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Interest in the study of computer technology in schools (often in the form of Computer Science subjects or coding initiatives) is seen to have undergone two waves of interest, one in the late 1970s/early 1980s and the other more recently since about 2010. Through a historical exploration of the rationales for the study of computer technology in schools in both the first wave and the second wave, this paper aimed to explore the various curriculum ideologies underpinning their justification. In doing so, the paper highlights the chameleon‐like nature of this change agenda in aligning with contemporary trends to advance the study of computer technology on the curriculum. The paper argues that current manifestations of the study of computer technology in schools are at odds with broader curriculum reform goals and international policies and raises questions about students' access to such knowledge. [ABSTRACT FROM AUTHOR]

Popular discourses of computing and computer science can often frame the sector and the people within it as highly intelligent yet socially challenged, contributing to stereotypes that can potentially exclude those perceived to lack these skills or characteristics. For young people, such stereotypes can influence their educational and career aspirations, especially if there are discrepancies between their own identity and perceptions of what is desirable for computer science students. Drawing on open-ended questionnaire data from 3235 young people in England (aged 11–16), we collected 9442 keywords that students used to describe their “ideal student” in computer science education. An understanding of these perceptions allows us to recognise the prevailing stereotypes that may be shaping young people’s views and aspirations. In this paper, we employ an innovative large-scale descriptive analysis of the most common words that students use to describe the ideal computer science student, including its differences, if any, by students’ demographic background (e.g. gender, ethnicity, free school meal) and responses to the questionnaire (e.g. aspirations to be a computer scientist). We tentatively identified eight clusters of popular ideal student characteristics, namely being Smart & Clever; Knowledgeable & Interested; Determined & Hardworking; Kind & Helpful; Creative; Independent; Confident; and Collaborative. By examining how students imagine the ideal student in computer science, we gain better understanding of their educational aspirations and choice of study and provide educators with valuable insights to potentially challenge and reshape these perceptions. These insights can inform educational interventions to foster a more inclusive computing education. [ABSTRACT FROM AUTHOR]

The reform of the European academic landscape with the introduction of bachelor's and master's degree programs has brought about several profound changes for teaching and assessment in higher education. With regard to the examination system, the shift towards output-oriented teaching is still one of the most significant challenges. Assessments have to be integrated into the teaching and learning arrangements and consistently aligned towards the intended learning outcomes. In particular, assessments should provide valid evidence that learners have acquired competences that are relevant for a specific domain. However, it seems that this didactic goal has not yet been fully achieved in modeling education in computer science. The aim of this study is to investigate whether typical task material used in exercises and exams in modeling education at selected German universities covers relevant competences required for graphical modeling. For this purpose, typical tasks in the field of modeling are first identified by means of a content-analytical procedure. Subsequently, it is determined which competence facets relevant for graphical modeling are addressed by the task types. By contrasting a competence model for modeling with the competences addressed by the tasks, a gap was identified between the required competences and the task material analyzed. In particular, the gap analysis shows the neglect of transversal competence facets as well as those related to the analysis and evaluation of models. The result of this paper is a classification of task types for modeling education and a specification of the competence facets addressed by these tasks. Recommendations for developing and assessing student's competences comprehensively are given. [ABSTRACT FROM AUTHOR]

Traditional assessment methods often fail to provide a robust evaluation of the multifaceted knowledge and skills involved in modern computing competencies. This paper proposes a learning analytics model that utilizes data on students' interactions within digital programming environments to map competency development. Machine learning classifiers identify patterns in student process data that serve as evidence of skill proficiency. The model aims to generate fine-grained and multidimensional insights into competency attainment grounded in authentic student work. A pilot implementation of the model in an introductory programming course provides preliminary support for the validity and utility of the approach. With further research, data-driven learning analytics models show strong potential to transform computing assessment toward more meaningful representations of complex skills. [ABSTRACT FROM AUTHOR]

