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Garces, Sebastian; Vieira, Camilo; Ravai, Guity; Magana, Alejandra J. – Education and Information Technologies, 2023
Worked examples can help novice learners develop early schemata from an expert's solution to a problem. Nonetheless, the worked examples themselves are no guarantee that students will explore these experts' solutions effectively. This study explores two different approaches to supporting engineering technology students' learning in an…
Descriptors: Learner Engagement, Active Learning, Programming, Engineering Education
Chun-Hsiung Tseng; Hao-Chiang Koong Lin; Andrew Chih-Wei Huang; Jia-Rou Lin – Cogent Education, 2023
This study explores the use of machine learning and physiological signals to enhance learning performance based on students' personality traits. Traditional personality assessment methods often yield unreliable responses, prompting the need for a novel approach utilizing objective data collection through physiological signals. Participants from a…
Descriptors: Artificial Intelligence, Personality Traits, Foreign Countries, Engineering Education
David Roldan-Alvarez; Francisco J. Mesa – IEEE Transactions on Education, 2024
Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…
Descriptors: Intelligent Tutoring Systems, Grading, Artificial Intelligence, Feedback (Response)
Danielak, Brian – Cognition and Instruction, 2022
This paper focuses on a historically understudied area in computing education: attending to students' *design thinking* in university-level introductory programming courses. I offer an account of one student--"Rebecca"--and her experiences and code from a second-semester course on programming concepts for engineers. Using data from both…
Descriptors: Design, Computer Science Education, Programming, Introductory Courses
Pakpour, Nazzy; Nouredini, Sahar; Tandon, James – IEEE Transactions on Education, 2022
Contribution: Although engineering hackathon events are common, this is one of the first reports of such an event used for the purpose of teaching engineering students about public health concepts. Results from this study suggest that hackathons are an effective format for teaching topics that are not core to the engineering discipline in a short…
Descriptors: Undergraduate Students, Engineering Education, Computer Science Education, Programming
Kenney, Rachael; An, Tuyin; Kim, Sung-Hee; Uhan, Nelson A.; Yi, Ji Soo; Shamsul, Aiman – International Journal of Science and Mathematics Education, 2020
In linear programming, many students find it difficult to translate a verbal description of a problem into a valid mathematical model. To better understand this, we examine the existing characteristics of college engineering students' errors across linear programming (LP) problems. We examined textbooks to identify the types of problems typically…
Descriptors: Programming, Error Patterns, Engineering Education, Word Problems (Mathematics)
R. Rosario; T. S. Hopper; A. Huang-Saad – Biomedical Engineering Education, 2022
There are increasing calls for the use of research-based teaching strategies to improve engagement and learning in engineering. In this innovation paper, we detail the application of research-based teaching strategies in a computer programming focused biomedical engineering module. This four-week, one-credit undergraduate biomedical engineering…
Descriptors: Undergraduate Students, Biomedicine, Engineering Education, Programming
Lockwood, Elise – Cognition and Instruction, 2022
In this paper, I discuss undergraduate students' engagement in basic Python programming while solving combinatorial problems. Students solved tasks that were designed to involve programming, and they were encouraged to engage in activities of prediction and reflection. I provide data from two paired teaching experiments, and I outline how the task…
Descriptors: Undergraduate Students, Thinking Skills, Prediction, Teaching Methods
Riese, Emma; Stenbom, Stefan – IEEE Transactions on Education, 2023
Contribution: This study evaluates the generalizability of previously identified perceptions among engineering students of assessments in introductory programming (CS1). The students' perceptions of their instructors' and teaching assistants' (TAs) roles in these assessments are also studied, and differences based on prior programming experience,…
Descriptors: Student Attitudes, Educational Experience, Computer Science Education, Student Evaluation
Kittur, Javeed – IEEE Transactions on Education, 2020
Contribution: This article has shown that self-efficacy in performing complex computer programming tasks and the self-regulation of electrical and electronics engineering undergraduate students varies with respect to the class standing and prior experience in computer programming. Background: Computer programming is an essential skill that all…
Descriptors: Measures (Individuals), Programming, Self Efficacy, Engineering Education
Yenkie, Kirti Maheshkumar – Chemical Engineering Education, 2020
The current business trends, such as Industry 4.0, require a modern chemical engineer to know about programming, advanced computational tools, and holistic thinking. To this end, an integrated approach, where theoretical concepts are supplemented by computational lab-based exercises and team projects promoting "Design Thinking" is…
Descriptors: Chemical Engineering, Engineering Education, Undergraduate Students, College Instruction
Shmallo, Ronit Shmallo; Shrot, Tammar – Journal of Information Systems Education, 2020
A class diagram is one of the most important diagrams of Unified Modeling Language (UML) and can be used for modeling the static structure of a software system. Learning from errors is a teaching approach based on the assumption that errors can promote learning. We applied a constructive approach of using errors in designing a UML class diagram in…
Descriptors: Programming Languages, Programming, Information Systems, Engineering Education
Devine, Kevin; Chang, Yi-hsiang Isaac; Klitzing, Gunnar – Engineering Design Graphics Journal, 2019
Recent developments in Virtual Reality (VR) technology has prompted the manufacturing industry and software vendors to investigate VR's potential for process enhancement. In this paper, we present a study to investigate whether using VR could reduce an individual's cognitive workload during the process of programming an industrial robot. The…
Descriptors: Computer Simulation, Cognitive Processes, Difficulty Level, Programming
Bakke, Christine; Sakai, Rena – Journal of Information Technology Education: Innovations in Practice, 2022
Aim/Purpose: This research aims to describe layering of career-like experiences over existing curriculum to improve perceived educational value. Background: Feedback from students and regional businesses showed a clear need to increase student's exposure to career-like software development projects. The initial goal was to develop an…
Descriptors: Computer Software, Best Practices, Feedback (Response), Computer Science Education
Jegede, Philip Olu; Olajubu, Emmanuel Ajayi; Ejidokun, Adekunle Olugbenga; Elesemoyo, Isaac Oluwafemi – Journal of Information Technology Education: Innovations in Practice, 2019
Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However,…
Descriptors: Programming Languages, Programming, Low Achievement, High Achievement