Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…

Data extraction is a time-consuming and resource-intensive task in the systematic review process. Natural language processing (NLP) artificial intelligence (AI) techniques have the potential to automate data extraction saving time and resources, accelerating the review process, and enhancing the quality and reliability of extracted data. In this…

Accurate data extraction is a key component of evidence synthesis and critical to valid results. The advent of publicly available large language models (LLMs) has generated interest in these tools for evidence synthesis and created uncertainty about the choice of LLM. We compare the performance of two widely available LLMs (Claude 2 and GPT-4) for…

Unnoticed by most, some technology corporations have changed their terms of service to allow user data to be transferred to clouds and even to be used to train artificial intelligence systems. As a result of these developments, remote data collection may in many cases become impossible to be conducted anonymously. Researchers need to react by…

Artificial intelligence (AI) and data science (DS) are receiving a lot of attention in various fields. In the educational field, the need for education utilizing AI and DS is also being emerged. In this context, we have created an AI/DS integrating program that generates a compound classification/regression model using characteristics of compounds…

Recent approaches to the detection of cheaters in tests employ detectors from the field of machine learning. Detectors based on supervised learning algorithms achieve high accuracy but require labeled data sets with identified cheaters for training. Labeled data sets are usually not available at an early stage of the assessment period. In this…

This study combines product- and process-oriented research methods and tools to observe whether and how the presence of pre-translated text affects translation quality and influences the translator's research patterns. It is part of the LeMaTTT project, a simulated longitudinal empirical study exploring the impact of MT on info-mining and thematic…

Vision classification tasks, a fundamental and transformative aspect of deep learning and computer vision, play a pivotal role in our ability to understand the visual world. Deep learning techniques have revolutionized the field, enabling unprecedented accuracy and efficiency in vision classification. However, deep learning models, especially…

Learners' satisfaction with Massive Open Online Courses (MOOCs) has been evaluated through quantitative approaches focusing on survey-based methods in several studies. User-Generated Content (UGC) has been an effective approach to assess users' interactions with e-learning systems. Other than survey-based methods, the UGC generated from MOOCs…

With the advent of readily accessible generative artificial intelligence (GAI), a concern exists within the academic community that research data collected in the context of conducting doctoral dissertation research is authentic. The purpose of the present study was to explore the role of GAI in the production of new research paying particular…

Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

In the swiftly changing realm of education, technology serves as a key instrument in transforming the methods of teaching, learning experiences, and educational outcomes. Legal and governance issues, integral to maintaining order and justice in societies, are equally pertinent in the realm of education. The digital age introduces concerns like…

The nature of teaching and learning has evolved over the years, especially as technology has evolved. Innovative application of educational analytics has gained momentum. Indeed, predictive analytics have become increasingly salient in education. Considering the prevalence of learner-system interaction data and the potential value of such data, it…

The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…

Purpose: It has been demonstrated that AI-powered, data-driven tools' usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy. Design/methodology/approach: The authors…