Recently, researchers have proposed to leverage technology-supported data (log files) to investigate temporal and sequential patterns of interaction behaviors in learning processes. There are two major challenges to be addressed: clarifying the positioning of interaction levels and identifying the evolution of the interaction action patterns in learning processes, particularly for students with differing achievements. This paper explores the use of sequential pattern mining to address the evolution of student action patterns in Massive Private Online Courses (MPOCs) and compare these patterns between different achievement groups. The study was conducted with first-year undergraduate computer science students enrolled in a computer application course at a traditional open university in one of the Chinese provinces (N = 1375). The results showed the development of various action patterns in each phase of the course and the distinct action patterns for high-achieving and low-achieving students. The findings of study provide a new perspective for instructors and students to understand interaction patterns at the fine-grained level, and can help instructional designers develop learner-cantered courses and platforms to improve online learning. [ABSTRACT FROM AUTHOR]

Computational thinking, defined as a way of thinking that can be applied to various fields that require problem-solving skills, has become prevalent in education. Students, i.e., future specialists, have to be prepared for complex thinking competence, necessary for solving business and societal problems, for which a combination of mathematical thinking and computational thinking is essential. The preliminary premise is that there is a correlation between ability in specific mathematical and computational fields. Therefore, this paper aims to highlight the significance of investigating the relations between those fields from linguistic point of view. In order to better understand the relationship between abilities in specific mathematical and computational fields, this paper presents an analysis of a new approach, namely, developing hypotheses for exploring the relationship between metalanguages of different fields of Mathematics and Computer Science. Additionally, the paper describes the first stage of a study on a doctoral level in an attempt to suggest possible statistical analyses suitable for testing hypotheses based on meta-analysis of the current literature. [ABSTRACT FROM AUTHOR]

This paper describes a study for teaching number system in a computer arithmetic course and addresses the existing gap in the current course by focusing on the characteristics of applications. A redundant residue number system (RRNS) is an efficient and innovative number system that inherits the interesting properties of both residue number system (RNS) and redundant number systems. It breaks the operands into residues by considering a moduli-set and then signifies the residues by a redundant representation. So, by limiting the carry propagation chain inside and outside the moduli, RRNS proposes more efficient arithmetic units which could be employed in digital signal processing (DSP) applications. Despite the applicability of RRNS, there is not well-organized teaching on RRNS covering the recent achievements. Besides, there is an important question for students and researchers what is the most appropriate number representation for each application category? In this paper, we present a step-by-step education process for RRNS that includes basic concepts of RNS and the redundant number system. Then we address characteristics of different applications that RRNS is suitable to be employed for them. So, the method gives a well-organized proceeding to computer arithmetic designers and students. [ABSTRACT FROM AUTHOR]

Over 60 years of technology development, transformation of educational policy and curriculum innovation in Ireland have resulted in the introduction of the Computer Science (CS) subject in Post‐Primary (PP) Education. CS has always been conceived digitally and the Digital Learning Experiences (DLE) enacted through its curriculum are strongly interconnected to the opportunities and limitations offered by Digital Spaces (DS). However, key challenges have been identified for the successful implementation of CSE, from teachers' digital competencies and educational strategies in the classroom to learners' varying experiences of CSE. Through a systematic literature review of the educational policies and practices in Ireland's Educational System, this paper documents the digital evolution from the 1960s accounting for the CS curriculum. The literature review identifies key themes in how DS have been conceptualised through CSE, responding to learners' needs and teachers' skills and competencies, informed by emerging societal demands by providing evidence on the disparity between educational policy and practice for DS. Building upon the identified themes, this paper emphasises the importance of the design and implementation of DLE in DS such as the CS subject that considers historical lessons learned to respond to the uncertainties of the digital future. [ABSTRACT FROM AUTHOR]

