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Zengqing Wu; Huizhong Liu; Chuan Xiao – IEEE Transactions on Education, 2024
Contribution: This research illuminates information entropy's efficacy as a pivotal educational tool in programming, enabling the precise quantification of algorithmic complexity and student abstraction levels for solving problems. This approach can provide students quantitative, comparative insights into the differences between optimal and…
Descriptors: Information Theory, Student Evaluation, Thinking Skills, Algorithms
Elena Novak; Chia-Ling Kuo; Janet Lynne Tassell; Grace Morris – TechTrends: Linking Research and Practice to Improve Learning, 2024
Recently, creativity has been acknowledged for its importance in improving computer science learning and attitudes. However, very little is known about how to integrate creativity in preservice teacher computing education. Toward this end, we developed a creativity-enhancement intervention in an online Creative Computing instructional module to…
Descriptors: Preservice Teachers, Elementary School Teachers, Creativity, Intervention
Pavlos Toukiloglou; Stelios Xinogalos – Education and Information Technologies, 2024
Hour of Code is a widely recognized global event that aims to introduce programming to novice users and integrate computer science into education. This paper presents an analysis of the effectiveness of the support system and user interface of Minecraft Adventurer, a serious game designed for the Hour of Code global event. Although previous…
Descriptors: Novices, Programming, Coding, Computer Science Education
Maria Llambrich; Pau Satorra; Eudald Correig; Josep Gumà; Jesús Brezmes; Cristian Tebé; Raquel Cumeras – Research Synthesis Methods, 2024
Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics…
Descriptors: Meta Analysis, Programming Languages, Information Technology, Computer Oriented Programs
Oscar Karnalim; Hapnes Toba; Meliana Christianti Johan – Education and Information Technologies, 2024
Artificial Intelligence (AI) can foster education but can also be misused to breach academic integrity. Large language models like ChatGPT are able to generate solutions for individual assessments that are expected to be completed independently. There are a number of automated detectors for AI assisted work. However, most of them are not dedicated…
Descriptors: Artificial Intelligence, Academic Achievement, Integrity, Introductory Courses
Paul Biberstein; Thomas Castleman; Luming Chen; Shriram Krishnamurthi – Informatics in Education, 2024
CODAP is a widely-used programming environment for secondary school data science. Its direct-manipulation-based design offers many advantages to learners, especially younger students. Unfortunately, these same advantages can become a liability when it comes to repeating operations consistently, replaying operations (for reproducibility), and also…
Descriptors: Data Science, Secondary School Students, Programming, Open Source Technology
Maya B. Mathur – Research Synthesis Methods, 2024
As traditionally conceived, publication bias arises from selection operating on a collection of individually unbiased estimates. A canonical form of such selection across studies (SAS) is the preferential publication of affirmative studies (i.e., those with significant, positive estimates) versus nonaffirmative studies (i.e., those with…
Descriptors: Meta Analysis, Research Reports, Research Methodology, Research Problems
Menon, Pratibha – Journal of Information Systems Education, 2023
This paper introduces a teaching process to develop students' problem-solving and programming efficacy in an introductory computer programming course. The proposed teaching practice provides step-by-step guidelines on using worked-out examples of code to demonstrate the applications of programming concepts. These coding demonstrations explicitly…
Descriptors: Introductory Courses, Programming, Computer Science Education, Feedback (Response)
Hoq, Muntasir; Brusilovsky, Peter; Akram, Bita – International Educational Data Mining Society, 2023
Prediction of student performance in introductory programming courses can assist struggling students and improve their persistence. On the other hand, it is important for the prediction to be transparent for the instructor and students to effectively utilize the results of this prediction. Explainable Machine Learning models can effectively help…
Descriptors: Academic Achievement, Prediction, Models, Introductory Courses
Shen, Guohua; Yang, Sien; Huang, Zhiqiu; Yu, Yaoshen; Li, Xin – Education and Information Technologies, 2023
Due to the growing demand for information technology skills, programming education has received increasing attention. Predicting students' programming performance helps teachers realize their teaching effect and students' learning status in time to provide support for students. However, few of the existing researches have taken the code that…
Descriptors: Prediction, Programming, Student Characteristics, Profiles
Silva, Leonardo; Mendes, Antonio Jose; Gomes, Anabela; Fortes, Gabriel – IEEE Transactions on Education, 2023
Contribution: Students' problem-understanding abilities and their relationship with programming learning were investigated using a methodology little explored in the existing literature. Background: Problem comprehension is an ability used during software development. Current research points to conflicting results on students' ability to interpret…
Descriptors: Programming, Comprehension, Computer Software, Electronic Learning
Fernandez-Gauna, Borja; Rojo, Naiara; Graña, Manuel – International Journal of Educational Technology in Higher Education, 2023
We describe an automated assessment process for team-coding assignments based on DevOps best practices. This system and methodology includes the definition of Team Performance Metrics measuring properties of the software developed by each team, and their correct use of DevOps techniques. It tracks the progress on each of metric by each group. The…
Descriptors: Computer Software, Programming, Coding, Teamwork
Liu, Enrui; Cai, Su; Liu, Zifeng; Liu, Changhao – IEEE Transactions on Learning Technologies, 2023
Augmented reality (AR) has been incorporated into the educational context for years. Numerous studies have demonstrated the effectiveness of AR in different disciplines, learning styles, and learning environments. However, few studies have focused on the problem of generating AR applications in authentic educational contexts. In this study, an AR…
Descriptors: Simulated Environment, Computer Simulation, Programming, Educational Resources
Mosquera, Jose Miguel Llanos; Suarez, Carlos Giovanny Hidalgo; Guerrero, Victor Andres Bucheli – Education and Information Technologies, 2023
This paper proposes to evaluate learning efficiency by implementing the flipped classroom and automatic source code evaluation based on the Kirkpatrick evaluation model in students of CS1 programming course. The experimentation was conducted with 82 students from two CS1 courses; an experimental group (EG = 56) and a control group (CG = 26). Each…
Descriptors: Flipped Classroom, Coding, Programming, Evaluation Methods
Ana Paula Juliana Perin; Deivid Eive dos S. Silva; Natasha M. C. Valentim – Informatics in Education, 2023
In Education 4.0, a personalized learning process is expected, and that students are the protagonist. In this new education format, it is necessary to prepare students with the skills and competencies of the 21st-Century, such as teamwork, creativity, and autonomy. One of the ways to develop skills and competencies in students can be through block…
Descriptors: Programming, High School Students, Learning, Learning Processes