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In our post-pandemic world, where the majority of higher education institutions have transitioned back to in-person classes, this paper argues that we must not return to pre-COVID teaching practices. Instead, we have the obligation and opportunity to create an educational experience and environment that better facilitates learning and instruction. This paper presents post-COVID best practices for employing technology in higher education based on an original survey and follow-up interviews of seventeen computing instructors at our institution. After a literature review, we describe four general categories of practices that enhance the post-COVID classroom: online student activities, digital instructor notes, remote classroom participation and collaboration, and a paperless classroom. For each of these categories, we provide vignettes to illustrate scope and intent. We also offer recommendations for addressing digital dishonesty, required infrastructure, institutional support, and being prepared to seamlessly return to a blended or fully remote environment in the event of another crisis. Finally, we identify additional emerging technological challenges and opportunities that require further effort. Overall, this paper emphasizes the need for a shift towards improved practices in the classroom rather than just a return to pre-pandemic norms. We believe implementing these recommendations will result in a more flexible, accessible, and robust post-COVID educational experience.

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.

Few high schools offer Information Technology (IT)) as a subject in South Africa. This paper used Bourdieu's conception of cultural capital to investigate the reasons why many public schools are shunning away from including IT in their curriculum. Data were collected using a questionnaire and analysed using ANOVA, to determine whether cultural capital influences choosing IT as one of the subjects in the school curriculum. The results showed that public high school principals view IT as a subject that should be done in schools where there is medium-to-high cultural capital status. It is a challenge for schools with low cultural capital to offer IT among their subjects as it is not practiced by the community or society in which the schools exist. The paper concludes by recommending that there is room for the so-called 'low cultural capital' schools to offer IT among their subjects despite the challenges they are facing. Cultural capital does not hinder students' performance. Students from low cultural capital communities can achieve good grades even though they learn under difficult circumstances of inadequate educational resources.

In higher education institutions, critical race theory (CRT) is known to be associated with fields that study racial disparities or systemic oppression such as law, education, and ethnic studies. The impression that CRT is unrelated to fields like business or computer science may have led scholars and practitioners from these disciplines to put their focus on elsewhere than on racial inequality and its implication in their research and practice, despite apparent need. To counter such fallacy, this review article--focusing primarily on the US context--discusses CRT literature in fields where its presence is less known which are nevertheless among the major domains of higher education institutions: health sciences, computer science and information technology, sports, business, and religion. By discussing example research of how scholars have utilized CRT in different fields to challenge the race-neutral thinking that often obscures structural racism, this paper exposes racism's ability to alter manifestations and to appear through various shapes and forms within the higher education context. Initial recommendations on how educators may engage in further discussions or actions will also be considered. This paper concludes that racist ideologies are often hidden behind discipline-specific vocabulary or technical language, and it is by tackling the ideologies at work underneath the technicalities can we address the chameleon-like nature of racism more effectively.

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.

In this paper we discuss the types of knowledge used by six middle school students as they engaged with a debugging task designed to integrate ideas from computer science, mathematics and science. Our findings show that the computational thinking practice of debugging is a rich source of opportunities to integrate these different disciplines. The analysis illustrates how the types of knowledge the students did and did not use at each step of the debugging process were related to their ability to succeed at each step. Our work contributes to theory and practice by uncovering implications for studying debugging through two refined frameworks and for designing debugging tasks to support transdisciplinary learning.

Purpose: The purpose of this paper is twofold: to identify and map contemporary research on advanced technology implementations for problem-solving purposes in the manufacturing industry, and to further understand the organizational learning possibilities of advanced technology problem-solving in the manufacturing industry. Design/methodology/approach: This paper outlines a scoping review of contemporary research on the subject. The findings of the review are discussed in the light of theories of contradicting learning logics. Findings: This paper shows that contemporary research on the subject is characterized by technological determinism and strong solution-focus. A discussion on the manufacturing industries' contextual reasons for this in relation to contradicting learning logics shows that a Mode-2 problem-solving approach could facilitate further learning and expand knowledge on advanced technology problem-solving in the manufacturing industry. A research agenda with six propositions is provided. Originality/value: The introduction of advanced technology implies complex effects on the manufacturing industry in general, while previous research shows a clear focus on technological aspects of this transformation. This paper provides value by providing novel knowledge on the relationship between advanced technology, problem-solving and organizational learning in the manufacturing industry.

