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Zachary M. Savelson; Kasia Muldner – Computer Science Education, 2024
Background and Context: Productive failure (PF) is a learning paradigm that flips the order of instruction: students work on a problem, then receive a lesson. PF increases learning, but less is known about student emotions and collaboration during PF, particularly in a computer science context. Objective: To provide insight on students' emotions…
Descriptors: Student Attitudes, Psychological Patterns, Fear, Failure
Zhaojun Duo; Jianan Zhang; Yonggong Ren; Xiaolu Xu – Education and Information Technologies, 2025
"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…
Descriptors: Students, Programming, Problem Solving, Self Management
Xu, Weiqi; Wu, Yajuan; Ouyang, Fan – International Journal of Educational Technology in Higher Education, 2023
Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students' discourses, behaviors, and socio-emotions, it is of critical importance to examine…
Descriptors: Cooperative Learning, Problem Solving, Computer Science Education, Programming
Mingli Han – International Society for Technology, Education, and Science, 2023
Teaching robotics courses online is challenging due to the complexity of the interdisciplinary topics involved. One of the most challenging topics is 3D coordinate transformations. Students often struggle to grasp the concept of 3D coordinate transformations and their relevance to real-world robotic applications. This paper applies the Scholarship…
Descriptors: Self Evaluation (Individuals), Robotics, Assignments, Computer Software
Francesco C. Ugolini; Panagiotis Kakavas – Research on Education and Media, 2024
This study consists of a 17-year (2006-2021) systematic literature review on the effective instructional strategies for developing Computational Thinking (CT) in primary school students (K-5). The aim of this paper is to identify instructional strategies that have been implemented and evaluated by means of a pre- and post-test, with the aim of…
Descriptors: Teaching Methods, Computer Science Education, Kindergarten, Elementary School Students
Saba, Janan; Hel-Or, Hagit; Levy, Sharona T. – Instructional Science: An International Journal of the Learning Sciences, 2023
This article concerns the synergy between science learning, understanding complexity, and computational thinking (CT), and their impact on near and far learning transfer. The potential relationship between computer-based model construction and knowledge transfer has yet to be explored. We studied middle school students who modeled systemic…
Descriptors: Transfer of Training, Science Instruction, Learning Management Systems, Learning Processes
Margulieux, Lauren E.; Morrison, Briana B.; Decker, Adrienne – International Journal of STEM Education, 2020
Background: Programming a computer is an increasingly valuable skill, but dropout and failure rates in introductory programming courses are regularly as high as 50%. Like many fields, programming requires students to learn complex problem-solving procedures from instructors who tend to have tacit knowledge about low-level procedures that they have…
Descriptors: Programming, Computer Science Education, Introductory Courses, Withdrawal (Education)
Malik, Sohail Iqbal; Tawafak, Ragad M.; Shakir, Mohanaad – International Journal of Information and Communication Technology Education, 2021
A teaching approach plays an important role in teaching and learning process of an introductory programming (IP) course. The teaching approach should focus on different programming skills required by novice programmers. In this study, we introduced the teaching and learning approach based on an ADRI (Approach, Deployment, Result, Improvement)…
Descriptors: Computer Science Education, Programming, Teaching Methods, Learning Processes
Marmur, Ofer; Koichu, Boris – Mathematical Thinking and Learning: An International Journal, 2023
This paper explores student emotion and learning experiences fostered by lecturing-style instruction in Real-Analysis problem-centered lessons. We focus on two lessons that were taught by two reputable instructors and involved challenging, mathematically-related problems the students did not understand. Nonetheless, one lesson evoked negative…
Descriptors: Heuristics, Discourse Analysis, Recall (Psychology), Correlation
Stone, Jeffrey A.; Cruz, Laura – Teaching & Learning Inquiry, 2021
Higher education has embraced integrative learning as a means of enabling students to tackle so-called "wicked" problems, i.e. problems that are sufficiently complex, contested, and ambiguous that conventional, disciplinary specific approaches are inadequate to address. However, challenges remain in defining integrative learning…
Descriptors: Introductory Courses, Computer Science Education, Interdisciplinary Approach, Integrated Activities
Sbaraglia, Marco; Lodi, Michael; Martini, Simone – Informatics in Education, 2021
Introductory programming courses (CS1) are difficult for novices. Inspired by "Problem solving followed by instruction" and "Productive Failure" approaches, we define an original "necessity-driven" learning design. Students are put in an apparently well-known situation, but this time they miss an essential ingredient…
Descriptors: Programming, Introductory Courses, Computer Science Education, Programming Languages
Hosseini, Roya; Akhuseyinoglu, Kamil; Brusilovsky, Peter; Malmi, Lauri; Pollari-Malmi, Kerttu; Schunn, Christian; Sirkiä, Teemu – International Journal of Artificial Intelligence in Education, 2020
This research is focused on how to support students' acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student's learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage…
Descriptors: Programming, Computer Science Education, Problem Solving, Learner Engagement
Prates, Jorge Marques; Melo, Silvana Morita; Valle, Pedro Henrique Dias; Garcia, Rogério Eduardo; Maldonado, José Carlos – Informatics in Education, 2023
Nowadays, SPOCs (Small Private Online Courses) have been used as complementary methods to support classroom teaching. SPOCs are courses that apply the usage of MOOCs (Massive Open Online Courses), combining classroom with online education, making them an exciting alternative for contexts such as emergency remote teaching. Although SPOCs have been…
Descriptors: Computer Software, Computer Science Education, COVID-19, Pandemics
Behera, Ardhendu; Matthew, Peter; Keidel, Alexander; Vangorp, Peter; Fang, Hui; Canning, Susan – International Journal of Artificial Intelligence in Education, 2020
Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of…
Descriptors: Nonverbal Communication, Intelligent Tutoring Systems, Eye Movements, Learning Processes
DeLiema, David; Kwon, Yejin Angela; Chisholm, Andrea; Williams, Immanuel; Dahn, Maggie; Flood, Virginia J.; Abrahamson, Dor; Steen, Francis F. – Cognition and Instruction, 2023
When teachers, researchers, and students describe productively responding to moments of failure in the learning process, what might this mean? Blending prior theoretical and empirical research on the relationship between failure and learning, and empirical results from four data sets that are part of a larger design-based research project, we…
Descriptors: Guidelines, Learning Processes, Correlation, Failure