The words "Programming is the second literacy" were coined more than 40 years ago [13], but never came to life. The paper develops and details that old slogan by proposing that the mainstream mathematics education in schools should merge with education in computer science/programming. Of course, this means a deep structural reform of school mathematics education. We are not talking about adapting the 20th century mathematics to the 21st century—as it outlined in [10, 19], we mean the 21st century mathematics education for the 21st century mathematics. To the best of our knowledge, this paper is perhaps the first known attempt to start a proper feasibility study for this reform. The scope of the paper does not allow us to touch the delicate socio-political (and financial) sides of the reform, we are looking only at general curricular and didactic aspects and possible directions of the reform. In particular, we indicate approaches to development of a Domain Specifiic Language (DSL) as a basis for all programming aspects of a new course. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) applications have been implemented across all levels of education, with the rapid developments of chatbots and AI language models, like ChatGPT, demonstrating the urgent need to conceptualize the key debates and their implications for a new era of learning and assessment. This adoption occurs in a context where AI is dramatically remapping "the human," the purposes of schooling, and pedagogy. Focus of Study: The paper examines how different formulations of "human" became interwoven with the sliding signifier of "intelligence" through a series of violent exclusions, and how the shifting contour of "intelligence" produces uneven and unjust ontological scales undergirding both education and AI fields. Its purpose is to engage the education research community in dialogue about biases, the nature of ethics, and decision-making concerning AI in education. Research Design: This paper adapts a historical-philosophical method. It traces the effects of colonialism and racialization within humanism's emergence through Sylvia Wynter's historiography of "figure of Man," especially via the invention of "intelligence," which has linked education and computer science. It also investigates themes central to modern education such as justice, equity, and in/exclusion through a philosophical examination of the ontological scales of "human." Conclusions: After outlining how "intelligence" has shifted from reason-as-morality to concepts of natural intelligence, we argue that current examples of AI in Education (AIEd), like classroom chatbots and social agents, constitute an intermediary point in the arc toward a new computational superintelligence—the emergence of man3—illustrating the opportunities, risks, and ethical issues in pedagogical applications based on emotion. We outline three differing visions of AIEd's future, concluding with a series of provocations (onto-epistemological, practice-based, and purposes of schooling) that exceed such models and that, given rapid innovations in machine learning, require urgent consideration from multiple stakeholders. [ABSTRACT FROM AUTHOR]

There is a call for more students to continue into computer science (CS), but as many leave their studies before completing, there is a potential in retaining students rather than focusing on recruitment alone. The retention literature proposes 'sense of belonging' as a key concept. This paper contributes with nuancing how sense of belonging is shaped differently within different spaces at the same CS study-programme, by drawing on narrative interviews and ethnographic fieldwork with BA-students, analysed through a spatial analytic lens. By applying the metaphors of a solar system and force fields, we investigate how sense of belonging was constructed within relational spaces and students' identity-negotiations within them. Three spaces are found: The study-lounge (the epicenter of the solar system), the pulsating planet, and the distant isolated planet. Conclusions show how the epicenter are enforced by teaching and learning activities, and how broadening what counts hold potential to retain students. [ABSTRACT FROM AUTHOR]

This paper discusses the suitability of different approaches to computer aided education and to evaluate, discuss methods in language learning study focusing on computer-based language learning field. Several methods are used to investigate how to use computers in a learning process. Computer - assisted technology provide learners with teaching strategies, information, and multimedia platforms to make the learning process easy. However, it does not mean that whole education process replaces traditional education and teachers but improve resources and save time. By which, students can grasp new knowledge and engage themselves at their own pace in a co-relational environment. The purpose of this paper is to distinguish the advantages of computer-centered education. [ABSTRACT FROM AUTHOR]

Learning computer programming can be challenging for primary school students due to its abstract concepts. While teachers seek effective ways to introduce such concepts, the application of learning objects (LOs) can potentially reduce the effort of creating new material from and allows teachers to adapt LOs to students' needs. Although numerous LOs have been developed for multiple disciplines, there is a current research gap using LOs in teaching and learning computer programming at the primary school level. The current paper aims to explore the quality of five Scratch-based LOs created to facilitate teaching and learning programming in primary education. We followed a single instrumental case study collecting data from 25 in-service teachers and 91 primary school students, who, using the LORI instrument, evaluated Scratch-based LOs created in real learning contexts. The results showed that participants assessed the LOs' quality positively, highlighted their learning effectiveness, pleasant design, and increase in student motivation. While the findings cannot be generalized, the LOs can serve as support material both for teachers to introduce programming, and for students to comprehend key programming concepts. Future work concerns the exploration of the LOs affordability when applied in real situations. [ABSTRACT FROM AUTHOR]

