In this study, which focuses on selecting the material and predicting its mechanical behaviors in materials science, an Artificial Neural Network (ANN) was used to predict and simulate the low-speed impact effects of hybrid nano-doped aramid composites. There are not enough studies about open education practices in this field. Since error values…

Communication strategies define audience-specific behavioral goals, identify priority cognitive and affective communication objectives necessary to achieving those goals, and propose specific communication tactics meant to increase the likelihood of achieving those objectives. Unfortunately, it appears that few scientific organizations have…

This paper presents a systematic literature review of using Machine Learning (ML) techniques in higher education career recommendation. Despite the growing interest in leveraging Artificial Intelligence (AI) for personalized academic guidance, no previous reviews have synthesized the diverse methodologies in this field. Following the Kitchenham…

In the context of introductory courses in physical geography and meteorology, it is common around February 2 for curiosity to arise among students regarding the veracity of "Groundhog Day" predictions. Historically, most instructors' immediate response to such inquiries has been a definitive "NO," emphasizing the impossibility…

In the last years special "ovals" appear increasingly often in diagrams and applets for discussing crucial items of statistical inference (when dealing with confidence intervals for an unknown probability p; approximation of the binomial distribution by the normal distribution; especially in German literature, see e.g. [Meyer,…

Individuals and organizations frequently tout creative ideas as a desirable goal, and yet, creative ideas are frequently rejected. Creativity researchers have often suggested that creative ideas are rejected because they are perceived as riskier due to their inherent novelty or originality. Although this assumption is prevalent, we are unaware of…

This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…

Theories of self-regulated learning suggest a positive link between knowledge monitoring accuracy (the ability to predict test performance) and performance on tests. Put differently, students who accurately monitor their knowledge of course content more efficiently regulate study of course materials. However, a plethora of literature indicates…

The early detection of neurodevelopmental disorders (NDDs) can significantly improve patient outcomes. The differential burden of non-synonymous de novo mutation among NDD cases and controls indicates that de novo coding variation can be used to identify a subset of samples that will likely display an NDD phenotype. Thus, we have developed an…

In this work, we introduce a novel oversampling technique, the theory of inheritance and Gower distance-based oversampling (TIGO) method, designed to address class imbalance issues in mixed categorical and continuous variables data set. Drawing inspiration from genetic inheritance principles, TIGO synthesizes new minority class data,…

The purpose of this study is to determine if personality traits can predict the coaching intervention style preferences of teachers in the United States of America. The rationale for this study is to gain a better understanding of whether there are personality traits that are better suited to particular coaching techniques/methods. To address this…

School districts increasingly gauge school quality with surveys that ask about school climate and student engagement. We use data from New York City's middle and high schools to compare the long-run predictive validity of surveys with that of conventional test score value-added models (VAMs). Our analysis leverages the New York school match, which…

As an excellent means of improving students' effective learning, knowledge tracking can assess the level of knowledge mastery and discover latent learning patterns based on students' historical learning evaluation of related questions. The advantage of knowledge tracking is that it can better organize and adjust students' learning plans, provide…

The ability to predict upcoming events is essential in infancy because it enables babies to process information optimally and have successful goal-directed interactions with their environment. In this article, we examine how infants generate predictions in perception, cognition, and action, and address whether and how their predictions are…

The recommendation is an active area of scientific research; it is also a challenging and fundamental problem in online education. However, classical recommender systems usually suffer from item cold-start issues. Besides, unlike other fields like e-commerce or entertainment, e-learning recommendations must ensure that learners have the adequate…