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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]

In computer science and engineering education, teaching PC interfacing courses and laboratory experiments are strongly required. PC interfacing is the field of developing or simulating real/virtual solutions for exchanging data/commands between PC and the outer world of sensors and actuators. Recently, virtual experiments and Labs have been adopted by engineering educators to preclude the physical presence of students and tutors and to provide effective skills acquisition and hands‐on experience in a virtual manner. High‐cost LabVIEW from National Instruments company is the dominant platform to develop, execute, and animate virtual PC interfacing experiments similar to real ones. This paper presents a toolchain, the course contents, and virtual experiments that cover many different PC interfacing technologies such as UART, SPI, RS232, USB, SD card interfacing, and wireless GSM/GPRS. The virtual nature of VFST toolchain refers to enabling the students to design, animate, and run their prototypes or solutions inside only PC programs without the need to build physical or real ones until making sure of their prototypes' functionality. The main aim of the VFST platform is to make students able to develop C# based applications and to implement solutions with an aesthetic similar to LabVIEW capabilities to become a low‐cost alternative of it. VFST consists of a group of free‐of‐charge and third‐party software programs such as VSPD, Virtual USB driver, WinImage, and Real‐Term alongside with Proteus simulator and C# programming language. This paper presents qualitative and quantitative evaluations of the benefits and effectiveness of VFST. Findings are collected via feedback responses using an online questionnaire survey. These findings clarify that the student cohort is, in general, supportive that VFST Lab's content and virtual experiments have a considerable effect on their career after and before their graduation. [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]

This paper addresses the production scheduling and inventory management in a closed‐loop supply chain that recycles both high‐quality and low‐quality cores and makes products using cores and new raw materials. The manufacturing/remanufacturing supply chain consists of a vendor and a buyer, and they collaborate under a consignment stock (CS) agreement. We investigate and compare three operation policies under the CS agreement, covering continuous and intermittent production manners and shipments of equal and unequal batch sizes. For each operation policy, we develop a mixed integer nonlinear programming model to jointly optimize the production sequence of two classes of cores, production cycle length, shipment frequency, and shipment batch sizes, with the objective of minimizing the cost rate. By analyzing the respective decisions and conducting an extensive numerical study with various scenarios, we explore the advantages and applications of each operation policy. Based on our research findings, we provide general guidelines and criteria for operation policy selection. [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]

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]

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]

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]

Education 4.0 is a recently introduced concept focused on innovation, novelty, use of technology and connections with employment and industry. In particular, in engineering disciplines like computer science (CS) it is essential that educators keep up to date with industry developments. Indeed, how CS educators effectively design and implement innovative teaching and learning deserves more systematic attention. This study aims to catalogue and synthesise learning design approaches to teaching and learning within CS: (1) Which innovative pedagogic approaches are used in teaching of CS? (2) Which approaches align with Education 4.0? (3) What skills and competences do educators require to align CS teaching with Education 4.0? Our systematic literature review (SLR) included CS papers published between 2016 and 2020. Two hundred and thirty‐one studies were identified of which 66 were included in the final phase, which were coded by a multidisciplinary team. The findings indicated that many CS educators included Education 4.0 learning design elements. We found a clear distinctive three‐cluster solution: (1) EDU4 light, (2) project‐based/hands‐on learning and (3) full EDU4 (refer to Reference [7] conceptualisation, while Education 4.0 refers to our own definition [Reference 71]. These findings suggest three broad flavours when designing innovative CS practices, which might help educators align their practice. [ABSTRACT FROM AUTHOR]

In the last decade, single‐board computers (SBCs) have been employed more frequently in engineering and computer science (CS) at both technical and educational levels. These devices are of importance to educators and students due to several factors such as the versatility, the low cost, and the possibility to enhance the learning process through technology. However, the implications, possibilities, and constraints of these devices in engineering and CS education have not been explored in detail. In this systematic literature review, we explore how the SBCs are employed in engineering and CS and what educational results are derived from their usage in the period 2010–2020 at tertiary education level. For this, 154 studies were selected out of n = 605 collected from the academic databases Ei Compendex, Inspec, and ERIC. The analysis was carried out in two phases, identifying, for example, areas of application, learning outcomes, and students' and researchers' perceptions. The results of the review mainly indicate the following aspects: (1) The areas of laboratories and e‐learning, computing education, robotics, Internet of Things, and persons with disabilities gather the studies in the review. (2) Researchers highlight the importance of the SBCs to transform the curricula in engineering and CS for the students to learn complex topics through experimentation in hands‐on activities. (3) The typical cognitive learning outcomes reported by the authors are the improvement of the students' grades and the technical skills regarding the topics in the courses. Concerning the affective learning outcomes, the increase of interest, motivation, and engagement is commonly reported by the authors. [ABSTRACT FROM AUTHOR]

