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Integrating Computational Thinking in STEM Education: A Literature Review
Abstract
Research focusing on the integration of computational thinking (CT) into science, technology, engineering, and mathematics (STEM) education started to emerge. We conducted a semi-systematic literature review on 55 empirical studies on this topic. Our findings include: (a) the majority of the studies adopted domain-general definitions of CT and a few proposed domain-specific CT definitions in STEM education ; (b) the most popular instructional model was problem-based instruction, and the most popular topic contexts included game design, robotics, and computational modelling; (c) while the assessments of student learning in integrated CT and STEM education targeted different objectives with different formats, about a third of them assessed integrated CT and STEM; (d) about a quarter of the studies reported differential learning processes and outcomes between groups, but very few of them investigated how pedagogical design could improve equity. Based on the findings, suggestions for future research and practice in this field are discussed in terms of operationalizing and assessing CT in STEM contexts, instructional strategies for integrating CT in STEM, and research for broadening participation in integrated CT and STEM education.
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... In this context, LLM- 16 based GenAI serves as a medium that enables users to program computers using natural language, 17 allowing them to generate desired responses without mastering the syntax rules and semantics of 18 traditional programming languages (Reynolds & McDonell, 2021). By integrating LLM-based 19 GenAI into CT education, learning becomes more interactive through question-and-answer 20 sessions, which was suggested to be highly effective for employing NLP (Capindale & Crawford, 21 1990). For instance, a study by Yilmaz and Yilmaz (2023) evaluated the impact of supported Java programming education on university students' CT development. ...
... For example, the pupils prompt ChatGPT to outline a digital book project, 18 including specific sections, such as the welcome page, the local landmarks and the community 19 figures. To further make the project personally meaningful, the pupils prompt ChatGPT to 20 include a dedicated section about their local football pitch where they play Gaelic football daily. ...
... The process demonstrates the application of abstraction, 21 algorithmic thinking, decomposition, debugging, generalisation and iteration as the pupils adapt a peer's insight to iteratively and logically refine their work and divide the landmark section into 1 two interrelated subsections, with two team members working on each subsection. learners to make decisions about their prompts and how they incorporate feedback from AI, 20 peers, and teachers. Together, these principles co-create a systematic approach to support CT ...
The advancement of large language model-based generative artificial intelligence (LLM-based GenAI) has sparked significant interest in its potential to address challenges in computational thinking (CT) education. CT, a critical problem-solving approach in the digital age, encompasses elements such as abstraction, iteration, and generalisation. However, its abstract nature often poses barriers to meaningful teaching and learning. This paper proposes a constructionist prompting framework that leverages LLM-based GenAI to foster CT development through natural language programming and prompt engineering. By engaging learners in crafting and refining prompts, the framework aligns CT elements with five prompting principles, enabling learners to apply and develop CT in contextual and organic ways. A three-phase workshop is proposed to integrate the framework into teacher education, equipping future teachers to support learners in developing CT through interactions with LLM-based GenAI. The paper concludes by exploring the framework’s theoretical, practical, and social implications, advocating for its implementation and validation.
... The developing body of research and curriculum integrating science and CT leverages CT for problem solving and computational modeling (Wang, Shen, and Chao 2022;Ogegbo and Ramnarain 2022). The vast majority of these integrations utilize programming and computers to teach CT, presenting a barrier for schools without reliable access to computers (Rogers 2000). ...
... While computational modeling has been implemented in science education contexts (Arastoopour Irgens et al. 2020;Buckley et al. 2004;Klopfer 2003;Schwarz, Meyer, and Sharma 2007;Saba, Hel-Or, and Levy 2023;Sengupta et al. 2013;White and Frederiksen 1998;Wilensky and Reisman 2006;Wilkerson-Jerde, Wagh, and Wilensky 2015), CT and science integration is still growing, resulting in a shortage of empirical investigations, especially for CT practices beyond programming and computational modeling (Ogegbo and Ramnarain 2022;Wang, Shen, and Chao 2022). Extensive reviews of science and CT interventions identify trends in the literature: (1) the majority of CT and science integrations are within programming contexts; (2) most integrations focus on problem solving, computational modeling, and automation with algorithms and programming; (3) there are insufficient empirical investigations of CT and science integration; and (4) There are few definitions and assessments of integrated CT and STEM (Hsu, Chang, and Hung 2018;Lockwood and Mooney 2017;Ogegbo and Ramnarain 2022;Wang, Shen, and Chao 2022). ...
... While computational modeling has been implemented in science education contexts (Arastoopour Irgens et al. 2020;Buckley et al. 2004;Klopfer 2003;Schwarz, Meyer, and Sharma 2007;Saba, Hel-Or, and Levy 2023;Sengupta et al. 2013;White and Frederiksen 1998;Wilensky and Reisman 2006;Wilkerson-Jerde, Wagh, and Wilensky 2015), CT and science integration is still growing, resulting in a shortage of empirical investigations, especially for CT practices beyond programming and computational modeling (Ogegbo and Ramnarain 2022;Wang, Shen, and Chao 2022). Extensive reviews of science and CT interventions identify trends in the literature: (1) the majority of CT and science integrations are within programming contexts; (2) most integrations focus on problem solving, computational modeling, and automation with algorithms and programming; (3) there are insufficient empirical investigations of CT and science integration; and (4) There are few definitions and assessments of integrated CT and STEM (Hsu, Chang, and Hung 2018;Lockwood and Mooney 2017;Ogegbo and Ramnarain 2022;Wang, Shen, and Chao 2022). The emerging empirical literature provides initial grounds for CT and science integration. ...
Computational thinking (CT) is becoming increasingly important for K‐12 science education, thus warranting new integrations of CT and science content. This intervention study integrated CT through unplugged, or handwritten, algorithmic explanations of natural selection. As students investigated natural selection in varying contexts (specific and context‐general), students created explanations based on evidence of natural selection by using algorithm concepts and engaging in CT practices. Students' CT learning over time was analyzed through algorithmic explanations created during the unit. Research questions guiding the investigation were: (1) How do students learn CT over the course of a CT and science integrated unit? (2) What are students' perspectives of learning CT in an integrated unit? (3) How do students come to think about CT and its applications? Students' CT competencies significantly increased from pre‐ to post‐unit. Students indicated creating algorithmic explanations helped them learn natural selection and develop CT competencies. At the end of the unit, students recognized the universal application of CT as a way to logically and clearly explain processes. Implications of this work are that CT can be used as a science practice that helps students simultaneously learn science and CT practice competencies. Moreover, these student learning outcomes can be achieved with unplugged, or computer‐free, CT.
... Mathematics and science literacy plays an important role in students' computational thinking (CT) development (Lockwood & Mooney, 2018;Weintrop et al., 2016). CT is an essential skill that must be possessed in the 21st century (Ansori, 2020; Masfingatin & Maharani, 2019;Shute et al., 2017) because it can prepare students to adapt to an increasingly digital and technology-based world (Grover, 2021) and offers systematic methods for solving increasingly complex problems (Wang et al., 2022;Yadav et al., 2016). 10594 CT is a thinking process involving solving problems using available data to represent the resulting solution logically, efficiently, and effectively (Wing, 2006). ...
... This finding is in line with the research of (Wang et al., 2022), which states that CT-based learning can improve students' ability to break down problems into smaller parts, recognize patterns, and design logical solutions. In addition, Yadav et al., (2016) study also confirmed that the CT-based approach provides a systematic framework that helps students develop higher-order thinking skills. ...
... In contrast, although the level of achievement in school A was lower, an increase in learning outcomes was still seen. This finding supports the research of Wang et al., (2022), which shows that students from less supportive backgrounds can still experience increased CT abilities through appropriate learning design. However, the lack of exposure to technology-based learning and the lack of supporting facilities are obstacles that need to be considered. ...
The results of PISA 2022 show that Indonesian students are still weak in science literacy, mathematics, and technology-based problem solving, which are the basis for developing computational thinking (CT) skills. CT includes four primary indicators: decomposition to break down significant problems into smaller parts, pattern recognition to find similarities in data, abstraction to filter out irrelevant information, and algorithms to design systematic steps in solving problems. There are many ways to train CT, so this study uses block programming and the Quarky robot. This approach was chosen because it is visual and interactive and makes it easier to apply CT concepts practically, making it suitable for building 21st-century skills. The study was conducted in two high schools in Banda Aceh, involving 20 students from school A and 26 students from school B. Students were divided into two study groups in each school. Learning activities were designed based on STEMC in the form of Student Worksheets (LKPD), which include interactive learning scenarios, block programming challenges, and exploration of the Quarky robot's functions to solve real problems. The activities were arranged in stages, from a basic introduction to applying CT concepts in solving complex problems. The results showed a significant increase in students' CT abilities, especially in the algorithm indicator. Although both schools progressed, school B recorded higher growth, with better pre-test and post-test results than school A. This shows that block programming-based learning and Quarky robots effectively improve CT skills, which is essential in 21st-century education
... While there is growing consensus on the definition of CT, how it should be integrated with other topics is still undefined. Yet, its integration into science is growing (reviewed in Wang et al., 2022). The taxonomy of CT practices for science and mathematics outlines a framework that specifically outlines the CT practices that are used in service of mathematics and science (Weintrop et al., 2016). ...
... Supporting teacher learning about equitable teaching is essential for achieving equity goals, yet most of the literature focuses on student outcomes, especially in the field of CT and STEM integration (Wang et al., 2022). In addition to challenges supporting teacher learning about equitable practice and culture, there are challenges supporting teacher learning about computer science and CT. ...
... Others, including ourselves in our prior work, have developed professional development programs to support teacher learning about CT and how to integrate it into science (Cabrera et al., 2024;Coenraad et al., 2022;Hestness et al., 2018;Kelter et al., 2021;Kite & Park, 2024;Peters-Burton et al., 2023;Wu et al., 2022). While these programs have been successful, more work is needed to fully understand how to support teachers with integrating and teaching CT in diverse contexts (Angeli & Giannakos, 2020;Barr & Stephenson, 2011;Wang et al., 2022;Yadav et al., 2014Yadav et al., , 2017). ...
Increasing access to computational ideas and practices is one important reason to integrate computational thinking (CT) in science classrooms. While integrating CT into science classrooms broadens exposure to computing, it may not be enough to ensure equitable participation in the science classroom. Equitable participation is crucial because providing students with an environment in which they are able to fully engage and participate in science and computing practices empowers students to learn and continue pursuing CT and science. To foreground equitable participation in CT-integrated curricula, we undertook a research project in which researchers and teachers examined teacher conceptualizations of equitable participation and how teachers design for equitable participation by modifying a lesson that introduces computational modeling in science. The following research questions guided the study: (1) What are
... In light of these considerations, there is a growing tendency to incorporate computer science (and thus, Computational Thinking) into disciplinary education, particularly in the domains of science and mathematics [7][8][9]. This approach is motivated by the recognition that these fields can offer valuable opportunities for CT learning [10,11]. ...
... However, the integration of CT into these disciplines remains a complex issue, as numerous practical challenges remain to be explored. These include the identification of effective activities and approaches, as well as the development of assessment strategies that are appropriate within the new context [9,12]. ...
... The conventional gender role may play a significant role in shaping attitudes towards technology. However, this can be effectively modified under the appropriate conditions [4,9]. ...
In the contemporary era, Computational Thinking has emerged as a crucial skill for individuals to possess in order to thrive in the 21st century. In this context, there is a need to develop a methodology for cultivating these skills within a science and mathematics content education framework, particularly among pre-service teachers. This study aimed to investigate the impact of Educational Robotics on the development of Computational Thinking skills, with a particular focus on the role of gender, through a scientific and mathematical content teaching approach. A pre-experimental design with a quantitative approach was employed, and it was implemented with a total of 116 pre-service teachers, 38 males and 78 females. The results demonstrated a notable enhancement between the pre-test (8.11) and post-test (9.63) scores, emphasising specific concepts such as simple functions, while, and compound conditional. With respect to gender, statistically significant differences were identified prior to the intervention, but not following its implementation. The high level of Computational Thinking exhibited by both genders was comparable (53.85% in females and 55.26% in males) following the intervention. This indicates that the intervention is a promising approach for enhancing Computational Thinking proficiency, independent of gender and initial proficiency levels. The implementation of Educational Robotics in the teaching of science and mathematics enables the enhancement of Computational Thinking abilities among pre-service teachers, while reducing the observed gender disparity in this area of skill development.
... According to Wang et al. (2022), Computational Thinking (CT) is emerging as a key skill within STEM education, integral for tackling complex, technology-driven problems. Logical reasoning, decomposition, and pattern detection are all part of CT (Sands et al., 2018), equipping students to tackle classroom and real-world problems methodically (Zhang et al., 2024). ...
... Computational thinking (CT), which gives students the problem-solving skills necessary for success in an increasingly complex society (Wang et al., 2022), is becoming more and more acknowledged as a critical competency in 21st-century education (Nouri et al., 2020). Fundamentally, Moschella and Basso (2020) claim that CT consists of several interrelated abilities: logical reasoning, which enables students to interpret information rationally; decomposition, which simplifies the process of solving complicated problems; and pattern recognition, which allows students to extrapolate and apply knowledge to related issues in the future. ...
