This paper explores using data mining in English teaching assessment in higher education within the 'Internet + Education' era. Traditional assessment methods struggle to meet modern teaching needs. By collecting diverse data like student performance and learning behavior, and employing data mining, a comprehensive assessment model is built. This…

The Data Culture Framework is a high-level guide designed for institutional leaders who want to create and sustain an effective data culture on campus. The Framework offers a set of practices designed to help institutions of higher education create and maintain an effective data-informed community among institutional leaders, faculty, and staff.

A course-level early final study status prediction task is to predict as soon as possible the final success of each student after studying a course. It is significant because each successful course accomplishment is required for a degree. Further, early predictions provide enough time to make necessary changes for ultimate success. This article…

Governments and educational authorities around the world are emphasizing performance evaluation of educational systems. Opinion Mining (OM) has gained acceptance among experts in various regions, including the preparation space. The proposed model involves Two modules: the data preprocessing module and the opinion mining module. The main objective…

Measurement systems give colleges a structure for collecting, sharing, and acting on data. The guidebook and tools presented here help faculty, staff, college leadership, and policymakers understand and use measurement systems--and specifically use data to improve completion rates, close institutional performance gaps, and facilitate economic…

Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques.…

The recent focus on learning analytics (LA) to analyze temporal dimensions of learning holds the promise of providing insights into latent constructs, such as learning strategy, self-regulated learning (SRL), and metacognition. These methods seek to provide an enriched view of learner behaviors beyond the scope of commonly used correlational or…

The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…

Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students' academic achievement early using Educational Data Mining (EDM). This study aims to predict students' final grades and identify honorary students at…

With the spread of the COVID-19 pandemic, many universities adopted a hybrid learning model as a substitute for a traditional one. Predicting students' performance in hybrid environments is a complex task because it depends on extracting and analyzing different types of data: log data, self-reports, and face-to-face interactions. Students must…

Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…

One of the most widely researched issue on higher education relates to exposed paths that lead to academic success. Nowadays information systems represent an essential part of the education sector in many universities. In particular, the increasing of the number of students in higher education in Portugal leads to the progressive increase of…

The aim of the study is to examine the doctoral theses in STEM education in Turkey in a comprehensive manner. Thematic content analysis method was used in the study. The data were obtained from the doctoral theses published until 2020 by examining CoHE National Thesis Center. As a result of the screenings, 30 doctoral theses were reached in the…

Student's academic performance prediction empowers educational technologies including academic trajectory and degree planning, course recommender systems, early warning and advising systems. Given a student's past data (such as grades in prior courses), the task of student's performance prediction is to predict a student's grades in future…

Online learning implementation has been growing year by year across countries, including Indonesia. Many higher education institutions use a Learning Management System (LMS) to facilitate online learning. Unfortunately, many issues arise during online learning implementation, such as a lack of student behaviour monitoring. This study adopts an…