Post-problem reflective tutorial dialogues between human tutors and students are examined to predict when the tutor changed the level of abstraction from the student's preceding turn (i.e., used more general terms or more specific terms); such changes correlate with learning. Prior work examined lexical changes in abstraction. In this work, we…

Today's Internet-based crime reporting systems make timely and anonymous crime reporting possible. However, these reports also result in a rapidly growing set of unstructured text files. Complicating the problem is that the information has not been filtered or guided in a detective-led interview resulting in much irrelevant information. To…

In this dissertation, I explore unsupervised techniques for the task of automatic short answer grading. I compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating…

The fundamental problem faced by automatic text understanding in Natural Language Processing (NLP) is to identify semantically related pieces of text and integrate them together to compute the meaning of the whole text. However, the principle of compositionality runs into trouble very quickly when real language is examined with its frequent…

This paper discusses Latent Semantic Analysis (LSA) as a method for the assessment of prior learning. The Accreditation of Prior Learning (APL) is a procedure to offer learners an individualized curriculum based on their prior experiences and knowledge. The placement decisions in this process are based on the analysis of student material by domain…

The past two decades have shown an unexpected effectiveness of "Web-scale" data in natural language processing. Even the simplest models, when paired with unprecedented amounts of unstructured and unlabeled Web data, have been shown to outperform sophisticated ones. It has been argued that the effectiveness of Web-scale data has…

This study expands upon an existing model of students' reading comprehension ability within an intelligent tutoring system. The current system evaluates students' natural language input using a local student model. We examine the potential to expand this model by assessing the linguistic features of self-explanations aggregated across entire…

We used event-related potentials (ERPs) to investigate the time course and distribution of brain activity while adults performed (1) a sequential learning task involving complex structured sequences and (2) a language processing task. The same positive ERP deflection, the P600 effect, typically linked to difficult or ungrammatical syntactic…

The neural basis of syntax is a matter of substantial debate. In particular, the inferior frontal gyrus (IFG), or Broca's area, has been prominently linked to syntactic processing, but the anterior temporal lobe has been reported to be activated instead of IFG when manipulating the presence of syntactic structure. These findings are difficult to…

The work we present in this paper aims to help teachers create multiple-choice science tests. We focus on a scientific vocabulary-learning scenario taking place in a Basque-language educational environment. In this particular scenario, we explore the option of automatically generating Multiple-Choice Questions (MCQ) by means of Natural Language…

Chat conversations and other types of online communication environments are widely used within CSCL educational scenarios. However, there is a lack of theoretical and methodological background for the analysis of collaboration. Manual assessing of non-moderated chat discussions is difficult and time-consuming, having as a consequence that learning…

Middle school students struggle to explain thermodynamics concepts. In this study, to help students succeed, we use a natural language processing program to analyze their essays explaining the aspects of thermodynamics and provide guidance based on the automated score. The 346 sixth-grade students were assigned to either the critique condition…

This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

In this paper we address the important task of automated discovery of speech act categories in dialogue-based, multi-party educational games. Speech acts are important in dialogue-based educational systems because they help infer the student speaker's intentions (the task of speech act classification) which in turn is crucial to providing adequate…

The Institute of Medicine has stated that legal structures and the authority vested in health agencies and other partners within the public health system are essential to improving the public's health. Variation between the laws of different jurisdictions within the United States allows for natural experimentation and research into their…