The application of natural language processing (NLP) technology in the field of education has attracted considerable attention. This study takes 716 articles from the Web of Science database from 1998 to 2023 as its research sample. Using bibliometrics as the theoretical foundation, and employing methods such as literature review and knowledge…

Social identity threat refers to the process through which an individual underperforms in some domain due to their concern with confirming a negative stereotype held about their group. Psychological research has identified this as one contributor to the underperformance and underrepresentation of women, Blacks, and Latinos in STEM fields. Over the…

Maps such as concept maps and knowledge maps are often used as learning materials. These maps have nodes and links, nodes as key concepts and links as relationships between key concepts. From a map, the user can recognize the important concepts and the relationships between them. To build concept or knowledge maps, domain experts are needed.…

Natural language processing (NLP) is a field of computer science and linguistics devoted to creating computer systems that use human (natural) language as input and/or output. The authors propose that NLP can also be used for game studies research. In this article, the authors provide an overview of NLP and describe some research possibilities…

Research related to online discussions frequently faces the problem of analyzing huge corpora. Natural Language Processing (NLP) technologies may allow automating this analysis. However, the state-of-the-art in machine learning and text mining approaches yields models that do not transfer well between corpora related to different topics. Also,…

Researchers that investigate the media's coverage of health have historically relied on keyword searches to retrieve relevant health news coverage, and manual content analysis methods to categorize and score health news text. These methods are problematic. Manual content analysis methods are labor intensive, time consuming, and inherently…

The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt…

Recent research in learning technologies has demonstrated many promising contributions from the use of ontologies and semantic web technologies for the development of advanced learning environments. In spite of those benefits, ontology development and maintenance remain the key research challenges to be solved before ontology-enhanced learning…

Purpose: The purpose of this paper is to present a computational approach and a toolset to infer spatial displacements as they occur in route narrative documents and report on first experiments done to produce computer-aided learning (CAL) applications and instructional design editors that exploit the inferred georeferenced itineraries.…

Text analytics refers to the process of analyzing unstructured data from documented sources, including open-ended surveys, blogs, and other types of web dialog. Text analytics has enveloped the concept of text mining, an analysis approach influenced heavily from data mining. While text mining has been covered extensively in various computer…