This study examined the relationship between student motivation and computational thinking (CT) skills within a Scratch-based learning environment for primary school students. Utilizing a quantitative research design with a pretest-posttest framework, the research involved 28 primary school students engaged in a computational learning program centered on the Jumping Bean concept. A confusion matrix analysis was employed to assess the predictive relationship between motivation levels and improvements in CT skills. The results showed that motivation is a reliable predictor of CT gains, with high precision indicating that highly motivated students are very likely to demonstrate measurable progress. However, the recall score suggests motivation alone is not a conclusive factor, as some motivated students did not achieve the expected CT improvements. This implies that other instructional elements, such as prior knowledge, cognitive differences, teaching methods, and learning design, also significantly impact outcomes. The implications of this research suggest that educators should cultivate motivating learning environments to foster students’ CT skills effectively. Recommendations include integrating gamified elements and personalized feedback to enhance student engagement and motivation in computational learning contexts.
... 11). STEM education has the goal of enhancing employability and practical skills development; it emphasizes a broad understanding of scientific and technical disciplines, spans various educational levels, and is offered in both theoretical and practical contexts (Wang et al., 2022). STEM programs are also designed to foster innovation, critical thinking, and creativity. ...
... STEM education is designed so that learners acquire the knowledge, skills, attitudes, and behaviors to make informed decisions toward meaningful engagement in inclusive and sustainable societies (UNESCO, 2017). Integrating CT in STEM enhances students' capacity to apply computational approaches to scientific and technical problems, thus preparing them for careers that require advanced technical skills (Wang et al., 2022). For example, integrating CT into high school mathematics classes has significantly enhanced students' problem-solving skills and engagement. ...
The knowledge society exists mainly due to advancing technology and the exponential development of professionals’ capabilities. Digital transformation and new technologies generate complex environments demanding high-level skills. This work analyzes the current state of pedagogical approaches with a special focus on project-based learning that develops computational thinking in STEM students. A Systematic Literature Review examined the current state of pedagogical approaches along with project-based learning aimed at enhancing computational thinking within the context of higher education. Results allowed us to infer that (a) computational thinking promotes sustainable development through STEM education and novel teaching practices; (b) it is a fundamental skill for the problem-solving processes that evolve with technological progress; (c) its development is a global concern, not limited to a country’s development level; and (d) its introduction at an early stage provides opportunities for the advancement of vulnerable groups. Outlining, this study conducts a Systematic Literature Review (SLR) using PRISMA 2020 guidelines to analyze pedagogical approaches including project-based learning for enhancing computational thinking in STEM higher education, identifying global research trends, common strategies, and areas for improvement, while proposing a framework to align computational thinking skills with emerging technological challenges and promote sustainable educational practices. This study presents relevant results on the construction of state-of-the-art computational thinking and education; it is valuable for curricular design underpinning disciplinary and interdisciplinary approaches.
... As technology advances to meet social needs, computational thinking (CT) has emerged as a critical competency for the twenty-first century, with a growing recognition of its importance in science, technology, engineering, and mathematics (STEM) fields (Wang et al., 2022). Wing (2006) emphasized CT as a set of skills encompassing problem-solving, designing systems, and understanding human behaviors. ...
... Recognizing these challenges, the educational research has turned its focus toward innovative teaching methodologies that promise to better cultivate CT skills (Fang et al., 2022;Hsu et al., 2018;Lin et al., 2021). A review of literature by Wang et al. (2022) revealed a prevailing trend in the STEM field regarding the adoption of a problem-based instructional model for cultivating CT skills among students. Lyon and Magana (2020) emphasized the dominance of STEM disciplines in studies 1. ...
Teaching computational thinking skills to novice college students via programming poses considerable challenges. It involves learning programming language syntax and commands, along with fostering higher-order skills crucial for both computational thinking proficiency and future careers. To address this, we proposed a pedagogical approach integrating project-based learning with self-regulated learning in a C programming course. Guided by the higher-order computational thinking framework, this quasi-experimental study enrolled 173 students divided into three groups, a group with project-based learning design alone, a group with both project-based learning design and self-regulated learning scaffolding, and a control group with traditional teacher centered teaching. One-way analysis of covariance results showed the group with both project-based learning design and self-regulated learning scaffolding presented the most advancement of problem-solving and metacognitive skills. Paired samples t-tests showed this group also displayed the most significant improvements in computational thinking tendency and other higher-order skills. While the students’ cognitive knowledge gain in the group with both pedagogical supports didn't surpass students of the control group, it did outperform students from the group with project-based learning design alone. Overall, our findings supported the effectiveness of this integrated method in boosting computational thinking and other higher-order skills in novice programming students. This warranted further research to refine and enhance the proposed pedagogical strategy.
... This environment can accelerate the acquisition of knowledge and provides students with a sense of achievement (Ke et al., 2019). Thus, students can achieve the objectives of the courses by designing their own games (Kapp, 2012;Wang et al., 2022). ...
... Likewise, in the elaboration phases, students had opportunities to apply their learning into practice by designing games; they were asked to dream and design their own games related to the subjects. As previous researches (Kapp, 2012;Puttick et al., 2024;Wang et al., 2022) stated, game design activities have been promising contexts for supporting gifted learners. Consistent with the idea of the Puttick et al. (2024), learning through building game in constructivist environment led students choose their pathways through learning experiences. ...
Coding and digital game design activities have been used in recent years to contribute to students' academic achievement and twenty-first century skills. This study aimed to investigate the effect of the 5E model enriched with coding and digital game design activities (5EECD) on gifted students' academic achievement and problem-solving skills. A quasi-experimental design with pre-test post-test control group was used in the research. The sample of the study consists of 80 3rd grade gifted primary school students studying at a Science and Art Center affiliated to the Ministry of National Education in Türkiye. The study was completed in a five-week treatment period. The experimental group studied the force and motion concept with the 5EECD and the control group studied it with the proposed conventional method. Academic Achievement Test and Problem-Solving Skills Scale were used as pre and post-tests as measuring tools. The data were analyzed by descriptive and inferential statistics. The descriptive statistics results revealed that the experimental group students showed higher performances in science achievement and problem-solving skills. Inferentially, MANCOVA results showed that the 5EECD had a statistically significant effect on the collective dependent variables of the academic achievement and problem-solving skills. The ANCOVA findings also supported the above outcomes and it indicated that each of the academic achievement and problem-solving skills of experimental group was significantly higher than those of the control group. Therefore, the findings of the current research suggest that the 5EECD would be used for 3rd grade gifted students’ science education.
... Keterampilan ini tidak hanya relevan dalam bidang ilmu komputer, tetapi juga dalam berbagai disiplin ilmu lainnya (Cuny, et al., 2011;Wing, 2006;Grover & Pea, 2013). Untuk mengintegrasikan berpikir komputasi dalam media ajar digital, guru dapat: 1) memilih perangkat lunak yang tepat; 2) merancang aktivitas pembelajaran yang menarik; 3) memberikan umpan balik yang konstruktif; 4) membangun komunitas belajar (Chan, et al., 2021;Acevedo-Borrega, et al., 2022;Wang, et al., 2022;McCormick & Hall, 2021). Integrasi berpikir komputasi dalam media ajar digital merupakan langkah penting untuk guru dalam mempersiapkan siswa menghadapi tantangan di masa depan. ...
... Berpikir komputasi ini bermanfaat pada bidang sains dan teknologi, bidang rekayasa, bisnis dan ekonomi, pendidikan bahkan dalam bidang kehidupan sehari-hari (Chan, et al., 2021;Acevedo-Borrega, et al., 2022;Wang, et al., 2022;McCormick & Hall, 2021). Pemateri juga menyatakan bahwa terdapat tantangan dan peluang di era Teknologi di zaman sekarang ini. ...
Pelatihan integrasi berpikir komputasi dalam media ajar digital bertujuan untuk meningkatkan kemampuan pendidik dalam mengembangkan bahan ajar yang inovatif dan relevan dengan kebutuhan pembelajaran abad ke-21. Berpikir komputasi, yang mencakup keterampilan seperti dekomposisi, pengenalan pola, abstraksi, dan algoritma, merupakan pendekatan penting untuk memecahkan masalah secara sistematis. Pelatihan ini dirancang untuk membekali pendidik dengan pengetahuan dan keterampilan dalam mengintegrasikan prinsip-prinsip berpikir komputasi ke dalam media ajar digital interaktif, seperti modul pembelajaran, video, atau aplikasi berbasis teknologi. Metode pelatihan meliputi sesi teori, praktik langsung, dan diskusi kelompok untuk menghasilkan produk media ajar yang dapat diterapkan di kelas. Hasil dari pelatihan menunjukkan bahwa peserta mengalami peningkatan pemahaman tentang konsep berpikir komputasi dan mampu mengimplementasikannya dalam media ajar digital yang sesuai dengan mata pelajaran masing-masing. Pelatihan ini diharapkan dapat memberikan kontribusi dalam meningkatkan kualitas pembelajaran, mendorong inovasi pendidikan, serta mempersiapkan peserta didik untuk menghadapi tantangan era digital.
... Реализация инженерной направленности элективного курса опирается на образовательную концепцию STEM, оправдавшую себя в международной практике инженерного образования [10][11][12][13], и использование специальных технологий, включая BYOD [14]. ...
... AI serves as a translator, connecting teachers to all students, even those who speak a different language in a multi-lingual and varied learning environment. Over the years, language has always been a major obstacle to achieve global education, but with AI technology, the barriers of education are breaking down with cross-lingual learning and multilanguage support (Wang et al., 2022). With AI-based translation tools, students and educators can access content translated into multiple languages, promoting inclusivity in diverse classrooms and international learning environments. ...
By leveraging AI-driven solutions, students also have the ability to adjust learning based on personal preference, with unique content that both improves understanding and boosts interest. Virtual tutors, interactive simulations, and smart assessments allow students to learn at their own pace and get real-time feedback. AI-enabled data analytics tools can spot skill gaps and forecast the likelihood of students that feed back into their re-evaluated teaching and streamline to boost success in the classrooms. AI collaborative platforms create a shared worldwide ecosystem for learning having students from all walks of life. Administrative aspects of teaching like grading and curriculum development are streamlined through automation, enabling educators with more bandwidth for mentorship and innovation. AI-assisting technologies are thus building blocks of a better educational system, with equitable, efficient, and future-proof learning developed by bridging the entry gaps.
... Their research primarily concentrated on fostering computational thinking skills. Wang et al. (2022) highlighted the need for further investigation into instructional strategies for integrating CT in STEM education. Additionally, ...
Background
Virtual laboratories are used to supplement or even replace physical laboratories in engineering education. Although these virtual laboratories allow students to learn foundational experimental skills, they do not provide the learners with the chance to develop higher‐order thinking skills (HOTS). Computational thinking (CT) is an approach to problem‐solving. Incorporating the CT approach into virtual laboratories to enhance problem‐solving skills and critical thinking skills is still understudied.
Objectives
This study investigated the effect of incorporating the CT approach into virtual laboratories on the learning motivation, engagement, and HOTS of students.
Methods
A quasi‐experimental study was conducted to investigate the impact of the proposed approach. Forty‐eight undergraduate electrical engineering students participated in this study. Pre‐ and post‐test questionnaire data on learning motivation, engagement, and HOTS were collected from both an experimental group that utilised virtual laboratories and a computational thinking approach and a control group that used virtual laboratories only.
Results and Conclusions
The result of the quantitative analysis revealed that incorporating the CT approach into virtual laboratories resulted in a significant difference in learning motivation, engagement, and HOTS between the experimental and control groups. These findings point out that incorporating the CT approach into virtual laboratories positively affects the learning motivation, engagement, and HOTS of learners who are enrolled in practical courses.
... Students' performance can be enhanced in programming classes by CT skills (Agbo et al., 2019), this implies that CT makes understanding of programming easier. Robotic tools have also been used to teach and enhance the learning of CT (Jormanainen & Tukiainen, 2020), In addition, Wang et al. (2022) revealed that CT practices have the potential to enhance the interest of students in learning other fields, particularly in STEM. CT can also be used to enhance student problemsolving skills. ...
The need to integrate the teaching and learning of computational thinking (CT) in K-12 education has been on the rise since it was identified as a skill for solving 21st-century problems. The co-design pedagogical approach has shown great potential in promoting effective communication of CT to both university and K-12 students with the support of different educational tools in different contexts. To ensure Nigerian secondary school (K-12) students develop CT skills, a four-day co-design CT activities workshop was organized. Co-design pedagogy and constructivism theory were deployed in this study with students co-designing COVID-19 disease spread game for learning CT. A mixed method was adopted to investigate student’s interest, attitudes, understanding of CT, and their learning experience from implementing CT-based prototype using Scratch. This study recruited 40 students from two different secondary schools in Nigeria as participants. The result revealed that student’s interest in learning CT was aroused through the use of co-design pedagogy and Scratch (μ = 4.55, σ = 0.815). Similarly, students attitude toward CT after the intervention study shows positive (μ = 4.50, σ = 0.716). This study paved way for student’s skills development in teamwork and collaborative learning, communication, idea sharing, personal skill development, game design, and understanding of programming. This study instigates thinking ideation, inspires the application of CT concepts in daily life activities, and improves problem-solving skills. This study promotes and advocates for the application of co-design pedagogy to foster the teaching and learning of CT in a Nigerian context. This study contributes to knowledge by promoting the use of Scratch as a tool for co-designing in learning CT, proposing a four-phase co-design application flow for the integration of co-design pedagogy with Scratch for learning CT in the Nigerian K-12 context and suggesting ways to implement the teaching and learning of CT in K-12 education.
