Effects of Professional Development on Programming Knowledge and Self-Efficacy

Scholars believe that computational thinking is one of the essential competencies of the 21st century and computer programming courses have been recognized as a potential means of fostering students’ computational thinking. In tradition instruction, PFCT (problem identification, flow definition, coding, and testing) is a commonly adopted procedure to guide students to learn and practice computer programming. However, without further guidance, students might focus on learning the syntax of computer programming language rather than the concept of solving problems. This study proposes a peer-assessment-supported PFCT (PA-PFCT) approach for boosting students’ computer programming knowledge and computational thinking awareness. A quasi-experiment was conducted on a computer programming course in a high school to evaluate its influence on students’ learning achievement, computational thinking awareness, learning motivation, and self-efficacy. An experimental group of 51 students learned with the proposed approach, while a control group of 49 students learned with the traditional PFCT (T-PFCT) approach. The experimental results show that the proposed approach significantly enhanced the students’ computational thinking awareness, learning motivation, and self-efficacy, while not having significant impacts on their computer programming knowledge test scores.

Seventeen Sustainable Development Goals (SDGs) stated by the United Nations include a call for Gender Equality, emphasizing the challenges women face in male-dominated fields such as computer science (CS). Introducing programming at an early age can help girls perceive computer science as enjoyable and accessible. This study presents an example of interdisciplinary collaboration and provides empirical evidence on the positive impact of STEAM (Science, Technology, Engineering, Arts, and Mathematics) integration in robotics programming for female students. The purpose of this study was to examine how interdisciplinary STEAM-based robotics programming activities influence secondary school female students’ programming self-efficacy and computational thinking (CT) self-efficacy. The research employed a single-group pretest–posttest experimental design with 60 seventh-grade female students from a public school in Türkiye. Over six weeks, students participated in a robotics programming course using mBlock, supported by STEAM-themed tasks across science, technology, mathematics, and design curricula. Data were collected using two validated instruments: the Computer Programming Self-Efficacy Scale (CPSES) and the Computational Thinking Skills Self-Efficacy Scale (CTSSES). Paired samples t-tests revealed statistically significant improvements in both programming and computational thinking self-efficacy scores after the intervention (p < 0.05). These findings support the effectiveness of interdisciplinary, STEAM-based pedagogies in enhancing female students’ engagement and confidence in computing. The study highlights the importance of inclusive educational strategies in narrowing the gender gap in computer science education.

The number of undergraduates entering computer science has declined in recent years. This is paralleled by a drop in the number of high school students taking the CS AP exam and the number of high schools offering computer science courses. The declines come at a time when career opportunities in CS continue to grow and computer science graduates are seen as crucial in building a globally competitive workforce for the 21st century. Efforts aimed at reversing the declining interest in computer science include curriculum revisions at the undergraduate level at many institutions, a re-design of computer science AP courses [1], and the inclusion of computational thinking into disciplines outside computer science [3].This panel discusses four projects of computer science researchers collaborating with high school teachers on integrating computing and computational thinking into their courses. The majority of the high school teachers involved is teaching science and math courses. They are teaching a diverse group of talented and college-bound students. The goal of all projects is to integrate computing into disciplines represented in the high school curriculum and to raise the awareness of computer science as an exciting and intellectually rewarding field.This panel will outline recent and on-going activities and interaction with high school teachers. Each panelist will describe how he/she got involved and the nature of the interaction. The panelists will talk about their individual projects, outline their visions for future interactions, and how their effort can be replicated by others. The session will briefly describe NSF's RET program which provided teacher support for three of the four projects. The session will then be opened for discussion; the audience will be encouraged to ask questions and contribute additional ideas for the inclusion of computational thinking in high school courses.

