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Online learning has been widely discussed in education research, and open educational resources have become an increasingly popular way to help learners acquire knowledge. However, these resources contain massive amounts of information, making it difficult for learners to identify Web articles that refer to computer science knowledge. This study developed an Internet articles retrieval agent combined with dynamic associative concept maps (DACMs). The system used text mining technology to analyze keywords to filter computer science articles. In previous research, concept maps were manually constructed; in this study, such maps can be automatically and dynamically generated in real time. In a case study of a fundamental course of artificial intelligence, this study designed two experiments to compare students' learning behaviors while using this system and the Google search engine. The results of the first experiment showed that the experimental group searched for more knowledge articles on computer science using this agent, compared to the control group using the Google search engine. The learning performance of the experimental group was significantly better than that of the control group, while the cognitive load of the experimental group was significantly lower than that of the control group. Furthermore, the results of the second experiment showed that the learning progress of students using the agent was significantly greater than that of students who used the Google search engine. This illustrates that the agent effectively filtered computer science articles, and DACMs helped students gain a deeper understanding of academic concepts and knowledge related to artificial intelligence.

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.

The impact of hate speech, both on a personal and social level, has increased due to social media. This has made it the focus of interest of numerous scientific journals, which increases the visibility of this global problem. The aim of this research is to analyse the basic descriptive metrics of the scientific production on hate speech and social media, as well as to explore the interdisciplinarity of these approaches. A bibliometric study has been carried out on the basis of the works indexed in the Scopus database related to the binomial 'hate speech' and 'social media' over a period of 20 years (2001 to 2020). The metrics used show that it is from 2017 onwards when this topic begins to arouse greater interest among researchers and that they constitute a sufficient indicator to consider the topic as one of interest to the scientific community. The joint research between both concepts raises its quality levels from a strictly metric point of view. 'Computer Science' and 'Social Sciences' are the two areas that clearly define the scientific production on this subject. The inversion of percentages in terms of the areas of origin of the works and citations in these two areas, is evidence of this interdisciplinarity. The indicators obtained show the relevance and transcendence of a social problem in the face of which proactive measures must be implemented.

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.

Computational thinking is a strategy of thinking to tackle complex problems. There is a paucity of conceptualization and instruments that cogitate on computational thinking disposition and attitudes. This study reacts to these constraints by establishing an instrument to test computational thinking related dispositions and attitudes. The computational thinking disposition Instrument is an indicator of student's disposition towards computational thinking in daily life. The objective of this study is to investigate the psychometric features using Rasch model. Data of 535 form four computer science students in Malaysia were obtained. Instrument consists of 55 core measures in three domains: cognitive, affective and conative. The Rasch analysis indicated good psychometric features of the instrument. In these three domains no items showed disordered thresholds and the reliability was good. As a result, the Rasch analysis provides basis for cautious optimism permitting more detailed and finer level investigation of the instrument.

Everyone uses a traditional five-point grading system to assess students' activities, however, it is not always possible to objectively evaluate students' work using this method. Therefore, the authors use the criteria-based student assessment system in our lessons. The purpose of this article was to compile a model of a system for assessing students' functional literacy based on a criteria-based approach. An experiment was conducted on 32 people and data was collected using observation and interviews. As a result of the study, it was revealed that the assessment system makes it possible to determine how successfully one or another educational material is mastered, or a certain practical skill is formed. Based on the conducted practical experiment, the effectiveness of the content-structural model of the system for assessing the functional literacy of students based on the criteria-based approach in computer science has been proved.

Interdisciplinary project teams are increasingly vital in organizations that are focused on providing successful technical solutions that include a positive user experience. In response to the need for experience in this area, some higher education institutions have created interdisciplinary project-based experiential learning opportunities. In this research, we examine an interdisciplinary computing capstone course and present results from a qualitative study of student participants. We investigate how teams in an interdisciplinary capstone course self-organize, what convictions drive these decisions, and how they assess and value the expected contributions from disciplines other than their own. We analyze students' attitudes, beliefs, and motivations as gleaned from interviews and offer suggested improvement strategies for future interdisciplinary capstone courses.

The purpose of this study is to introduce a developed activity which is named "CityMap" and to present an example of the implementation and evaluation process of a computer science unplugged activity through this activity. The aim of this activity is to write algorithms of going from one place to another using step by step instructions. The rules are also to reach the destination with the shortest way and the least number of steps using correct instructions. Accordingly, a map and a worksheet was designed to implement the "CityMap" which is related to daily life and scenario based. For the evaluation, an answer key was prepared and scoring criteria were determined. Then, the case study was used as a research method and the process of writing algorithms using step by step instructions of students was examined by implementing the the activity with 15 sixth grade students. Both individual and group evaluation were made and for this process game components were used. The findings revealed that, in general, students could wrote algorithms step by step instructions for the tasks determined in the activity. In addition, during the implementation, it was observed that using of the gamification made the activity more enjoyable.

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.

Computational thinking (CT) has emerged as an important method in the United States for helping children learn to solve complex problems and develop skills necessary for coding and other computer science-related endeavors. Research has revealed that CT can be encouraged with children as young as 3-4 years of age. While some preschools and schools are incorporating CT into their curriculum for young children, ages 0-8 years, it is important to understand how environments outside of schools are using CT with young children, particularly given that, in the United States, a large percent of young children, ages 0-5 years, are not in formal school settings. This study provides insight into this area through 20 interviews with educators in libraries and museums to understand how they incorporate CT into their work with young children, ages 0-8 years, and their families. The interviews reveal that library and museum educators are using a variety of developmentally-appropriate approaches, such as play, experimentation, and narrative, to design and offer a diverse array of engaging, hands-on CT activities that allow young children to practice CT in child-centered, meaningful ways.