... For example, some studies proposed a framework to facilitate problem-solving in STEM learning (Priemer et al., 2019) or investigated students' problem-solving skills in engineering design or maker-centred contexts (e.g., Chen & Lin, 2019;Yu et al., 2015). Other studies explored the relationships between STEM programs and students' development of computational thinking (Wang et al., 2022) or creativity (e.g., Chung et al., 2017;Davies & Gilbert, 2003). The assessments on the affective domain include but are not limited to, students' interests towards STEM (Mohd Shahali et al., 2016), self-efficacy (Musavi et al., 2018), and attitudes towards STEM majors and careers (Lin et al., 2020;Nugent et al., 2015). ...
Background
Given that limited well-developed instruments are available to assess students’ transdisciplinary STEM practices (T-STEMP), this study aims to develop and validate an instrument for examining secondary students’ T-STEMP competence. According to the T-STEMP assessment framework proposed in our previous study, we developed items and validated the items using Bayesian structural equation modeling (BSEM) and item response theory (IRT).
Results
First, the structure of T-STEMP has been justified, that the four design phases are related to a common third-order factor: knowledge-based reasoning and each design phase is composed of three key design challenges. The goodness of fit indices indicated that a two-parameter logistic (2PL) graded response model could fit the data well. The discrimination parameters indicated that most of the items for different grades performed well in distinguishing between students with various ability levels. The Cronbach’s alpha also indicated that the instrument had good reliability in terms of internal consistency.
Conclusions
The model of one third-order factor with four second-order factors and 12 first-order factors was justified as the fitted model representing the structure of the T-STEMP instrument. It means that the four design phases are related to knowledge-based reasoning and each design phase is composed of three key design challenges. The IRT findings show that Taiwanese students may have basic T-STEMP competence, but the breadth and depth of their responses to the key design challenges need to be advanced. Implications for further studies and suggestions for STEM teaching are also provided.
... Teachers' professional development plays a crucial role in integrating CT into their teaching (Mumcu et al., 2023;Wang et al., 2022). Drawing from self-efficacy theory (Bandura, 1977), we argue that teachers' value beliefs and self-efficacy are key drivers in how successfully they implement CT and programming in their classrooms. ...
Many education policy strategy documents at the European Union level, as well as national strategies of various countries, recommend including computational thinking as a fundamental skill in curricula. The professional development of teachers should be supported to disseminate computational thinking in K12 education. Teachers’ value beliefs about computer science and programming should be first known when designing professional development programs. This study aims twofold. The first is to adapt the Teacher Beliefs about Coding and Computational Thinking (TBaCCT) Scale into Turkish. The second is to explore Turkish primary and secondary school teachers' value beliefs about computational thinking and programming. The study involved 417 teachers. Confirmatory factor analysis was used for the validity studies of the scale. Independent samples t-test, one-way ANOVA, and MANOVA analysis were used to examine whether the scores differed according to gender and subject, respectively. The findings show that the Turkish form of the TBaCCT Scale is valid and reliable. For programming self-efficacy and teaching programming efficacy, there is a significant difference between male and female teachers, computer science teachers and other subjects, and elementary mathematics, class and science teachers and other teachers. Teachers working in social sciences especially need professional development programs that will transform their beliefs and knowledge about computational thinking.
... The significant increase in abstraction skills indicates that students in the experimental group developed the ability to simplify abstract physics concepts into more comprehensible representations. Previous research on the integration of computational thinking in STEM education supports these findings, highlighting that STEM-based multimedia approaches markedly improve students' computational thinking abilities (Wang et al., 2022). This is further corroborated by interview results showing that students found it easier to grasp physics concepts when presented in the context of Islamic literacy. ...
This study aims to evaluate the effectiveness of Islamic literacy-based STEM (Science, Technology, Engineering, and Mathematics) multimedia in enhancing students' computational thinking skills in a basic physics practicum course. The research employed a quasi-experimental design with a mixed-methods approach, involving two groups: an experimental group that received instruction through Islamic literacy-based STEM multimedia and a control group that used conventional methods. The instruments used included a computational thinking skills test, designed to measure four primary indicators: abstraction, algorithm, decomposition, and pattern generalization, as well as in-depth interviews to explore students' learning experiences. Quantitative data were analyzed using a t-test to determine significant differences between the two groups, while qualitative data were analyzed thematically. The findings indicated a significant improvement across all computational thinking indicators in the experimental group. Qualitative analysis further revealed that integrating Islamic literacy deepened students' understanding of physics concepts, offering a spiritual context that enriched their learning experiences. These findings suggest that Islamic literacy-based STEM multimedia is not only effective in enhancing computational thinking skills but is also well-suited for educational contexts that integrate technology and spirituality. The implications of this study support the development of a holistic curriculum in STEM education aligned with spiritual values. Abstrak: Penelitian ini bertujuan untuk mengukur efektivitas multimedia STEM (Science, Technology, Engineering, and Mathematics) berbasis literasi Islam dalam meningkatkan kemampuan berpikir komputasional mahasiswa pada mata kuliah praktikum fisika dasar. Penelitian ini menggunakan metode kuasi-eksperimental dengan pendekatan mixed methods, melibatkan dua kelompok: kelompok eksperimen yang mendapatkan pembelajaran menggunakan multimedia STEM berbasis literasi Islam, dan kelompok kontrol yang menggunakan metode konvensional. Instrumen yang digunakan meliputi tes kemampuan berpikir komputasional untuk mengukur empat indikator utama yaitu abstraksi, algoritma, dekomposisi, dan generalisasi pola, serta wawancara mendalam untuk mendalami pengalaman belajar mahasiswa. Data kuantitatif dianalisis menggunakan uji t-test untuk melihat perbedaan signifikan antara kedua kelompok, sementara data kualitatif dianalisis menggunakan analisis tematik. Hasil penelitian menunjukkan peningkatan signifikan pada semua indikator berpikir komputasional dalam kelompok eksperimen. Analisis kualitatif juga mengungkapkan bahwa integrasi literasi Islam memperdalam pemahaman mahasiswa terhadap konsep-konsep fisika, memberikan konteks spiritual yang memperkaya pengalaman belajar. Temuan ini mengindikasikan bahwa pendekatan multimedia STEM berbasis literasi Islam tidak hanya
... Teaching CT in schools is based on computer science courses (Grover & Pea, 2013). However, since these courses are generally not mandatory, most students do not have sufficient opportunities to learn CT (Wang et al., 2022). On the other hand, more students may have the opportunity to learn CT in more widely offered courses such as science and mathematics (Weintrop et al., 2016). ...
Computational thinking (CT) has gained more value for individuals in a world reshaped by digital transformation in the last decade. Therefore, educators and researchers are trying to integrate CT into teaching practices. Efforts to teach CT are increasing, especially in basic courses widely included in school curricula. The focus of this study is the integration of CT into science teaching in the flipped classroom model. In this context, the effects of flipped computational science laboratory (Flipped-CSL) activities carried out with teacher candidates on CT skills, laboratory entrepreneurship, and attitude were investigated. An intertwined mixed research design, in which quantitative and qualitative data were evaluated together, was used in the study. Findings showed that flipped-CSL activities were effective for teacher candidates and improved their CT skills, laboratory entrepreneurship, and attitudes significantly and positively. The results of this study include the practical use of flipped-CSL activities when planning laboratory activities for school science subjects to improve CT skills. Implications for using of flipped-CSL activities in science education were discussed, and suggestions were made regarding the results.
... Gap analysis between previous studies conducted by Wang et al.,[41] tend to provide a general overview of the various approaches and challenges in the integration of computational thinking in STEM education. The focus is on identifying broad trends, strategies, and research gaps. ...
Purpose of the study: The aim of this study is to explore the effectiveness of integrating Computational Thinking (CT) and Mathematical Modelling (MM) in STEM education to improve students’ understanding of mathematical concepts, problem-solving skills, and engagement in the learning process. Methodology: This study utilized a quasi-experimental method with pre-test and post-test design. The sample of this study consisted of 200 students, who were randomly selected from four high schools in the Jambi City and Muaro Jambi areas. Tools included a mathematics achievement test and a student engagement questionnaire. Data were analyzed using paired t-tests and independent t-tests with the aid of SPSS software. Main Findings: The integration of Computational Thinking and Mathematical Modelling significantly improved students' understanding of mathematical concepts, problem-solving skills, and engagement. The experimental group showed a notable increase in post-test scores and higher engagement levels compared to the control group. Novelty/Originality of this study: This study introduces a novel framework for integrating Computational Thinking and Mathematical Modelling in STEM education, highlighting its potential to enhance both cognitive and affective aspects of learning. It provides empirical evidence supporting the use of innovative approaches to advance mathematics education.
... Students showed higher self-confidence in solving complex problems through the computational thinking programs, which increased their likelihood of choosing a STEM major [125]. Furthermore, computational thinking is strongly correlated with real-world applications in STEM fields, further driving students' interest in majoring in STEM [126]. The integration of computational thinking and interdisciplinary STEM learning can help students integrate what they have learned to understand and apply STEM knowledge [127,128]. ...
Faced with a shortage of college graduates with STEM degrees, many countries are seeking ways to attract more high school students to pursue STEM majors after graduation. This study aims to promote the sustainability of high school students in STEM fields by analyzing the effects of digital competence on the STEM major intentions of high school students. The survey collected data from 2415 participants comprising 1230 females and 1185 males from 16 high schools in China. Using hierarchical logistic regression, the study found that digital competence had significant positive effects on high school students’ STEM major intention. Also, computational thinking was the strongest predictor among the four areas of digital competence. Moreover, latent profile analysis identified two profiles of male students and four profiles of female students. Among male students, advanced male users had the strongest STEM major intention; among female students, low-level female novices had the weakest STEM major intention. Thus, digital competence can be considered an effective way to bridge the gender gap in STEM major selection. Based on the findings, strategies are discussed for improving high school students’ STEM major intentions and promoting digital competence, thereby ensuring the sustainable development of students in STEM fields in the digital era.
... Female students remain severely underrepresented in many STEM disciplines, including programming (Leonard et al., 2021), due to a lack of access to learning opportunities to develop and sustain interest in STEM (Hill et al., 2010). A review study (Wang et al., 2021) examined existing literature on integrating computational thinking and discussed gender and other equity issues in CT. Their review showed that females had lower levels of interest and confidence in computational thinking. ...
Aiming to promote equity in computing, this study proposes an educational model that offers an alternative approach to inspire K-12 students to become interested in CS and develop their computational thinking (CT) skills. It also examines the experience of marginalized students during the COVID pandemic in a learning environment grounded in the model. Adopting a mixed methods case study, this work focused on the experience of 82 girls enrolled in a free after school program. The results show that access to the opportunities is critical to promote equity. The experience allows the underrepresented population, i.e. the girls, to gain deepened understanding of not only CT/CS, but also other topics like work ethics, digital citizenship, and how to work with peers to achieve goals. The girls have also broadened their views of computing related fields by working on meaningful projects that demonstrated the value of abstract concepts of coding and programming. A combination of human facilitators and well-constructed tutorials has the potential of improving girls’ self-study skills and preparing them to become more independent learners.
... Furthermore, the integration of computer science and computational thinking within the STEM framework has been emphasized as a crucial component for preparing teachers and students for future academic and professional challenges in the digital age (Mallik & Mallik, 2019;.Coding as an integral part of computer science education, plays a pivotal role in fostering computational thinking (CT) skills among students (Blackley & Howell, 2019;Mecca et al., 2021). CT involves problem-solving processes that are essential for computer science and can be applied to other disciplines as well (Li et al., 2020;Wang et al., 2021). The introduction of coding in the curriculum not only equips students with tools for digital expression but also lays the foundation for understanding complex computational concepts (Noraini Lapawi & Hazrati Husnin, 2020). ...
The rapid evolution of educational paradigms has led to the emergence of Next Generation Learning Spaces (NGLS), which are designed to foster collaborative, student-centered learning experiences. Central to this paradigm shift is the integration of Science, Technology, Engineering, and Mathematics (STEM) education, which emphasizes interdisciplinary learning and real-world applications. This study aimed to explore the specific needs of teachers in relation to the features of the Magnetcode Coding Module, and how it can be optimized to enhance NGLS for STEM teachers. This study employed the Design and Development Research (DDR) approach and currently is at phase one: identifying the teachers' need for the coding module. A qualitative research design was employed in phase one, utilizing semi-structured interviews with three STEM educators to gather in-depth insights. Purposive sampling was used to ensure that the participants were well-versed in the challenges and requirements of integrating coding modules into STEM education. The findings indicated six broad themes namely; Skill development, Integration of computational and logical thinking, deep understanding of coding, Technological relevance, Practical integration, and real-world relevance. The findings reached a point of saturation, revealing a significant demand among teachers for a coding module that can serve as a guideline to bolster NGLS. Specifically, the results highlighted the importance of integrating STEM education in teaching and learning processes to fully realize the potential of NGLS. Thus, the Magnetcode Coding Module holds promise as a pivotal tool for STEM educators. By addressing the identified needs of teachers, it can play a crucial role to design and develop a coding module in enhancing the efficacy of NGLS, paving the way for a more holistic and integrated approach to STEM education.