Formative assessment is considered to be helpful in students' learning support and teaching design. Following Aufschnaiter's and Alonzo's framework, formative assessment practices of teachers can be subdivided into three practices: eliciting evidence, interpreting evidence and responding. Since students' conceptions are judged to be important for meaningful learning across disciplines, teachers are required to assess their students' conceptions. The focus of this article lies on the discussion of learning analytics for supporting the assessment of students' conceptions in class. The existing and potential contributions of learning analytics are discussed related to the named formative assessment framework in order to enhance the teachers' options to consider individual students' conceptions. We refer to findings from biology and computer science education on existing assessment tools and identify limitations and potentials with respect to the assessment of students' conceptions. Practitioner notesWhat is already known about this topic Students' conceptions are considered to be important for learning processes, but interpreting evidence for learning with respect to students' conceptions is challenging for teachers.Assessment tools have been developed in different educational domains for teaching practice.Techniques from artificial intelligence and machine learning have been applied for automated assessment of specific aspects of learning.What does the paper add Findings on existing assessment tools from two educational domains are summarised and limitations with respect to assessment of students' conceptions are identified.Relevent data that needs to be analysed for insights into students' conceptions is identified from an educational perspective.Potential contributions of learning analytics to support the challenging task to elicit students' conceptions are discussed.Implications for practice and/or policy Learning analytics can enhance the eliciting of students' conceptions.Based on the analysis of existing works, further exploration and developments of analysis techniques for unstructured text and multimodal data are desirable to support the eliciting of students' conceptions. [ABSTRACT FROM AUTHOR]

Analogy-based learning methods map the concept being learned to a concept well understood by the learner. An analogy is primarily useful when learners do not know the topic being studied. Computer science is an area where the concepts exhibit a high level of abstraction and, hence, are hard for students to comprehend. The use of analogies in instruction can significantly reduce the cognitive load a student faces in learning abstract computer science concepts. The role of analogies in helping students learn computer science topics has not been explored adequately. This paper presents our efforts related to using analogy-based teaching in computer science. Over the last several years, we have developed extensive analogies for many advanced computer science concepts. We have used these analogies extensively in classroom teaching at our institution. We list the analogies that we have developed and used in our classroom teaching and, as illustration, discuss two analogies: one from the field of operating systems and another one in modular software design. We have also conducted experiments to evaluate the impact of using these two analogies on student learning outcomes. Our results confirm our hypothesis that analogy-based instruction techniques are effective and result in improved student learning outcomes. [ABSTRACT FROM AUTHOR]

Contribution: This article features a systematic literature review with the objective of presenting a study that reflects the current scenario of research on the cognitive load theory (CLT) in the domain of teaching and learning computer programming. Background: Computer programming is a highly cognitive skill, requiring mastering multiple competencies, and recognized as being difficult to learn, for this reason, the cognitive load (CL) in the learner’s working memory emerged as an influential concept, making CLT one of the most common theories in computing education research. Research Questions: What are the approaches that relate CLT to teaching and learning computer programming? What CLT-related concepts are covered? What evidence is reported with respect to this context? Methodology: Following a formal protocol, a survey was performed for papers linking CLT to teaching and learning programming published between 2010 and 2020. The selection of papers was based on a set of criteria established to drive the selection process, including alignment with the research questions and paper quality assessment. Findings: The approaches applied in the papers are based on measuring the CL; through instructional design based on the development or use of resources or tools, a range of different pedagogy strategies and the CLT concepts. With respect to the concepts, the subjective measurement technique and worked example effect are the most commonly deployed. As far as the evidence reported, the better part is related to the worked example effect and measuring CLs. [ABSTRACT FROM AUTHOR]

