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Kerstin Wagner; Agathe Merceron; Petra Sauer; Niels Pinkwart – Journal of Educational Data Mining, 2024
In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…
Descriptors: At Risk Students, Algorithms, Foreign Countries, Course Selection (Students)
Irene-Angelica Chounta; Alejandro Ortega-Arranz; Sophia Daskalaki; Yannis Dimitriadis; Nikolaos Avouris – International Journal of Educational Technology in Higher Education, 2024
This paper aims to address Digital Readiness in Higher Education Institutions from the perspective of data-informed and evidence-based assessment of Digital Readiness. Related research suggests that existing instruments for assessing digitalization aspects are limited to self-assessment, and there is a need for data-informed frameworks that will…
Descriptors: Colleges, Technological Literacy, Stakeholders, Foreign Countries
Alturki, Sarah; Cohausz, Lea; Stuckenschmidt, Heiner – Smart Learning Environments, 2022
The tremendous growth in electronic educational data creates the need to have meaningful information extracted from it. Educational Data Mining (EDM) is an exciting research area that can reveal valuable knowledge from educational databases. This knowledge can be used for many purposes, including identifying dropouts or weak students who need…
Descriptors: Information Retrieval, Data Analysis, Data Use, Prediction
Hahnel, Carolin; Kroehne, Ulf; Goldhammer, Frank; Schoor, Cornelia; Mahlow, Nina; Artelt, Cordula – British Journal of Educational Psychology, 2019
Background: With digital technologies, competence assessments can provide process data, such as mouse clicks with corresponding timestamps, as additional information about the skills and strategies of test takers. However, in order to use variables generated from process data sensibly for educational purposes, their interpretation needs to be…
Descriptors: Computer Assisted Testing, Test Interpretation, Foreign Countries, College Students
Li, Kam-Cheong; Wong, Billy Tak-Ming – Interactive Technology and Smart Education, 2020
Purpose: This paper aims to present a review of case studies on the use of learning analytics in Science, Technology, Engineering, (Arts), and Mathematics (or STE[A]M) education. It covers the features and trends of learning analytics practices as revealed in case studies. Design/methodology/approach: A total of 34 case studies published from 2013…
Descriptors: Learning Analytics, Art Education, STEM Education, Adoption (Ideas)
Höhne, Jan Karem; Schlosser, Stephan – International Journal of Social Research Methodology, 2019
Participation in web surveys via smartphones increased continuously in recent years. The reasons for this increase are a growing proportion of smartphone owners and an increase in mobile Internet access. However, research has shown that smartphone respondents are frequently distracted and/or multitasking, which might affect completion and response…
Descriptors: Online Surveys, Handheld Devices, Response Rates (Questionnaires), Response Style (Tests)