... et al., 2023;Master et al., 2021;Mirakhur et al., 2024;Ross et al., 2020). To make sure all students have access to computer science, it can be integrated into core courses, such as science and math (Barr & Stephenson, 2011;Grover & Pea, 2013;Wang et al., 2022). This paper utilized this approach and focused on integrating computer science with high school biology through computational thinking (CT). ...
Evolution is a key biological concept, and natural selection is an important mechanism of evolution, but studies indicate students reason about natural selection differently based on organismal context. This paper investigates students’ explanations of natural selection in varying contexts after a computational thinking (CT)-central unit designed to scaffold natural selection transfer. The research questions address natural selection change, contextual differences in students’ explanations, and patterns of cooccurrences in students’ natural selection explanations. Students learned about natural selection through scaffolded transfer via Computational Thinking through Algorithmic Explanations (CT-AE), an unplugged instructional approach. The data source is students’ explanations of four pre- and post-unit natural selection scenarios about bacteria, mice, lilies, and mosquitos. This mixed methods study included nonparametric statistics to determine differences between contexts in post-unit explanations and Epistemic Network Analysis (ENA) to create and compare networks of co-occurrences in students’ explanations. There were significant differences between the four pre-unit scenario explanations, but the post-unit explanations displayed fewer differences. ENA analysis indicated that student responses for each scenario were not significantly different. These trends indicate students’ explanations of natural selection based on context varied less after the unit. These results suggest that the unit was successful in scaffolding transfer of natural selection context across contexts.
... Siswa juga siap dalam menyelesaikan masalah yang kompleks dan terbuka. Di beberapa negara, konsep CT sudah secara bertahap dimasukkan ke dalam kurikulum pendidikan di sekolah (Dagienė & Sentance, 2016;Mannila et al., 2014;Wang, et al., 2022). Berdasarkan hasil penelitian-penelitian sebelumnya, CT dapat meningkatkan penguasaan materi number sense dan kemampuan aritmatika (Sung et al., 2017) yang dipengaruhi oleh gaya berpikir, keberhasilan akademik dan sikap terhadap matematika (Durak & Saritepeci, 2018). ...
Penelitian ini bertujuan untuk mengetahui pengaruh pembelajaran berbantuan geogebra berbasis batik nusantara terhadap computational thinking siswa. Penelitian ini menggunakan metode Quasi Experiment Design dengan desain the non-equivalent grup design. Uji hipotesis menggunakan uji non parametrik Mann-Whitney U Test karena data tidak berdistribusi normal. Uji dilakukan dengan program IBM SPSS Statistic 25. Penelitian ini dilakukan di SMPN 8 Madiun pada 4-18 September 2023 dengan materi transformasi geometri. Populasi dalam penelitian ini adalah seluruh siswa kelas IX SMPN 8 Madiun yang berjumlah 219 siswa. Sampel diambil secara acak, diperoleh siswa kelas IX A berjumlah 26 sebagai kelas kontrol dan siswa kelas IX E berjumlah 23 sebagai kelas eksperimen. Instrumen penelitian ini adalah tes berpikir komputasi. Tes ini diperlukan untuk mengukur CT siswa dalam pembelajaran materi transformasi geometri setelah perlakuan diberikan. Sebelum instrumen diberikan dilakukan pembuktian validitas dan reliabilitas. Hasil penelitian menunjukan bahwa berdasarkan output “Test Statistics” dalam uji mann-whitney diperoleh bahwa nilai Asymp. Sig. (2-tailed) sebesar 0,000 lebih kecil dari < nilai probabilitas 0,05 maka Ho ditolak. Dengan demikian terdapat perbedaan hasil tes CT siswa antara kelas dengan pembelajaran berbantuan geogebra berbasis batik nusantara dan kelas konvensional dengan rata-rata kelas eksperimen sebesar 81,52 dan rata-rata nilai kelas konvensional sebesar 50,46. Karena ada perbedaan yang signifikan maka dapat disimpulkan terdapat pengaruh pembelajaran berbantuan geogebra berbasis batik nusantara terhadap CT siswa. Kata kunci: Geogebra, Transformasi geometri, Computational Thinking, Batik Nusantara
... Some systematic reviews have addressed topics such as the integration of CT in mathematics Barcelos et al. (2018); Chan et al. (2023); Irawan et al. (2024); Ye et al. (2023), statistics education Irawan et al. (2024), STEM education Wang et al. (2022), early childhood education Bati, 2022;Zeng et al. (2023), primary and secondary education Grover & Pea, 2013;Montiel & Gomez-Zermeño, 2021;Quiroz-Vallejo et al. (2021), higher education Lu et al. (2022); Lyon & J. Magana, (2020), computer science education Lee et al. (2022), learning and teaching CT Hsu et al. (2018), CT learning without the use of computers Kuo & Hsu (2020), mapping programming for a specific CT in high school students Tikva & Tambouris (2021), and CT learning using Scratch (Zhang & Nouri, 2019). However, no systematic review has been conducted on the use of programming to promote computational thinking. ...
This systematic research aims to provide a comprehensive overview of the development of analysis related to the use of programming in the development of Computational Thinking (CT), especially in the context of education from primary to tertiary levels. This study analyzed 88 articles from empirical studies related to the use of programming to develop CT sourced from the Scopus database. The analysis process followed the PRISMA 2020 guidelines and consisted of three stages: search, selection, and data analysis. Descriptive and thematic statistical approaches were used for data analysis. Instruments used in the selection of articles included Rayyan for screening based on inclusion criteria, as well as Microsoft Excel for coding and thematic analysis. The results showed that articles related to the use of programming to promote CT have appeared since 2011 but have increased significantly since 2016, with an annual growth rate of 17.6%. Most studies used quantitative approaches, followed by qualitative and mixed methods. Overall, 270 authors from 27 countries contributed to the study, with the United States having the highest number of publications. A total of 33 programming tools were identified, with Scratch being the most widely used tool, followed by Blockly, LEGO, Scratch Jr., Code.org, Python, Alice, App Inventor, Kodu, R, MakeCode, and Arduino. Scratch Jr. is most commonly used at the early childhood education level, while programming languages such as Python, R, and MATLAB are more commonly used in higher education. The implications of these findings suggest that the trend of using programming tools such as Scratch and Blockly has the potential to influence CT teaching strategies in the classroom, as well as the importance of using varied programming tools in efforts to integrate CT into the education curriculum.
... This has also been mentioned in a relatively recent review [12]. The integration of CT into curricula has also shown to be effective in STEM subjects in general, with game design-based instructional methods being one of the most popular ones [13]. Examples include the integration of MIT app inventor to teach mobile app development [14], and as a game-based classroom course for 3rd and 4th-grade students [15]. ...
Computational thinking skills are recognised as the
necessary 21st century competency among learners of various
levels. There is an increase in awareness on the potential
benefits of introducing computational thinking (CT) skills in the
school level curriculum. The existing solutions like block-based
activities, AR-VR apps, game-based learning solutions require
more relatable and authentic learning contexts. The present
study conducted with 49 middle school students (7th and 8th)
traces how an educational application called CT@Home can
be used to foster logical thinking and CT skills by providing
authentic learning experiences through a relevant context which
is meaningful to the learner. We investigated the effectiveness
of the application around three specific constructs: learning
gain, usability, and self-perception. The results suggest that
applications like CT@Home which can provide context-based
learning, helps in building a positive perception towards learning
CT skills among middle school students. Finally, we also discuss
some of the important challenges that students faced while
interacting with the CT@Home application.
... Acknowledging that one of the challenges in interdisciplinary collaboration derives from educators' different intentions for students' learning outcomes, which are anchored in disciplines and subject areas (Stentoft, 2017), the "FERTILE" Design Methodology introduces Computational Thinking (CT) skills (Wing, 2006) as the interdisciplinary learning's primary outcome. It leverages computer programming as a natural habitat for CT skills development (Yeni et al., 2023) and employs the popularity of ER as a motivational and engaging programming practice (Wang, Shen and Chao, 2022;Tzagkaraki, Papadakis and Kalogiannakis, 2021). Also, it exploits the dynamic of Arts as a discipline that has been reported to foster creativity and promote the cultivation of CT skills in recent years (Yeni et al., 2023). ...
The growing call to foster interdisciplinary learning has found educators struggling to co-design learning across disciplinary boundaries. Aiming to contribute to the area of interdisciplinary learning design, we explored how to support educators in co-designing interdisciplinary projects integrating Educational Robotics (ER) and Arts, hereafter called Artful ER projects. Our research included developing the "FERTILE" Learning Design methodology as a conceptual tool scaffolding the integration of discipline-oriented viewpoints while educators co-design. Acknowledging that one of the challenges in interdisciplinary collaboration derives from educators’ different intentions for students’ learning outcomes, the "FERTILE" methodology introduces Computational Thinking (CT) skills as an Artful ER project’s primary learning outcome. In this line, the “FERTILE” methodology adapts the Creative Computational problem-solving model, which has been reported to cultivate CT skills through its staged process. Furthermore, we developed the "FERTILE" Community Platform as an online environment providing two-fold support to educators as designers of interdisciplinary learning. The "FERTILE" Community Platform incorporates community functionalities that address collaboration practicalities while educators co-design. Additionally, it integrates authoring functionalities scaffolding educators in designing Artful ER projects based on the "FERTILE" Learning Design methodology. This paper explores how the authoring functionalities of the "FERTILE" Community Platform support educators in designing interdisciplinary learning. We report on a pilot study conducted with Greek and Spanish educators. In this study, we applied a mixed-method research design with a quantitative strand adopting indicators from the Usability Metric for User Experience (UMUX) model and a qualitative strand providing insights into participants’ perceptions. The findings indicate that scaffolding disciplinary elaboration (e.g., robot technical requirements and art forms) and systematising interdisciplinary context (e.g., through project categories) may trigger educators’ mutual understanding. The participants endorsed authoring functionalities that adopted high contextualisation levels for learning design representation to communicate their design ideas across disciplinary boundaries. Also, the participants valued CT skills as the primary outcome of interdisciplinary learning, indicating that CT skills’ cultivation may be the broker among disciplines and trigger educators to overcome disciplinary barriers. Finally, we discuss the findings and implications for refining the "FERTILE" Community Platform as an online environment for educators co-designing Artful ER projects.
... This deep comprehension enables students to make connections across different STEM fields, fostering a more integrated and holistic approach to learning (English, 2017;Ortiz-Revilla et al., 2022). Science, Technology, Engineering, and Mathematics knowledge is often divided into theoretical and practical categories (Gao et al., 2020;Ortiz-Revilla et al., 2020;Wang et al., 2022), with the former focusing on scientific laws, mathematical theorems, and engineering concepts, and the latter gained through hands-on experience and experimentation (Lee, Cheng, et al., 2023;Wu, Lee, Wang, et al., 2023). Skills, particularly HOTS, are essential for tackling complex societal issues (Lu et al., 2021). ...
Background
Science, Technology, Engineering, and Mathematics (STEM) education in Asian universities struggles to integrate Knowledge, Skills, and Attitudes (KSA) due to large classes and student reluctance. While ChatGPT offers solutions, its conventional use may hinder independent critical thinking.
Objectives
This study introduces PA‐GPT, using ChatGPT as a “virtual peer” in peer assessments to promote active learning and enhance knowledge, higher‐order thinking skills (HOTS), and attitudes—the core of KSA in STEM.
Methods
A randomised controlled trial involved 61 first‐year engineering students (43 males, 18 females) from a university in Southern Taiwan enrolled in “Network Embedded Systems and Applications.” Participants, all with prior ChatGPT experience but no programming background, were purposively sampled. They were randomly assigned to the experimental group (n = 31) using PA‐GPT or the control group (n = 30) using traditional ChatGPT. Over 8 weeks, data were collected using pre‐ and post‐tests: a knowledge construction test (20 items, α = 0.85); a HOTS scale (α = 0.78–0.83) measuring critical thinking, problem‐solving, and creativity; and the S‐STEM questionnaire (α >0.80) assessing attitudes towards STEM subjects and 21st‐century learning. ANCOVA analysed the data, controlling for pre‐test scores, and Levene's test checked homogeneity of variances.
Results and Conclusions
ANCOVA results showed that PA‐GPT significantly outperformed traditional ChatGPT in enhancing knowledge construction (F = 9.89, p = 0.002), critical thinking (F = 37.00, p < 0.001), problem‐solving (F = 9.40, p = 0.003), creativity (F = 7.22, p = 0.009), and attitudes towards mathematics (F = 25.52, p < 0.001), engineering/technology (F = 16.06, p < 0.001), and 21st‐century learning (F = 26.38, p < 0.001). These findings demonstrate that PA‐GPT effectively addresses challenges in student engagement and HOTS development in STEM education by simulating peer interactions. Peer Assessment with ChatGPT (PA‐GPT) promotes active learning and self‐reflection, potentially revolutionising AI‐assisted education in large class settings. This study provides pioneering evidence for the effectiveness of AI‐driven peer assessment in enhancing comprehensive STEM competencies, offering a promising direction for future educational technology integration.
... Much of the research on teachers' engagement with assessment has focused on teachers' knowledge of assessment (Quilter & Gallini, 2010; see also Coombe et al., 2020;Iqbal, et al., 2023;Wang et al., 2022) teachers' assessment competence or procedural knowledge of assessment (DeLuca et al., 2019;Popham, 2009: see also Tierney, 2006;Willis et al., 2013), and teachers' assessment practices and assessment for instruction (Carless, 2005;De Lisle, 2015;James & McCormick, 2009). All these components serve as complementary skills to teachers' classroom instruction and by extension student achievement. ...
