Text classification has allowed researchers to analyze natural language data at a previously impossible scale. However, a text classifier is only as valid as the the annotations on which it was trained. Further, the cost of training a classifier depends on annotators' ability to quickly and accurately apply the coding scheme to each text. Thus,…

Since its first adoption as a computational model for language learning, evidence has accumulated that Rescorla-Wagner error-correction learning (Rescorla & Wagner, 1972) captures several aspects of language processing. Whereas previous studies have provided general support for the Rescorla-Wagner rule by using it to explain the behavior of…

Investigating links between temporal features of the writing process (e.g., bursts and pauses during writing) and the linguistic features found in written products would help us better understand intersections between the writing process and product. However, research on this topic is rare. This article illustrates a method to examine associations…

The 26th annual Teaching Pre-Conference organized by the Advertising Division of the Association for Education in Journalism and Mass Communication focused on the topic of innovating data storytelling and visualization with AI and ChatGPT. Five prominent speakers from leading media companies and universities shared insights with advertising…

Adaptive comparative judgment (ACJ) has been widely used to evaluate classroom artifacts with reliability and validity. In the ACJ experience we examined, students were provided a pair of images related to backpack design. For each pair, students were required to select which image could help them ideate better. Then, they were prompted to provide…

This paper provides a thorough examination of the role of Artificial Intelligence (AI), particularly ChatGPT and other AI language models, in the realm of education. Drawing insights from existing literature and a novel study on educator perspectives, the paper delves into the potential advantages, ethical dilemmas, and factors shaping educators'…

This dissertation investigates how collective process-oriented documentation tools, combined with Natural Language Processing (NLP) techniques, can enhance knowledge construction in hands-on, open-ended learning environments, such as makerspaces. Through a three-year design-based research, the study developed and tested a collective documentation…

Background or Context: Although many scholars have evaluated how Hispanic-serving institutions (HSIs) "serve" and can better "serve" Latinx students and their communities, scant research has integrated artificial intelligence (AI) technology within this evaluation of diversity and "servingness." With institutions of…

The rapid proliferation of the Internet has sparked a resurgence of attention toward the function of novel artificial intelligence technologies in the higher education. The effective adoption of recent advancements in human-computer interaction is crucial for inclusive education and innovation, resulting in sustainable socioeconomic growth and…

Although ChatGPT provides excellent features as a writing assistant tool, few empirical studies have been conducted on its integration into writing education investigating students' usage pattern and impact on the writing skills of students. This exploratory research aims to fill this research gap by analyzing prompts initiated by students and…

This study examines the effectiveness of a custom-designed chatbot in a blended learning environment, focusing on its adherence to instructional guidelines and its impact on student engagement. The chatbot was designed to prompt students with questions about concepts related to various academic majors, encourage elaboration on their responses, and…

Background/Objectives: There is no attempt to investigate the relationships between dependency and markedness even though the syntactic roles in language are decided by dependency relations and markers. The main objective of this study was to understand markedness beyond syntactical tables and propose a syntax graph with various syntax structures…

This study aimed to examine the potentials of the NLP approach in detecting discourse markers (DMs), namely okay, in transcribed spoken data. One hundred thirty-eight concordance lines were presented to human referees to judge the functions of okay in them as a DM or Non-DM. After that, the researchers used a Python script written according to the…

According to the Presupposition-Denial Account, complement set reference arises when focus is on the "shortfall" between the amount conveyed by a natural language quantifier and a larger, expected amount. Negative quantifiers imply a shortfall, through the denial of a presupposition, whereas positive quantifiers do not. An exception may…

Speech in everyday conversations is riddled with discourse markers (DMs), such as "well," "you know," and "like." However, in many lab-based studies of speech comprehension, such DMs are typically absent from the carefully articulated and highly controlled speech stimuli. As such, little is known about how these DMs…