This manuscript presents an exploratory mixed-methods case study examining the impact of artificial intelligence (AI) in the form of generative pretrained transformers (GPTs) and large language models on special education administrative practices in one school district in the Northeast United States. AI holds tremendous potential to positively…

It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…

This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…

As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…

The presented work is a student marks and grade prediction system using supervised machine learning techniques, the system is developed on the historic performance of students. The data used in this research is collected from Federal Board of Intermediate and Secondary Education Islamabad Pakistan, there are 7 regions in FBISE i.e. Punjab, Sindh,…

In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life…

The objectives of this research were 1) to study the problems of stress and depression among Grade 12 students; 2) to investigate the machine learning technique in analyzing and predicting stress, depression, and academic performance among Grade 12 students; and 3) to evaluate the stress and depression prediction platform. Students from schools in…

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…

Educational data mining has allowed for large improvements in educational outcomes and understanding of educational processes. However, there remains a constant tension between educational data mining advances and protecting student privacy while using educational datasets. Publicly available datasets have facilitated numerous research projects…

Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…

Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by…

Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…

To date, many AI initiatives (eg, AI4K12, CS for All) developed standards and frameworks as guidance for educators to create accessible and engaging Artificial Intelligence (AI) learning experiences for K-12 students. These efforts revealed a significant need to prepare youth to gain a fundamental understanding of how intelligence is created,…

This article utilizes speculative and visual storytelling alongside interdisciplinary research on artificial intelligence (AI) and algorithmic oppression to engage in a thought experiment on how literacy studies might refuse the oppressionist logics currently undermining the possibilities of AI in literacy education. As technological advancements…

With the development of technology allowing for a rapid expansion of data science and machine learning in our everyday lives, a significant gap is forming in the global job market where the demand for qualified workers in these fields cannot be properly satisfied. This worrying trend calls for an immediate action in education, where these skills…