Relationship between creative thinking and outcomes in a digital STEM-based learning environment: A mixed methods case study

Thinking Skills and Creativity, Journal Year: 2025, Volume and Issue: unknown, P. 101816 - 101816

Published: March 1, 2025

Language: Английский

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Methodology for developing students’ algorithmic thinking about creating applications

AIP conference proceedings, Journal Year: 2025, Volume and Issue: 3268, P. 070016 - 070016

Published: Jan. 1, 2025

Language: Английский

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Teaching programming in higher education: a bibliometric analysis of trends, technologies, and pedagogical approaches

Frontiers in Education, Journal Year: 2025, Volume and Issue: 10

Published: March 28, 2025

The continuous evolution of digital technologies has significantly reshaped the landscape higher education, particularly in programming instruction. As skills become increasingly essential across multiple disciplines, analyzing research trends, key contributors, and institutional impact on education is crucial. This study presents a bibliometric analysis to identify influential works, leading authors, major institutions that have shaped this field over years. By systematically examining scholarly publications, explores most recurrent pedagogical approaches, role emerging technologies, methodological frameworks used assess competencies. Additionally, it highlights prevailing knowledge gaps, future directions for improving institutions. findings work will support educators, curriculum designers, policymakers refining instructional strategies, fostering innovative learning environments, aligning academic programs with industry demands.

Language: Английский

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How are primary school computer science curricular reforms contributing to equity? Impact on student learning, perception of the discipline, and gender gaps

International Journal of STEM Education, Journal Year: 2023, Volume and Issue: 10(1)

Published: Oct. 10, 2023

Abstract Background Early exposure to Computer Science (CS) and Computational Thinking (CT) for all is critical broaden participation promote equity in the field. But how does introduction of CS CT into primary school curricula impact learning, perception, gaps between groups students? Methodology We investigate a CS-curricular reform teacher Professional Development (PD) programme from an standpoint by applying hierarchical regression structural equation modelling on student learning perception data three studies with, respectively, 1384, 2433 1644 grade 3–6 students (ages 7–11) their 83, 142 95 teachers. Results Regarding instruction appears contribute closing performance gap low-achieving high-achieving students, as well pre-existing gender gaps. Despite lack direct influence what was taught there no teachers’ demographics or motivation with CS-PD positively influencing learning. perceive its teaching tools (robotics, tablets) positively, even more so when they role model close them doing CS. Nonetheless, differences exist around boys perceiving than girls despite access education. However, CS-education affects differently: larger are (namely those related robotics), while smaller increasing tablets). Conclusion This article highlights curricular impacts supports importance (i) early introductions all; (ii) preparing teachers teach removing outcomes; (iii) having developmentally appropriate activities that signal students.

Language: Английский

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Researching Computational Thinking in Early Childhood STE(A)M Education Context: A Descriptive Review on the State of Research and Future Directions

Journal for STEM Education Research, Journal Year: 2023, Volume and Issue: 6(3), P. 427 - 455

Published: May 25, 2023

Language: Английский

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Development of algorithmic thinking skills in K-12 education: A comparative study of unplugged and digital assessment instruments

Computers in Human Behavior Reports, Journal Year: 2024, Volume and Issue: 15, P. 100466 - 100466

Published: Aug. 1, 2024

Language: Английский

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Characterising algorithmic thinking: A university study of unplugged activities✰

Thinking Skills and Creativity, Journal Year: 2023, Volume and Issue: 48, P. 101284 - 101284

Published: March 16, 2023

Algorithmic thinking is a type of that occurs in the context computational thinking. Given its importance current educational context, it seems pertinent to deepen into conceptual and operational understanding for teaching. The exploration research shows us there are almost no studies at university level where algorithmic connected mathematical thinking, more importantly, characterise be able analyse evaluate better. aim this Bachelor's Degree Mathematics by unplugged tasks, offering model analysis through categories establish connections between working spaces three dimensions, semiotic, instrumental discursive. results confirm interaction these dimensions their predictive value better programming performance. study also adds novel considerations related role involved

Language: Английский

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Exploratory factor analysis-instrument for self-assessment of computation thinking skills and collaboration skills

International Journal of Evaluation and Research in Education (IJERE), Journal Year: 2024, Volume and Issue: 13(2), P. 1045 - 1045

Published: Jan. 23, 2024

This study focuses on developing and validating instruments to assess the computational thinking skills (CTS) collaboration (CS) of undergraduate students in Indonesia. Employing a quantitative research approach with exploratory factor analysis (EFA) technique, process unfolded three validation steps. First, face validity was established through expert judgment. Second, discriminant examined using product-moment correlations Cronbach’s alpha. Finally, EFA were employed factorial structure. The instrument development followed five phases: drafting instrument, assessment by experts, data collection involving 242 as samples, (product moment alpha), group items construct dimensions. identified six dimensions for CTS (algorithmic thinking, cooperative problem reformulation, creativity, critical systematic testing) CS (knowledge sharing, planning, responsibility). These findings support self-assessment scale, making it valuable tool evaluating student learning researching Researchers educators are encouraged utilize purposes further exploration these competencies among students.

Language: Английский

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Using students’ cognitive, affective, and demographic characteristics to predict their understanding of computational thinking concepts: a machine learning-based approach

Interactive Learning Environments, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 14

Published: March 19, 2024

Logistic regression models have traditionally been used to identify the factors contributing students' conceptual understanding. With advancement of machine learning-based research approach, there are reports that some learning algorithms outperform logistic in terms prediction. In this study, we collected cognitive, affective, and demographic data from 4,142 primary students as features predict their understanding computational thinking (CT) concepts. We identified five popularly models. All outperformed model, with extreme gradient boosting (XGBoost) model achieving highest predictive accuracy. these K-means algorithm unsupervised clustering technique four optimal clusters students. By comparing representative each clusters, selected by t-distributed stochastic neighbour embedding algorithm, found cluster had its characteristics. For example, one consisted who other three mathematics, scored prior experience programming, computers Internet most frequently. identifying characteristics pedagogical design, resource support can be proposed CT

Language: Английский

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Analysis of Computational Thinking Skill Through Technology Acceptance Model Approach Using Augmented Reality in Electronics Engineering Education

TEM Journal, Journal Year: 2024, Volume and Issue: unknown, P. 1423 - 1431

Published: May 28, 2024

Technological progress has brought about modifications in the educational process. This transformation led to numerous technological innovations for supporting student learning, with smartphones being one of prominent tools. Despite widespread use, students have primarily used online gaming and social media, leading a decline effectiveness purposes. Therefore, this study aimed explore how electronics engineering education responded novel technology, augmented reality (AR), when integrated into fundamental learning process, order maximize utility smartphones. A cross-sectional survey approach quantitative methodology comprising 101 field higher institutions Indonesia was adopted. Data were collected through questionnaire, which subsequently analyzed using Structural Equation Model (SEM) method SmartPLS 3 software. Additionally, Fuzzy C-Means (FCM) clustering examine influence each cluster values on others. The analytical results showed that Computational Thinking Skill (CTS) significantly impacted Actual System Use (ASU) AR. Furthermore, perceived usefulness (PU) ease use (PEU) technology played crucial roles as mediators ASU

Language: Английский

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