Using a descriptive cross-sectional design, this research examined the assessment knowledge, competence, and practices of a sample of graduate language and literacy English teachers. Data were collected from a convenience sample of 57 graduate students using a researcher-designed questionnaire which focused on aspects of teachers’ general assessment knowledge and their competence as it relates to their classroom assessment practices in Literacy. Analysis of the results was conducted using descriptive statistics, independent samples T-tests and correlational analyses. The results indicated that even with significant years of teaching and sound professional qualifications, teachers’ assessment knowledge was moderate. However, there was a significant difference in assessment knowledge based on years of teaching experience. The findings also revealed that, generally, teachers’ perceived assessment competence was also moderate, with teachers reporting lowest skills on standards related to developing assessment methods appropriate for instructional decisions and developing valid grading procedures which use student assessments. The teachers reported using a variety of assessment practices with classroom discussions being the most frequently used and journaling, the least popular practice. The results also indicated a significant positive correlation between teachers’ perceived assessment competence and the assessment practices used in their English classrooms.
... Furthermore, the importance of collaboration was underscored; activities enhanced social interactions and communication among students, fostering a supportive community that facilitated effective teamwork. This feedback suggests that integrating these elements creates a dynamic and supportive educational environment conducive to both personal and academic growth (Wang, et al., 2022). ...
Integrating unplugged computational thinking across curricula: A qualitative study of students' and teachers' perspectives. Integrating computational thinking into the K-12 curriculum presents challenges due to the lack of a standardized approach. This study examines the use of "unplugged" computational thinking-activities that do not require digital devices-in teaching mathematics and language arts to tenth-grade students. The instructional method followed phases such as abstraction, decomposition, algorithms, evaluation, and generalization. Data were collected through focus groups with teachers and a sample of students from both subjects and analyzed qualitatively to capture their perspectives. The findings suggest that unplugged computational thinking increased student engagement and helped achieve learning objectives. Both teachers and students reported that this approach fostered deeper conceptual understanding and enhanced the educational experience by developing skills in problem-solving, collaboration, and perseverance (grit). Teachers observed that students could explore and articulate their thoughts more expansively compared to traditional methods, leading to a richer understanding of the material. Students emphasized that integrating computational thinking, fostering grit, and encouraging collaboration are crucial for enriching their educational experiences and creating a supportive, effective learning environment.
The study examined pre-service teachers' perceptions, interests, confidence levels, and practical application of computational thinking (CT). The research incorporated CT professional development within the Methods and Content of Teaching Mathematics course tailored for elementary pre-service teachers. Findings from the study revealed a significant increase in both perception and competency in CT. Although there was no statistically significant improvement in their interest in CT, substantial advancements were noted in their ability to apply CT within mathematics lesson design. Pre-service teachers showed a preference for algorithms, followed by decomposition, pattern recognition, and abstraction when designing math activities. Furthermore, the research underscores the positive impact of CT professional development, with an improvement in pre-service teachers' ability to infuse real-world applications and adopt an inter-curricular approach in their lesson designs.
Research in Science, Technology, Engineering, and Mathematics (STEM) education has demonstrated a relationship between the use of information and communications technology and a better learning for students. Conventional teaching will not be able to meet the needed criteria for motivating and increasing the number of students in STEM related fields. The purpose of this research is to present an overview of a new learning approach using disruptive innovations such as Internet of Things (IoT), 3D printing, E-learning, Robotics, and Artificial Intelligence (AI) focused on children education based on a literature review. The proposed approach highlights the benefits for teachers and learners in kindergarten and formal primary education. This article proposes a review demonstrating positive results of disruptive innovations, using different technologies, focused on the improvement of STEM education. At the end of the work, a techno-pedagogical framework using disruptive innovations is presented.
KeywordsSTEMEducationDisruptive innovationFrameworkTechno-pedagogy
The emergence of the digital revolution has placed an impeccable demand on the education sector around the globe to foster digital citizenship. The educators lack effective and necessary vocational training to impart digital citizenship skills to adolescents. At the global level, the cyber-security laws and regulations vary significantly across various jurisdictions leading to non-uniformity in implementation of consistent standards for digital citizenship. The core premise of the study proposes to encapsulate the complexities in fostering digital citizenship in the education industry globally. This chapter focuses on the addressing the legal and social challenges with regards digital citizenship in the education sector, which entails a collective effort and multifaceted collaboration among educational community, legislators, technology corporations, etc. to provide for a more effective and inclusive digital world for society.
Digital literacy is a basic life skill in today's interconnected world. So, integrating digital education in the overall educational planning even globally becomes a necessity eventually creating a more knowledgeable and responsible generation of citizens. A common-sense option might be to teach students the tools and knowledge they need to thrive in the digital space, as well. Others like the teaching of digital literacy, critical thinking, problem solving and effective communication are administered as well. Additionally, schools should be teaching digital citizenship as how to use technology in ways that are safe, secure, and ethical. Digital literacy and Citizenship will empower students to be engaged and thoughtful world citizens who can support the promise of our digital age.
Increased technological advances within marine biology requires professionals to become versed in interdisciplinary computer-based skills. Computational thinking (CT) is a contemporary concept used in educational settings across the globe to meet this need. CT has been incorporated into many curricula; however, incorporation strategies are vague and result in specific challenges for post-secondary marine science educators. We developed a framework to support an intervention which incorporated CT into learning marine biology quantitative skills for students in an introductory marine science course at a small liberal arts university in the northeastern United States through a quasi-experimental action research design. We assessed student participant content knowledge through two assessments, student artifacts and a self-perception survey. Results indicate that the intervention was successful in overall participant knowledge gains in both quantitative marine biology skills and computational thinking. Our research design may shed light on how post-secondary institutions may address student range of computational thinking skills within marine science to better support sustainability practices and promote equity and present its applicability to other settings.
Computational thinking (CT) is a problem-solving methodology that involves breaking down complex problems into smaller, more manageable parts and draws upon principles used in computer science and programming. Problem-solving is an important skill in scientific reasoning, so it is crucial for Science, Technology, Engineering, and Mathematics (STEM) learning in K-12. While CT in STEM context is an understudied area of research, the main question is how to integrate CT rather than why to integrate it in STEM context. Therefore, this chapter, firstly, discusses how CT and STEM are related and support each other as both concepts involve modeling, reasoning, and problem-solving. Secondly, this chapter provides ways to integrate CT in STEM context to promote students learning. For the second aim, the reviewing related research shows that there are three main approaches for integration of CT in K-12 education: (1) introducing programming activities that are separate from content learning, (2) connecting CT with content learning by utilizing problem-solving scenarios to describe, compare, and test predictions about systems, and (3) providing students with insights into how STEM professionals apply CT. In this chapter, I also discuss the advantages and limitations of each of these approaches in supporting CT in STEM context. Regardless of these approaches, the chapter also explains: (a) instructional strategies including problem-based learning, experiential learning and game-based learning, (b) plugged and unplugged instructional tools including Scratch, Lego, card sorting and Robotics and (c) assessments that can be used in STEM context to promote CT skill. Lastly, as the success of any innovation in education depends on how teachers apply it in classrooms, the chapter discusses the requirements that STEM teachers need to possess to successfully integrate CT in STEM instruction.
The revolutionize teacher centric approach in intelligent tutoring systems (ITS) and adaptive learning environments shaping the curriculum design and course management. These systems may present real-time feedback, adaptive knowledge customized to the needs of particular students and personalized educational pathways by utilizing artificial intelligence and machine learning Teachers may use AI to create more customized, effective, and captivating educational adventures for learners through employing a teacher-centric approach. This chapter attempts to emphasize the potential of AI to completely alter classroom procedures while emphasizing the important function of teachers in directing and encouraging students through AI-powered instructional settings by looking at the working partnership between professionals and artificial intelligence (AI) instruments in curriculum development and course management.
Innovation is the key factor boosting economics and international competitiveness, but it takes a long time for a nation to get to the point where innovation becomes the main force. The concept of innovation has to be seen somewhat differently when applied to latecomer nations than it is when applied to leaders. The technology combines textual feedback and machine learning and this approach examines the remarks, viewpoints and assessments of instructors made by students. Also, textual criticism enhances teaching style and provides valuable insights on the effectiveness of instruction. The inputs are recorded by the technology and stored in an authorized database. To assist the teacher see the input, ratings and graphs are provided. This chapter evaluates current econometric research on how changes in IPR policy affect educational growth and comes to research points to the acceleration of education and innovation development with stronger IPR regimes.
In this study, it was aimed to determine the pedagogical principles for building functional science literacy of school children in line with the Program for International Student Assessment (PISA) by examining the performing countries in PISA. The statistical results of the PISA results reports of China, Singapore, Hong Kong and Estonia were compared with the results of Kazakhstan. It was concluded that students in the top-ranked countries actively participate in scientific activities, enjoy practicing scientific activities, exhibit high-level cognitive skills, test and monitor the results of scientific research, and compete in national and international activities. The economic status of the family, learning environment, discipline, school equipment, and the number of teachers in the school are among the factors affecting children's science literacy. Teachers' continuous participation in in-service trainings, keeping their motivation at a high level, choosing different teaching methods, encouraging students to conduct research and activating high-level cognitive skills were considered among the most important reasons for good results in science PISA research. It is recommended that countries that want to rank higher in an international platform such as PISA should implement student-centered activities in their educational reforms and create educational environments where students can test their high-level skills.
Block-based visual programming tools are widely used in elementary education. Nonetheless, these tools alone may not ensure the spontaneous and efficient acquisition of concepts and skills in computational thinking (CT). Using mind mapping as a form of scaffolding to facilitate the visualization of abstract thinking processes may enhance the effectiveness of programming instruction. This study therefore investigated the effects of mind mapping-based scaffolding that integrates five CT skills on elementary students’ CT development. Eighty-six fifth-grade students participated in our pretest-posttest quasi-experimental study. In the experimental group, mind mapping-based scaffolding was used to help students learn programming, while in the comparison group it was not used. The results showed that both groups achieved significant improvements in concept understanding and skill development; however, students instructed using mind mapping-based scaffolding obtained notably superior performance in understanding CT concepts and mastering CT skills. The results also revealed that the students had positive perceptions of mind mapping-based scaffolding, although challenges were also identified. This study enriches the relevant empirical research and offers insights for practitioners on designing effective scaffolding to promote students’ CT development.
Students often require personalized attention, yet teachers face challenges with large classes and limited time. Tutoring offers tailored guidance and promotes effective learning. An Intelligent Tutoring System (ITS) serves as an excellent alternative to traditional tutoring. This software simulates a real tutor by presenting problems, offering support, correcting mistakes, and providing encouragement. ITS operates as an intelligent, computer-assisted instructional program and it customized environments for education works most when complemented with a teacher-centric methodology. Teachers play a crucial role in assisting children to learn, helping them navigate new AI-powered platforms, and encouraging creativity and critical thinking. The chapter focuses on the relevance of teacher preparedness and the shifting function of academics in AI-augmented classrooms as it studies the opportunities of ITS and adaptive learning environments to improve the quality of education.
Much attention has been paid to computational thinking (CT) as a problem-solving approach across various curricula, particularly in mathematics. Most studies solely used a digital instrument or examined transfer of program solving ability, neglecting the mathematics knowledge domain or how the novel digital instrument functions alongside the dominant paper-and-pencil instrument in a classroom. Using Instrument-Mediated Activity Theory, our qualitative case study compares how secondary level students appropriated computer programming (as a means of using CT) and paper-and-pencil instruments to solve mathematics textbook word problems, via the analysis of three cases. Our results show that each instrument privileged certain ways of thinking that, by extension, de-emphasized others. The finding implies that teachers seeking to introduce computational concepts should be aware of an epistemic clash arising from the long-term use of paper-and-pencil for solving mathematics problems. We suggest that a more effective way to bring CT into secondary level mathematics is to introduce new types of problems or tasks that are less likely to interfere with the dominant instrument.
Computational thinking (CT) has been advocated as an essential problem solving skill students need to develop. Emphasizing on CT applied in both programming and everyday contexts, we developed a humanoid robotics curriculum and a computerized assessment instrument. We implemented the curriculum with six classes of 125 fifth graders. Quantitative methods were used to compare students’ performance from pretest to posttest. Learning analytics techniques were applied to examine students’ problem solving processes. The results showed that students’ CT performance improved in both programming and everyday reasoning contexts and that the curriculum benefited students with varied initial performance. The study shed light on how to connect and assess CT in everyday reasoning and programming contexts.
(here's the instrument: https://umiami.qualtrics.com/jfe/form/SV_6KZgZT46iZVczFr )
The recognized importance of computational thinking has helped to propel the rapid development of related educational efforts and programs over the past decade. Given the multi-faceted nature of computational thinking, which goes beyond programming and computer science, however, approaches and practices for developing students’ computational thinking are not always self-explanatory in terms of their foci and feasibility in diverse educational contexts. In this editorial, we first examine relevant publications in computational thinking to identify a trend of integrating computational thinking into disciplinary education. We subsequently build on recent discussions about the concept of computational thinking to (1) frame a review of educational efforts in developing students’ computational thinking, (2) discuss opportunities and challenges to further such educational efforts through not only programming and computer science but also other disciplines, and (3) articulate needed research and scholarship to support educational practices.
