Search Results (77)

This research is focused on exploring the importance of STEM (Science, Technology, Engineering, and Mathematics) education in the development of critical competencies among secondary school students in the 21st century. This was aimed to assess the impact of STEM-based activities on students’ creative and computational thinking skills. A quasi-experimental design that included 77 secondary school students from public and private schools in Bandar Lampung, Indonesia, who participated in STEM interventions for over 5 weeks, was adopted. Data were collected through creative thinking tests and questionnaires on CT and STEM attitudes. The results showed that students who participated in STEM activities exhibited significantly higher creative thinking scores compared to peers taught with the traditional curriculum. Specifically, the experimental group showed a progressive increase in weekly test scores, suggesting that STEM methods improved students’ performance over time. Structural equation modeling (SEM) disclosed strong positive associations between attitudes towards STEM, CT, and creativity. The implications of these results outlined the need to integrate STEM education into curricula to foster essential skills for future challenges. This research contributes to the understanding of effective educational strategies and also advocates for a shift towards more interactive and integrative methods in secondary education to meet the demands of the contemporary workforce. Full article

This study presents the design and validation process of a new Bebras-based instrument to assess computational thinking (CT) in 7th-grade students. An initial version of the test, composed of 18 multiple-choice items, was piloted with 80 students and revised based on their performance and classroom feedback. The final version, composed of 17 tasks balanced across CT components and difficulty levels, was administered to 1513 students from 86 Spanish schools. No significant gender differences were found in overall performance, supporting the potential of Bebras tasks to provide equitable assessment. An exploratory factor analysis revealed a dominant factor explaining 20% of the variance, and additional evidence (Lord’s index = 10.61) supported the use of a one-dimensional model despite the ambiguous dimensionality of the domain. BBACT offers a balanced and theoretically grounded tool for assessing CT in compulsory education and lays the foundation for future work exploring its validity and application across diverse contexts. Full article

Blending child-led exploration with purposeful teacher guidance and clearly defined learning goals, playful learning has been promoted as a promising approach for introducing computational thinking (CT) in early childhood education (ECE). However, there is a lack of practical guidance for teachers on how to design and implement playful CT learning effectively. To address this gap, we conducted a collaborative action research project and asked these two questions: (1) How can teachers effectively prepare and design a playful learning CT program using tangible CT toys? (2) How do teachers facilitate playful learning in the CT program? Through iterative cycles of planning, acting, observing, and reflecting, the first and second authors (teacher-researchers) designed and implemented their CT programs in a preschool classroom and an afterschool program respectively, and collected data including video recordings of sessions, participant-generated artifacts, program documentation, and anecdotal reflection notes. Based on our thematic analysis of the data, we identified practical principles for selecting CT toys, three key themes for CT program design and preparation—interest, ownership, and application, and two forms of teacher scaffolding during implementation: embodied approach and storytelling as scaffolding and assessment. The findings highlight practical ways that teachers can enhance children’s engagement, problem-solving skills, and conceptual understanding of CT, while also promoting autonomy and creativity through coding and storytelling. Full article

Rapid digital transformation demands educational approaches that effectively equip students with competencies crucial for addressing real-world sustainability challenges. This study introduces and evaluates a Living Lab-based collaborative problem-solving educational model explicitly designed to enhance collaborative problem-solving (CPS), computational thinking (CT), and collaborative communication (CC) within elementary informatics education. Aligned with South Korea’s 2022 revised curriculum, this quasi-experimental research involved 196 elementary students, divided into experimental and control groups. Both groups participated in pre- and post-tests measuring CPS, CC, and CT competencies. The experimental group actively engaged in structured, community-based tasks integrating informatics concepts with authentic, real-world problems, whereas the control group experienced traditional instruction methods. Statistical analysis demonstrated significant improvements in the experimental group’s CPS and CT competencies (e.g., applying problem-solving strategies increased from 3.44 to 3.93, p < 0.001; ICT usage from 3.40 to 3.82, p = 0.002). However, advancements in CC were comparatively modest (creative communication increased from 3.31 to 3.81, p = 0.006), highlighting the necessity for explicit and structured communication interventions within collaborative frameworks. This study confirms the effectiveness of the Living Lab-based collaborative problem-solving educational model in cultivating comprehensive competencies essential for sustainable development, while underscoring the need for further integration of targeted communication strategies to maximize educational impact. Future implementations should prioritize structured communication training to fully leverage the model’s interdisciplinary potential. Full article

