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Lepori, Benedetto – Studies in Higher Education, 2022
Classifications are a basic tool for research, which allow summarizing the diversity of objects in a number of categories that fits the cognitive abilities of the human mind. Their relevance for higher education is emphasized by the differentiation of institutional profiles. Yet, unlike in the US, there is currently no classification of European…
Descriptors: Foreign Countries, Higher Education, Classification, Specialization
Meriem Zerkouk; Miloud Mihoubi; Belkacem Chikhaoui; Shengrui Wang – Education and Information Technologies, 2024
School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a binary classification model that anticipates students' activity levels based on their current achievements and engagement on a Canadian Distance learning Platform. Predicting student dropout, a common…
Descriptors: Artificial Intelligence, Dropouts, Prediction, Distance Education
Muhammad Andiri Hendrawan; Romadhani Ardi – International Society for Technology, Education, and Science, 2023
The use of smartphones has become a primary need in supporting human daily activities. With the presence of a smartphone, various activities can be carried out only through an application. One application that is currently popular with Indonesians is an investment application with products such as stocks, mutual funds, and crypto. The presence of…
Descriptors: Handheld Devices, Computer Oriented Programs, Models, Investment
Geschwind, Lars; Broström, Anders – Higher Education: The International Journal of Higher Education Research, 2022
Classifications of higher education institutions into categories that are more or less clearly differentiated through prestige and status are legion in the world of higher education. The notion of parallel categories with comparable statuses, such as those of different types of universities, is however much less well understood. This paper…
Descriptors: Technical Institutes, Universities, Technical Education, Classification
Haffenden, Chris; Fano, Elena; Malmsten, Martin; Börjeson, Love – College & Research Libraries, 2023
How can novel AI techniques be made and put to use in the library? Combining methods from data and library science, this article focuses on Natural Language Processing technologies, especially in national libraries. It explains how the National Library of Sweden's collections enabled the development of a new BERT language model for Swedish. It…
Descriptors: Foreign Countries, Artificial Intelligence, Models, Languages
Yoonjae Noh; YoonIl Yoon; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
The default risk, one of the main risk factors for bonds, should be measured and reflected in the bond yield. Particularly, in the case of financial companies that treat bonds as a major product, failure to properly identify and filter customers' workout status adversely affects returns. This study proposes a two-stage classification algorithm for…
Descriptors: Prediction, Classification, Accuracy, Risk
Hyemin Yoon; HyunJin Kim; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…
Descriptors: Classification, Artificial Intelligence, Prediction, Decision Making
Yerin Kwak; Zachary A. Pardos – British Journal of Educational Technology, 2024
The adoption of large language models (LLMs) in education holds much promise. However, like many technological innovations before them, adoption and access can often be inequitable from the outset, creating more divides than they bridge. In this paper, we explore the magnitude of the country and language divide in the leading open-source and…
Descriptors: Foreign Countries, Multilingualism, Instructional Materials, Access to Education
Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
Anna Fergusson; Maxine Pfannkuch – Journal of Statistics and Data Science Education, 2024
Statistics teaching at the high school level needs modernizing to include digital sources of data that students interact with every day. Algorithmic modeling approaches are recommended, as they can support the teaching of data science and computational thinking. Research is needed about the design of tasks that support high school statistics…
Descriptors: High School Students, Statistics Education, Thinking Skills, Computer Science Education
Selma Tosun; Dilara Bakan Kalaycioglu – Journal of Educational Technology and Online Learning, 2024
Predicting and improving the academic achievement of university students is a multifactorial problem. Considering the low success rates and high dropout rates, particularly in open education programs characterized by mass enrollment, academic success is an important research area with its causes and consequences. This study aimed to solve a…
Descriptors: Academic Achievement, Open Education, Distance Education, Foreign Countries
Liu, Ren; Liu, Haiyan; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2022
Assessments with a large amount of small, similar, or often repetitive tasks are being used in educational, neurocognitive, and psychological contexts. For example, respondents are asked to recognize numbers or letters from a large pool of those and the number of correct answers is a count variable. In 1960, George Rasch developed the Rasch…
Descriptors: Classification, Models, Statistical Distributions, Scores
Purificación Alcaide-Pulido; Belén Gutiérrez-Villar; Mariano Carbonero-Ruz; Helena Alves – Journal of Marketing for Higher Education, 2024
Currently, the higher education sector can be considered a marketplace, within which university education is considered a marketable service in the literature on higher education management. The analysis of the variables that generate university image has been the subject of numerous studies on higher education institutions (HEIs). The purpose of…
Descriptors: Undergraduate Students, Student Attitudes, Reputation, Institutional Characteristics
Gorgun, Guher; Yildirim-Erbasli, Seyma N.; Epp, Carrie Demmans – International Educational Data Mining Society, 2022
The need to identify student cognitive engagement in online-learning settings has increased with our use of online learning approaches because engagement plays an important role in ensuring student success in these environments. Engaged students are more likely to complete online courses successfully, but this setting makes it more difficult for…
Descriptors: Online Courses, Group Discussion, Learner Engagement, Student Participation
Wai Tong Chor; Kam Meng Goh; Li Li Lim; Kin Yun Lum; Tsung Heng Chiew – Education and Information Technologies, 2024
The programme outcomes are broad statements of knowledge, skills, and competencies that the students should be able to demonstrate upon graduation from a programme, while the Educational Taxonomy classifies learning objectives into different domains. The precise mapping of a course outcomes to the programme outcome and the educational taxonomy…
Descriptors: Artificial Intelligence, Engineering Education, Taxonomy, Educational Objectives