In the International Computer and Information Literacy Study (ICILS) 2018, computational thinking (CT) assessment was an option for participating countries participating. Eight countries and one benchmarking participant participated in the CT assessment. In this chapter, the CT assessment instrument and the proficiency scale derived from the ICILS 2018 test instrument and data are described and the international student results relating to CT are discussed. CT achievement is described across three regions of increasing sophistication from a functional working knowledge of computation as input and output (lower region) through to an understanding of computation as a generalizable problem-solving framework (upper region). Students’ CT achievement varied more within countries than across countries. CT tended to be higher among male students, although statistically significant gender differences were found in only two countries. In one of those countries the difference was in favor of female students and in the other it was in favor of male students. Socioeconomic status was significantly positively associated with student CT achievement. Immigrant background, language background, access to computers at home, and experience with computers were also associated with student CT achievement. In all countries, student CT achievement was strongly associated with student computer and information literacy (CIL) achievement.
Despite STEM education communities recognizing the importance of integrating computational thinking (CT) into high school curricula, computation still remains a separate area of study in K-12 contexts. In addition, much of the research on CT has focused on creating generally agreed-upon definitions and curricula, but few studies have empirically tested assessments or used contemporary learning sciences methods to do so. In this paper, we outline the implementation of an assessment approach for a 10-day high school biology unit with computational thinking activities that examines student pre-post responses as well as responses to embedded assessments throughout the unit. Using pre-post scores, we identified students with both positive and negative gains and examined how each group’s CT practices developed as they engaged with the curricular unit. Our results show that (1) students exhibited science and computational learning gains after engaging with a science unit with computational models and (2) that the use of embedded assessments and discourse analytics tools reveals how students think differently with computational tools throughout the unit.
Integrating computational thinking (CT) and science education is complex, and assessing the resulting learning gains even more so. Arguments that assessment should match the learning (Biggs, Assessment & Evaluation in Higher Education, 21(1), 5–16. 1996; Airasian and Miranda, Theory into Practice, 41(4), 249–254. 2002; Hickey and Zuiker, Journal of the Learning Sciences, 21(4), 522–582. 2012; Pellegrino, Journal of Research in Science Teaching, 49(6), 831–841. 2012; Wiggins, Practical Assessment, Research and Evaluation, 2(2). 1990) lead to a performance-oriented approach to assessment, using tasks that mirror the integrated instruction. This approach reaps benefits but also poses challenges. Integrated CT is a new approach to learning. Movement is being made toward understanding what it means to operate successfully in this context, but consensus is neither general nor time tested (Kaput and Schorr 2008). Movement is also being made toward developing methods for assessing CT. Despite the benefits of matching assessment with pedagogy, there may be intrinsic losses. One problem is that interactions between the two domains may invalidate the results, either because the gains in one may be easier to measure at certain times than the gains in the other, or because interactions between the two domains may cause measurement interference. Our examination draws upon both theoretical basis and also existing practices, particularly from our own work integrating CT and secondary science. We present a mixed-methods analysis of student assessment results and consider potential issues with moving too quickly toward relying on a rubric-based approach to evaluating this student learning. Centrally, we emphasize the importance of assessment approaches that reflect one of the most important affordances of computational environments, that is, the expression of multiple ways of knowing and doing (Turkle and Papert, Journal of Mathematical Behavior, 11(1), 3–33. 1992).
Computational thinking (CT) is believed to be a critical factor to facilitate STEM learning, and a vital learning objective itself. Therefore, researchers are continuing to explore effective ways to improve and assess it. Makerspaces feature various hands-on activities, which can attract students with diverse interests from different backgrounds. If well designed, scaffolded maker activities have the potential to improve students’ CT skills and STEM learning. In this study, we explore ways to improve and assess physics and engineering integrated CT skills through developing maker activities and assessments, which are applicable in both informal and formal educational settings. Our paper presents our work on improving and assessing CT in maker activities with two primary goals. First, it introduces the maker activities and instruments we developed to improve and assess CT that are integrated in physics and engineering learning. Second, it presents the students’ CT skill and disposition change from pretest to posttest in two summer academies with CT enhanced maker activities, which was respectively led by after school educators and formal educators in a public library.
Synergistic learning combining computational thinking (CT) and STEM has proven to be an effective method for advancing learning and understanding in a number of STEM domains and simultaneously helping students develop important CT concepts and practices. We adopt a design-based approach to develop, evaluate, and refine our Collaborative, Computational STEM (C2STEM) learning environment. The system adopts a novel paradigm that combines visual model building with a domain-specific modeling language (DSML) to scaffold learning of high school physics using a computational modeling approach. In this paper, we discuss the design principles that guided the development of our open-ended learning environment (OELE) using a learning-by-modeling and evidence-centered approach for curriculum and assessment design. Students learn by building models that describe the motion of objects, and their learning is supported by scaffolded tasks and embedded formative assessments that introduce them to physics and CT concepts. We have also developed preparation for future learning (PFL) assessments to study students’ abilities to generalize and apply CT and science concepts and practices across problem solving tasks and domains. We use mixed quantitative and qualitative analysis methods to analyze student learning during a semester-long study run in a high school physics classroom. We document some of the lessons learned from this study and discuss directions for future work.
This article provides an introduction for the special issue of the Journal of Science Education and Technology focused on computational thinking (CT) from a disciplinary perspective. The special issue connects earlier research on what K-12 students can learn and be able to do using CT with the CT skills and habits of mind needed to productively participate in professional CT-integrated STEM fields. In this context, the phrase “disciplinary perspective” simultaneously holds two meanings: it refers to and aims to make connections between established K-12 STEM subject areas (science, technology, engineering, and mathematics) and newer CT-integrated disciplines such as computational sciences. The special issue presents a framework for CT integration and includes articles that illuminate what CT looks like from a disciplinary perspective, the challenges inherent in integrating CT into K-12 STEM education, and new ways of measuring CT aligned more closely with disciplinary practices. The aim of this special issue is to offer research-based and practitioner-grounded insights into recent work in CT integration and provoke new ways of thinking about CT integration from researchers, practitioners, and research-practitioner partnerships.
Computational thinking (CT) and modeling are authentic practices that scientists and engineers use frequently in their daily work. Advances in computing technologies have further emphasized the centrality of modeling in science by making computationally enabled model use and construction more accessible to scientists. As such, it is important for all students to get exposed to these practices in K-12 science classrooms. This study investigated how a week-long intervention in a regular middle school science classroom that introduced CT and simulation-based model building through block-based programming influenced students’ learning of CT and force and motion concepts. Eighty-two seventh-grade students from a public middle school participated in the study. Quantitative data sources included pre- and post-assessments of students’ understanding of force and motion concepts and CT abilities. Qualitative data sources included classroom observation notes, student interviews, and students’ reflection statements. During the intervention, students were introduced to CT using block-based programming and engaged in constructing simulation-based computational models of physical phenomena. The findings of the study indicated that engaging in building computational models resulted in significant conceptual learning gains for the sample of this study. The affordances of the dynamic nature of computational models let students both observe and interact with the target phenomenon in real time while the generative dimension of model construction promoted a rich classroom discourse facilitating conceptual learning. This study contributes to the nascent literature on integrating CT into K-12 science curricula by emphasizing the affordances and generative dimension of model construction through block-based programming.
This paper describes analyses of the K–12 computational thinking (CT) integration activities collected at two NSF-funded workshops, “Developing an Interdisciplinary Framework for Integrating Computational Thinking in K–12 Science, Mathematics, Technology, and Engineering Education,” held in August and November of 2017 at Education Development Center, Inc., in Waltham, Massachusetts. The workshops convened a working group of principal investigators, researchers, and educators from the National Science Foundation (NSF) ITEST (Innovative Technology Experiences for Students and Teachers) and STEM + C (STEM + Computing) funded projects to draft an interdisciplinary framework for integrating CT into K–12 education. The goal of this paper is to share that framework and our findings on promising learning progressions, gaps that exist in the collected set of activities, specific advances in STEM fields that were made possible through CT, and suggested ways that CT integration in K-12 can evolve to reach what the CT integration framework proposes as five “computational thinking integration elements” or “CTIEs”. This framework is designed to help educators see ways to engage students in CT within disciplinary learning. The analyses and findings may benefit STEM and computing education fields by elucidating the target of CT as used within CT-integrated STEM fields.
The importance of computational thinking (CT) as a goal of science education is increasingly acknowledged. The representational affordances of computational tools are changing the way knowledge can be constructed, expressed, and understood across disciplines. Our group has worked to explicitly characterize CT practices used by computational STEM researchers (CT-STEM practices) and to develop computational science curricula that teach both CT-STEM practices and science content. We have previously characterized four strands of CT-STEM practices: data practices, modeling and simulation practices, computational problem-solving practices, and systems thinking practices. In this chapter, we show that a group of 9th grade students developed competencies for modeling and simulation practices as a result of their engagement in our computational biology curriculum. As evidence, we present findings from a quantitative analysis of students’ written responses to assessments given before and after their participation in three computational biology units. Results suggest that the computational biology curriculum helped students develop a number of important competencies for the strand on modeling and simulation practices. Our work contributes to the field’s understanding of how science curricula can be designed to foster students’ development of CT-STEM practices and how this development can be assessed.
Making activities and environments have been shown to foster the development of computational thinking (CT) skills for students in science, technology, engineering, and math (STEM) subject areas. To properly cultivate CT skills and the related dispositions, educators must understand students’ needs and build awareness of how CT informs a deeper understanding of the academic content area. “Assessing Computational Thinking in Maker Activities” (ACTMA) is a design-based research study that developed a curricular unit around physics, making, and CT. The project in this paper studied how instructors could use formative assessment to uncover students’ prior knowledge and improve their use of CT. This study aims to provide a qualitative analysis of one lesson in the unit implementation of an informal makerspace environment that strived to be culturally responsive. The study examined “moments of notice,” or instances where formative assessment could guide students’ understanding of CT. We found elements in the establishment of a classroom culture that can generate a continual use of informal formative assessment between instructors and students. This culture includes using materials in conjunction with the promotion of CT concepts and dispositions, focusing on drawing for understanding, the practice of debugging, and fluidity of roles in the learning space.
Knowledge production within the field of business research is accelerating at a tremendous speed while at the same time remaining fragmented and interdisciplinary. This makes it hard to keep up with state-of-the-art and to be at the forefront of research, as well as to assess the collective evidence in a particular area of business research. This is why the literature review as a research method is more relevant than ever. Traditional literature reviews often lack thoroughness and rigor and are conducted ad hoc, rather than following a specific methodology. Therefore, questions can be raised about the quality and trustworthiness of these types of reviews. This paper discusses literature review as a methodology for conducting research and offers an overview of different types of reviews, as well as some guidelines to how to both conduct and evaluate a literature review paper. It also discusses common pitfalls and how to get literature reviews published.
There is a growing need to present all students with an opportunity to learn computer science and computational thinking (CT) skills during their primary and secondary education. Traditionally, these opportunities are available outside of the core curriculum as stand-alone courses often taken by those with preparatory privilege. Researchers have identified the need to integrate CT into core classes to provide equitable access to these critical skills. We have worked in a research-practice partnership with two magnet middle schools focused on digital sciences to develop and implement computational thinking into life sciences classes. In this report, we present initial lessons learned while conducting our design-based implementation research on integrating computational thinking into middle school science classes. These case studies suggest that several factors including teacher engagement, teacher attitudes, student prior experience with CS/CT, and curriculum design can all impact student engagement in integrated science-CT lessons.
Computational Thinking is argued to be an essential skill for the workforce of the 21st century. As a skill, Computational Thinking should be taught in all schools, employing computational ideas integrated into other disciplines. Up until now, questions about how Computational Thinking can be effectively taught have been underexplored preventing efforts to cross the large gap between early adopters and the early majority, conceptualized as the Computer Science Education chasm. A promising strategy to cross the chasm is underway in Switzerland. Switzerland recently introduced a national curriculum, called Lehrplan 21, mandating Computer Science Education. This mandate requires the Computer Science education of elementary and middle school students. In 2017, the School of Education of Northwestern Switzerland (PH FHNW), introduced a mandatory pre-service teacher Computer Science Education course, to satisfy this mandate. All the PH FHNW students who study to become elementary school teachers must pass this two-semester course. The first part of this course was taught for the first time in fall of 2017. This paper presents the philosophy of this course and an initial analysis of both qualitative data capturing the students’ perceptions of Computational Thinking and quantitative data describing shifts in students’ skills and attitudes as effect sizes. The data suggest that it is possible to teach a basic understanding of programming to non-self-selected pre-service elementary school teachers.
Our research uses game creation and play to explore methods for computational thinking assessment and practice in mathematics classrooms. We present the first iteration of this research that aims to evaluate the feasibility of using game creation with high school students. Students designed math-related games, modified the game to incorporate technology, then visually depicted the technological behavior in a finite state machine diagram (FSMD). We found that students were able to create math-related games, meet the constraints given for game creation, and design logical FSMDs. These findings preliminarily suggest that game creation can be used as a method for students to practice CT.