Computational thinking (CT), an interrelation of skills and practices, is a crucial competency that empowers individuals to tackle logical problems, enabling them to overcome various challenges in their daily lives. To help Deaf students (those with hearing loss and using sign language for communication) enhance their CT, a STEAM learning program using a physical computing tool is proposed. The learning program composes four courses: learning concepts, implementing concepts, finding solutions to real problems and developing innovations. The program engaged Deaf students from 18 Deaf schools. It is geared towards boosting students’ CT and facilitating their capacity to devise technology-based solutions. The program measured students’ CT effectiveness based on the CT framework: concepts, practices, and perspectives. The measurement encompassed multiple-choice assessments for CT concepts, task rubrics for CT practices, and interview and invention observations for CT perspectives. The program concludes with participating in a science project competition, using a physical computing tool, called KidBright, to solve real-world issues by integrating science, mathematics, and art. After completing the learning program, Deaf students demonstrated an improved understanding of CT concepts, performing high-level CT practices, and expressing strong CT perspectives. These indicate that a STEAM learning program utilizing a physical computing tool can help Deaf students enhance their computational thinking. Full article

In order to meet the learning demands and challenges of the 21st century, computational thinking (CT) skills are important to start developing in early childhood education. The best way to cultivate CT skills, such as algorithmic thinking, is by implementing multidisciplinary education, introducing state-of-the-art technological tools, and adopting engaging teaching strategies like robotics. Within this context, we introduce a play-based educational framework that is developmentally appropriate for second graders and aims to exercise pupils’ algorithmic thinking amid the Environmental Studies course. Keeping in mind that the early childhood period is crucial in developing environmentally friendly attitudes, intentions, and behaviours, we designed the proposed educational framework not only to cultivate pupils’ algorithmic thinking but environmental awareness too. The main technology exploited was the Bee-Bot, which stimulates children to learn how to solve problems efficiently and imaginatively through playful programming. This article reports a relevant case study conducted in October 2023 in Crete, Greece, adopting a robust ethical framework and being implemented under the umbrella of the qualitative research methodology. Studying the data obtained shows that the pupils embraced the proposed robotics activities, exercised their algorithmic thinking, and cultivated their environmental awareness in a playful, collaborative, and engaging learning environment. Full article

The rapid integration of computational thinking (CT) into STEM education highlights its importance as a critical skill for problem-solving in the digital age, equipping students with the cognitive tools needed to address complex challenges systematically. This study evaluates CT skills among Engineering and Computer Science students using a multi-method approach by combining quantitative methods (CTT scores and CTS responses) with qualitative methods (thematic analysis of open-ended questions), integrating objective assessments, self-perception scales, and qualitative insights. The Computational Thinking Test (CTT) measures proficiency in core CT sub-competencies, abstraction, decomposition, algorithmic thinking, and pattern recognition through objective tests. The Computational Thinking Scale (CTS) captures students’ perceived CT skills. At the same time, open-ended questions elicit perspectives on the practical applications of CT in academic and professional contexts. Data from 196 students across two Mexican universities were analyzed through quantitative and thematic methods. The results show that students excel in pattern recognition and abstraction but face decomposition and algorithmic thinking challenges. Cross-sectional analyses were conducted between CTT, CTS and the open-ended part to compare CT skills across different demographic groups (e.g., age, gender, academic disciplines), showing clear differences based on age, gender, and academic disciplines, with Computer Science students performing better than engineering students. These findings highlight the importance of CT in preparing students for modern challenges and provide a foundation for improving teaching methods and integrating these skills into university programs. Full article

