A working knowledge of Artificial Neural Networks is rapidly becoming critical for navigating the modern world. Although the last few years have seen an explosion of the use of these tools in research, and there are many do-it-yourself articles on the web, they have not yet filtered down to wide implementation in introductory courses. I report…

This proceedings volume presents outstanding advances, with a multidisciplinary perspective, in the technological ecosystems that support Knowledge Society building and development. With its learning technology-based focus using a transversal approach, TEEM is divided into thematic and highly cohesive tracks, each of which is oriented to a…

This paper investigates the role of English in voice assistant (Siri, Alexa, Google Assistant) use from the perspective of language ideology. Major commercial companies in the voice assistant market use English as a training language for their speech technologies and offer the most optimised support for standardised varieties of English. This…

Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been…

EFL learners generally have the problem of logical fallacies in EFL argumentative writings. Logical fallacies are errors in reasoning that can undermine EFL argumentative writing quality. Explicit training on logical fallacies may help learners deal with the problem and enhance their self-efficacy and proficiency in EFL argumentative writing,…

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…

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…

Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver and have low ecological validity and accuracy. To support an SIB monitoring system for autism spectrum disorder (ASD), we evaluated machine learning methods for detecting and distinguishing diverse SIB types. SIB episodes were captured with body-worn…

For many years, learning continues to be a vital developing field since it is the key measure of the world's civilization and evolution with its enormous effect on both individuals and societies. Enhancing existing learning activities in general will have a significant impact on literacy rates around the world. One of the crucial activities in…

Identifying critical decisions is one of the most challenging decision-making problems in real-world applications. In this work, we propose a novel Reinforcement Learning (RL) based Long-Short Term Rewards (LSTR) framework for critical decisions identification. RL is a machine learning area concerning with inducing effective decision-making…

Techniques from the branch of artificial intelligence known as machine learning (ML) have been applied to a wide range of problems in chemistry. Nonetheless, there are very few examples of pedagogical activities to introduce ML to chemistry students in the chemistry education literature. Here we report a computational activity that introduces…

Collaborative learning (CL) can be a powerful method for sharing understanding between learners. To this end, strategic regulation of processes, such as cognition and affect (including metacognition, emotion and motivation) is key. Decades of research on self-regulated learning has advanced our understanding about the need for and complexity of…

The aim of this paper is to survey recent research publications that use Soft Computing methods to answer education-related problems based on the analysis of educational data 'mined' mainly from interactive/e-learning systems. Such systems are known to generate and store large volumes of data that can be exploited to assess the learner, the system…

This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…

It is common to use anthropomorphic labels when talking about technology, for example describing some robots and phones as smart, thinking and talking. This article describes a workshop in which students considered ways that words such as 'hearing', 'smart' and 'intelligence' might change in meaning when they are used in the context of robotics…