This study investigates the integration of Computational Thinking (CT) into STEAM education, particularly focusing on Mathematics and Professional Development (PD) for educators. Through a systematic review conducted across several databases, we analyzed 40 articles on the current state of Professional Development in CT within STEAM subjects, emphasizing definitions and their integration into existing curricula. We focused on scientific papers that examined the relationship between the studied concepts (CT, Computer Science - CS, and Math), excluding those that solely focused on CT or CS. We applied a dual review protocol to ensure accuracy and reduce the risk of bias. Our findings reveal a strong emphasis (82.5%) on curriculum integration. Interestingly, pre-service and in-service teachers are disproportionately targeted, while university-level training remains limited (5%). Additionally, a growing trend highlights an interest in exploring the synergy between Computer Science and CT and underscores CT PD’s infancy within STEAM education. Furthermore, the study identifies a surprising need for increased reference (25%) to pioneering figures like Papert and Wing in the existing literature. The methodology employs keyword analysis and the Jaccard index to measure concept similarity. This study uniquely focuses on studying the reported transfer of CT knowledge and definition in the context of PD. It offers a new perspective on the reported envisioned relationship between CT and CS when preparing and delivering PD. It also identifies gaps, preferences in teacher training, and opportunities for enhancing CT integration in STEAM education. It emphasizes the need for improved Professional Development and clearer definitions to effectively integrate CT into STEAM education, particularly at the university level, and provides recommendations for both educators and policymakers.

Promoting computational thinking is a priority in CS education and other STEM and non-STEM disciplines. Our innovative, NSF-funded IC2Think project blends computational and creative thinking. In Spring 2013, we deployed Computational Creativity Exercises (CCE) designed to engage creative competencies (Surrounding, Capturing, Challenging and Broadening) in an introductory CSI course for engineering students. We compared this CCE implementation semester (80 students, 95% completing 3 or 4 CCEs) to the Fall 2013 semester of the same course (55 students) without CCEs. CCE implementation students had significantly higher scores on a CS concepts and skills knowledge test (F(1, 132) = 7.72, p < 01, partial Eta2 = .055; M=7.47 to M=6.13; 13 items) and significantly higher self-efficacy for applying CS knowledge in their field (F(1, 153) = 12.22, p < .01, partial Eta2 = .074; M=70.64 to M=61.47; 100-point scale). CCE implementation students had significantly higher study time (t(1, 136) = 2.08, p = .04; M=3.88 to M=3.29; 7-point scale) and significantly lower lack of regulation, which measures difficulties with studying (t(1, 136) = 2.82, p = .006; M=2.80 to M=3.21; 5-point scale). The addition of computational creativity exercises to CS courses may improve computational thinking and learning of CS knowledge and skills.

In this study, the authors constructed structural equation models in order to determine the relationship between students’ learning attitudes and their computational thinking perspectives and programming empowerment. The purpose is to understand students’ perceived competence to use computational thinking effectively, along with their computer programming learning attitude regarding the C++ programming language for one semester (2 hours per week, 36 total learning hours). A total of 495 students specializing in the medical field participated in the study. Structural equation models were constructed according to three adapted scales: the computer programming learning attitude scale, the computational thinking perspectives scale, and the programming empowerment scale. The computer programming learning attitude scale is based on three factors: willingness, negativity, and necessity. The computational thinking perspectives scale also considers three factors: the ability to express, the ability to connect, and the ability to question. The programming empowerment scale is composed of four factors: meaningfulness, impact, creative self-efficacy, and programming self-efficacy. The results showed that a positive learning attitude will positively affect computational thinking perspectives and programming empowerment. However, when students have a negativity attitude, feeling that they are being forced to learn the C++ programming language, their computational thinking perspectives and programming empowerment will be negatively affected. In order to promote students’ learning attitude, various teaching strategies, teaching curriculum design, and pedagogy design could be further explored.