Computational Thinking (CT) and programming encompass a range of skills that are essential in everyday life and play a crucial role in addressing social and environmental challenges. They facilitate the analysis and understanding of global issues, the evaluation of viable solutions, and the formulation of strategic decisions that contribute to Education for Sustainable Development and the achievement of the Sustainable Development Goals. The primary objective of this study was to examine pre-service teachers’ perceptions of these areas. A quantitative study was conducted with 134 university students from the Faculty of Education and Tourism at the University of Salamanca. The findings indicate that CT and programming significantly contribute to enhancing digital competence, fostering essential skills for the effective use of technological tools, developing problem-solving strategies, and increasing self-confidence in identifying and refining solutions to complex problems. Regarding gender differences, significant differences were observed, with women scoring higher on average in various aspects. These included the ability to actively seek, compare, and select digital information from diverse sources and contexts, assess the potential risks associated with digital tools—such as security and identity concerns—and demonstrate confidence in accessing the necessary resources and training to integrate CT and programming into education. Full article

This paper explores the association between computational thinking (CT) skills and learning to play musical instruments. While CT has often been linked to programming and STEM fields, its application to non-digital contexts remains underexplored. The two studies presented here address this gap. In the first, a quantitative study (N = 91), self-report questionnaires were filled out by young adults with varied musical backgrounds, who also undertook CT tests. We found a strikingly positive association between musical experience and CT performance, with some nuanced associations based on the characteristics and experience of music playing. In the second, qualitative study (N = 10), interviews were conducted with high school students who are highly experienced in music performance, aiming at identifying CT skills they use while learning to play musical pieces. The analysis revealed that they employ a wide range of CT skills, and that the manifestation of these skills differs by the stage of learning. These two studies complement each other, hence this paper sheds important new light on the associations between CT and the field of music education. Full article

Computational thinking (CT) in young children (K to three) has been of much interest among educational researchers due to the applicability of CT to solving problems in daily life and various academic disciplines. This study uses existing data from children’s gameplay in a block-based programming game called codeSpark Academy to examine the extent to which we can use children’s gameplay behavior to measure their CT and, more generally, their problem-solving skills. The objectives of the study are to operationalize CT and problem-solving constructs using gameplay data, investigate the relationship between CT and problem-solving, and position codeSpark Academy as a valid assessment tool. A total of 72 elementary students (aged 6–9) played codeSpark Academy once a week for six weeks. TechCheck, an externally developed and validated measure of CT, was administered before the first game day and after the last game day. Using fine-grained, moment-to-moment gameplay data, we developed and validated seven game-based indicators (GBIs) of CT using correlational analysis and nonparametric tests and integrated them into a problem-solving framework. Our findings showed that children’s gameplay behavior can be used to measure their CT and problem-solving skills. Full article

Coding and computational thinking (CT) are important skills to include in early childhood education. Measuring these vital skills in preschool-age children can be challenging. We modified the TechCheck-PreK assessment, an unplugged measure of CT for 3-to-5-year-old children, to increase reliability and to add foundational coding concepts. We created the Coding Readiness Assessment (CRA) from a subset of nine TechCheck-PreK items and twelve new items that assess additional CT and coding readiness constructs. In an initial feasibility study of the CRA, teachers observed impulsive responses by children. We mitigated this by implementing a brief delay between the appearance of the question and the timeframe in which children could respond. In a subsequent randomized control trial, the CRA was administered 1637 times by Head Start educators. The assessment took an average of 9.8 min to administer. CRA scores were normally distributed and increased on average as a function of age. Girls scored slightly higher than boys, although the difference was not significant when age and race were taken into account. The CRA showed acceptable levels of reliability in terms of internal consistency (α = 0.78) and test–retest reliability (r = 0.65). Results from a 3PL indicate that the CRA has suitable levels of difficulty and skill level discrimination for 3-to-5-year-olds. The 3PL guessing parameter was 0.28, indicating that steps to reduce impulsive responses were successful. We conclude that the CRA has suitable properties for assessing preschool-age children’s CT skills and coding readiness. Full article

