Youth Hackathons in Computing for the Community: A Design Case

Hospitals increasingly promote clinically expert, postgraduate-prepared nurses into first-line administration, yet the transition from bedside to leadership is often under-supported. This descriptive phenomenological study explored early career growth among ten novice nursing administrators (nine head nurses, one nursing-quality officer) in a tertiary public hospital in Henan Province, China. Semi-structured interviews (32-70 minutes) were analyzed with Colaizzi’s method in NVivo 12. Trustworthiness was strengthened through member checking, peer debriefing, external audit, triangulation of field notes and reflexive journals, and thick description. Four themes emerged: (1) Challenges encountered in nursing management process; complicated in administration (competing role demands), challenges in innovation, challenges in communication and coordination, and lack of administration and professional experience; (2) Growth in nursing administration process; cognitive transformation in nursing profession, improvement of administration ability, and developing psychological quality (resilience); (3) Advisement for other novice nursing administrators; prepare for role transition, advance professional competence (build technical credibility), seek support actively (mentorship and networks), and investing in higher education (appropriately leverage postgraduate education); and (4) Suggestions for nurses with postgraduate degrees; clarify future career direction, maintain original intentions, avoid assimilation, be willing to dedicate and integrate into the team, and develop versatility, pursue continuous learning. A “mountain-journey” simulacrum integrates Self-Leadership Theory, Benner’s Novice-to-Expert model, and McClelland’s Human Motivation Theory to depict progression from instability to a consolidated leadership identity. Postgraduate preparation confers advantages, but does not substitute for structured transition support; institutions should formalize mentorship, implement competency-based orientation, and align incentives with innovation and evidence-based practice to accelerate safe, confident leadership among novice nurse administrators.

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.

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.

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.

The computer science education research community has thought deeply about how students learn computational thinking (CT) as it relates to other domains of computer science (CS; e.g. programming) and core content areas (STEM, humanities), but less work has examined the role of CT in pathways to computer science for K-5 teachers. This panel examines the experiences of practitioners - educators, administrators, and curriculum designers--who have both experienced and supported others in incorporating CT in elementary school settings as a pathway to or component of computer science education. All panelists have worked with teachers not previously trained to teach CS and have encountered the many opportunities and difficulties of bringing CS to in-service teachers. They will reflect on the multiple ways educators grapple with CT: as an entry point to computer science, as a way to enrich core disciplines, and as a way to support equitable practice - for example, several of the panelists have experiences leveraging CT and other domains of CS to support the expression and development of emergent bilingual students. The panel will explore ways in which CT and its associated language and strategies for problem solving may provide a particularly helpful onramp to CS generally, including integration with other disciplines and with language about academic skills more generally.

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.

The purpose of this study was to explore the nine components of computational thinking (CT) practices and their operational definitions from the view of science education and to develop a CT practice framework that is going to be used as a planning and assessing tool for CT practice, as it is required for students to equip with in order to become creative problem solvers in 21st century. We employed this framework into the earlier developed STEAM programs to see how it was valid and reliable. We first reviewed theoretical articles about CT from computer science and technology education field. We then proposed 9 components of CT as defined in technology education but modified operational definitions in each component from the perspective of science education. This preliminary CTPF (computational thinking practice framework) from the viewpoint of science education consisting of 9 components including data collection, data analysis, data representation, decomposing, abstraction, algorithm and procedures, automation, simulation, and parallelization. We discussed each component with operational definition to check if those components were useful in and applicable for science programs. We employed this CTPF into two different topics of STEAM programs to see if those components were observable with operational definitions. The profile of CT components within the selected STEAM programs for this study showed one sequential spectrum covering from data collection to simulation as the grade level went higher. The first three data related CT components were dominating at elementary level, all components of CT except parallelization were found at middle school level, and finally more frequencies in every component of CT except parallelization were also found at high school level than middle school level. On the basis of the result of CT usage in STEAM programs, we included ‘generalization’ in CTPF of science education instead of ‘parallelization’ which was not found. The implication about teacher education was made based on the CTPF in terms of science education.