Across the world there has been a paradigm shift in school education, as many countries are incorporating Computer Science (CS), programming, and Thinking (CT), into their K-12 curriculums for the first time. In 2018 these subjects will be introduced to the New Zealand (NZ) Digital Technologies curriculum under the subject of Computational Thinking. Like the majority of countries who have introduced these topics, NZ faces challenges in preparing teachers, and in successfully implementing a curriculum which achieves its educational goals. To support this curriculum, we have been conducting studies in primary schools across NZ, trialing resources with teachers and students. Building on a 2014 exploratory study on CS and programming in intermediate school, this project investigates the existing assumptions around CT education in K-12. It aims to address the specific questions: How do we teach CT concepts and approaches to primary aged students? If they learn CT, does it have the expected positive impacts on students learning? And, what other positive and negative impacts does this have? Throughout 2015 and 2016 a study was conducted with 18 primary school teachers from across NZ, who used CS Unplugged and educational programming languages in their classrooms. Teachers submitted feedback on these classes through an online form, and participated in semi-structured interviews. The feedback responses and interview transcripts were analysed using a thematic approach, which revealed many positive impacts on students general learning, minimal negative impacts, and observations of CT development.

Enhancing elementary school students' computational thinking and programming learning with graphic organizers

In this paper, we propose the computational thinking education framework which provides three steps of computational thinking process and three kind of activities about computational thinking learning in class. The key idea of this framework is to provide the guidelines of designing activity steps of teaching and learning computational thinking in class using three axles of framework such as problem area, process of learning, and steps of computational thinking process. After designing a framework, we show that sample course of programming education program containing contents of Informatics subject in middle school by implementing our framework. Proposed framework and programming education program in middle school will be the good case study and guide to implement computational thinking concerned education programs in elementary, secondary, and universities.

Admittedly, the teaching and learning of programming courses in the computer science and information technology programs have been extremely challenging. Currently, most instructors depend on either the problem-solving technique or the metacognitive technique to help students develop a range of cognitive skills, including metacognitive skills, which are important in the development of a strong computational thinking skill required for 21st-century learning. Studies focusing on the practices of instructors in using both techniques are scarce, thus motivating the researchers to carry out this study. This study was based on a qualitative approach involving a case-study design in which five (5) male and five (5) female instructors were selected from 10 pre-university centers in Malaysia as the respondents and participants in an intervention program. The research instruments used were an interview checklist and intervention guidelines. As anticipated, the findings showed that the activities of each technique could only help students develop certain sub-skills of the computational thinking skill, thus underscoring the need for instructors to integrate both techniques in their teaching practices. Thus, it could be reasoned that using either the metacognitive technique or the problem-solving technique alone would not be sufficient to help students develop strong computational thinking skills, as each technique has its strengths and weaknesses. Therefore, it becomes imperative for instructors to leverage the strengths of both techniques by integrating both of them in the teaching and learning of programming courses.

Computational Thinking (CT) involves fundamental concepts and reasoning, distilled from computer science and other computational sciences, which become powerful general mental tools for solving problems, increasing efficiency, reducing complexity, designing procedures, or interacting with humans and machines. An easy-to-understand guidebook, From Computing to Computational Thinking gives you the tools for understanding and using CT. It does not assume experience or knowledge of programming or of a programming language, but explains concepts and methods for CT with clarity and depth. Successful applications in diverse disciplines have shown the power of CT in problem solving. The book uses puzzles, games, and everyday examples as starting points for discussion and for connecting abstract thinking patterns to real-life situations. It provides an interesting and thought-provoking way to gain general knowledge about modern computing and the concepts and thinking processes underlying modern digital technologies.

This study compares computational thinking skills evidenced by two groups of students in two different secondary schools: one group per school was studying a qualification in Computer Science. The aim was to establish which elements of computational thinking were more prevalent in students studying Computer Science to a higher level. This in turn would evidence those elements likely to be present from their earlier computing education or through their complementary studies in Science or Mathematics, which all students also studied. Understanding this difference was important to identify any increased competence in computational thinking that was present in the Computer Science groups. Artefact-based interviews were carried out using questions and practical computing problems designed to elicit and demonstrate the students’ computational thinking skills based on the Brennan and Resnick (2016) model of computational concepts, practices and perspectives. Analysis of students’ responses showed surprisingly little difference between the computational thinking practices of the two groups in relation to abstraction, decomposition, evaluation, generalisation/reusing, logical reasoning and debugging/testing. The study concludes that general computational thinking skills can be developed either at a lower level of study or in cognate curriculum areas, leaving computer science as the rightful locus of computational thinking for automation.

