Related papers: Class attendance, peer similarity, and academic pe…
In recent years, there is a lot of interest in modeling students' digital traces in Learning Management System (LMS) to understand students' learning behavior patterns including aspects of meta-cognition and self-regulation, with the…
Peer grading systems aggregate noisy reports from multiple students to approximate a true grade as closely as possible. Most current systems either take the mean or median of reported grades; others aim to estimate students' grading…
The idea to unite smartphones used as personal environmental sensors and health indicators into a scalable network for data collection and processing by the internet-cloud is proposed. Access to the sensors, which are available in every…
Research on mobile phone use often starts with a question of "How much time users spend on using their phones?". The question involves an equal-length measure that captures the duration of mobile phone use but does not tackle the other…
The study explores the potential of AI technologies in personalized learning, suggesting the prediction of academic success through leadership personality traits and machine learning modelling. The primary data were obtained from 129…
Improving students academic performance is not an easy task for the academic community of higher learning. The academic performance of engineering and science students during their first year at university is a turning point in their…
We present a new method for measuring the effectiveness of online learning resources, through the analysis of time-stamped log data of students' interaction with a sequence of online learning modules created based on the concept of mastery…
Wearable technologies have traditionally been used to measure and monitor vital human signs for well-being and healthcare applications. However, there is a growing interest in using and deploying these technologies to facilitate teaching…
We present a scantron-based survey which examines the teacher-learner collaboration. The survey includes questions which probe student preparedness, behaviors, attitudes, and expectations - as well as questions addressing key measures of…
Due to the COVID 19 pandemic, smartphone-based proximity tracing systems became of utmost interest. Many of these systems use BLE signals to estimate the distance between two persons. The quality of this method depends on many factors and,…
Supporting equitable instruction is an important issue for teachers attending diverse STEM classrooms. Visual learning analytics along with effective student survey measures can support providing on time feedback to teachers in making…
Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs, this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may…
The question of how to best serve the student populations of our country is a complex topic. Since public funding is limited, we must explore the best ways to direct the money to improve student outcomes. Previous research has suggested…
Teachers' visual attention and its distribution across the students in classrooms can constitute important implications for student engagement, achievement, and professional teacher training. Despite that, inferring the information about…
Predicting students' academic performance is one of the key tasks of educational data mining (EDM). Traditionally, the high forecasting quality of such models was deemed critical. More recently, the issues of fairness and discrimination…
Peer grading is an educational system in which students assess each other's work. It is commonly applied under Massive Open Online Course (MOOC) and offline classroom settings. With this system, instructors receive a reduced grading…
Smartphone is a powerful internet connected computer packed with internal sensors that measure sound, light, acceleration and magnetic field strength. Physics teachers can use them as measurement devices to demonstrate science concepts and…
The use of deep learning methods to automatically detect students' classroom behavior is a promising approach for analyzing their class performance and improving teaching effectiveness. However, the lack of publicly available datasets on…
In this paper, we propose an intelligent embedded system for monitoring class attendance and sending the attendance list to a remote computer. The proposed system consists of two parts : an embedded device (Raspberry with PI camera) for…
In this paper, the authors propose a software metric called Class Activeness Metric which helps to determine the level of accessibility of the members of a class when it is instantiated as objects. Object interactions need to be straight…