This article offers Ancestral Computing for Sustainability (ACS) to dismantle the logics of settler colonialism that affect accessibility, identities, and epistemologies of computer science education (CSE). ACS centers Indigenous epistemologies in researching CSE across four public universities in the United States. This paper describes Ancestral Computing for Sustainability and explores reflections of two students engaging as researchers in ACS inquiry. Drawing on Indigenous methodologies and Participatory Action Research, they share their reflections as co-researchers in ACS through storywork. These critical reflections include their relationship to computing, observations of the interdependent work within ACS, ethics and sustainability, and their experiences within the focus groups. The article ends with recommendations for furthering ACS as a decolonial approach that centers Indigenous epistemologies in CSE. Recommendations for CSE education include Ancestral Knowledge Systems and adding sustainability as a topic within computing education pathways and building student-faculty relationships based on trust is recommended to foster students' academic and personal growth within CSE education and research. [ABSTRACT FROM AUTHOR]

Background: Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited. Objectives: The current work presents the development and empirical evaluation of instructional design targeting students' difficulties in code tracing particularly in integrating component skills in the Trace Table Tutor (T3), an intelligent tutoring system. Methods: Beyond the instructional features of active learning, step‐level support, and individualized problem selection of intelligent tutoring systems (ITS), the instructional design of T3 (e.g., hints, problem types, problem selection) was optimized to target skill integration based on a domain model where integrative skills were represented as combinations of component skills. We conducted an experimental study in a university‐level introductory Python programming course and obtained three findings. Results and Conclusions: First, the instructional features of the ITS technology support effective learning of code tracing, as evidenced by significant learning gains (medium‐to‐large effect sizes). Second, performance data supports the existence of integrative skills beyond component skills. Third, an instructional design focused on integrative skills yields learning benefits beyond a design without such focus, such as improving performance efficiency (medium‐to‐large effect sizes). Major Takeaways: Our work demonstrates the value of designing for skill integration in learning technologies and the effectiveness of the ITS technology for computing education, as well as provides general implications for designing learning technologies to foster robust learning. Lay Description: What is currently known about the subject matter?: Skill integration is vital in students' mastery development, and is especially prominent in developing coding tracing skills.Coding tracing skills are foundational to programming, an increasingly important area in the current STEM education, yet many novice students struggle with code tracing.Instructional design to support skill integration in learning technologies has been limited.One of the most effective technologies for skill mastery, intelligent tutoring systems (ITS), is underused or only used in a partial form in programming education. What our paper adds to this?: We present the development and empirical evaluation of instructional design targeting students' difficulties in code tracing particularly in integrating component skills in an ITS, the Trace Table Tutor.The instructional features of the ITS technology (e.g., active learning, step‐level support, individualized problem selection) support effective learning of code tracing.Students' performance data supports the existence of integrative skills beyond component skills.An instructional design that provides deliberate practice and focused practice on integrative skills yields learning benefits beyond a design without such features. The implications of study findings for practitioners: Designing for skill integration is valuable and should receive more attention in designing learning technologies to foster robust learning.The instructional features of full‐scale ITSs are effective in supporting learning and merit further application in learning technologies in computing education. [ABSTRACT FROM AUTHOR]

In this paper, we describe the design, development, and implementation of a curriculum based on teaching computer science using an industry-standard game-design software: Unity 3D. We discuss the theoretical underpinnings of our instructional design process and steps we have taken to introduce complexity and maintain student motivation. We discuss the challenges of this implementation and possible solutions and detail the additional steps related to teacher professional development, which is a key element for success of new and innovative curricular implementations such as ours. [ABSTRACT FROM AUTHOR]

Live streaming platforms like Twitch.tv count millions of viewers and performers, pointing to novel practices and interactions. Instructional applications of this phenomenon are rising with thematic channels and shows aimed at teaching and debating a variety of subjects ranging from art to programming. However, few research publications have specifically explored trends in pedagogical strategies and learning behaviours of viewing audiences. This study responded to this need by analysing computer science shows on Twitch.tv. A total of 40 hours of live streaming were analysed within a Community of Inquiry framework using the concepts of social affordances, computational thinking, and teaching style. Data collected from both expert and novice streamers included streamers' actions, on‐screen activity, and online discussions. Results pointed to specific tactics employed by both performers and viewers for exploring computer science issues and dynamics together, with instances of peer‐tutoring, construed learning, and significant transparency, even when top‐down instruction was staged. Practitioners notesWhat is already known about this topic Live streaming is a popular media practice all around the world, with Twitch.tv as the leading hosting platform.A rising number of live streaming shows are focusing on education and learning topics, from STEM to art.What this paper adds A first exploration of instructional streaming focused on computer science education.An analysis of best practices in instructional streaming in terms of community building, teaching style, and computational thinking processes.A better understanding of how communities of inquiry can be hosted on Twitch.tv.Implications for practice and/or policy Practitioners can harness this study's results for informing better educational streaming.Educators may refer to this article's highlights for selecting and evaluating educational streaming shows.Policy makers will be able to use this article's insights for monitoring and re‐applying effective computer science activities in other educational environments. [ABSTRACT FROM AUTHOR]

