Artificial Intelligent in Education

Abstract

The application of Artificial Intelligence or AI in education has been the subject of academic research for more than 30 years. The field examines learning wherever it occurs, in traditional classrooms or at workplaces so to support formal education and lifelong learning. It combines interdisciplinary AI and learning sciences (such as education, psychology, neuroscience, linguistics, sociology and anthropology) in order to facilitate the development of effective adaptive learning environments and various flexible, inclusive tools. Nowadays, there are several new challenges in the field of education technology in the era of smart phones, tablets, cloud computing, Big Data, etc., whose current research questions focus on concepts such as ICT-enabled personalized learning, mobile learning, educational games, collaborative learning on social media, MOOCs, augmented reality application in education and so on. Therefore, to meet these new challenges in education, several fields of research using AI have emerged over time to improve teaching and learning using digital technologies. Moreover, each field of research is distinguished by its own vision and methodologies. In this article, to the authors present a state of the art finding in the fields of research of Artificial Intelligence in Education or AIED, Educational Data Mining or EDM and Learning Analytics or LA. We discuss their historical elements, definition attempts, objectives, adopted methodologies, application examples and challenges.

Machine learning for the improvement of adaptive learning in university education

“…En cuanto a la retroalimentación inmediata, se menciona el uso de sistemas de gestión del aprendizaje y datos sociodemográficos y educativos para predecir objetivos integrales, como la deserción estudiantil y las actividades científicas. (42,43,44,45,46) https://doi.org/10.56294/sctconf2023473 El desempeño académico se midió a través de una serie de técnicas y enfoques interrelacionados. Primero, se utilizó el modelo del conocimiento del estudiante, una técnica que consiste en desarrollar un modelo individual para cada estudiante basado en sus respuestas a preguntas y tareas.…”

Complex thinking through a Transition Design-guided Ideathon: testing an AI platform on the topic of sharing economy

“…Figure 1 shows the establishment of the Ideathon, which setting was based on Sanabria-Z et al (2020). The starting point was the provision of an instructional design guideline that contemplated three types of models according to Hamal et al (2022): domain model (sharing economy), pedagogical model (Transition Design) and learner model (Ideathon). It can be seen that four modules were integrated into the platform for implementation.…”

“…Most e-learning platforms or learning management systems (LMS) offer functionalities to analyze the interactions of students and teachers to create statistics that give clues to the behavior of the actors. Hamal et al (2022) emphasize that one of the most common applications of AI in education is intelligent tutoring systems (ITS), which can determine step-by-step an optimal path through support and learning activities; they are integrated with three models: (a) domain model represents the knowledge intended for students to acquire, (b) the pedagogical model represents knowledge of effective teaching and learning approaches that have been obtained from pedagogical experts and researchers in the learning sciences (Siemens, 2012), and (c) the learner model refers to the initial representation of the learner's state of knowledge. It is ideal to have these three models to create AIEd data structures that provide more information on the aspects that need to be addressed to improve student performance.…”

“…Taking into account the intelligent tutoring system created by Hamal et al (2022), the three proposed models are described below: (a) domain model, (b) pedagogical model, and (c) learner model, which were considered for this research.…”

AI and Big Data in Education: Learning Patterns Identification and Intervention Leads to Performance Enhancement

“…In the study of Yousuf and Wahid [11] , various AI applications in education are listed from various points of view emphasizing the market prospects and the future scope for AI in education. On the other hand, AI and big data driven research also face some challenges in terms of how to apply technology to educational fields, Hamal et al [12] addressed and provided some scenarios in higher education which also provide insights when designing the experiment in this study.…”