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Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
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Varga, Erika B.; Sátán, Ádám – Hungarian Educational Research Journal, 2021
The purpose of this paper is to investigate the pre-enrollment attributes of first-year students at Computer Science BSc programs of the University of Miskolc, Hungary in order to find those that mostly contribute to failure on the Programming Basics first-semester course and, consequently to dropout. Our aim is to detect at-risk students early,…
Descriptors: Identification, At Risk Students, Computer Science Education, Undergraduate Students
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Rodríguez, M. Elena; Guerrero-Roldán, Ana Elena; Baneres, David; Karadeniz, Abdulkadir – International Review of Research in Open and Distributed Learning, 2022
This work discusses a nudging intervention mechanism combined with an artificial intelligence (AI) system for early detection of learners' risk of failing or dropping out. Different types of personalized nudges were designed according to educational principles and the learners' risk classification. The impact on learners' performance, dropout…
Descriptors: Artificial Intelligence, Electronic Learning, College Students, Intervention
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Jimenez, Fernando; Paoletti, Alessia; Sanchez, Gracia; Sciavicco, Guido – IEEE Transactions on Learning Technologies, 2019
In the European academic systems, the public funding to single universities depends on many factors, which are periodically evaluated. One of such factors is the rate of success, that is, the rate of students that do complete their course of study. At many levels, therefore, there is an increasing interest in being able to predict the risk that a…
Descriptors: Prediction, Risk, Dropouts, College Students
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Kolikant, Y. Ben-David; Genut, S. – Computer Science Education, 2023
Background and Context: In line with interest in recruiting underrepresented groups to CS studies, our study dealt with Israeli Hasidic young women who successfully studied CS at an academic institute. Objective: We investigated what factors governed Hasidic young women's decision to enrol in a CS program and shaped their studying experience.…
Descriptors: Computer Science Education, Womens Education, Females, Jews
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Mao, Ye; Zhi, Rui; Khoshnevisan, Farzaneh; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2019
Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…
Descriptors: Difficulty Level, Learning Activities, Prediction, Programming
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Atapattu, Thushari; Falkner, Katrina – Journal of Learning Analytics, 2018
Lecture videos are amongst the most widely used instructional methods within present Massive Open Online Courses (MOOCs) and other digital educational platforms. As the main form of instruction, student engagement behaviour, including interaction with videos, directly impacts the student success or failure and accordingly, in-video dropouts…
Descriptors: Lecture Method, Video Technology, Online Courses, Mass Instruction
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Ruiz-Iniesta, Almudena; Jiménez-Díaz, Guillermo; Gómez-Albarrán, Mercedes – IEEE Transactions on Education, 2014
This paper describes a knowledge-based strategy for recommending educational resources-worked problems, exercises, quiz questions, and lecture notes-to learners in the first two courses in the introductory sequence of a computer science major (CS1 and CS2). The goal of the recommendation strategy is to provide support for personalized access to…
Descriptors: Semantics, Computer Science Education, Dropout Rate, Educational Resources
Iowa Department of Education, 2021
The 2021 edition of the Annual Condition of Education Report (COE) marks the 32nd edition of the report. For over 30 years, the Department has published the COE in order to provide education stakeholders critical data about the status of Iowa's education system. The 2021 COE covers a wide variety of content including information about Iowa's…
Descriptors: College Entrance Examinations, National Competency Tests, Enrollment Trends, Early Childhood Education
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Tekin, Ahmet – Eurasian Journal of Educational Research, 2014
Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…
Descriptors: Foreign Countries, Prediction, Grade Point Average, Undergraduate Students
Iowa Department of Education, 2020
For over 30 years, the Department has published the Annual Condition of Education (COE) report in order to provide education stakeholders quality information about the status of Iowa's education system. The 2020 COE covers a wide variety of content from information about Iowa's students, schools, educators, administrators, performance and school…
Descriptors: Enrollment Trends, Early Childhood Education, Teacher Characteristics, Academic Achievement
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Balter, Olle; Cleveland-Innes, Martha; Pettersson, Kerstin; Scheja, Max; Svedin, Maria – Canadian Journal of Higher Education, 2013
This study investigates the relationship between approaches to studying and course completion in two online preparatory university courses in mathematics and computer programming. The students participating in the two courses are alike in age, gender, and approaches to learning. Four hundred and ninety-three students participating in these courses…
Descriptors: Foreign Countries, Higher Education, Online Courses, Computer Science Education
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Méndez, Gonzalo; Ochoa, Xavier; Chiluiza, Katherine; de Wever, Bram – Journal of Learning Analytics, 2014
Learning analytics has been as used a tool to improve the learning process mainly at the micro-level (courses and activities). However, another of the key promises of learning analytics research is to create tools that could help educational institutions at the meso- and macro-level to gain better insight into the inner workings of their programs…
Descriptors: Data Analysis, Data Collection, Educational Research, Curriculum Design
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Warren, Scott J.; Dondlinger, Mary Jo; Jones, Greg; Whitworth, Cliff – Journal of Educational Technology, 2010
The purpose of this paper is to discuss one instructional design that leverages problem-based learning and game structures as a means of developing innovative higher education courses for students as responsive, lived experiences. This paper reviews a curricular redesign that stemmed from the evaluation of an introductory course in computer…
Descriptors: Problem Based Learning, Instructional Design, Educational Games, Introductory Courses
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Yadin, Aharon; Or-Bach, Rachel – Journal of Information Systems Education, 2010
In this paper we describe an instructional tactic of individually assigned homework that promotes and strengthens individual learning processes. We claim that current emphasis on the benefits of collaborative learning belittles the importance of individual learning processes and reduces the opportunities to require and assess individual learning…
Descriptors: Homework, Research Tools, Dropout Rate, Learning Processes
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