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Cheers, Hayden; Lin, Yuqing – Computer Science Education, 2023
Background and Context: Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…
Descriptors: Plagiarism, Programming, Computer Science Education, Identification
Kleb Dale G. Bayaras – Online Submission, 2023
In course design, topic outline organization encompasses the structuring and sequencing of topics to be delivered in a learning environment. Recent studies in topic outline optimization revolve around massive open online courses (MOOCs) due to their abundance but not much has been studied on the traditional courses. This study investigates the…
Descriptors: Foreign Countries, Universities, Introductory Courses, Programming
Myint, Leslie; Hadavand, Aboozar; Jager, Leah; Leek, Jeffrey – Journal of Statistics Education, 2020
We performed an empirical study of the perceived quality of scientific graphics produced by beginning R users in two plotting systems: the base graphics package ("base R") and the ggplot2 add-on package. In our experiment, students taking a data science course on the Coursera platform were randomized to complete identical plotting…
Descriptors: Statistics, Randomized Controlled Trials, Teaching Methods, Courseware
Hartati, Sulis Janu; Vitianingsih, Anik Vega; Kurniati, Neny; Sulistyowati; Muhajir – International Education Studies, 2020
This paper examines the limited proficiency to engage in programming algorithms among university students in information technology and information system in several universities across Surabaya, Indonesia. The purpose of this research is to find the most influential factor in learning programming algorithm using a quantitative approach. The…
Descriptors: Mathematics Skills, Thinking Skills, Programming, Information Technology
Akar, Sacide Guzin Mazman; Altun, Arif – Contemporary Educational Technology, 2017
The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…
Descriptors: Individual Differences, Learning Processes, Programming, Self Efficacy
Paassen, Benjamin; Hammer, Barbara; Price, Thomas William; Barnes, Tiffany; Gross, Sebastian; Pinkwart, Niels – Journal of Educational Data Mining, 2018
Intelligent tutoring systems can support students in solving multi-step tasks by providing hints regarding what to do next. However, engineering such next-step hints manually or via an expert model becomes infeasible if the space of possible states is too large. Therefore, several approaches have emerged to infer next-step hints automatically,…
Descriptors: Intelligent Tutoring Systems, Cues, Educational Technology, Technology Uses in Education
Yang, Junfeng, Ed.; Liu, Dejian, Ed.; Kinshuk, Ed.; Tlili, Ahmed, Ed.; Chang, Maiga, Ed.; Popescu, Elvira, Ed.; Burgos, Daniel, Ed.; Altinay, Zehra, Ed. – Lecture Notes in Educational Technology, 2022
This book provides an archival forum for researchers, academics, practitioners, and industry professionals interested and/or engaged in the reform of the ways of teaching and learning through advancing current learning environments towards smart learning environments. It facilitates opportunities for discussions and constructive dialogue among…
Descriptors: Educational Technology, Audio Equipment, Information Dissemination, Synchronous Communication
Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D. – IEEE Transactions on Learning Technologies, 2014
In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…
Descriptors: Artificial Intelligence, Concept Mapping, Teaching Methods, Student Evaluation
Decker, Robert – International Journal for Technology in Mathematics Education, 2011
Dynamic/interactive graphing applets can be used to supplement standard computer algebra systems such as Maple, Mathematica, Derive, or TI calculators, in courses such as Calculus, Differential Equations, and Dynamical Systems. The addition of this type of software can lead to discovery learning, with students developing their own conjectures, and…
Descriptors: Expertise, Investigations, Discovery Learning, Computer Software
Sa, Leonardo; Hsin, Wen-Jung – InSight: A Journal of Scholarly Teaching, 2010
Recursion is a concept that can be used to describe the phenomena and natural occurrences in many different fields. As many applications utilize computer software to model recursion, recursion is a particularly important concept in the computing discipline. However, it is a difficult concept for many undergraduate students to master. A Recursion…
Descriptors: Computer Science Education, Undergraduate Students, Programming, Mathematics
Stankov, Slavomir; Glavinic, Vlado; Krpan, Divna – International Journal of Distance Education Technologies, 2012
Students' collaboration while learning could provide better learning environments. Collaboration assumes social interactions which occur in student groups. Social theories emphasize positive influence of such interactions on learning. In order to create an appropriate learning environment that enables social interactions, it is important to…
Descriptors: Socialization, Action Research, Cooperation, Programming
Nunes, Miguel Baptista, Ed.; Isaias, Pedro, Ed. – International Association for Development of the Information Society, 2019
These proceedings contain the papers and posters of the International Conference on e-Learning (EL) 2019, which was organised by the International Association for Development of the Information Society and co-organised by the Instituto Superior de Engenharia do Porto, in Porto, Portugal, July 17-19, 2019. The EL 2019 conference aims to address the…
Descriptors: Educational Technology, Technology Uses in Education, Mathematics Instruction, Cooperation
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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