Identifying students facing difficulties and providing them with timely support is one of the educator's key responsibilities. Yet, this task is becoming increasingly challenging as the complexity of physical learning spaces grows, along with the emergence of novel educational technologies and classroom designs. There has been substantial research…

This paper presents an application of the Kalman filter in signal processing in instrumentation systems when the conditions of the environment generate a large amount of interference for the acquisition of signals from measurement systems. The unwanted interferences make important use of the instrumentation system resources and do not represent…

Help-seeking is a valuable practice in online discussion forums. However, the asynchronicity and information overload of online discussion forums have made it challenging for help seekers and providers to connect effectively. This study formulated a new method to provide fair and accurate insights toward building a peer recommender to support…

The use of social robots in education is a growing area of research and the potential future applications are various. However, the conversational models behind current social robots and chatbot systems often rely on rule-based and retrieval-based methods. This limits the social robot to predefined responses and topics, thus hindering it from…

The paper aims to identify the new requirements of young people for education in the digital economy of the future and, considering these requirements, identify the attractiveness of higher education programs on training digital personnel to work with breakthrough technologies among young people in Central Asia and Russia. The authors conduct a…

Background/Context: Early warning indicators (EWI) are often used by states and districts to identify students who are not on track to finish high school, and provide supports/interventions to increase the odds the student will graduate. While EWI are diverse in terms of the academic behaviors they capture, research suggests that indicators like…

In massive open online courses (MOOCs), learners can interact with each other using discussion boards. Automatically inferring the states or needs of learners from their posts is of interest to instructors, who are faced with a high attrition in MOOCs. Machine learning has previously been successfully used to identify states such as confusion or…

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 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…

Digital technology has provided users with new connections that have reset our understanding of social architectures. As a reaction to Artificial Intelligence (AI) and Big Data, the educational field has rearranged its structure to consider human and non-human stakeholders and their actions on digital platforms. In light of this increasingly…

While synthesis projects are not uncommon in the undergraduate organic curriculum, the problems posed are usually not representative of what chemists actually do. The sudden dislocation to online learning precipitated by the COVID-19 pandemic provided both a need and an opportunity to develop an organic synthesis project with greater relevance to…

Quality feedback is crucial to learning; the growth of online delivery has altered how it is obtained and shared. Educators interested in improving online learning can benefit from understanding formal and informal feedback flows existing in face-to-face environments and how these transfer online. This article examines the nuance of informal…

This study investigated how preschool children processed and understood critical information in Magical Garden, a teachable agent-based play-&-learn game targeting early math. We analyzed 36 children's (ages 4-6 years) real-time behavior during game-use to explore whether children: (i) processed the information meant to support number sense…

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…

Extensive literature in artificial intelligence in education focuses on developing automated methods for detecting cases in which students struggle to master content while working with educational software. Such cases have often been called "wheel-spinning," "unproductive persistence," or "unproductive struggle." We…