The concept of computational thinking originated in the 1950s and 1960s as “algorithmic thinking” (Denning, 2009), which involves using a systematic and precise sequence of steps to solve problems, potentially using computers to automate the process. Today, 'computational thinking' is defined as is a solving problem process that involves formulating problems and solutions in a way that can be represented and solved through a series of computational steps, designing systems and understanding human behaviour, based on fundamental computer concepts. It includes processes such as abstraction and decomposition when dealing with complex tasks or designing extended systems (Wing, 2006). From an educational point of view, the challenge is to identify the cognitive skills that are expected of a person with this type of thinking and their ability to apply them in practice. Computational thinking encompasses a set of thought processes that originate from computer science, but are applicable in various fields. However, it is often wrongly perceived as “technological thinking”, which implies a mindset aimed exclusively at the effective use of technologies. The contribution points out that the lack of a clear definition hinders the integration of this concept into teacher training and broader educational contexts. If understood correctly, computational thinking could significantly improve understanding of the procedural aspects of knowledge, which are very useful for teaching. In this sense, the contribution also describes an exploratory research on the opinions of primary school teachers in central Italy aimed at understanding the perceived benefits that the incorporation of computational thinking could bring in a teaching context.

Science, Technology, Engineering, and Math (STEM) and Computer Science (CS) are the driving forces of the United States prosperity. While there is a high demand to close the gap in STEM+CS jobs, there is little research in K-12, especially in K-5 level. Elementary teachers lack of self-confidence in STEM+CS and there is limited number of teacher training. Here, Integrating Computational Thinking (CT) in elementary science classrooms comes into prominence. International Society for Technology in Education (ISTE), Computer Science Teachers Association (CSTA) and Next Generation Science Standards (NGSS) emphasize that CT learning is an important part of the elementary curriculum. It can be translated that elementary science teachers should have the self-efficacy, interest, and confidence to integrate CT into their teaching. It is not an easy task to expect such a demand from pre-service elementary science teachers (PST) unless necessary training is provided. It leads us to modify our elementary science teaching methods course to integrate CT to improve PST’ CT self-efficacy beliefs, interest, and confidence in elementary science teaching. The goal of our research is to investigate the changes in PST’ CT teaching efficacy beliefs, interest, and confidence after participating in CT training as part of an undergraduate elementary science teaching methods course. We have found that our course improved PST’ CT self-efficacy, interest, and coding confidence.

Computational thinking is a new concept that is hardly known by most ordinary Malaysians. On a positive note, in 2017, the Ministry of Education of Malaysia implemented a new curriculum by introducing two new secondary school subjects, namely Fundamental of Computer Science and Computer Science. These subjects contain five components of computational thinking called ‘techniques, which are taught to Form 1 and Form 4 students, respectively. Likewise, the Department of Teachers Education of Malaysia also introduced six components of computational thinking in its training programs. In contrast, there is a lack of attention to such a concept given to tertiary education. A preliminary survey was conducted in early 2019, which involved 50 students majoring in 21 educational programs. The findings showed 92% of the respondents had no knowledge regarding the computational thinking skill, signifying an urgent need to determine relevant components that characterize such a skill needed in educational programs, which according to Wing (2006) has numerous components. In this study, the researchers aimed to identify relevant components that characterize the computational thinking skill required for students in learning educational programs. An extensive review of documents published in leading online databases, such as IEEEXplore, Science Direct, and Web of Science, was carried out that yielded 116 articles. Further analysis reduced this number to 29 articles that were related to the characterization of the computational thinking skill with 66 components. Among these components, algorithm, abstraction, and decomposition were the top three components with the highest frequency of being cited in the selected articles, registering percentage points of 9.78%, 7.41%, and 5.35%, respectively. As such, the design and development of new instructional approaches for the teaching of educational programs should emphasize three components to help students develop strong computational thinking skills.

The World Health Organization recently launched a global campaign to end ageism due to its widespread, insidious negative health impacts on older adults. Similarly, racism is a key driver of health disparities and has been declared a public health crisis by jurisdictions around the United States. While a strong literature summarizes coping theory in general as well as beneficial and maladaptive coping mechanisms among older adults, limited research describes how older adults cope with experiences of ageism and racism, particularly through an intersectional lens. The aim of this qualitative, phenomenological study was to understand how older adults cope with intersectional experiences of ageism and racism. Twenty adults 60+ residing in the U.S. Mountain West who identified as Black, Hispanic/Latino(a), Asian-American/Pacific Islander, Indigenous, or White participated in a one-hour, semi-structured interview. A team of five coders engaged in an inductive coding process through independent coding followed by critical discussion. Peer debriefing, member checking, and an audit trail enhanced credibility. Nine themes were identified: 1) resistance, 2) exhaustion, 3) acceptance/‘let it go,’ 4) avoidance, 5) increased awareness through aging, 6) help others, 7) educate others, 8) self-determination/defy stereotypes, and 9) healthy lifestyle. These themes exemplify problem-focused and emotion-focused, as well as individual and collective coping strategies. Novel findings include how older adults may cope with ageism and racism through helping peer older adults and via increased awareness through aging. Practitioners should recommend coping strategies which combine collective and problem-focused responses to ageism and racism such as resistance, helping others, and educating others.

