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…

Professional experience elicits enduring effects on teacher self-efficacy (TSE); however, despite a growing understanding of early TSE formation, limited quantitative studies have been conducted. No research has applied a person-centred method, meaning personal variation or simultaneity in the integration of different TSE sources has been…

Perfectionism is a component of multiple disorders, necessitating valid measurement. However, most perfectionism research has used predominantly White samples, a notable limitation for many reasons including past findings that different sociocultural factors can impact perfectionistic tendencies. As similar dynamics might be deleterious to the…

Purpose: Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literature related to prediction, the field lacks a self-assessment…

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…

Research on educational television has overwhelmingly investigated the impact of viewing on children's knowledge acquisition. However, this content might influence other important outcomes, such as children's interest in learning about new topics. To investigate this possibility, we invited parents of 3- to 8-year-old children (N = 83) to answer…

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…

Purpose: Academic anxiety is a common phenomenon in the college student population, which has an important impact on students' psychological health and academic performance. Therefore, by exploring the effects of college students' professional commitment and achievement goal orientation variables on academic anxiety, it helps to understand…

This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…

Purpose: This research employs machine learning and mediation analysis, along with path analysis, to investigate the correlations between factors such as body mass index (BMI) and the occurrence of diabetes and heart disease among the Indian population. The objective is to enhance models that are specifically designed to accommodate lifestyles,…

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…