NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 20 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
Peer reviewed Peer reviewed
Direct linkDirect link
Barczak, Andre L. C.; Mathrani, Anuradha; Han, Binglan; Reyes, Napoleon H. – Educational Technology Research and Development, 2023
An important course in the computer science discipline is 'Data Structures and Algorithms' (DSA). "The coursework" lays emphasis on experiential learning for building students' programming and algorithmic reasoning abilities. Teachers set up a repertoire of formative programming exercises to engage students with different programmatic…
Descriptors: Computer Assisted Testing, Automation, Computer Science Education, Programming
Peer reviewed Peer reviewed
Direct linkDirect link
Meina Zhu – Journal of Computer Assisted Learning, 2025
Background: Computer programming learning and education play a critical role in preparing a workforce equipped with the necessary skills for diverse fields. ChatGPT and YouTube are technologies that support self-directed programming learning. Objectives: This study aims to examine the sentiments and primary topics discussed in YouTube comments…
Descriptors: Computer Science Education, Programming, Social Media, Video Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Lakshminarayanan, Srinivasan; Rao, N. J. – Higher Education for the Future, 2022
There are many grey areas in the interpretation of academic integrity in the course on Introduction to Programming, commonly known as CS1. Copying, for example, is a method of learning, a method of cheating and a reuse method in professional practice. Many institutions in India publish the code in the lab course manual. The students are expected…
Descriptors: Integrity, Cheating, Duplication, Introductory Courses
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michalis – Journal of Learning Analytics, 2020
Programming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when…
Descriptors: Learning Analytics, Data Collection, Instructional Design, Learning Modalities
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Peer reviewed Peer reviewed
Direct linkDirect link
Cetin, Ibrahim – Journal of Educational Computing Research, 2016
Computational thinking has been gaining new impetus in the academic community and in K-12 level education. Scratch is a visual programming environment that can be utilized to teach and learn introductory computing concepts. There are some studies investigating the effectiveness of Scratch for K-12 level education. However, studies that have been…
Descriptors: Preservice Teachers, Preservice Teacher Education, Computation, Programming
Peer reviewed Peer reviewed
Direct linkDirect link
Hundhausen, C. D.; Olivares, D. M.; Carter, A. S. – ACM Transactions on Computing Education, 2017
In recent years, learning process data have become increasingly easy to collect through computer-based learning environments. This has led to increased interest in the field of "learning analytics," which is concerned with leveraging learning process data in order to better understand, and ultimately to improve, teaching and learning. In…
Descriptors: Learning Analytics, Computer Science Education, Programming, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Berland, Matthew; Martin, Taylor; Benton, Tom; Smith, Carmen Petrick; Davis, Don – Journal of the Learning Sciences, 2013
Many have suggested that tinkering plays a critical role in novices learning to program, and recent work in learning analytics (Baker & Yacef, 2009 Blikstein, 2011) allows us to describe new relationships in the process. Using learning analytics, we explore how students progress from exploration, through tinkering, to refinement, a pathway…
Descriptors: Learning Processes, Data Collection, Novices, Females
Peer reviewed Peer reviewed
Direct linkDirect link
Pellas, Nikolaos; Peroutseas, Efstratios – Journal of Educational Computing Research, 2016
While pedagogical and technological affordances of three-dimensional (3D) multiuser virtual worlds in various educational disciplines are largely well-known, a study about their effect on high school students' engagement in introductory programming courses is still lacking. This case study presents students' opinions about their participation in a…
Descriptors: High School Students, Educational Games, Computer Simulation, Simulated Environment
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Maaliw, Renato R. III; Ballera, Melvin A. – International Association for Development of the Information Society, 2017
The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…
Descriptors: Classification, Cognitive Style, Electronic Learning, Decision Making
Peer reviewed Peer reviewed
Direct linkDirect link
Berland, Matthew; Davis, Don; Smith, Carmen Petrick – International Journal of Computer-Supported Collaborative Learning, 2015
AMOEBA is a unique tool to support teachers' orchestration of collaboration among novice programmers in a non-traditional programming environment. The AMOEBA tool was designed and utilized to facilitate collaboration in a classroom setting in real time among novice middle school and high school programmers utilizing the IPRO programming…
Descriptors: Computer Science Education, Active Learning, Programming, Novices
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis
Polo, Blanca J. – ProQuest LLC, 2013
Much research has been done in regards to student programming errors, online education and studio-based learning (SBL) in computer science education. This study furthers this area by bringing together this knowledge and applying it to proactively help students overcome impasses caused by common student programming errors. This project proposes a…
Descriptors: Computer Science Education, Programming, Online Courses, Electronic Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
Previous Page | Next Page »
Pages: 1  |  2