The adoption of Computational Thinking (CT) in the educational worldwide curricula is progressively gaining importance from various perspectives. One particular approach, known as unplugged, does not require electronic devices and offers notable benefits as it is replicable and adaptable. Moreover, it serves to dismantle the misconception that computer science is exclusively confined to the digital realm. While both plugged and unplugged methodologies are recognized, further exploration of the unplugged approach is required, especially in Upper Secondary Education, where there is less evidence of its effectiveness. This paper presents a summary of a quasi-experimental study conducted with 11th grade students (approximately 16 years old) in a Spanish public high school. 57 students participated: 28 in the control group and 29 in the experimental group. The conducted research, based on a quantitative and experimental design, aimed to investigate the effectiveness of unplugged activities to improve CT abilities in Upper Secondary Education. The results indicated improved skills in the experimental group, suggesting the potential efficacy of unplugged methods in fostering CT abilities.
The underrepresentation of women in computing science is a persistent issue, heightend by cultural stereotypes and a lack of female role models. This poster investigates the impact of a gender-sensitive career orientation narrative in addressing this problem by examining teachers’ attitudes. The narrative, featuring a female protagonist exploring computing science careers, aims to inspire and educate students. Semi-structured interviews with six teachers revealed positive feedback on the narrative’s authenticity and its potential to create role models. Female teachers appreciated the focus on female characters, while some male teachers suggested broader diversity inclusion. This pilot study underscores the need for a more inclusive approach to diversity in educational materials and highlights the potential of gender-sensitive career orientation narratives to empower female students and challenge stereotypes in computing science careers. Future research should consider the intersectionality of gender with other factors such as race and disability, as well as reassess teachers’ attitudes and evaluate student attitudes.
Teaching programming requires the use of a programming tool (PT) for the classroom. Utilising the strengths of said PT and offsetting its weaknesses requires teachers to analyse the PT taking into account both specific computer science (CS) and teaching aspects - or in other terms CS related pedagogic content knowledge (CS-PCK). This poster presents the results of an exploratory, qualitative study that leads to a suggestion for categorising this knowledge. Results hint at areas where the alignment of perspectives of teachers and teacher educators could be improved.
Introducing programming to non-majors is challenging. To increase accessibility, Ozobots are integrated into an introductory programming class for grammar schools focusing on economic topics (Economics major). Besides a description of how to integrate the tool, a comparison of students’ learning outcomes exposed to Ozobot-assisted instruction with those using traditional programming tools is described. Therefore, three classes were assessed with a pre-/post-test on basic algorithmic competencies. The results highlight the potential of robotics in programming education and emphasize the importance of hands-on, experiential learning for fostering a deeper understanding of algorithmic design and programming concepts.
In Aotearoa New Zealand, assessment of programming for the national NCEA standards is carried out manually by teachers, many of whom are not experienced programmers. In an attempt to decrease teacher workload, we have adapted Moodle CodeRunner [23] to assess a widely used recently released high school programming standard. This paper explores in detail how we have automated each criterion of the new standard, including dealing with judgement calls for the more subjective criteria. We then report on interviews with experienced programming teachers who were shown example tasks from our system, as well as model answers for each example. We found that teachers were enthusiastic about using automated assessment to assess the standard, and while there wasn’t one agreed upon interpretation of the standard, teachers were happy with how the system supported marking. We also found no universal agreement among the level of context desired in programming questions to assess the standard, despite the small sample size. These interviews have given us confidence to both release these examples to teachers across New Zealand, many of whom are struggling with how to teach the standard, and to move forward with the pilot of our automated assessment system.
We describe our experience introducing computational thinking skills at teacher colleges through project-based learning (PBL). We have designed projects that use technology to tackle driving questions derived from the national school curriculum, and at the same time are aligned with learning objectives from pre-service teacher training programs. We have carried out a preliminary validation of these projects with teacher educators, who are now incorporating these experiences into their courses with pre-service teachers.
Novice programmers often start their learning journey with block-based editors, to later focus on traditional text-based editors. The transition between these two different editing paradigms is notably known to be difficult, as students may not easily transfer the knowledge they acquired while using blocks to the textual counterpart in a text-based editor, and in a programming language that differs in syntax. In a response to facilitate this transition, Strype, an online editor for Python, proposes an intermediate approach using frame-based editing that combines the safeguards and simplicity of the blocks, with the flexibility and realism of the text. With educational purposes in mind, Strype can be used to create different kinds of applications. This poster aims to briefly (1) introduce the advantages of frame-based editing when transitioning from blocks to text, and (2) present Strype core environment principles along with (3) the different kinds of applications students can create using Strype to learn Python: console-based, Turtle Graphics, or micro:bit.