Fiber crafts occupy a vital position in technology innovation and present a promising space for computer science education, which continues to face lopsided participation. It remains unclear whether and how fiber crafts can become a context for computational learning and what role different materials play with the risk to miss computational approaches that could broaden computational cultures. Fusing constructionist and posthuman perspectives, this study analyzed how middle school students performed computational concepts while weaving and manipulating fabric and how the craft materials drove what could be learned computationally in these contexts. Present the fiber crafts as a context for performing computational concepts (i.e., variables, conditionals, functions) and that the materials play a role in what can be learned computationally. While weaving drove computing as the performance of automation, fabric manipulation required speculative and physical three-dimensional modeling as computational. The paper presents fiber crafts as a promising context for computational learning and theorizes the ongoing material as material syntonicity, contributing a material direction to fostering more inclusive and sustainable computing cultures. [ABSTRACT FROM AUTHOR]

To date, many AI initiatives (eg, AI4K12, CS for All) developed standards and frameworks as guidance for educators to create accessible and engaging Artificial Intelligence (AI) learning experiences for K‐12 students. These efforts revealed a significant need to prepare youth to gain a fundamental understanding of how intelligence is created, applied, and its potential to perpetuate bias and unfairness. This study contributes to the growing interest in K‐12 AI education by examining student learning of modelling real‐world text data. Four students from an Advanced Placement computer science classroom at a public high school participated in this study. Our qualitative analysis reveals that the students developed nuanced and in‐depth understandings of how text classification models—a type of AI application—are trained. Specifically, we found that in modelling texts, students: (1) drew on their social experiences and cultural knowledge to create predictive features, (2) engineered predictive features to address model errors, (3) described model learning patterns from training data and (4) reasoned about noisy features when comparing models. This study contributes to an initial understanding of student learning of modelling unstructured data and offers implications for scaffolding in‐depth reasoning about model decision making. Practitioner notes: What is already known about this topic Scholarly attention has turned to examining Artificial Intelligence (AI) literacy in K‐12 to help students understand the working mechanism of AI technologies and critically evaluate automated decisions made by computer models.While efforts have been made to engage students in understanding AI through building machine learning models with data, few of them go in‐depth into teaching and learning of feature engineering, a critical concept in modelling data.There is a need for research to examine students' data modelling processes, particularly in the little‐researched realm of unstructured data. What this paper adds Results show that students developed nuanced understandings of models learning patterns in data for automated decision making.Results demonstrate that students drew on prior experience and knowledge in creating features from unstructured data in the learning task of building text classification models.Students needed support in performing feature engineering practices, reasoning about noisy features and exploring features in rich social contexts that the data set is situated in. Implications for practice and/or policy It is important for schools to provide hands‐on model building experiences for students to understand and evaluate automated decisions from AI technologies.Students should be empowered to draw on their cultural and social backgrounds as they create models and evaluate data sources.To extend this work, educators should consider opportunities to integrate AI learning in other disciplinary subjects (ie, outside of computer science classes). [ABSTRACT FROM AUTHOR]

In this article, we present a conceptual framework for teaching computer science (CS) to address the unique challenges faced by marginalized groups. The framework is grounded in feminist standpoint theory and describes three key practitioner-focused areas aimed at broadening participation and increasing participation in CS education (CSEd). These principles are 1) Creating dialogic and dialectical relationships with the CS community, 2) Embracing intersectionality in CSEd, and 3) Framing CS education as a lived experience. It also offers a distinct perspective in that it is concerned with how both sides of the dialogue (i.e., the oppressed and the oppressor) grow and change in relation to one another. The strategies, along with the framework detailed in this paper, provide scholars and educators with new avenues for unpacking underrepresentation in CSEd and potential methods to address it. [ABSTRACT FROM AUTHOR]