This qualitative case study reports descriptive findings of digital game-based learning involving 15 Taiwanese middle school students’ use of computational thinking skills elicited through programmed activities in a game design workshop. Situated learning theory is utilized as framework to evaluate novice game designers’ individual advancement in developing a designer language, mindset, and use of computational thinking skills. Three strands of findings were extrapolated from analyzing observational data, participant-generated written responses and artifacts: Understanding games as systems and how components work together in meaningful relationships in game design; Developing growing sophistication in communicating with other novice game designers using language germane to game design; Improving understanding and application of computational thinking skills through game design activities. Extended discussions on three focal cases revealed that using design pedagogy, participants operationalized computational thinking skills in design tasks. Promises and pitfalls of using game design to facilitate computational thinking skills are discussed.
This paper reports the design and evaluation of semester-scale teaching intervention addressing the teaching of Scratch programming environment followed by pre-service kindergarten students. The overall aim of this course was to assist students in utilizing computational thinking and programming as an instructional tool within other subject areas (i.e. mathematics and physics). The methodology used is the research based design, which is interventional and recursive in nature. The observations of the researchers, the recordings of students' actions, as well as their projects, were used to draw conclusions, to identify strengths or weaknesses of the teaching intervention implemented and to assess its efficacy regarding a computer course structure using the educational environment ScratchJr. We argue that the teaching of ScratchJr can assist teachers in utilizing Computational Thinking and programming as an instructional tool within other subject areas (i.e. mathematics and physics).
This paper examines the growing field of computational thinking (CT) in education. A review of the relevant literature shows a diversity in definitions, interventions, assessments, and models. After synthesizing various approaches used to develop the construct in K-16 settings, we have created the following working definition of CT: The conceptual foundation required to solve problems effectively and efficiently (i.e., algorithmically, with or without the assistance of computers) with solutions that are reusable in different contexts. This definition highlights that CT is primarily a way of thinking and acting, which can be exhibited through the use particular skills, which then can become the basis for performance-based assessments of CT skills. Based on the literature, we categorized CT into six main facets: decomposition, abstraction, algorithm design, debugging, iteration, and generalization. This paper shows examples of CT definitions, interventions, assessments, and models across a variety of disciplines, with a call for more extensive research in this area.
A science, technology, engineering, and mathematics-influenced classroom requires learning activities that provide hands-on experiences with technological tools to encourage problem-solving skills (Brophy et al. in J Eng Educ 97(3):369–387, 2008; Mataric´ et al. in AAAI spring symposium on robots and robot venues: resources for AI education, pp 99–102, 2007). The study aimed to bring computational thinking, an
applicable skill set in computer science, into existing mathematics and programming education in elementary classrooms. An essential component of computational thinking is the ability to think like a computer scientist when confronted with a problem (Grover and
Pea in Educ Res 42(1):38–43. doi:10.3102/0013189X12463051, 2013). Computational perspectives (Berland and Wilensky in J Sci Educ Technol 24(5):628–647. doi:10.1007/ s10956-015-9552-x, 2015) refer to the frame of reference programmers or computer scientists adopt when approaching a problem. The study examined the effects of taking computational perspectives through various degrees of embodied activities (i.e., full vs. low) on students’ achievement in mathematics and programming. The study employed a 2 (full vs. low embodiment) * 2 (with vs. without computational perspective taking) factorial condition to evaluate four learning conditions from a combination of embodiment
and computational perspective-taking practice. The results from this experimental study (N = 66 kindergarten and first graders) suggest that full-embody activities combined with the practice of computational perspective-taking in solving mathematics problem improved mathematics understanding and programming skills as demonstrated in Scrath Jr. among novice young learners. Moreover, the practice of using a computational perspective significantly improved students’ understanding of core programming concepts regardless of the level of embodiment. The article includes recommendations for how to make the
computational thinking process more concrete and relevant within the context of a standard curriculum, particularly mathematics.
Learner modeling has been used in computer-based learning environments to model learners’ domain knowledge, cognitive skills, and interests, and customize their experiences in the environment based on this information. In this paper, we develop a learner modeling and adaptive scaffolding framework for Computational Thinking using Simulation and Modeling (CTSiM)—an open ended learning environment that supports synergistic learning of science and Computational Thinking (CT) for middle school students. In CTSiM, students have the freedom to choose and coordinate use of the different tools provided in the environment, as they build and test their models. However, the open-ended nature of the environment makes it hard to interpret the intent of students’ actions, and to provide useful feedback and hints that improves student understanding and helps them achieve their learning goals. To address this challenge, we define an extended learner modeling scheme that uses (1) a hierarchical task model for the CTSiM environment, (2) a set of strategies that support effective learning and model building, and (3) effectiveness and coherence measures that help us evaluate student’s proficiency in the different tasks and strategies. We use this scheme to dynamically scaffold learners when they are deficient in performing their tasks, or they demonstrate suboptimal use of strategies. We demonstrate the effectiveness of our approach in a classroom study where one group of 6th grade students received scaffolding and the other did not. We found that students who received scaffolding built more accurate models, used modeling strategies effectively, adopted more useful modeling behaviors, showed a better understanding of important science and CT concepts, and transferred their modeling skills better to new scenarios.
In this paper we present the background, aims and methodology of the ScratchMaths (SM) project, which has designed curriculum materials and professional development (PD) to support mathematical learning through programming for pupils aged between 9 and 11 years. The project was framed by the particular context of computing in the English education system alongside the long history of research and development in programming and mathematics. In this paper, we present a “framework for action” (diSessa and Cobb 2004) following design research that looked to develop an evidence-based curriculum intervention around carefully chosen mathematical and computational concepts. As a first step in teasing out factors for successful implementation and addressing any gap between our design intentions and teacher delivery, we focus on two key foundational concepts within the SM curriculum: the concept of algorithm and of 360-degree total turn. We found that our intervention as a whole enabled teachers with different backgrounds and levels of confidence to tailor the delivery of the SM in ways that can make these challenging concepts more accessible for both themselves and their pupils.
The current impetus for increasing STEM in K-12 education calls for an examination of how preservice teachers are being prepared to teach STEM. This paper reports on a study that examined elementary preservice teachers’ (n = 21) self-efficacy, understanding of science concepts, and computational thinking as they engaged with robotics in a science methods course. Data collection methods included pretests and posttests on science content, prequestionnaires and postquestionnaires for interest and self-efficacy, and four programming assignments. Statistical results showed that preservice teachers’ interest and self-efficacy with robotics increased. There was a statistically significant difference between preknowledge and postknowledge scores, and preservice teachers did show gains in learning how to write algorithms and debug programs over repeated programming tasks. The findings suggest that the robotics activity was an effective instructional strategy to enhance interest in robotics, increase self-efficacy to teach with robotics, develop understandings of science concepts, and promote the development of computational thinking skills. Study findings contribute quantitative evidence to the STEM literature on how robotics develops preservice teachers’ self-efficacy, science knowledge, and computational thinking skills in higher education science classroom contexts.
Designing games requires a complex sequence of planning and executing actions. This paper suggests that game design requires computational thinking, and discusses two methods for analyzing computational thinking in games designed by students in the visual programming language Scratch. We present how these two analyses produce different narratives of computational thinking for our case studies, and reflect on how we plan to move forward with our larger analysis.
Recent government moves in many countries have seen coding included in school curricula, or promoted as part of computing, mathematics or science programmes. While these moves have generally been associated with a need to engage more young people in technology study, research has hinted at possible benefits from learning to program including fostering general thinking skills. However, little research has been carried out exploring these ideas. This study analysed data collected while 5‐ and 6‐year‐old students in a New Zealand primary school were using Scratch Jnr. to learn about basic shapes, as part of a numeracy topic. Analysis combined Brennan and Resnick's (2012) computational thinking skills framework and Krathwohl's (2002) revision of Bloom's Taxonomy to evaluate any role general thinking skills played in these students' coding work. Results suggest including basic coding in primary curricula provides teachers with an effective means of exercising their students' general and higher order thinking skills. They build on Brennan and Resnick's (2012) framework by including conceptualization as an important element in students' computational work and highlight the role of predictive thinking in debugging code. Findings support historical arguments that more needs to be done to investigate students' cognitive processes when undertaking computational work.
Lay description
What is already known about the topic
Computational learning is an emerging area of school curricula;
Limited research exists exploring thinking processes within computational learning;
Early studies challenge more recent claims of thinking skill transfer from computational work.
What this paper adds
Computational work supports a range of general and higher order thinking skills;
Task design and teacher skills are critical to achieving higher order thinking outcomes from computational work;
Computational work in teams can support collaborative, cooperative and self‐management key competencies.
Implications for practice and/or policy
Findings broaden the base of empirical support for including computational work in school curricula;
Coding provides an engaging means of exercising complex thinking skills and key competencies in students;
The data methods used provide teachers with visible evidence of students' thinking processes during computational work.
This paper describes the findings of a pilot study that used robotics and game design to develop middle school students’ computational thinking strategies. One hundred and twenty-four students engaged in LEGO® EV3 robotics and created games using Scalable Game Design software. The results of the study revealed students’ pre–post self-efficacy scores on the construct of computer use declined significantly, while the constructs of videogaming and computer gaming remained unchanged. When these constructs were analyzed by type of learning environment, self-efficacy on videogaming increased significantly in the combined robotics/gaming environment compared with the gaming-only context. Student attitudes toward STEM, however, did not change significantly as a result of the study. Finally, children’s computational thinking (CT) strategies varied by method of instruction as students who participated in holistic game development (i.e., Project First) had higher CT ratings. This study contributes to the STEM education literature on the use of robotics and game design to influence self-efficacy in technology and CT, while informing the research team about the adaptations needed to ensure project fidelity during the remaining years of the study.
This article presents a systematic review of research related to the use of robotics construction kits (RCKs) in P–12 learning in the STEM disciplines for typically developing children. The purpose of this review is to configure primarily qualitative and mixed methods findings from studies meeting our selection and quality criterion to answer the review question: How do robotic construction kits function as computational manipulatives in P–12 STEM education? Our synthesis of the literature has resulted in four key insights that are new to the field. First, RCKs have a unique double application: They may be used for direct instruction in robotics (first-order uses) or as analogical tools for learning in other domains (second-order uses). Second, RCKs make possible additional routes to learning through the provision of immediate feedback and the dual modes of representation unique to RCKs. Third, RCKs support a computational thinking learning progression beginning with a lower anchor of sequencing and finishing with a high anchor of systems thinking. And fourth, RCKs support evolving problem-solving abilities along a continuum, ranging from trial and error to heuristic methods associated with robotics study. Furthermore, our synthesis provides insight into the second-order (analogical) uses of RCKs as computational manipulatives in the disciplines of physics and biology. Implications for practice and directions for future research are discussed. (Keywords: computational manipulatives, constructionism, computational thinking, problem solving, robotics, STEM)
This article has two purposes: firstly to introduce this special issue on scaffolding and dialogic teaching in mathematics education and secondly to review the recent literature on these topics as well as the articles in this special issue. First we define and characterise scaffolding and dialogic teaching and provide a brief historical overview of the scaffolding metaphor. Then we present a review study of the recent scaffolding literature in mathematics education (2010–2015) based on 21 publications that fulfilled our criteria and 14 articles in this special issue that have scaffolding as a central focus. This is complemented with a brief review of the recent literature on dialogic teaching. We critically discuss some of the issues emerging from these reviews and provide some recommendations. We argue that scaffolding has the potential to be a useful integrative concept within mathematics education, especially when taking advantage of the insights from the dialogic teaching literature.
Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include “computational thinking” as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new urgency has come to the challenge of defining computational thinking and providing a theoretical grounding for what form it should take in school science and mathematics classrooms. This paper presents a response to this challenge by proposing a definition of computational thinking for mathematics and science in the form of a taxonomy consisting of four main categories: data practices, modeling and simulation practices, computational problem solving practices, and systems thinking practices. In formulating this taxonomy, we draw on the existing computational thinking literature, interviews with mathematicians and scientists, and exemplary computational thinking instructional materials. This work was undertaken as part of a larger effort to infuse computational thinking into high school science and mathematics curricular materials. In this paper, we argue for the approach of embedding computational thinking in mathematics and science contexts, present the taxonomy, and discuss how we envision the taxonomy being used to bring current educational efforts in line with the increasingly computational nature of modern science and mathematics.
The use of quantitative, qualitative, and mixed methods approaches has been foundational to research on emerging adulthood, yet there remain many unresolved methodological issues pertaining to how to handle qualitative data. The purpose of this article is to review best practices for coding and establishing reliability when working with narrative data. In doing so, we highlight how establishing reliability must be seen as an evolving process, rather than simply a focus on the end product. The review is divided into three broad sections. In the first section, we discuss relatively more quantitatively focused methods of coding and establishing reliability, whereas in the second section we discuss relatively more qualitatively focused methods. In the final section, we provide recommendations for researchers interested in coding narrative and other types of open-ended data. This article is intended to serve as an essential resource for researchers working on a variety of topics related to emerging adulthood and beyond.
Various aspects of computational thinking, which builds on the power and limits of computing processes, whether they are executed by a human or by a machine, are discussed. Computational methods and models are helping to solve problems, design systems, and understand human behavior, by drawing on concepts fundamental to computer science (CS). Computational thinking (CT) is using abstraction and decomposition when attacking a large complex task or designing a large complex systems. CT is the way of thinking in terms of prevention, protection, and recovery from worst-case scenarios through redundancy, damage containment, and error correction. CT is using heuristic reasoning to discover a solution and using massive amount of data to speed up computation. CT is a futuristic vision to guide computer science educators, researchers, and practitioners to change society's image of the computer science field.