This paper describes educational software for visualization and finite automata simulation. The system was developed in Java programming language, and its main purpose is learning process improvement. Using this software, finite automata can be defined in a graphical editor in the form of a state diagram, or by defining the transition function using the transition table. Upon defining an automaton, it is possible to run a visual simulation of the automaton operation for an arbitrary input string, whereby a textual description of the automaton simulation is also obtained. Furthermore, the system allows for conversion of regular expressions to deterministic finite automata and nondeterministic finite automata. The simulation of Thompson's construction algorithm is implemented, so that transformation of a regular expression to the corresponding NFA can be monitored in a step‐by‐step process. The quantitative analysis and evaluation of the effectiveness of the simulator are based on a survey of undergraduate students at two universities. The majority of students found the tool a useful means for better understanding and mastering of finite automata concepts. [ABSTRACT FROM AUTHOR]

Automated program assessment systems have been widely adopted in many universities. Many of these systems judge the correctness of student programs by comparing their actual outputs with predefined expected outputs for selected test inputs. A common weakness of such systems is that student programs would be marked as incorrect as long as their outputs deviate from the predefined ones, even if the deviations are only minor, insignificant, and considered acceptable by a human assessor that the programs have satisfied the specifications. This critical weakness caused undue frustration to students and undesirable pedagogical consequences that undermine these systems' benefits. To address this issue, we developed an improved mechanism for program output comparison to serve as a versatile test oracle that brings the results of automated assessment much closer to those of human assessors. We evaluated the new mechanism in real programming classes using an existing automated program assessment system. We found that the new mechanism achieved zero false‐positive error (did not wrongly accept any incorrect output) and very low (0%–0.02%) false‐negative error (that wrongly rejected correct outputs), with very high accuracy (99.8%–100%) in correctly recognizing outputs deemed acceptable by instructors. This represents a major improvement over an existing assessment mechanism, which had 56.4%–64.1% false‐negative error with an accuracy of 25.4%–40.9%. Moreover, about 67%–96% of students achieved their best results in their first attempt, which could be encouraging to them and reduce their frustration. Furthermore, students generally welcomed the new assessment mechanism and agreed it was beneficial to their learning. [ABSTRACT FROM AUTHOR]

As we become ever more dependent on computer systems for much of what we do, we are losing the battle with cyber criminals and suffer from poor‐quality offerings. Mission‐critical, life‐critical, and infrastructure‐critical systems should be secure, reliable, and worthy of trust. Yet, that is not our experience. Many firms complain that entry‐level software workers do not have the skills and abilities to do what is required and yet we continue to teach computer science in ways very similar to what we did in the 1970s and '80s. As we spiral downward, it's hard to know precisely where the event horizon might be, so let us deal with it now. It's time for an educational and societal sea change when it comes to computing. Society has demonstrated the willingness to deal with such issues in medicine and other critical domains. Highly‐skilled clinical professors teach new physicians and specialists using the processes, methods, tools, and disciplines learners are expected to use as practicing professionals. It is time for the crucial software domains to leverage these proven methods and stop pushing off to employers these critical aspects of what it means to be a software professional. [ABSTRACT FROM AUTHOR]

In this study, an innovative tool for enabling contextual teaching based on visual inputs, named Visual Stimuli‐based Teaching Aid (VISTA), was developed. This system establishes the meaning and significance of concepts that are taught in the classroom within different environmental contexts. The idea of contextual teaching has been deliberated for more than a decade now. Nevertheless, using this in a classroom with limited time and resources has several challenges. VISTA leverages the ubiquitous mobile devices to boost conventional teaching methods with contextual teaching–learning. With VISTA, contextual teaching does not require any specialized device, expensive sensors, or simulated environment. To assess the applicability of VISTA in computer science education, we gathered the responses and experiences from 42 computer science teachers teaching in various universities of India. The responses garnered indicate that contextualization through VISTA is relevant as well as interesting. In total, 86.31% of the teachers found the contextual information provided by VISTA to be significantly related to both the captured images and the concepts presented in the class. These results encourage the use of VISTA as a pedagogical tool for contextual teaching. [ABSTRACT FROM AUTHOR]