In order to learn the mappings from words to referents, children must integrate co-occurrence information across individually ambiguous pairs of scenes and utterances, a challenge known as cross-situational word learning. In machine learning, recent multimodal neural networks have been shown to learn meaningful visual-linguistic mappings from…

Purpose: The prediction of student attrition is critical to facilitate retention mechanisms. This study aims to focus on implementing a method to predict student attrition in the upper years of a physiotherapy program. Design/methodology/approach: Machine learning is a computer tool that can recognize patterns and generate predictive models. Using…

Although Writing Across the Curriculum (WAC) has long focused on incorporating writing and related literacy activities into STEM education, the extent to which these pedagogies are widely used in STEM teaching remains unclear, as does their impact on student course performance, especially for underrepresented and marginalized student groups. Using…

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 conceived multivariate learning concepts and aimed at the implementation of integrating artificial intelligence (AI) life learning of face recognition, self-driving, and robots' situational issues into problem-based learning (PBL) in natural science. This research put forward problem-solving and group cooperation in which students…

The paper's main aim is to investigate and predict major factors in students' behavioral intentions toward academic use of Facebook/Meta as a virtual classroom, taking into account its adoption level, purpose, and education usage. In contrast to earlier social network research, this one utilized a novel technique that comprised a two-phase…

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…

Artificial Intelligence and its sub-disciplines are becoming increasingly relevant in numerous areas of academia as well as industry and can now be considered a core area of Computer Science. The Higher Education sector are offering more courses in Machine Learning and Artificial Intelligence than ever before. However, there is a lack of research…

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…

Modern language learning applications have become 'smarter' and 'intelligent' by including Artificial Intelligence (AI) and Machine Learning (ML) technologies to collect different kinds of data. This data can be used for analysis on a microscopic and/or macroscopic level to provide granulation of knowledge. We analyzed 1,213 French language…

Early interaction is a dynamic, emotional process in which infants influence and are influ­enced by caregivers and peers. This chapter reviews new developments in behavior imag­ing--objective quantification of human action--and computational approaches to the study of early emotional interaction and development. Advances in the automated…

Objective. The objective of this work was to apply the capabilities of augmented reality (AR) to improve how general aviation student pilots learn about weather and learn to make weather-related decisions. Background. A pilot's level of weather experience is a strong indicator of their ability to make safe weather-related decisions. However, the…

Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…

To examine the utility of spoken dialog systems (SDSs) for learning and low-stakes assessment, we administered the same role-play task in two different modalities to a group of 47 tertiary-level learners of English. Each participant completed the task in an SDS setting with a fully automated agent and engaged in the same task with a human…