In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

Visual data have dramatically increased in quantity in the digital age, presenting new opportunities for social science research. However, the extensive time and labor costs to process and analyze these data with existing approaches limit their use. Computer vision methods hold promise but often require large and nonexistent training data to…

This paper examines ways in which the ethics of data-driven technologies might be (re)politicised, particularly where educational institutions are involved. The recent proliferation of principles, guidelines, and frameworks for ethical 'AI' (artificial intelligence) have emerged from a plethora of organisations in recent years, and seem poised to…

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…

Despite calls to increase the focus on explainability and interpretability in EDM and, in particular, student success prediction, so that it becomes useful for personalized intervention systems, only few efforts have been undertaken in that direction so far. In this paper, we argue that this is mainly due to the limitations of current Explainable…

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…

Generative artificial intelligence (AI) has shown the potential to reshape the world and redefine daily workflows. One specific instance of generative AI, ChatGPT, specializes in understanding natural language and generating human-like conversational text. Its free access, user-friendly interface, and instant feedback have propelled its popularity…

With the development of internet technology, big data has been used to evaluate the singing and pronunciation quality of vocal students. However, current methods have several problems such as poor information fusion efficiency, low algorithm robustness, and low recognition accuracy under low signal-to-noise ratio. To address these issues, this…

This paper offers guidance on employing open and creative methods for co- designing critical data and artificial intelligence (AI) literacy spaces and learning activities, rooted in the principles of Data Justice. Through innovative approaches, we aim to enhance participation in learning, research and policymaking, fostering a comprehensive…

This brief explores data science methods that workforce programs can use to predict participant success. With access to vast amounts of data on their programs, workforce training providers can leverage their management information systems (MIS) to understand and improve their programs' outcomes. By predicting which participants are at greater risk…

As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

Data mining approaches have been widely used to estimate student performance in online education. Various Machine Learning (ML) based data mining techniques have been developed to evaluate student performance accurately. However, they face specific issues in implementation. Hence, a novel hybrid Elman Neural with Apriori Mining (ENAM) approach was…

An effective educational program warrants the inclusion of an innovative construction that enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational decision support system has currently been a hot topic in educational systems, facilitating the pupil…

I review opportunities and threats that widely accessible Artificial Intelligence (AI)-powered services present for educational statistics and measurement. Algorithmic and computational advances continue to improve approaches to item generation, scale maintenance, test security, test scoring, and score reporting. Predictable misuses of AI for…

Our primary objective in this Special Issue was to respond to potential criticisms of AIED in potentially "perpetuating poor pedagogic practices, datafication, and introducing classroom surveillance" and to comment on the future of AIED in its coming of age. My overarching assumption in response to this line of critiques is that humans…