In this paper, we describe our solution to predict student STEM career choices during the 2017 ASSISTments Datamining Competition. We built a machine learning system that automatically reformats the data set, generates new features and prunes redundant ones, and performs model and feature selection. We designed the system to automatically find a…

Although the general purpose in this research is to use the artificial neural network model in mathematics education, the main purpose is to show the relationship between students' tendency towards the types of mathematical proof and the learning styles they have by using the artificial neural network model. In addition, SOM-Ward clustering…

Apart from the fact that human-like robots are still one of the most interesting topics in science fiction, artificial intelligence (AI) continues to develop rapidly as a popular phenomenon for all sectors. Although the idea that this rapid rise of AI means the rise of humanity has been voiced by many, the point of how AI will affect humanity…

By applying educational data mining methods to big data related to large-scale exams, functional relationships are discovered in a basic sense and hidden pattern(s) can be revealed. Within the scope of the research, to show how the self-organizing map (SOM) method can be used in terms of educational data mining, how SOM differs from other…

The understanding of online classroom talk is a challenge even with current technological advancements. To determine the quality of ideas in classroom talk for individual and groups of students, a new approach such as precision education will be needed to integrate learning analytics and machine learning techniques to improve the quality of…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

Over the past 20 years, the authors have designed an interdisciplinary approach that integrates Arts-based methods into STEM education. This integrated STEAM education perspective is particularly useful for enabling students to develop (i) not only their traditional scientific (and mathematical) understanding of the outer world but also (ii) their…

Artificial intelligence (AI) has become more prevalent in education in recent years. Specifically, the perception of generative AI chatbots that generate essays based on the input of student prompts has invoked mixed reviews among educators. The negative learning implications of generative AI chatbots include plagiarism, academic dishonesty, and…

This study addresses the challenge of teaching genetics effectively to high school students, a topic known to be particularly challenging. Leveraging the growing importance of artificial intelligence (AI) in education, the research explores the perspectives, attitudes, and behavioral intentions of pre-service teachers regarding the integration of…

Artificial intelligence (AI) technologies continue to revolutionize various sectors, including their incorporation into education, particularly in K-12 science education, which has become evidently significant. This paper presents a bibliometric analysis and systematic review that examines the incorporation of AI technologies in K-12 science…

This study analyzed the post-high school outcomes of exited high-school students with intellectual disability and autism spectrum disorder from a southwestern U.S. state. A predictive analytics approach was used to analyze these students' post-high school outcomes data, which every state is required to collect each year under U.S.…

We use an autoethnographic case study of a Latinx high school student from a rural, agricultural community in California to highlight how AI is learned outside classrooms and how her personal background influenced her social-justice-oriented applications of AI technologies. Applying the concept of learning pathways from the learning sciences, we…

This research intended to identify key contextual factors that synergistically influence high- and low-performing students' science outcomes by drawing upon a dynamic model of educational effectiveness. The dataset, the Programme for International Student Assessment (PISA) 2015, consisted of 79,963 science scores for secondary students (49,924…

This study examines how lower secondary school students understand the circulatory system, using the structure-behavior-function (SBF) framework for conceptual representation. It evaluates the progress of students' understanding after interventions with two different teaching approaches, one using a biology textbook supported by augmented reality…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…