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Huijuan Fu; Yangcai Xiao; Isaac Kofi Mensah; Rui Wang – Education and Information Technologies, 2024
The nation's explosive growth in Massive Open Online Courses (MOOCs) is likely to lead to low effectiveness of MOOCs, therefore, it is necessary to promote the high-quality and long-term development of MOOCs through understanding learner satisfaction. The present research adopted the Latent Dirichlet Allocation (LDA) to derive factors affecting…
Descriptors: Student Satisfaction, MOOCs, Computer Science Education, Curriculum Design
Belland, Brian R.; Kim, Chanmin; Zhang, Anna Y.; Lee, Eunseo – ACM Transactions on Computing Education, 2023
This article reports the analysis of data from five different studies to identify predictors of preservice, early childhood teachers' views of (a) the nature of coding, (b) integration of coding into preschool classrooms, and (c) relation of coding to fields other than computer science (CS). Significant changes in views of coding were predicted by…
Descriptors: Predictor Variables, Preservice Teachers, Student Attitudes, Programming
Johnson, Amy L.; Gleit, Rebecca D. – Teaching Sociology, 2022
Despite the centrality of data analysis to the discipline, sociology departments are currently falling short of teaching both undergraduate and graduate students crucial computing and statistical software skills. We argue that sociology instructors must intentionally and explicitly teach computing skills alongside statistical concepts to prepare…
Descriptors: College Students, Sociology, Social Science Research, Computer Science Education
Saito, Daisuke; Yajima, Risei; Washizaki, Hironori; Fukazawa, Yoshiaki – Education Sciences, 2021
In evaluating the learning achievement of programming-thinking skills, the method of using a rubric that describes evaluation items and evaluation stages is widely employed. However, few studies have evaluated the reliability, validity, and consistency of the rubrics themselves. In this study, we introduced a statistical method for evaluating the…
Descriptors: Scoring Rubrics, Computer Science Education, Programming, Reliability
Heckman, Sarah; Carver, Jeffrey C.; Sherriff, Mark; Al-zubidy, Ahmed – ACM Transactions on Computing Education, 2022
Context: Computing Education Research (CER) is critical to help the computing education community and policy makers support the increasing population of students who need to learn computing skills for future careers. For a community to systematically advance knowledge about a topic, the members must be able to understand published work thoroughly…
Descriptors: Computer Science Education, Educational Research, Periodicals, Replication (Evaluation)
Zhao, Yijun; Lackaye, Bryan; Dy, Jennifier G.; Brodley, Carla E. – International Educational Data Mining Society, 2020
Accurately predicting which students are best suited for graduate programs is beneficial to both students and colleges. In this paper, we propose a quantitative machine learning approach to predict an applicant's potential performance in the graduate program. Our work is based on a real world dataset consisting of MS in CS [Master of Science in…
Descriptors: Artificial Intelligence, College Admission, Masters Programs, Professional Education
Furtado, Julio; Oliveira, Sandro Ronaldo Bezerra; Chaves, Rafael Oliveira – International Journal of Information and Communication Technology Education, 2021
In organizations that are seeking a high degree of maturity, it is necessary to achieve a statistical control of software processes and to know their behavior and operational performance. The approach adopted for the research involves reading articles and experience performance reports, practical cases, discussion, the use of games and simulators,…
Descriptors: Undergraduate Students, Computer Science Education, Teaching Methods, Computer Software
Khosravi, Hassan; Cooper, Kendra M. L. – Journal of Learning Analytics, 2018
Educational environments continue to evolve rapidly to address the needs of diverse, growing student populations while embracing advances in pedagogy and technology. In this changing landscape, ensuring consistency among the assessments for different offerings of a course (within or across terms), providing meaningful feedback about student…
Descriptors: Graphs, Academic Achievement, Student Evaluation, Models
Margulieux, Lauren; Ketenci, Tuba Ayer; Decker, Adrienne – Computer Science Education, 2019
Background and context: The variables that researchers measure and how they measure them are central in any area of research, including computing education. Which research questions can be asked and how they are answered depends on measurement. Objective: To summarize the commonly used variables and measurements in computing education and to…
Descriptors: Measurement Techniques, Standards, Evaluation Methods, Computer Science Education
Xinogalos, Stelios; Pitner, Tomáš; Ivanovic, Mirjana; Savic, Miloš – Education and Information Technologies, 2018
The choice of the first programming language (FPL) has been a controversial issue for several decades. Nearly everyone agrees that the FPL is important and affects students' subsequent education on programming. The study presented in this article investigates the suitability of various C-like and Pascal-like programming languages as a FPL.…
Descriptors: Student Attitudes, Programming Languages, Computer Software, Questionnaires
Bonet, Nicolás; Garcés, Kelly; Casallas, Rubby; Correal, María Elsa; Wei, Ran – Computer Science Education, 2018
Bad smells affect maintainability and performance of model-to-model transformations. There are studies that define a set of transformation bad smells, and some of them propose techniques to recognize and--according to their complexity--fix them in a (semi)automated way. In academia it is necessary to make students aware of this subject and provide…
Descriptors: Foreign Countries, Graduate Students, Masters Programs, Programming
Berdousis, Ioannis; Kordaki, Maria – Gender and Education, 2018
This study focuses on the investigation of gender representation of faculty members of all ranks (professors, associate professors, assistant professors and lecturers) of Computing and STEM (Science, Technology, Engineering and Mathematics) in Greek tertiary education during the decade 2003-2013. To this end, a quantitative study was conducted,…
Descriptors: STEM Education, College Faculty, Foreign Countries, Gender Differences
Xia, Belle Selene; Liitiäinen, Elia – European Journal of Engineering Education, 2017
The benefits of using online exercises have been analysed in terms of distance learning, automatic assessment and self-regulated learning. In this study, we have not found a direct proportional relationship between student performance in the course exercises that use online technologies and the exam grades. We see that the average submission rate…
Descriptors: Computer Science Education, Electronic Learning, Programming, Academic Achievement
Master, Allison; Cheryan, Sapna; Meltzoff, Andrew N. – Journal of Educational Psychology, 2016
Computer science has one of the largest gender disparities in science, technology, engineering, and mathematics. An important reason for this disparity is that girls are less likely than boys to enroll in necessary "pipeline courses," such as introductory computer science. Two experiments investigated whether high-school girls' lower…
Descriptors: Gender Differences, Computer Science, Sex Stereotypes, Computer Science Education
Coetzee, Bronwynè; Kagee, Ashraf – Africa Education Review, 2021
In psychology departments in South Africa, the Statistical Package for the Social Sciences (SPSS) is routinely used for quantitative analysis. While SPSS has a user-friendly interface, it does not permit application of some of the more sophisticated analytic approaches and therefore has limited functionality. The programming language R can perform…
Descriptors: Teaching Methods, Faculty Development, Psychology, Programming Languages