Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…

This study presents several multivariate Generalizability theory designs for analyzing automatic item-generated (AIG) based test forms. The study used real data to illustrate the analysis procedure and discuss practical considerations. We collected the data from two groups of students, each group receiving a different form generated by AIG. A…

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…

How are educational values and pedagogical approaches inscribed into automated education technologies and their data visualizations? In this article we analyze the design process and technical and pedagogical debates of a team of researchers and developers working on an automated scoring tool for primary school students' early writing as part of…

In this essay, we explored the feasibility of utilizing artificial intelligence (AI) for qualitative data analysis in equity-focused research. Specifically, we compare thematic analyses of interview transcripts conducted by human coders with those performed by GPT-3 using a zero-shot chain-of-thought prompting strategy. Our results suggest that…

There is an increasing interest and growing practice in Citizen Science (CS) that goes along with the usage of websites for communication as well as for capturing and processing data and materials. From an educational perspective, it is expected that by integrating information about CS in a formal educational setting, it will inspire teachers to…

The Powerful Learning with Computational Thinking report explains how the Digital Promise team works with districts, schools, and teachers to make computational thinking ideas more concrete to practitioners for teaching, design, and assessment. We describe three powerful ways of using computers that integrate well with academic subject matter and…

Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…

To train two-versus-two sports, it is beneficial to play regularly with varying teammates and opponents of similar skill level. However, even in small classes, it is almost impossible for a human instructor to maintain an accurate overview of each student's skill development to optimize teams and pairings accordingly. Therefore, we propose an…

Smart supply chain management (SSCM) has recently attracted significant attention from both industry and academia, particularly in light of the COVID pandemic. This article reviews current literature on information and integration, process automation, advanced analytics, and related business curriculum in SSCM. Our survey results demonstrate a…

Background: Traditional survey efforts to gather outcome data at scale have significant limitations, including cost, time, and respondent burden. This pilot study explored new and innovative large-scale methods of collecting and validating data from publicly available sources. Taking advantage of emerging data science techniques, we leverage…

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…

Recognizing learners' engagement during learning processes is important for providing personalized pedagogical support and preventing dropouts. As learning processes shift from traditional offline classrooms to distance learning, methods for automatically identifying engagement levels should be developed. This article aims to present a literature…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…