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Green, Michael; Chen, Xiaobo – Journal of Chemical Education, 2020
For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop.…
Descriptors: Undergraduate Students, Data, Chemistry, Programming Languages
Pang, Bo; Nijkamp, Erik; Wu, Ying Nian – Journal of Educational and Behavioral Statistics, 2020
This review covers the core concepts and design decisions of TensorFlow. TensorFlow, originally created by researchers at Google, is the most popular one among the plethora of deep learning libraries. In the field of deep learning, neural networks have achieved tremendous success and gained wide popularity in various areas. This family of models…
Descriptors: Artificial Intelligence, Regression (Statistics), Models, Classification
Villamor, Maureen M. – Research and Practice in Technology Enhanced Learning, 2020
High attrition and dropout rates are common in introductory programming courses. One of the reasons students drop out is loss of motivation due to the lack of feedback and proper assessment of their progress. Hence, a process-oriented approach is needed in assessing programming progress, which entails examining and measuring students' compilation…
Descriptors: Novices, Problem Solving, Computer Science Education, Introductory Courses
Werner, Linda; Denner, Jill; Campe, Shannon; Torres, David M. – ACM Transactions on Computing Education, 2020
This article builds on prior work that aims to measure computational learning (CL) during middle school. Since game computational sophistication (GCS) has been used as a proxy for a student's engagement in CL we build on their model to more completely describe the relationship between different types of building blocks of computer games and GCS.…
Descriptors: Computation, Middle School Students, Knowledge Level, Learner Engagement
Lynch, Tom Liam; Ardito, Gerald; Amendola, Pam – Eye on Education, 2020
"Integrating Computer Science Across the Core" is a guide to systematizing computer science and computational thinking practices in your school. While most books explain how to teach computer science as a stand-alone discipline, this innovative approach will help you leverage your existing curriculum to deepen and expand students'…
Descriptors: Elementary Secondary Education, Computer Science, Computer Science Education, Thinking Skills
Hadjerrouit, Said; Hansen, Nils Kristian – International Association for Development of the Information Society, 2020
This paper aims at exploring students' experiences when engaging in mathematical problem-solving through computational thinking and programming by a combination of theoretically derived insights and task-based activities. The main method used is a semi-structured interview with two undergraduate students who were presented with a mathematical task…
Descriptors: Learner Engagement, Mathematics Education, Problem Solving, Computation
Kathryn Irene Cunningham – ProQuest LLC, 2020
Introductory programming courses typically focus on building generalizable programming knowledge by focusing on a language's syntax and semantics. Assignments often involve "code tracing" problems, where students perform close tracking of code's execution, typically in the context of 'toy' problems. "Reading-first" approaches…
Descriptors: Programming, Coding, Teaching Methods, Introductory Courses
Olelewe, Chijioke Jonathan; Agomuo, Emmanuel E.; Obichukwu, Peter Uzochukwu – Education and Information Technologies, 2019
Achieving learner engagement in the teaching and learning process is paramount towards ensuring knowledge retention in QBASIC programming. This study focuses on effects of b-learning and face-to-face (F2F) on college students' engagement and retention in QBASIC programming. The study adopted quasi-experimental design with non-equivalent group…
Descriptors: College Students, Learner Engagement, Retention (Psychology), Programming
Moskal, Adon Christian Michael; Wass, Rob – Computer Science Education, 2019
Background and Context: Encouraging undergraduate programming students to think more about their software development processes is challenging. Most programming courses focus on coding skill development and mastering programming language features; subsequently software development processes (e.g. planning, code commenting, and error debugging) are…
Descriptors: Computer Software, Undergraduate Students, Programming, Programming Languages
Deepak Dawar – Information Systems Education Journal, 2024
Learning computer programming is typically difficult for newcomers. Demotivation and learned helplessness have received much attention. Besides the subject's intricacy, low in-class participation has been associated with poor student achievement. This paper presents a follow-up, stage 2 study on the novel instructional technique, Student-Driven…
Descriptors: College Students, Computer Science Education, Required Courses, Elective Courses
Zoe C. M. Davidson; Shuping Dang; Xenofon Vasilakos – IEEE Transactions on Learning Technologies, 2024
Raspberry Pi Pico, based on chip RP2040, is an easy-to-use development microcontroller board that can provide flexible input/output functions and meets the teaching needs of basic electronics to first-year university undergraduates. This article presents our blended laboratory design using Raspberry Pi Pico for the course unit Digital Circuits and…
Descriptors: College Freshmen, Electronics, Technology Education, Scientific Concepts
Construction and Analysis of a Decision Tree-Based Predictive Model for Learning Intervention Advice
Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
Alex Fegely; Cory Gleasman; Tammi Kolski – Educational Technology Research and Development, 2024
Computer science teaching standards for grades K-8 have been implemented in nearly all U.S. states, and the core subject area teachers (e.g., math, science, English, social studies) have been asked to integrate these standards into their instruction. Thus, it is important that K-8 pre-service teachers of all subjects are both prepared and…
Descriptors: Educational Technology, Robotics, Shared Resources and Services, Preservice Teacher Education
Zebel-Al Tareq; Raja Jamilah Raja Yusof – IEEE Transactions on Education, 2024
Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available; however, being…
Descriptors: Models, Problem Solving, Computation, Thinking Skills
Jessica M. M. Hamer; Peter E. J. Kemp; Billy Wong; Meggie Copsey-Blake – Cambridge Journal of Education, 2024
Digital skills are beneficial for young people and society, but some individuals, particularly girls, are less likely to choose computing post-compulsory education. Coding is a crucial skill in the school computing curriculum. The authors collected survey data from 4983 secondary-school students (ages 11-16) as well as conducted exploratory factor…
Descriptors: Foreign Countries, Secondary School Students, Computer Science Education, Coding