Worldwide, the COVID-19 pandemic and the growing reliance on technology underscored the need for K-12 teachers to be digitally competent and able to teach their students 21st century digital skills. The purpose of this quantitative correlational predictive study was to examine if and to what extent perceived usefulness of technology and perceived…

Elementary teachers around the world were recently faced with transitioning to hybrid or virtual teaching due to the COVID-19 pandemic. This was a situation that teachers had never been in before and one in which they had not been trained. Due to the availability of educational technology, teachers were able to adopt new programs, often having to…

This study investigated the relationship between teachers' mindsets (growth mindset and fixed mindset), teachers' digital competence, teachers' age, gender, years of teaching experience, and information and communication technology (ICT) use in teaching in elementary schools, in a city located at the Northwest region of Saudi Arabia. This study…

Determining which students are at-risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of both research and practice in K-12 education. The models produced from this type of predictive modeling research are increasingly used by high schools in Early Warning…

The purpose of the current study was to examine the effectiveness of virtual reality as a creative adaptive learning tool to help participants control their perceived stress and, in turn, their psychological well-being. The study leveraged humanistic learning theory to conceptualize findings. 353 participants were recruited from five high schools…

Having a job immediately after graduation is the dream of every IT graduate. However, not everyone can achieve this outcome. The study's primary goal is to develop predictive models to forecast IT graduates' chances of finding a job based on factors such as academic performance, socioeconomic status, academic habits, and demographic data.…

Intelligent Tutoring Systems (ITSs) have emerged as valuable systems to promote active learning. It is critical to build accurate student models to support the learning process. In order to provide efficient and effective personalized instructions for students, tracking a student's time-varying knowledge state is essential to an ITS. Prior…

At the molecular level, chemical processes involve the rearrangement of atoms in space and time. Students often struggle with visualizing the 3D spatial characteristics of molecules and transition states, as well as recognizing the dynamic nature of chemistry. Both visual spatial skills and representational competence should be explicitly trained…

This predictive correlational study explored the lack of generalizable data regarding the use of technology in the Christian K-12 environment. The study searched for a predictive correlation between teachers' overall use of technology, openness to change, amount of technology training, and hours of work beyond the contractual work week, based on…

The purpose of this quantitative, correlational predictive study was to determine if, and to what extent, scoring of an academic supervisor's transformational, transactional, or passive avoidant leadership by faculty members of regionally accredited four-year, degree-granting educational institutions across the United States separately predicts…

Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…

This study addresses a gap in research literature regarding educator's experiences teaching online high school, focusing on strengths, challenges, and professionalism, from an online high school teacher's perspective. In addition, teachers provided their perceived level of professionalism as online high school teachers and provided their…

Video compression and communication has been an important field over the past decades and critical for many applications, e.g., video on demand, video-conferencing, and remote education. In many applications, providing low-delay and error-resilient video transmission and increasing the coding efficiency are two major challenges. Low-delay and…

Data science is a broad, interdisciplinary field concerned with the extraction of knowledge or insights from data, with the classification of data as a core, fundamental task. One of the most persistent challenges faced when performing classification is the class imbalance problem. Class imbalance refers to when the frequency with which each class…

This study mainly talks about U.S. PhD education and applications of machine learning methods. On one hand, PhD education, as a way to cultivate future researchers, attracts a lot of attention. On the other hand, machine learning methods are utilized more and more often in academic research. This study, as an attempt, would like to contribute to…