Computational thinking (CT), which encompasses strategies for problem analysis and solution design, is highly applicable in all STEM disciplines, including computer science, for learning concepts as well as solving problems. Yet, the exposure of K-12 students to CT in many schools is practically non-existent. For students to acquire this important skill, teachers require in-depth knowledge of the problem solving strategies that define CT, and strategies for integrating CT into their lesson plans. The proposed special session will be both a tutorial on CT and an interactive session for sharing the experience and results from a CT workshop held at Columbus State University for middle and high school STEM subject teachers. This workshop, offered as a part of the ACT4STEM (Applying Computational Thinking for STEM Disciplines) project, took place in the summer of 2015. It brought together teachers from the metropolitan Columbus area in Georgia with priority given to teachers from high-need schools (as determined by the GA Department of Education [1]). The workshop introduced the participants to CT concepts and demonstrated how CT strategies of pattern recognition, generalization, problem decomposition and algorithmic thinking can be used to improve student learning of STEM concepts. The proposed special session will present sample CT modules developed for the ACT4STEM workshop in the form of a tutorial and projects and lesson plans designed by participants during the workshop. It will include interactive, hands-on activities and discussions in addition to results from the teachers' actual experiences on applying these lesson plans in their classes. This special session will benefit K12 teachers of STEM subjects interested in improving their students' comprehension of discipline related concepts and their application. Moreover, computer science faculty interested in helping K-12 teachers by organizing training sessions will gain valuable insights from the first-hand accounts of the presenters of their own experience with such an effort.

Computational thinking has become a interesting subject and important concept in education throughout the nation. Computational Thinking (CT) has been defined as an important skill as digital literacy that must be learned by next generation. Along with the need to make an agreed definition of CT many countries are still in the process of, or have not started, introducing CT into the curriculum at all levels of education. It was also found in Indonesia that Computer Science / Computing, which could be the most obvious place to teach CT, has not been the main subject in several schools. This research aim is to design an alternative CT learning media to study interestingly and effectively computational concept which consists of 4 elements, namely decomposition, abstraction, pattern recognition and algorithm. Research and Development followed by ADDIE development model (Analysis, Design, Development, Implementation and Evaluation) is used to capture the problem, identify the user need to be implemented in digital media. This learning media application product is equipped with an educational game based on computational thinking. The media has several features such as presentation of material and examples of problems and the solution, and small challenges in a games consisting of 3 stages. The subjects of this study were students of K-12. The data used for analysis was collected in several ways, including observation, questionnaire, pre-test and post-test in similar question. The result is the use of CT learning media is very helpful to improve students' understanding of CT in problem solving even in different topics.

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.

As schools and districts across the United States adopt computer science standards and curriculum for K-12 computer science education, they look to integrate the foundational concepts of computational thinking (CT) into existing core subjects of elementary-age students. Research has shown the effectiveness of teaching CT elements (abstraction, generalization, decomposition, algorithmic thinking, debugging) using non-programming, unplugged approaches. These approaches address common barriers teachers face with lack of knowledge, familiarity, or technology tools. Picture books and graphic novels present an unexplored non-programming, unplugged resource for teachers to integrate computational thinking into their CT or CT-integrated lessons. This analysis examines 27 picture books and graphic novels published between 2015 and 2020 targeted to K-6 students for representation of computational thinking elements. Using the computational thinking curriculum framework for K-6, we identify the grade-level competencies of the CT elements featured in the books compared to the books’ target age groups. We compare grade-level competencies to interest level to identify each CT element representation as “foundational,” “on-target,” or “advanced.” We conclude that literature offers teachers a non-programming unplugged resource to expose students to CT and enhance CT and CT-integrated lessons, while also personalizing learning based on CT readiness and interest level.