Policy emphases on early childhood and elementary computer science education have led to the development of many developmentally appropriate computer science and robotics tools, pedagogies, and high-quality curricula. One example is the integrated Coding as Another Language pedagogy for coding, literacy, and social and emotional learning. The pedagogy was initially developed for students in kindergarten and early elementary school and has not previously been aligned to prekindergarten learning frameworks or used in the prekindergarten setting. In this paper, we describe a pilot program if the CAL pedagogy could be successfully used for the prekindergarten setting. The study used a design-based method to adapt the Coding as Another Language curriculum for the prekindergarten setting and a mixed-methods protocol to evaluate the program at a preschool site serving children experiencing homelessness in classrooms that are part of the local school district’s universal prekindergarten program. Students were assessed using the Coding Stages Assessment of coding knowledge and the TechCheck-PreK assessment of computational thinking. Teachers completed semi-structured interviews over the course of the project. Teachers reported overall positive experiences teaching the curriculum including for English language learners, although some reported challenges integrating the curricula in their bilingual classrooms. Children participating in the program significantly improved on their coding knowledge by 4.60 points on the Coding Stages Assessment, p < .0001. These findings suggest that the Coding as Another Language pedagogy can be successfully integrated with preschool learning frameworks and implemented in preschool classrooms. [ABSTRACT FROM AUTHOR]

Nowadays, the actual post pandemic context of computer science teaching is having some special attributes: big number of students, low budgets, need for STEAM, need of what we can call "pre-robotics" abilities. Otherwise, the costs should be kept low. This paper is a workaround the need of buying expensive Arduino kits. Instead, it is focused on how to teach elementary computer science skills with less accessories added to an Arduino Uno board and is proposing a set of lessons based on this idea and the principle of learning by discovery. [ABSTRACT FROM AUTHOR]

Culturally-relevant computing has been discussed as a way to promote K-12 Computer Science education and address ongoing challenges related to diversity, equity, and inclusion. What is not well understood about the practice of culturally-relevant computing, however, is how to bring together existing cultural frameworks and Computer Science curricula effectively. To help address this area, focus group interviews were conducted with ten (n = 10) in-service Computer Science teachers working in the multicultural context of Hawai'i. The focus group sessions were designed to reveal teachers' perceptions of the principles and processes involved in designing and implementing culturally-relevant CS lessons and resources. Results revealed a number of key themes, including important variations in the practitioners' philosophical and operational approaches to culturally-relevant computing. The paper ends with a detailed discussion of the findings and their implications for designers, practitioners, and researchers working in Computer Science education. [ABSTRACT FROM AUTHOR]

Implementing computer science education in an elementary classroom is at the forefront of computing education. Nevertheless, the literature on K-12 Computer Science (CS) education offers limited guidance for developing elementary CS curricula that lead to multiple career paths through project-based learning. Particularly, more research is needed on culturally responsive elementary school computing that leverages students' cultural references to create a more equitable CS education that acknowledges one's identity, culture, or background in the curriculum planning. This paper offers an approach for designing culturally responsive computing for upper elementary students from a highly diverse, low socio-economic school district using a research-practice approach. The approach can be adapted for other schools that face unique diversity and curricular challenges. [ABSTRACT FROM AUTHOR]

Current research surrounding online computer science education emphasizes the need for high-quality professional development opportunities. However, there is a gap in research in the inclusion of online computer science educators to identify needs and strategies that make the online computer science courses effective. Through a Research-to-Practice Partnership (RPP), this paper examines the instructional strategies and recommendations from online Computer Science teachers. This study seeks to better understand (1) What design, facilitation, and assessment strategies do teachers use to teach programming online? and (2) What recommendations do teachers have for those interested in teaching programming online? The feedback teachers provided during the study assisted in identifying the current needs in online AP Computer Science. The participants suggested additional ways the RPP could support teachers in strengthening their practice, which has assisted in the production of high-quality professional development to support novice teachers entering the field of Computer Science. [ABSTRACT FROM AUTHOR]

Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biological counterparts, which we denote synthetic biological neural networks (SYNBIONNs). Their use in the fields of medicine, biosensors, biotechnology, and many more shows great potential and presents exciting possibilities. So far, many different synthetic biological networks have been successfully constructed, however, SYNBIONN implementations have been sparse. The latter are mostly based on neural networks pretrained in silico and being heavily dependent on extensive human input. In this paper, we review current implementations and models of SYNBIONNs. We briefly present the biological platforms that show potential for designing and constructing perceptrons and/or multilayer SYNBIONNs. We explore their future possibilities along with the challenges that must be overcome to successfully implement a scalable in vivo biological neural network capable of online learning. [ABSTRACT FROM AUTHOR]

The final issue of TechTrends for 2023 features two columns and ten original papers that focus on the use of educational technologies to enhance teaching and learning. The articles cover topics such as artificial intelligence (AI), analytics, personalized learning, and broadening access to computer science education. One paper discusses a virtual librarian chatbot that uses IBM Watson to provide customized assistance to library users, while another explores an automated classroom analytics system called TEACHActive. The issue showcases emerging AI technologies and their potential applications in education, as well as learner-focused approaches enabled by education technology. The findings presented in this issue have implications for the design of responsive learning environments that prepare all students for future success. [Extracted from the article]

This paper presents a game-design workshop built around a digital art installation featuring video games displayed over a real-world skyscraper to stimulate students' interest in computer science and a study testing its short-term effects on improving middle school students' computational thinking (CT) skills and attitudes towards computing. Following a STEAM approach, the workshop aimed to engage participants in age-appropriate activities that focus on CT skills through the lens of creating their own game. A web-based game design interface that allows students to code and play games as simulated on a skyscraper was developed to support the workshop's core activities. The web environment also featured step-by-step tutorials and fully functional games to promote the accessibility of the learning materials for a diverse body of students and educators around the globe. The results of the study indicated that the workshop helped students improve their CT skills and differentially influence their attitudes towards computing. In particular, the workshop experience led students from underserved community districts to lower their attitude ratings, whereas the reverse pattern was observed for students from more affluent districts. The workshop reportedly informed students' perception of computing as a profession and their appreciation of the analytical effort required for developing functional games. Qualitative analysis of artifact-based interviews indicated that students could begin to make abstractions and devise algorithms by associating variables through conditional statements while solving problems related to game development. Interview analysis also revealed that students took pride in the effort that they made during the workshop. [ABSTRACT FROM AUTHOR]

The paper proposes a novel index to classify how well UK Computer Science courses articulate cybersecurity-related content through their course/module pages. The aim of this work is to raise awareness among British Universities to pay more attention to include and standardize cybersecurity content in computer science courses. Our results show that 80% of analyzed courses scored 1 or 2-stars on a 5-Stars scale. The results also suggest the need for a formal delivery of cybersecurity content from the first year of the courses and possibly in a collaborative manner with the British Computer Society (BCS). To emphasize cybersecurity education in mitigating security lapses, the analogy is: it is better if most people know how to use a match than to train many fire-fighters. [ABSTRACT FROM AUTHOR]

Educators make consequential curricular decisions, often with little support, particularly as it relates to equity and how to support all students. This paper investigates the use of a rubric to support educators evaluating computer science curricula, especially with regards to equity. Seventeen in-service elementary teachers evaluated a computer science curriculum with and without the Teacher Accessibility, Equity, and Content (TEC) Rubric. We examine teachers' responses to prompts and completed TEC Rubrics to understand if and how the rubric supported their evaluations. The TEC Rubric helped teachers attend not only to curricular factors related to instructional design but also to issues of equity and accessibility and to identify opportunities to draw on the cultural resources of students and their communities. We contribute evidence supporting curricular evaluation instruments, specifically the TEC Rubric, and their use to direct teachers' attention to attributes of equitable computing instruction. [ABSTRACT FROM AUTHOR]