Problem. With the expansion of K-12 Computer Science (CS) education across the United States, some schools are actively integrating CS into elementary schools (K-5). To successfully introduce CS into K-5 classrooms and integrate it into existing subjects like mathematics and literacy, understanding the key barriers to successful integration is necessary for paving the way for future adoption. However, little is still known about extrinsic barriers within the K-5 classroom and how they can be overcome. Research Question. Our research question for this study was What are the extrinsic barriers associated with integrating computer science in the elementary grade levels? Method. We conducted a mixed methods study, including a survey (n = 160) and a set of focus groups (n = 23) with decision makers in education. We synthesized the results, deriving categories within extrinsic. Findings. We found eight categories of extrinsic barriers: lack of physical resources, lack of curriculum, lack of funding, limited professional development, limited administrator knowledge about CS, limited time to plan and teach, lack of local policies and priorities, and limited community support. Implications. The majority of these barriers are not new and educators can lean on past practices for mitigating barriers. Researchers can also focus their studies on efforts where barriers still remain, such as how to plan, teach, and assess computing integrated with other K-5 subjects.
Game design is often considered a motivational approach to get young children interested in programming and computational thinking. However, while the idea of game programming may be compelling from an educational point of view, creating games with interesting interactions that are actually fun to play remains challenging. Modern tools aimed at novice programmers should empower their users to create games, such as Pac-Man, that approach or even exceed the gameplay of 1980's arcade games. By adding a high-level AI pathfinding block to the RULER.game tool, 13 students in grades 1-4 attempted to build Pac-Man-like games. The findings suggest that all students were able to create Pac-Man-like games with compelling gameplay interactions, including ghosts finding the shortest path through complex mazes to Pac-Man, multiple ghosts collaborating with each other, and sophisticated game world topologies featuring toroidal portals.
While experts disagree on whether large pretrained language models (LLMs) understand human language, youth use, play, and experiment with LLM-powered applications every day. Yet little attention has been given to young people’s perspectives on LLMs’ capacity for understanding and the ethical implications of synthetic texts produced by these systems. We conducted a participatory design session using big paper methods with 18 14-15-year-olds in which they (1) interacted with ChatGPT (GPT 3.5) and (2) prompted it with commonsense questions. We examined youths’ big papers, prompts, and conversations during the activity. Our analysis shows that youth had conflicting views on GPTs’ language comprehension and task completion, as well as synthetic text’s ethical implications with regards to misinformation, privacy, and safety. We discuss how these findings could inform the design of learning activities.
The landscape of education research and practice is undergoing significant socio-political transformation, driven by evolving heightened awareness and perceptions of what is meant through efforts to ensure that all students benefit from education. This keynote explores these changes in the context of primary and secondary computer science education. By analyzing policy shifts, advocacy movements, and grassroots initiatives, we uncover the ways in which education systems are being restructured and how this restructuring may influence future innovation and workforce development. Additionally, this keynote highlights the challenges and opportunities faced by researchers and practitioners in navigating these dynamic environments.
Although computing is increasingly taught to K-5 students, females and certain ethnic groups are underrepresented in examinations and careers. Disparities have been attributed to students feeling a disconnect between their identities and the computing stereotype. Culturally responsive teaching has been used in the US to adapt resources to start to address these disparities, but less so in England, particularly for K-5 classroom contexts. This study investigates the ways in which K-5 teachers in England adapt existing computing teaching resources to be more culturally responsive. Building on ten culturally responsive teaching prompts (called Areas of Opportunity (AOs)) and a sociocultural identity theory, funds of identity (FoI), we ask RQ1: In what ways do K-5 teachers collaboratively adapt resources to deliver culturally responsive computing teaching? and RQ2: What does a funds of identity analysis reveal about computing resource adaptations? Researchers and 12 teachers collaboratively adapted a set of computing lessons. Interviews were conducted with the teachers post-lesson delivery, and thematically analysed to identify seven culturally responsive adaptation themes. Teachers reported that students drew most on practical funds of identity (e.g., football, drawing), but support was needed, e.g., discovering lower socioeconomic background students' hobbies. Teacher adaptations aligned with other culturally responsive resources and all ten AOs were useful for identifying potential adaptations. But a prompt to foster community development was found to be missing. The significant contribution from this study is to introduce FoI, not used before in our context. We suggest FoI provides a nuanced view of identity that may be useful to teachers, resource developers, and researchers to reduce identity disparities in computing.