Collaborative learning has numerous benefits such as enhancing learners' critical thinking, developing social skills, and improving learning gains. While engaging in this interactive process, learners' satisfaction toward their partners plays a crucial role in defining the success of the collaboration. However, detecting learners' satisfaction during an ongoing collaboration remains challenging, and there are no automatic techniques to predict learners' satisfaction. In this paper, we propose a multimodal approach to automatically predict peer satisfaction for co-located collaboration with features extracted from 44 middle school learners' collaborative dialogues. We investigated three types of features extracted from learners' dialogues: 1) linguistic features indicating semantics and sentiment; 2) acoustic-prosodic features including energy and pitch; and 3) visual features including eye gaze, head pose, facial action units, and body pose. We then trained several regression models with each of those features to predict the peer satisfaction scores that learners received from their partners. The results revealed that head position and body location were significant indicators of peer satisfaction: lower head and body distances between partners were associated with more positive peer satisfaction. Next, we investigated the influence of multimodal feature fusion methods on peer satisfaction prediction accuracy: early fusion versus late fusion. We report the comparison results between models trained with (1) best-performing unimodal features, (2) multimodal features combined by early fusion, and (3) multimodal features combined by late fusion. This line of research reveals how multimodal features from collaborative dialogues are associated with peer satisfaction, and represents a step toward the development of real-time intelligent systems that support collaborative learning.

Contributions: The underrepresentation of women in computer science (CS) majors has long been a focus of attention in many academic documents, the majority of them from the United States and Europe. There is, however, a lack of information about educational interventions (EIs) for women in computing in Latin America. The contribution of this article is to cover this gap and describe what researchers in Latin American countries have been publishing about the recruitment and retention of women in the CS field. Background: Many EIs targeting female students at different educational levels--K-12, undergraduate, and graduate--have been undertaken to increase the participation of women in computing in Latin America. However, descriptions of these activities rarely are included in international academic databases. Research Questions: This literature mapping addresses two main research questions (RQ) about the topic of women in computing in academic publications in Latin American countries: RQ1) what are the characteristics of the publications about women in computing in Latin America? and RQ2) what are the published interventions to recruit and retain women in computing in Latin America? To answer RQ1, six subquestions were created covering year, language, country of origin, document type, and professional track. Furthermore, for RQ2, two subquestions were created involving educational level and the use of software development with a female theme. Methodology: This investigation used the systematic literature mapping process. To achieve a broad coverage of papers, the following sources were included: Scopus, Web of Science, Google Scholar, EBSCO, the proceedings of the Latin American Women in Computing Conference (LAWCC), and those of the Women in Technology (WIT) workshop colocated with the annual conference of the Brazilian Computer Society (SBC). The included papers were published in the last decade (2010-2020) and written in English, Portuguese, or Spanish. Findings: The literature mapping encompasses 197 academic documents, 48.2% of which were written in Portuguese, 28.7% in English, and 23.1% in Spanish. The papers originated from 15 of the 20 Latin American countries. Brazil and Costa Rica have the highest number of publications overall. The documents describe initiatives to increase the participation of women in computing majors that cover the entire educational spectrum, from K-12 to graduate programs, but papers targeting populations in higher education have started to appear recently.

Access Foundation Programmes are a widening-participation initiative designed to encourage engagement in higher education among underrepresented groups, including those with socioeconomic and educational disadvantage. In particular, mature students enrolled in these programmes experience greater difficulties making the transition to tertiary education, especially when they opt to study disciplines traditionally considered difficult. Computer programming is perceived as a traditionally difficult subject with typically lower pass rates and progression rates than other subjects. This paper describes the first of a three-cycle action research study examining the perceived effects of a structured Peer Assisted Learning (PAL) Programme for mature students enrolled in a computer science programming module for an Access Foundation Programme in an Irish University. The focus of this qualitative study was to evaluate the perceived effect of a PAL programme on learning and whether it offered a positive learning support structure. Findings from our study suggest that PAL programmes have an overall positive effect on subject comprehension as well as enhanced learner confidence for mature Access Foundation students. Furthermore, PAL sessions offered students a support structure that helped with their transition and acculturation to tertiary education. This study also highlights the importance the PAL leader's role has on the perceived effectiveness of the PAL sessions as well as the impact of the students' shared history on the near-peer bond. The study concludes that the implementation of PAL programmes for Access Foundation Programmes has the potential to offer mature students a supportive learning environment and to improve their learning experience.

