Purpose: Technology, such as artificial intelligence (AI), is transforming the way we work; however, it is yet to systemically transform learning at the workplace beyond augmentation of formal education's learning processes. This paper derives functional requirements for technologies that support workplace learning and assesses the suitability and…

Purpose: This paper explores the integration of generative artificial intelligence (GenAI) into the Community of Inquiry (CoI) framework, focusing on how GenAI can dynamically personalize online learning environments. The study aims to examine how GenAI can enhance social, cognitive and teaching presence, thus meeting the diverse needs of…

eLearning is fast progressing scientific field proposing novel and specific approaches in a range of domains. It is well established practice in universities, schools and organizations for delivering interactive, adaptive and flexible training, taking advantage of contemporary and emerging technologies. Informatics is a continuously evolving…

The technology enhancement learning (TEL) needs continuous use and high perception from learners with collaborative of technologies and multi-media applications. The problem of continuous intention in e-learning applications relies on the type of technology used that changes from one university to another. This study aims to design a framework…

Predicting learning and human behavior in general is a challenging endeavor. Machine learning driven predictive modeling have been an increasingly popular means to understand disparities in student performance. With more than a handful of approaches to predictive modeling, the current literature of predicting learning is plagued with issues such…

Ontologies are used with great success in education because they allow to formulate the representation of a learning domain by specifying all concepts involved, relations between concepts and all properties and conditions that exist. The goal of this paper is to present the field of ontologies and give an overview of recent research in the field,…

Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…

The models of E-learning Readiness (ELR) are basically designed to understand the process of obtaining the basic information necessary for measuring ELR among participants. They help organizations to identify the requirements for designing, developing and implementing E-learning. These models not only help the organizations to identify the degree…

This activity aims to assist students with persuasive tactics for argumentative speeches. The activity involves students creating an argumentative speech to defend a hot-take assertion chosen from a list provided by the instructor. In small groups, students will craft an argument supporting their hot-take assertion and present it to the class.…

Introduction: Psycholinguistics presents a challenge to teaching and learning because of the many abstract models in the field. Language-related games provide a vehicle for students to ground and demonstrate their understanding of these models. Statement of the problem: Models in psycholinguistics are challenging to teach and learn because they…

Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

Central to the institutionalization of learning analytics is the need to understand and improve student learning. Frameworks guiding the implementation of learning analytics flow from and perpetuate specific understandings of learning. Crucially, they also provide insights into how learning analytics acknowledges and positions itself as entangled…

Efklides and colleagues developed the Metacognitive and Affective model of Self-Regulated Learning (MASRL) to provide a comprehensive theoretical framework of self-regulated learning (SRL). The distinguishing feature of MASRL is that it stresses metacognitive experiences and other subjective experiences (e.g., motivational, affective) as critical…

This dissertation is about a particular style of research. The philosophy of this style is that in order to scientifically understand deep learning, it is fruitful to investigate what happens when neural networks are trained on simple, mathematically well-defined tasks. Even though the training data is simple, the training algorithm can end up…

Even highly motivated undergraduates drift off their STEM career pathways. In large introductory STEM classes, instructors struggle to identify and support these students. To address these issues, we developed co-redesign methods in partnership with disciplinary experts to create high-structure STEM courses that better support students and produce…