Artificial Intelligence (AI) is increasingly being used in education, but mostly to support individual teaching and learning. However, there are good reasons to think that thinking together and solving problems together, Collective Intelligence (CI), is also a valuable outcome of education. Accordingly, our main research question is: How can AI be…

Explanatory processes are at the core of scientific investigation, legal reasoning, and education. However, effectively explaining complex or large amounts of information, such as that contained in a textbook or library, in an intuitive, user-centered way is still an open challenge. Indeed, different people may search for and request different…

In recent years, the pre-training of Large Language Models (LLMs) in the educational domain has garnered significant attention. However, a discernible gap exists in the application of these models to mathematics education. This study aims to bridge this gap by pre-training LLMs on authentic K-12 mathematical dialogue datasets. Our research is…

Education is a dynamic field that must be adaptable to sudden changes and disruptions caused by events like pandemics, war, and natural disasters related to climate change. When these events occur, traditional classrooms with traditional or blended delivery can shift to fully online learning, which requires an efficient learning environment that…

Anatomical pathology (AP) is an anatomy-centric medical specialty devoted to tissue-based diagnosis of disease. The field faces a current and predicted workforce shortage, likely increasing diagnostic wait times and delaying patient access to urgent treatment. A lack of AP exposure is proposed to preclude recruitment to the field, as medical…

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…

Social media has the unique capacity to expose many learners to media literacy instruction "via" targeted campaigns. Investigating learner engagement and reaction to these efforts may be a fruitful endeavor for researchers that can inform the design of future campaigns. However, the massive datasets associated with social media posts are…

This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…

This qualitative descriptive case study explores how genealogists describe the mechanism of epistemic change in their research, highlighting the roles of epistemological doubt, epistemological volition, and resolution strategies. It explores the integration of digital technologies in genealogical practices in the United States and their…

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…

With the latest advances in conversational agents like Siri and Alexa, and Large Language Models (LLMs) like ChatGPT and PaLM, Question Answering (QA) systems have become more important. Users submit millions of queries per day and it is up to the system to provide reliable, to-the-point answers. In this dissertation, we explore various aspects to…

This article introduces a novel method that integrates collaborative filtering into the naive Bayes model to enhance predicting student academic performance. The combined approach leverages collaborative user behavior analysis and probabilistic modeling, showing promising results in improved prediction precision. Collaborative Filtering explores…

Educational Data Mining (EDM) is an interdisciplinary field that encapsulates different fields such as computer science, education, and statistics. It is crucial to make data mining in education to shape future trends in education for policymakers, researchers, and educators in terms of developments. To have an all-inclusive understanding of EDM…

The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing…

Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students' learning. To effectively evaluate maps, instructors must select the most informative map features that capture students' knowledge constructs. However, there is currently no clear and consistent criteria to select such features, as…