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…

Researchers have argued that many leaders, such as CEOs and politicians, tend to possess narcissistic traits. At healthy and productive levels, narcissistic traits, such as self-promotion, may actually be an advantage to achieving success in some fields. Yet, few researchers have explored gifted narcissists as a twice-exceptionality. This article…

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…

This cross-sectional survey questionnaire study explores the Petrides Model of Trait Emotional Intelligence (TEI) of school principals in the Commonwealth of Pennsylvania, employing the Trait Emotional Intelligence Questionnaire (TEIQue). This research study explored statistical differences in TEI components (Global Score, factor scores, and facet…

The improvements in attention by mindfulness training have been proved. However, the effects of mindfulness training on attention to emotional stimuli were mixed. We employed a randomized, controlled design to investigate the effects of mindfulness training on attention to emotional expressions, and investigated whether baseline levels of…

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…

Purpose: Guided by Habermas's three cognitive interests, this paper reviews the studies on school leaders' emotional labor. It seeks to provide a typology of how researchers inquire about school leaders' emotional labor by focusing on different understandings, topics and characteristics. Design/methodology/approach: This is a narrative review with…

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…

Purpose: Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic criteria has changed from DSM-IV to DSM-5, which can make diagnosing a disorder on the autism spectrum…