As generative AI (GenAI) continues to permeate academia, distinguishing between student-authored essays and those by Large Language Models (LLMs) becomes crucial for maintaining academic integrity. This study conducted a survey on the ethical awareness of using generative AI tools among a group of STEM students (n=156). Also, we empirically…

This study explores the use of large language models (LLMs) to generate feedback on essay-type assignments in Higher Education. Drawing on a seminal feedback framework, it examines the pedagogical and psychological effectiveness of LLM-generated feedback across three cohorts of MBA, MSc, and undergraduate students. Methods included linguistic…

The release of ChatGPT in 2022 has generated extensive speculation about how Artificial Intelligence (AI) will impact the capacity of institutions for higher learning to achieve their central missions of promoting learning and certifying knowledge. Our main questions were whether people could identify AI-generated text and whether factors such as…

An increasing number of studies have investigated how ChatGPT can aid in written assessment and feedback provision. However, many studies overlook its conversational design and underlying architecture, raising concerns about the reliability and validity of their analytical outputs. Therefore, applying first principles thinking to prompt use, and…

The aim of this project was to understand student perspectives on generative artificial intelligence (GAI) technologies such as Chat generative Pre-Trained Transformer (ChatGPT), in order to inform changes to the University of Liverpool Academic Integrity code of practice. The survey for this study was created by a library student team and vetted…

In postsecondary education institutions, where innovative technologies continually reshape research and pedagogical approaches, the integration of generative artificial intelligence (GenAI) tools presents promising avenues for enhancing student learning experiences. This study assesses the efficacy of integrating GenAI tools, specifically…

Various studies empirically proved the value of highly informative feedback for enhancing learner success. However, digital educational technology has yet to catch up as automated feedback is often provided shallowly. This paper presents a case study on implementing a pipeline that provides German-speaking university students enrolled in an…

Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenges for using such tools in college classrooms. To address this, an adaptable assignment called the…

Metaphors are known to present both opportunities and challenges for second language learners, but relatively little is known about learners' awareness of them. To investigate this, we analyzed 72 argumentative essays written in English by a group of 37 intermediate Chinese university students of English. We identified metaphors using an…

Contribution: Demonstrates how to use experiential learning (EL) to improve argumentative writing. Presents the design and development of a natural language processing (NLP) application for aiding instructors in providing feedback on student essays. Discusses how EL combined with automated support provides an analytical approach to improving…

This study analyzes the linguistic features of counter-arguments and support arguments using two computational linguistic tools: Coh-Metrix and Gramulator. The research question investigates whether counter-argument paragraphs and support paragraphs are different in terms of their linguistic features. To conduct this study, a corpus of 78…

This article, drawing on essays written by students with the assistance of ChatGPT and interviews with some students who used this learning machine, highlights a shift in the educational landscape brought about by this technology. In broader terms, Palestinian universities follow the traditional methods of teaching based on memorization and rote…

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

The study developed a model of linguistic constructs to predict writing quality for college basic writers and analyzed how those constructs changed following instruction. Analysis used a corpus of argumentative essays from a quasi-experimental, instructional study with 252 students (MacArthur, Philippakos, & Ianetta, 2015) that found large…