Effectively supporting students in mastering all facets of self-regulated learning is a central aim of teachers and educational researchers. Prior research could demonstrate that formative feedback is an effective way to support students during self-regulated learning. In this light, we propose the application of Large Language Models (LLMs) to…

As artificial intelligence proliferates, so do associated hopes and fears. This study explores such tensions within South African higher education following ChatGPT's launch, analyzing perceived threats alongside opportunities for responsibly harnessing benefits. Adopting a socio-technical framework recognizing technology's interdependence with…

In this thesis, I use a combination of simulations and empirical data to demonstrate that a small set of structural and functional principles - the basic tenets of predictive coding theory - succinctly accounts for a very wide range of properties in the language processing system. Predictive coding approximates hierarchical Bayesian inference via…

Background: Core lexicon (CL) analysis is a time efficient and possibly reliable measure that captures discourse production abilities. For people with aphasia, CL scores have demonstrated correlations with aphasia severity, as well as other discourse and linguistic measures. It was also found to be clinician-friendly and clinically sensitive…

The analyses of observed lessons are an important part of learning to teach. Pedagogically focused conversations are one way for pre-service teachers to do so. But how do pedagogically focused conversations enable pre-service teachers to make sense of observed teaching? Using a collective case-study approach, the study qualitatively explored the…

ChatGPT, a user-friendly and accessible AI tool, offers a revolutionary approach to academic learning. In spite of its benefits, the implementation of ChatGPT into university assignments presents possible risks for students. While extensive global research has studied these risks from students' perspectives, a notable gap exists in comprehending…

Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…

An important issue in second-language acquisition concerns the role of explicit information (EI) and how it is affected by individual differences. The present study explored this question through a partial replication and extension of Fernández (2008: Experiment 2), which investigated the effects of EI in processing instruction (PI) for the…

Artificial Intelligence (AI) is taking the world by storm. Higher education is not immune to this phenomenon and has many challenges in embracing AI. Much has been written lately concerning the typical application of AI in higher education, as well as in the classroom itself. The purpose of this paper is to gather information from students to…

In order to improve the accessibility and user friendliness of an accurately pretrained stacking ensemble machine learning regressor used to predict sulfate levels (mg/L) in Acid Mine Drainage (AMD), a Graphical User Interface (GUI) was developed using Python by combining human input with ChatGPT and deployed in the Jupyter Notebook environment.…

As education increasingly shifts towards a technology-driven model, artificial intelligence systems like ChatGPT are gaining recognition for their potential to enhance educational support. In university education and MOOC environments, students often select courses that align with their specific needs. During this process, access to information…

We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…

Automated writing evaluation (AWE) systems are developed based on interdisciplinary research and technological advances such as natural language processing, computer sciences, and latent semantic analysis. Despite a steady increase in research publications in this area, the results of AWE investigations are often mixed, and their validity may be…

In this article, we introduce an Open Education Resource (OER) on digital historical research with historical newspapers, intended to give students the means to understand the induced risks in working with large collections of digitised documents, as well as the keys to benefit from the advances of natural language processing over large…

The processing of morphologically complex words has been studied in many languages, leading to a variety of theoretical accounts. Prime type, individual differences, and cross-linguistic effects have emerged as potential factors in morphological processing, but the findings so far have been inconclusive, especially for young children. This study…