This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…

Graph neural networks (GNN) are vital for analyzing real-world problems (e.g., network analysis, drug interaction, electronic design automation, e-commerce) that use graph models. However, efficient GNN acceleration faces with multiple challenges related to high and variable sparsity of input feature vectors, power-law degree distribution in the…

Recent research has indicated that the manner in which single-case data are typically displayed for visual analysis may influence rater decisions regarding the effect of an intervention. Subsequently, researchers have encouraged adherence to a standard assembly for linear graphs in order to control these effects. Others, however, have encouraged…

Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…

The current study used a randomized control trial to evaluate a decision-making model on special education preservice candidates' instructional decision-making and self-reported confidence ratings when analyzing graphed student data. Thirty-two special education preservice candidates viewed authentic curriculum-based measurement (CBM) graphs and…

Nitrogen- or phosphorus-based fertilizers, used in agriculture, can run off into nearby waterways during periods of heavy rain or high flow and cause harmful blooms (Paerl et al. 2016), low oxygen (Joyce 2000), and decreased biodiversity (Sebens 1994). Studies of the effects wetlands can have on water and habitat quality (Verhoeven and Meuleman…

Understanding educators' networks can inform the field of school psychology by offering insight into how the structure of social relationships supports the implementation of school-based programs. However, the difficulties of collecting and modeling network data remain barriers to using network methods in school psychology. To overcome these…

In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed…

In the identification process, there may be gifted students who may be unnoticed or students who are misdiagnosed and are disappointed. In this context, this study is a step that may solve these two problems about the identification of mathematically gifted students with the help of data mining, which is data analysis methodology that has been…

When comparing social science phenomena through a time perspective, absolute and relative difference (RD) are the two typical presentation formats used to communicate interpretations to the audience, while time distance (TD) is the least frequently used of such formats. This article argues that the chosen presentation format is extremely important…

Single-case data are frequently used in school psychology. In research, single-case designs allow experimenters to provide rigorous demonstrations of treatment effects on a smaller scale and with more precise measurement than traditional group experimental design. In practice, single-case data are used to evaluate the effects of school-based…

This article is a presentation of a three-day sequence of lessons that engaged fifth-grade students in an exploration following the activities of scientists. From asking questions and analyzing data, to engaging in scientific modeling, to defending their theories to the scientific (classroom) community, these fifth graders were mirroring how…

Purpose: Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. Method: We propose a…

Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…