Beyond informing human resources (HR) policies and practices, information gleaned from predictive analytics, visualized via dashboards, can increase awareness and prompt employee and management actions based on identified variables often related to intent to leave and employee wellness. While considerable research, relevant measurements, and tools…

The use of artificial intelligence (AI) in higher education has mostly focused on issues associated with teaching and assessment. In this paper I used AI to support the analysis of data which consisted of public comments on a newspaper article. This small, low risk research was chosen to demonstrate the potential use of AI and how it may support…

Without regulations for higher education institutions in the metaverse, ethical transgressions are unavoidable. Educational metaverse systems, which integrate artificial intelligence, essentially depend on big data as their core technology, leading to considerable privacy issues. Therefore, this study examines data privacy and security issues, a…

Teachers often use open-ended questions to promote students' deeper understanding of the content. These questions are particularly useful in K-12 mathematics education, as they provide richer insights into students' problem-solving processes compared to closed-ended questions. However, they are also challenging to implement in educational…

Despite increased efforts to assess the adoption rates of open science and robustness of reproducibility in sub-disciplines of education technology, there is a lack of understanding of why some research is not reproducible. Prior work has taken the first step toward assessing reproducibility of research, but has assumed certain constraints which…

Text analytics in education has evolved to form a critical component of the future SMART campus architecture. Sentiment analysis and qualitative feedback from students is now a crucial application domain of text analytics relevant to institutions. The implementation of sentiment analysis helps understand learners' appreciation of lessons, which…

Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various data mining techniques have been used to improve learning outcomes by exploring large-scale data that…

The combination of the quantitative turn in linguistics and the emergence of text analytics has created a demand for new methodological skills among linguists and data scientists. This paper introduces KNIME as a low-code programming platform for linguists interested in learning text analytic methods, while highlighting the considerations…

This study focuses on Grounded Theory, which is one of the qualitative research designs. Glaser and Strauss developed the Grounded Theory; it has been revised by other scientists, resulting in three distinct Grounded Theory approaches: the systematic design (Corbin and Strauss approach), the classical design (Glaser approach), and the…

With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

Scholars in the field of art education have varied professional trajectories, yet they are networked in academia, both through their advisors as well as through the universities in which they completed their graduate degrees. This study makes these complex relationships visible through the use of visualizations and an interactive website created…

It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…

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…

Higher education (HE) is a challenging area for quality professionals because of its highly complex operational nature. While neither quality management (QM) in HE nor applications of analytics in QM is a new research discipline, few studies have examined the applications of analytics in the context of QM in HE. This study calls for more attention…

Students typically find research methods and statistics classes intimidating. In particular, learning different types of data measurement and operationalization can take significant time and practice to understand. Utilizing a pedagogical approach that turns a party game into a fun exercise, students collaboratively learn to operationalize…