This paper explored the attitudes and roles of computer science (CS) teachers in elementary and high schools in Croatia in the period from completely online to "normal" schooling. The research was conducted in two phases to gain insight into the adaption of online education in schools. The first part of the research was a quantitative study conducted during online education in 2019/2020 among 538 elementary and high school informatics teachers across Croatia. Data were collected from an online survey. The second part of the research was a qualitative study conducted in 2022, employing interviews for data collection. The interview questions were designed based on the survey results mentioned above. The results showed that CS teachers had a significant role in implementing online schools, acting as implementers of tools for online teaching and as helpdesk IT support to other teachers. Still, formal education nowadays is affected by online schooling, and some online practices are now adopted into regular teaching. Therefore, the findings can serve as a guideline for future education related to the digital competencies of teachers and students.

There is growing attention to the potential for developing professional learning experiences for content area teachers to infuse computational thinking (CT), which refers to the set of problem-solving practices related to the computer science discipline, into their classrooms. Although research has begun to document professional learning models and supports for CT infusion, an understudied area for both research and practice is how in-service teachers come to lead CT infusion efforts through determining curriculum, supporting their colleagues, and designing school and district-wide programs, once the professional development (PD) and related learning experiences are over. In this paper, we document findings from the final year of a five-year PD project, in which a subset of middle and high school content area teachers and teacher teams (n=12) proposed, designed, and carried out their own CT infusion projects. Using a practitioner inquiry framework, we analyze teachers' choices in project types (curriculum development, teacher PD, and activities designed to connect in-school and informal learning), motivating factors for applying for the grant, their inquiry processes, and their perceptions of project impact. We discuss suggestions for supporting teacher-led CT infusion, including taking incremental approaches that develop teacher knowledge over time, building both discipline-specific and interdisciplinary teacher communities, and engaging multiple stakeholders to build the culture necessary for CT infusion. We conclude with general implications for creating structures to sustain and extend researcher-practitioner partnerships.

Background: The coronavirus pandemic has caused a shift in how many teaching, learning and research activities are conducted internationally. Lockdowns compelled all education sectors, including higher education (HE), to adopt a variety of online learning practices at short notice. As these changes in practice have implications beyond the pandemic, more needs to be understood about settings across the globe where the move to online may pose particular challenges. This study brings a focus to how lecturers in a college of education in Nigeria responded to the professional demands of lockdowns and developed strategies for managing educational activities that have relevance during and beyond the pandemic itself. Purpose: The aim of the study reported in this paper was to examine lecturers' perceptions of the management of teaching, learning and research activities during a lockdown, drawing out longer term implications. Methods: Data were collected through in-depth, one-to-one interviews with six lecturers from a college of education in Nigeria. Interview data were analysed qualitatively. Findings: Detailed analysis indicated that lecturers' strategies included encouraging students to engage in self-directed learning, as they uploaded learning materials on messaging groups and the college's e-learning platform. However, lecturers felt that the quality of teaching and assessment was compromised by factors including: irregular power supply, poor internet connection, high data costs and some students' limited digital skills. A particular concern was students' lack of interaction on the online platforms, which lecturers perceived to result in a more passive teaching and learning process. Lecturers also experienced difficulties undertaking research activities. A range of strategies and implications for the ongoing management of educational activities was discussed. Conclusions: The study offers insights into how some of the challenges encountered could be addressed to support sustainable online and blended teaching and learning in the longer term, in settings internationally where there are barriers to accessing online teaching and learning. Crucial aspects include strengthening educational technology training for lecturers and students, enhancing e-learning platforms for teaching practical courses, and enabling lecturers to develop beneficial and valuable online resources.