Computational thinking (CT) and creativity have been recognized as crucial skills for adapting to the current digital era. However, despite being extensively studied over the last few decades, research on their associations has only emerged recently. We report on a study that examined how creativity is manifested in the context of CT, specifically while solving computational problems in an online game-based learning environment for early programming. We took a learning analytics log-based approach to evaluate measures of CT and creativity. We developed a Python algorithm to automatically analyze the logged solutions across four creativity measures. This allowed for an objective, quantitative, multidimensional analysis of 52,438 submissions of N = 111 primary and secondary school students over 85 tasks. We examined the relationships between measures of creativity, game level, and CT, utilized exploratory analysis to investigate how measures of creativity differ across age groups, and explored how these measures characterize students. Our findings suggest that creativity does not decrease throughout the game despite the increased difficulty and its mechanics that penalize creative solutions. We also point out how various dimensions of creativity play different roles in learning. These findings suggest that educators should foster intrinsic motivation and encourage students to explore multiple solution paths to enhance both CT and creativity skills. Researchers should keep investigating mechanisms to assess and enhance creativity in learning environments and explore the influence of personal and contextual factors. Full article

This study investigates the impact of AI-generated contexts on preservice teachers’ computational thinking (CT) skills and their acceptance of educational robotics. This article presents a methodology for teaching robotics based on AI-generated contexts aimed at enhancing CT. An experiment was conducted with 122 undergraduate students enrolled in an Early Childhood Education program, aged 18–19 years, who were training in the Computer Science and Digital Competence course. The experimental group utilized a methodology involving AI-generated practical assignments designed by their lecturers to learn educational robotics, while the control group engaged with traditional teaching methods. The research addressed five key factors: the effectiveness of AI-generated contexts in improving CT skills, the specific domains of CT that showed significant improvement, the perception of student teachers regarding their ability to teach with educational robots, the enhancement in perceived knowledge about educational robots, and the overall impact of these methodologies on teaching practices. Findings revealed that the experimental group exhibited higher engagement and understanding of CT concepts, with notable improvements in problem-solving and algorithmic thinking. Participants in the AI-generated context group reported increased confidence in their ability to teach with educational robots and a more positive attitude toward technology integration in education. The findings highlight the importance of providing appropriate context and support when encouraging future educators to build confidence and embrace educational technologies. This study adds to the expanding research connecting AI, robotics, and education, emphasizing the need to incorporate these tools into teacher training programs. Further studies should investigate the lasting impact of such approaches on computational thinking skills and teaching methods in a variety of educational environments. Full article

Computational thinking (CT) can be developed in a multitude of ways. Well-known examples are plugged-in and unplugged applications that focus primarily on the (combined) usage of visual, textual, or tangible modalities. Less obvious are applications where CT development can be established via an auditory modality, to which the importance of creativity is attributed. When reasoning from such a different contextual perspective, it is interesting to investigate whether the self-creation of electronic music influences CT development and what added value can be attributed to creativity. Therefore, a mixed-methods study was conducted on primary school pupils aged 10 to 13 using FL-Studio Mobile^© music-producing software. Quantitative data were obtained using a pre-test–post-test assessment administered via a validated Computational Thinking Test (CTt). Qualitative data were obtained by conducting interviews to ascertain identifiable effects on CT sub-characteristics to determine the influence of creativity and creative thinking and children’s perceptions in this regard. Our results indicate that applying music-making software has measurable effects on CT development, particularly with respect to invoking and using auditory modalities. Notable findings were identified on the CT sub-characteristics “loops”, “conditionals”, “functions”, “nesting”, and “CT tasks required”. Our study shows that producing music using technology stimulates creativity, which seems to be an important parameter for CT development. Differences between girls and boys were observable. Further research on the interaction between CT and creativity, combining different modalities, is recommended. Full article

Computational thinking (CT) currently has been mainly explored using programming robots and conducted in K12 education. In early childhood education, arts have a significant place in children’s learning, expression and cognitive development. Specifically, creating pop-up storybooks is a child-friendly activity. Our study aimed to explore the combination of CT and art, and to develop talented children’s CT abilities through a multimodal literacies educational approach, which referred to using different skills (i.e., writing, drawing, making, and storytelling) in the art activity. A total of 12 talented children were selected to participate in a pop-up storybook production workshop using a convenience sampling method. We adopted an observation method to capture talented children’s CT behaviors, generating a total of 180 min of activity videos and collecting fieldnotes and the children’s worksheets and artworks for the data analysis. Based on a content analysis, we found that talented children enhanced their CT development in multiple modes and practiced seven CT skills. In conclusion, our study emphasizes the importance of art in children’s education and provides new insights for subsequent research on children’s CT education. Full article