MOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion…

Significant advancements in voice chatbots have spurred interest into their role in second language learning (Conium, 2008), particularly their ability to assist in the development of learners' conversation skills in a target language. Many efforts have been made to explore AI's potential to act as conversation partners for language learners. Of…

Online discussion forums are highly valued by instructors due to their affordance for understanding class activities and learning. However, a discussion forum with a great number of posts requires a large amount of time to view, and help requests are easily overlooked. Various machine-learning--based tools have been developed to help instructors…

In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…

Administering Likert-type questionnaires to online samples risks contamination of the data by malicious computer-generated random responses, also known as bots. Although nonresponsivity indices (NRIs) such as person-total correlations or Mahalanobis distance have shown great promise to detect bots, universal cutoff values are elusive. An initial…

In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…

This article introduces my C.H.A.T.S. model (Conversational, Holistic, Authentic, Transformative, Situated), a novel pedagogical framework I designed to revolutionize language learning and teaching through the strategic integration of Artificial Intelligence (AI) and conversational chatbots with established learning theories. The model addresses…

A discussion forum is an indispensable part of a massive open online course (MOOC) environment as it enables knowledge construction through learner-to-learner interaction such as discussion of solutions to assigned problems among learners. In this paper, a machine prediction model is built based on the data from the MOOC forum and the depth of…

"Online Education" is a comprehensive exploration of fully online and blended teaching platforms, addressing history, theory, research, planning, and practice. As colleges, universities, and schools around the world accelerate their adoption of large-scale technologies and traditional class models shift into seamless, digitally…

Cyberbullying has become increasingly prevalent, particularly on social media. There has also been a steady rise in cyberbullying research across a range of disciplines. Much of the empirical work from computer science has focused on developing machine learning models for cyberbullying detection. Whereas machine learning cyberbullying detection…

The Flipped Classroom Model (FCM) has gained widespread acceptance in higher education as an effective pedagogical strategy. Despite its success, the FCM still faces persistent concerns, including a lack of personalized interaction, limited application to introductory courses, and insufficient analysis of the learning process. The integration of…

This study aims to evaluate the effectiveness and potential utility of using machine learning and natural language processing techniques to develop models that can reliably predict the relative difficulty of incoming chat reference questions. Using a relatively large sample size of chat transcripts (N = 15,690), an empirical experimental design…

This study explores the role of artificial intelligence (AI) in K-12 student assessment practices, focusing on educators' use of AI tools. Through content analysis of active Facebook groups dedicated to AI in education, the authors examined how educators integrate AI into assessment across various grade levels and subjects. Using the Technology…

This article presents an Internet data analysis model based on Web Mining with the aim to find knowledge about large amounts of data in cyberspace. To test the proposed method, suicide web pages were analyzed as a study case to identify and detect traits in students with suicidal tendencies. The procedure considers a Web Scraper to locate and…

This article provides computational and rule-based approaches for detecting confusion that is expressed in students' comments in couse forums. To obtain reliable, ground truth data about which posts exhibit student confusion, we designed a decision tree that facilitates the manual labeling of forum posts by experts. However, manual labeling is…