Despite being in a digital age, the diversity of young people choosing to study and work in computing is of ongoing concern, especially low numbers of girls. This paper aims to determine the profile of students who are more likely to aspire to be computer scientists and provide insights into the key factors that shape their aspirations in this area. We draw on questionnaire data from 4,983 secondary school students in England, in schools that have a higher-than-average uptake of GCSE Computer Science (a national exam taken by students at age 16). Amongst students who have chosen to study GCSE Computer Science, girls have a lower odds of aspiring to be a Computer Scientist compared to boys. Amongst younger students yet to pick their GCSE options, there are significantly more girls than boys wanting to work in digital art. Multivariable regression analysis identified 10 factors that were associated with aspirations to become a computer scientist. These include being a boy, being of Asian ethnicity, currently studying GCSE Computer Science, having a parent in computing, as well as having higher 'coding self-belief', elevated levels of 'family support' and aspiring towards 'technical jobs'. Implications for practice and curriculum design are discussed.

We introduce "Ricerca Operativa Applicazioni Reali" (ROAR; in English, "Real Applications of Operations Research"), a three-year project for higher secondary schools. Its main aim is to improve students' interest, motivation, and skills related to Science, Technology, Engineering, and Mathematics disciplines by integrating mathematics and computer science through operations research. ROAR offers examples and problems closely connected with students' everyday life or with the industrial reality, balancing mathematical modeling and algorithmics. The project is composed of three teaching units, addressed to grades 10, 11, and 12. The implementation of the first teaching unit took place in Spring 2021 at the scientific high school IIS Antonietti in Iseo (Brescia, Italy). In particular, in this paper, we provide a full description of this first teaching unit in terms of objectives, prerequisites, topics and methods, organization of the lectures, and digital technologies used. Moreover, we analyze the feedback received from students and teachers involved in the experimentation, and we discuss advantages and disadvantages related to distance learning that we had to adopt because of the COVID-19 pandemic.

Computing has become essential in modern-day problem-solving, making computational literacy necessary for practicing scientists and engineers. However, K-12 science education has not reflected this computational shift. Integrating computational thinking (CT) into core science courses is an avenue that can build computational literacies in all students. Integrating CT and science involves using computational tools and methods (including programming) to understand scientific phenomena and solve science-based problems. Integrating CT and science is gaining traction, but widespread implementation is still quite limited. Several barriers have limited the integration and implementation of CT in K-12 science education. Most teachers lack experience with computer science, computing, programming, and CT and therefore are ill-prepared to integrate CT into science courses, leading to low self-efficacy and low confidence in integrating CT. This theoretical paper introduces a novel instructional approach for integrating disciplinary science education with CT using unplugged (computer-free) activities. We have grounded our approach in common computational thinking in STEM frameworks but translate this work into an accessible pedagogical strategy. We begin with an overview and critique of current approaches that integrate CT and science. Next, we introduce the "Computational Thinking through Algorithmic Explanations" (CT-AE) instructional approach. We then explain how CT-AE is informed by constructionist writing-to-learn science theory. Based on a pilot implementation with student learning outcomes, we discuss connections to existing literature and future directions.

In this paper, I introduce the notion of participative epistemology and discuss how it can contribute to make social data science more accountable. I do so by offering the case of a project where ethnographic, computational and sequence analysis methods have been used in combination. By presenting here in greater detail research design and pilot results of a project using professional networking data to understand the careers of IT industry analysts, I suggest a view on the collaboration between data science and social science as coordinated labour. The application of participative epistemology to social data science is articulated in three points: (1) a more tactical view on the partnerships with commercial data where shared value system is not a pre-requisite for coordinated knowledge production; (2) an appreciation for complementarities in perspective between phenomenological sociology, expertise in computer science associated to digitalisation and the narrative positivism linked with the use of statistics; and (3) a view on social data science as contributing empirical sociology with new sensitizing concepts, taking ethnography to reflectively address its own presuppositions. [Note: The page range (391-403) shown is incorrect. The correct page range is 395-407.]

The main objective of this paper is the conceptual design of a computational AI system that emulates human creativity. To do this, extensive research has been done on recent discoveries about the neural bases of human creativity. As a result, eleven neurocognitive factors have been identified on which the tremendous creative capacity of the human brain is based. The integration of these factors has made it possible to create a neurocognitive model of human creativity. The analysis of each of creative neurocognitive structures separately suggests certain characteristics that must be present in the structure of a creative computational system to emulate brain creativity. Properly integrating these characteristics, a general architecture for a creative multi-agent system has been proposed, as well as the guidelines for the correct representation of knowledge. Based on this general architecture a creative computational system can be implemented for a specific field of knowledge, or general purpose.

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.