Progress made in Natural Language Processing (NLP) and Artificial Intelligence (AI) in recent years has resulted in these tools becoming more accessible for individuals who lack professional training. Of particular note are large language models, such as OpenAI's GPT-3.5. Discussions of utilizing AI for language education usually focus on the…

E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…

Computer-based Natural Language Processing (NLP) is the key to enabling humans and their computer-based creations to interact with machines using natural languages (English, Japanese, German, etc.) rather than formal computer languages. NLP is a major research area in the fields of artificial intelligence and computational linguistics. Commercial…

This report summarizes research on experienced programmers' comprehension of computer programs that was carried out over a three-year contract period (1982-85). Following an extensive review of the programming skill literature, an analysis of programs based on the multiple abstractions (points-of-view) that characterize program text and design was…

This paper examines the problem of automatic explanation of reasoning, or the ability of a program to discuss what it is doing in some understandable way, particularly as part of an expert system. An introduction presents a general framework in which to view explanation and reviews some of the research in this area. This is followed by a…

Traces the history of the Text Encoding Initiative (TEI) from the 1987 Vassar Conference to the publication, "Guidelines for the Electronic Text Encoding and Interchange." Explains the types of questions raised and attempts made to answer them. Discusses the organization of TEI committees and the project's future. (CFR)

Asserts that humanities computing techniques and methodologies remain marginal to mainstream literary scholarship. Argues for large scale analyses of text databases that would incorporate a shift in theoretical orientation to include greater stress on intertextuality and sign theory. (CFR)