One of the central challenges of task design for an English-speaking informatics class in German schools is the transfer of the compulsory, curriculum-based instructional verb set (IVS) into the English language. Simply translating each verb overlooks the fact that students might have learnt different approaches to an instructional verb in their English classes; hence, a thorough consideration of both IVS’, English and informatics, is mandatory. In order to spark discussions on the matter, we propose a first set of instructional verbs for a bilingual informatics class which attempts to be in line with both curricula.
In recent years, there has been a growing interest in exploring the capabilities of AI chatbots, such as ChatGPT. Studies have investigated diverse applications, including the response of AI chatbots to undergraduate exam questions and the generation of student exercises for programming. However, the question remains if AI chatbots provide adequate results for K-12 CS in different application scenarios. AI chatbots are increasingly integrated into K-12 education by both students and teachers. In this context, a tool using didactical parameters was created to differentiate tasks with ChatGPT-4 in an ongoing project. Preliminary findings from this work in progress reveal that teachers see a benefit using the tool. Future directions for using the tool are discussed.
MicroData is an application that makes it easy to interactively visualise and record live sensor data in support of data literacy in the classroom. It leverages a BBC micro:bit coupled with an Arcade shield accessory, and needs no other hardware. It makes data discovery and collection easier for school children and teachers. We describe some of MicroData’s key features and anticipate how it could be used in the classroom and beyond.
AI is omnipresent in our daily lives. It is, therefore, crucial that students acquire necessary competencies as part of their CS education in order to be able to use and develop this technology responsibly. However, this growing need has hit the educational landscape mostly unprepared. Curricula are only gradually adapted, and there is a lack of empirical evidence on how the topic can be implemented in K-12 education. The study presented in this article uses the cyclical and participatory approach of action research to address this gap. This ensures that theories found about teaching and learning processes can be implemented directly into practice to develop AI teaching on an empirical basis. The initial cycle focuses on content-specific difficulties experienced by learners. First findings indicate that, besides general barriers such as required mathematical and programming skills, students encounter problems when applying or transferring the concepts they have studied.
Although block-based programming languages like Scratch simplify the creation of programs, learning to program can nevertheless be challenging. Program analysis tools such as linters therefore support learners by providing feedback about potential bugs in their programs. What such tools cannot do, however, is detect whether these bugs are subsequently fixed correctly, even though this is a crucial aspect of learning to program. In this paper, we therefore introduce fix patterns as a way to automatically detect whether instances of bug patterns found by program analysis tools have been correctly fixed, in contrast to the relevant code just having been deleted. Using fix patterns to analyse a dataset of 32,000 publicly shared Scratch projects containing bug patterns reveals that only 2,566 projects received changes and out of these changes not even 8% fix the bug. This implies most Scratchers do not actually fix the bug patterns in their projects. This not only demonstrates that fix patterns are a valuable tool to understand what learners do, but they also hold promise to help encourage learners, and to inform instructors about the progress of their learners.
Modeling is a major component of Computer Science (CS) education implemented in K-12. We propose Information Encoding Modeling (IEM) to facilitate the development of modeling competencies, emphasizing semiotic competence and the creative representation of complex information. This research situates IEM within the context of existing modeling techniques, evaluates its application through various examples, and proposes an Encoding Diagram as a key representational tool. We present the potential integration of IEM into CS education to enhance students’ understanding of information encoding and Computational Thinking principles.
Problem. Currently, state- and district-level policies in the United States call for teachers to be qualified to teach computing in K-12 classrooms. Recognizing that equity-focused practices are key to reaching all students in computing and leveraging a researcher-practitioner partnership (RPP), we piloted an intervention designed to provide one-on-one coaching to teachers. Research Question. Our research questions for this project were: 1) What impact does CS coaching have on teacher capacity to implement equitable teaching practices? and 2) What, if any, changes to teacher practice are sustained during and after the CS coaching process? Methodology. Our mixed-methods study leveraged three primary forms of data from teachers who were coached (coachees) and teachers providing coaching (coaches). These included pre- and post-surveys, coaching logs, and self-reflection checklists. Findings. Participants reported use of high-impact instructional design and classroom practices increased significantly from pre- to post-intervention. Their abilities to discuss topics of identity and plan activities that use evidence-based, CS-specific teaching strategies saw the most dramatic increase from pre- to post-intervention. Implications. Coaching may be an impactful way to develop teacher’s use of equitable teaching practices.