This paper reports a no-tech coding activity to teach middle school students computational thinking. In this activity students work in teams and walk like a robot to accomplish "programming" tasks.
This paper describes our experiences developing and teaching two different interventions focused on computational thinking and computer science at a yearly STEM outreach program hosted by a local school district. We describe the creation of our lesson plans, how we worked with experienced and pre-service teachers alike to deliver the lessons, and how we assessed the effectiveness of each intervention. We will discuss our successes and failures, and provide information on our future plans to incorporate more formalized education theory, pedagogy, and research methodology in future years to further this project. Based on our assessment results, we observed statistically significant gains in student self-efficacy with creating computer programs that perform a variety of operations. In addition, students reported a significantly higher understanding of how computer programming can be used in daily life. Our survey also highlighted differences in student self-efficacy between the two interventions, and we discuss possible sources for that result. We discuss observed results based on student groups with various backgrounds, previous STEM experiences, and socioeconomic status.
In this article, we investigate the artistic puzzle of designing mathematics experiences (MEs) to engage young children with ideas of group theory, using a combination of hands-on and computational thinking (CT) tools. We elaborate on: (1) group theory and why we chose it as a context for young mathematicians’ experiences with symmetry and transformations; (2) our ME design principles of agency, access, surprise and audience; (3) the affordances of CT that complement our design principles; and (4) three ME variations we tested in grades 3–6 classrooms. We then reflect on the ME variations based on our design principles and the affordances of CT, and consider how the MEs may be further adapted and improved.
There is a great deal of overlap between the set of practices collected under the term “computational thinking” and the mathematical habits of mind that are the focus of much mathematics instruction. Despite this overlap, the links between these two desirable educational outcomes are rarely made explicit, either in classrooms or in the literature. This paper presents Lattice Land, a computational learning environment and accompanying curriculum designed to support the development of mathematical habits of mind and promote computational thinking practices in high-school mathematics classrooms. Lattice Land is a mathematical microworld where learners explore geometrical concepts by manipulating polygons drawn with discrete points on a plane. Using data from an implementation in a low-income, urban public high school, we show how the design of Lattice Land provides an opportunity for learners to use computational thinking practices and develop mathematical habits of mind, including tinkering, experimentation, pattern recognition, and formalizing hypothesis in conventional mathematical notation. We present Lattice Land as a restructuration of geometry, showing how this new and novel representational approach facilitates learners in developing computational thinking and mathematical habits of mind. The paper concludes with a discussion of the interplay between computational thinking and mathematical habits of mind, and how the thoughtful design of computational learning environments can support meaningful learning at the intersection of these disciplines.
Computational thinking describes key principles from computer science that are broadly generalizable. Robotics programs can be engaging learning environments for acquiring core computational thinking competencies. However, few empirical studies evaluate the effectiveness of a robotics programming curriculum for developing computational thinking knowledge and skills. This study measures pre/post gains with new computational thinking assessments given to middle school students who participated in a virtual robotics programming curriculum. Overall, participation in the virtual robotics curriculum was related to significant gains in pre- to posttest scores, with larger gains for students who made further progress through the curriculum. The success of this intervention suggests that participation in a scaffolded programming curriculum, within the context of virtual robotics, supports the development of generalizable computational thinking knowledge and skills that are associated with increased problem-solving performance on nonrobotics computing tasks. Furthermore, the particular units that students engage in may determine their level of growth in these competencies.
This article examines teacher preparation and teacher change in engineering and computer science education. We examined culturally responsive teaching self-efficacy (CRTSE), culturally responsive teaching outcome expectancy (CRTOE) beliefs, and attitudes toward computational thinking (CT) as teachers participated in one of three treatment groups: robotics only, game design only, or blended robotics/game design. Descriptive data revealed that CRTSE gain scores were higher in the robotics only and blended contexts than in the game design only context. However, CRTOE beliefs were consistent across all treatment groups. In regard to CT attitudes, teachers’ gain scores were higher in the game design only and blended contexts than in the robotics only context. In addition, there were differences by treatment group related to STEM (science, technology, engineering, and mathematics) practices, while cultural artifacts were evident in each learning environment. The results of this study reveal some variability by treatment type and inform future research on equitable practices in engineering and computer science education.
Based on a framework of computational thinking (CT) adapted from Computer Science Teacher Association's standards, an instrument was developed to assess fifth grade students' CT. The items were contextualized in two types of CT application (coding in robotics and reasoning of everyday events). The instrument was administered as a pre and post measure in an elementary school where a new humanoid robotics curriculum was adopted by their fifth grade. Results show that the instrument has good psychometric properties and has the potential to reveal student learning challenges and growth in terms of CT.
This paper details a series of pre-professional development interventions to assist teachers in utilizing computational thinking and programming as an instructional tool within other subject areas (i.e. music, language arts, mathematics, and science). It describes the lessons utilized in the interventions along with the instruments used to evaluate them, and offers some preliminary findings.
Computational thinking (CT) is being located at the focus of educational innovation, as a set of problem-solving skills that must be acquired by the new generations of students to thrive in a digital world full of objects driven by software. However, there is still no consensus on a CT definition or how to measure it. In response, we attempt to address both issues from a psychometric approach. On the one hand, a Computational Thinking Test (CTt) is administered on a sample of 1,251 Spanish students from 5th to 10th grade, so its descriptive statistics and reliability are reported in this paper. On the second hand, the criterion validity of the CTt is studied with respect to other standardized psychological tests: the Primary Mental Abilities (PMA) battery, and the RP30 problem-solving test. Thus, it is intended to provide a new instrument for CT measurement and additionally give evidence of the nature of CT through its associations with key related psychological constructs. Results show statistically significant correlations at least moderately intense between CT and: spatial ability (r = 0.44), reasoning ability (r = 0.44), and problem-solving ability (r = 0.67). These results are consistent with recent theoretical proposals linking CT to some components of the Cattel-Horn-Carroll (CHC) model of intelligence, and corroborate the conceptualization of CT as a problem-solving ability. Available at: http://www.sciencedirect.com/science/article/pii/S0747563216306185
While advances in game-based learning are already transforming educative practices globally, with tech giants like Microsoft, Apple and Google taking notice and investing in educational game initiatives, there is a concurrent and critically important development that focuses on ‘game construction’ pedagogy as a vehicle for enhancing computational literacy in middle and high school students. Essentially, game construction-based curriculum takes the central question “do children learn from playing games” to the next stage by asking “(what) can children learn from constructing games?” Founded on Seymour Papert’s constructionist learning model, and developed over nearly two decades, there is compelling evidence that game construction can increase student confidence and build their capacity towards ongoing computing science involvement and other STEM subjects. Our study adds to the growing body of literature on school-based game construction through comprehensive empirical methodology and evidence-based guidelines for curriculum design. There is still debate as to the utility of different software tools for game construction, models of scaffolding knowledge, and evaluation of learning outcomes and knowledge transfer. In this paper, we present a study we conducted in a classroom environment with three groups of grade 6 students (60+ students) using Game Maker to construct their own games. Based on a quantitative analysis and a qualitative discussion we organize results around several core themes that speak to the field of inquiry: levels of computational literacy based on pre- and post-tests; gender-based attitutdes to computing science and programming based on a pre- and post-survey; and the relationship between existing media literacy and performance in programming as part of the game construction curriculum. Significant results include some gender differences in attitudes towards computers and programming with boys demonstrating slightly higher confidence and performance. We discuss the complex reasons potentially contributing to that, particulaly against a diverse ecology of overal media use, gameplay experience and access to technology at home. Finally, we theorize game construction as an educational tool that directly engages foundational literacy and numeracy, and connects to wider STEM-oriented learning objectives in ways that can benefit both boys and girls in the classroom.
Studies of scientists building models show that the development of scientific models involves a great deal of subjectivity. However, science as experienced in school settings typically emphasizes an overly objective and rationalistic view. In this paper, we argue for focusing on the development of disciplined interpretation as an epistemic and representational practice that progressively deepens students' computational modeling in science by valuing, rather than deemphasizing, the subjective nature of the experience of modeling. We report results from a study in which fourth grade children engaged in computational modeling throughout the academic year. We present three salient themes that characterize the development of students' disciplined interpretations in terms of their development of computational modeling as a way of seeing and doing science.
Computer Science and programming are being introduced to school curricula in many western countries in an effort to equip students with Computational Thinking skills. However, as these subjects are still relatively new to pre-tertiary education there is much investigation to be done into how best to present these topics and how to prepare teachers. In this study we focus on the presentation of topics relating to computing, Computational Thinking, and Computer Science for primary schools.
We analyse English-language curricula that have been published, specifically the English, Australian and CSTA curricula for primary schools. From this we establish the main topics covered, and how they are positioned to be suitable for students from the first year of school to approximately their eighth year.
We then report on a pilot study of a curriculum based on Computational Thinking; long term the study will encompass a range of topics and year levels, but the pilot focused on topics suitable for 11 to 12 year old students. Here we detail the design of this part of the curriculum, the manner of its delivery, and the experiences and observations of the generalist teacher who taught the course. Through assessment data, student responses to an attitude survey, and class observations we have evaluated the pilot curriculum. The findings of this study are being used to inform the design of a planned larger scale study.
Current policy efforts that seek to improve learning in science, technology, engineering, and mathematics (STEM) emphasize the importance of helping all students acquire concepts and tools from computer science that help them analyze and develop solutions to everyday problems. These goals have been generally described in the literature under the term computational thinking. In this article, we report on the design, implementation, and outcomes of an after-school program on computational thinking. The program was founded through a partnership between university faculty, undergraduates, teachers, and students. Specifically, we examine how equitable pedagogical practices can be applied in the design of computing programs and the ways in which participation in such programs influence middle school students' learning of computer science concepts, computational practices, and attitudes toward computing. Participants included 52 middle school students who voluntarily attended the 9-week after-school program, as well as four undergraduates and one teacher who designed and implemented the program. Data were collected from after-school program observations, undergraduate reflections, computer science content assessments, programming products, and attitude surveys. The results indicate that the program positively influenced student learning of computer science concepts and attitudes toward computing. Findings have implications for the design of effective learning experiences that broaden participation in computing. (Keywords: computational thinking, programming, middle school, mixed methods)
Computational thinking (CT) draws on concepts that are fundamental to computing and computer science, however, as an approach, it includes practices, such as problem representation, abstraction, decomposition, simulation, verification, and prediction that are also central to modelling, reasoning, and problem solving in many scientific and mathematical disciplines. Recently, arguments have been made in favour of integrating programming and CT with K-12 curricula. In this paper, we present a theoretical investigation of key issues that need to be considered for integrating CT with K-12 science. We identify the synergies between programming and CT on one hand, and scientific expertise on the other. We then present a critical review of literature on educational computing, and propose a set of guidelines for designing learning environments in science that can jointly foster the development of computational thinking with scientific expertise. Finally, we describe the design of a learning environment that supports CT through modelling and simulation to help middle school students learn physics and biology.
The focus of this research was to create and test an introductory computer science course for middle school. Titled “Foundations for Advancing Computational Thinking” (FACT), the course aims to prepare and motivate middle school learners for future engagement with algorithmic problem solving. FACT was also piloted as a seven-week course on Stanford’s OpenEdX MOOC platform for blended in-class learning. Unique aspects of FACT include balanced pedagogical designs that address the cognitive, interpersonal, and intrapersonal aspects of “deeper learning”; a focus on pedagogical strategies for mediating and assessing for transfer from block-based to text-based programming; curricular materials for remedying misperceptions of computing; and “systems of assessments” (including formative and summative quizzes and tests, directed as well as open-ended programming assignments, and a transfer test) to get a comprehensive picture of students’ deeper computational learning. Empirical investigations, accomplished over two iterations of a design-based research effort with students (aged 11–14 years) in a public school, sought to examine student understanding of algorithmic constructs, and how well students transferred this learning from Scratch to text-based languages. Changes in student perceptions of computing as a discipline were measured. Results and mixed-method analyses revealed that students in both studies (1) achieved substantial learning gains in algorithmic thinking skills, (2) were able to transfer their learning from Scratch to a text-based programming context, and (3) achieved significant growth toward a more mature understanding of computing as a discipline. Factor analyses of prior computing experience, multivariate regression analyses, and qualitative analyses of student projects and artifact-based interviews were conducted to better understand the factors affecting learning outcomes. Prior computing experiences (as measured by a pretest) and math ability were found to be strong predictors of learning outcomes.
Both complex systems methods (such as agent-based modeling) and computational methods (such as programming) provide powerful ways for students to understand new phenomena. To understand how to effectively teach complex systems and computational content to younger students, we conducted a study in four urban middle school classrooms comparing 2-week-long curricular units—one using a physical robotics participatory simulation and one using a virtual robotics participatory simulation. We compare the two units for their effectiveness in supporting students’ complex systems thinking and computational thinking skills. We find that while both units improved student outcomes to roughly the same extent, they engendered different perspectives on the content. That is, students using the physical system were more likely to interpret situations from a bottom-up (“agent”) perspective, and students using the virtual system were more likely to employ a top-down (“aggregate”) perspective. Our outcomes suggest that the medium of students’ interactions with systems leads to differences in their learning from and about those systems. We explore the reasons for and effects of these differences, challenges in teaching this content, and student learning gains. The paper contributes operationalizable definitions of complex systems perspectives and computational perspectives and provides both a theoretical framework for and empirical evidence of a relationship between those two perspectives.