muscle injuries. We reviewed the classification and grading of muscle injuries...

A number of different research subfields are concerned with the automatic assessment of student answers to comprehension questions, from language learning contexts to computer science exams. They share the need to evaluate free-text answers but differ in task setting and grading/evaluation criteria, among others. This paper has the intention of fostering synergy between the different research s...

We invent referential translation machines (RTMs), a computational model for identifying the translation acts between any two data sets with respect to a reference corpus selected in the same domain, which can be used for automatically grading student answers. RTMs make quality and semantic similarity judgments possible by using retrieved relevant training data as interpretants for reaching sha...

Identification of short text similarity (STS) is a high-utility NLP task with applications in a variety of domains. We explore adaptation of STS algorithms to different target domains and applications. A two-level hierarchical Bayesian model is employed for domain adaptation (DA) of a linear STS model to text from different sources (e.g., news, tweets). This model is then further extended for m...