Incorporating computational thinking (CT) ideas into core subjects, such as mathematics and science, is one way of bringing early computer science (CS) education into elementary school. Minimal research has explored how teachers can translate their knowledge of CT into practice to create opportunities for their students to engage in CT during their math and science lessons. Such information can support the creation of quality professional development experiences for teachers. We analyzed how eight elementary teachers created opportunities for their students to engage in four CT practices (abstraction, decomposition, debugging, and patterns) during unplugged mathematics and science activities. We identified three strategies used by these teachers to create CT opportunities for their students: framing, prompting, and inviting reflection. Further, we grouped teachers into four profiles of implementation according to how they used these three strategies. We call the four profiles (1) presenting CT as general problem-solving strategies, (2) using CT to structure lessons, (3) highlighting CT through prompting, and (4) using CT to guide teacher planning. We discuss the implications of these results for professional development and student experiences.

Computational thinking (CT) is a critical set of 21st century skills that young learners must develop to be successful in contemporary work and life. As more K-12 schools begin to integrate CT into the curriculum, elementary preservice teachers (EPSTs) must be prepared to teach CT to their future students. Therefore, elementary teacher preparation programs should explore ways to incorporate CT into their coursework, ensuring that EPSTs graduate with the necessary knowledge and skills to teach CT. This study investigates the impacts of a three-week CT module implemented in a technology integration course in an elementary teacher preparation program on EPSTs’ CT value beliefs, self-efficacy, and teaching efficacy. The purpose of the module was to introduce EPSTs to basic concepts and big ideas in CT, support their application of CT in block-based coding environments, and promote connection building between CT and authentic real-world scenarios that balance different types of CT activities. Guided by the Interconnected Model of Professional Growth (IMPG), this study examined EPSTs’ learning as a dynamic process of change across the personal and external domains. The module was located in the external domain as a stimulus for learning, while the Teacher Beliefs about Coding and Computational Thinking (TBaCCT) instrument was used to assess changes in value beliefs, self-efficacy, and teaching efficacy within the personal domain. A convergent parallel mixed-methods design was used to analyze pre- and post-surveys administered to 50 EPSTs and semi-structured interviews with four of the EPSTs. The results showed that the beliefs of the CT value of EPSTs evolved and their self-efficacy and teaching efficacy of CT significantly improved after participating in the module, suggesting that the interaction between external learning experiences and internal belief systems - facilitated by reflection and action - contributed to early professional growth. Notably, EPSTs also developed a more accurate understanding of CT, recognized the benefits of both plugged and unplugged CT activities, and expressed a desire for continued CT learning and professional development. Although EPSTs expressed concerns with the scarcity of physical computing toys in schools, they demonstrated a commitment to incorporating CT activities into their teaching and exploring alternative funding avenues to acquire such resources. Practical implications include potential approaches for elementary teacher preparation programs to embed CT into existing curricula.

Computational Thinking is a skill that plays a significant role in improving students' skills, achievements, and global competitiveness. This research aims to determine the Computational Thinking abilities of preservice physics teachers for each indicator by creating a simulation using the Scratch application. This research is a descriptive qualitative study. The respondents involved in the research were 10 pre-service physics teachers at Khairun University. The respondents are students who have taken Computer Programming courses. The saturated sampling technique was used to determine the respondents. The data collection technique for this research is a test. The instrument used is a simple project to simulate projectile motion. The results of this research show that all students were able to complete the abstraction and generalization components perfectly. Furthermore, in the decomposition and algorithmic thinking components, two students made incorrect commands in the Scratch application. However, after the interview, it was revealed that the error was not due to their lack of understanding of physics concepts, but rather due to the limitations of mathematical operations in the Scratch application. Importantly, several students explained that most of the Computational Thinking components had already been developed through their habit of solving physics phenomena cases. Therefore, it can also be concluded that Computational Thinking can train students to solve physics problems effectively.