Despite originating in the tech industry, hackathons have now been adopted in a variety of domains. However, little is known about the status of hackathon literature within educational research. As the number of studies grows, it is essential to develop an understanding of the current state and identify prevalent topics and trends shaping the literature. Toward this goal, this study conducted a bibliometric analysis and scoping review on hackathon research in the field of education. A total of 249 documents written by 1,309 authors and published in 180 unique sources for the period 2014-2022 were identified. Collectively, the dataset amassed 1,312 citations with an average of 6.69 citations per document. The most prevalent subject areas were computer science, social sciences, engineering, medicine, and business. Word frequency analysis showed that "innovation" was the most occurring word, which represents the fundamental objective of hackathon events. The most influential work was the analysis of hackathons as an informal learning platform. Engineering education was the most trending topic while healthcare is an emerging research cluster. Overall, this study provides a better understanding of the hackathon literature and its research landscape in an educational setting.

There is persistent underrepresentation of female and ethnic and racial minority students in computing. While community colleges provide a unique opportunity to increase diversity in computing fields, many students do not persist. This study aims to understand the factors that predict students' momentum--completion of a certificate, degree, or transfer in an information and communications technology (ICT) major--in order to generate information that can be used to tailor interventions. Participants were enrolled in ICT classes at 17 community colleges. Surveys were collected from 474 students at three time points over two years. Multilevel logistic regression was used to identify the factors that predict momentum approximately one year after the class ended. The results expand on Wang's theoretical model of student momentum. Men were more likely than women to have achieved an academic milestone, which was partially a result of taking more prior ICT classes, having more positive interactions with faculty and a more positive perception of the classroom climate, as well as greater motivation and fewer childcare responsibilities. Among students from groups that are underrepresented in computing, momentum was positively associated with taking prior ICT classes, motivation during the class, and romantic relationships; it was negatively associated with educational barriers. Being enrolled less than full-time at baseline or having financial challenges did not undermine momentum. Implications for practice, as well as study limitations are discussed.

Integration of computational data science (CDS) into the university curriculum offers several advantages for students, faculty and the institution. This article discusses the benefits to students of introducing CDS into the university curriculum with a focus on developing skills in cheminformatics, data analysis, structure--activity relationships, modelling and simulation. Moreover, CDS can enable students to engage with complex chemical and toxicological data in new and dynamic ways, helping them to develop a more nuanced understanding of the potential hazards and risks associated with different chemicals and substances. On the other hand, it can foster greater collaboration between students and faculty and with external partners in industry and government. This can lead to the development of more effective and efficient toxicological testing methods and tools to screen chemicals for potential hazards and aid the development of environmentally friendly chemicals. Overall, the integration of CDS into the university curriculum will help prepare the next generation of scientists giving them a competitive edge to make considerable contributions to green chemistry, designing safer chemicals and non-animal testing methods. It will enable them to tackle modern challenges facing society including identifying safer and more sustainable chemicals and predicting the health and environmental impacts of novel chemical substances.

Context: With the introduction of Computer Science (CS) into curricula worldwide, teachers' adoption of CS pedagogical content is essential to ensure the long-term success of reform initiatives. Continuing Professional Development (CPD) programs play a key role in this process. Unfortunately, adoption is seldom evaluated in CS-CPDs or CPDs in general. The result is a dearth of studies: (1) modelling teachers' adoption of CS pedagogical content; or (2) investigating factors influencing the uptake of this new discipline. Both aspects are crucial to design and characterize successful CPD programs. Objectives: We thus propose the Teachers' Adoption of CS (TACS) model to investigate factors influencing the adoption of CS pedagogical content by teachers who are following a mandatory CS-CPD program. More specifically, the model proposes that contextual factors (e.g., age, gender, and general teaching experience), prior factors (e.g., experience, and CS perception), and acceptance factors (e.g., interest, and self-efficacy) may impact teachers' adoption of CS pedagogical content. Methods: The study included 180 grades 5 and 6 teachers (students aged 9-11) that were following a mandatory CS-CPD program. The CS-CPD program involved participation in three-day-long sessions distributed over the 2019-2020 academic year. In between sessions, with the support of instructional coaches in the schools, teachers were encouraged, but not required, to adopt the CS pedagogical content. Therefore, during the CPD, and employing surveys based on the TACS model, we evaluated teachers' adoption of the proposed content and investigated how the different factors influenced it. Results: At the PD-level, the results indicate that self-efficacy and interest queried during the CS-CPD are indicative of CS pedagogical content adoption. To shed more light on the relationship between these metrics, a more in-depth analysis was conducted with n = 92 teachers whose responses could be matched between sessions. While interest relates to how teachers adopt CS pedagogical content overall, both interest and self-efficacy are necessary to ensure the likelihood of a specific activity being adopted. Finally, individual teacher characteristics appear to impact adoption, with teachers with low experience with Information and Communication Technologies (ICT) requiring onboarding, while middle-aged teachers require convincing to adopt CS pedagogical content. Conclusion: Three takeaways emerge from the study. First, the analyses confirm the foundation of the TACS model. Second, the findings establish the key role that interest plays in said model. Finally, the results support the relationship between the contextual, prior and acceptance factors on the adoption of primary school CS pedagogical content.

In a nationwide initiative to increase computer science Education in K-12, many teachers were recruited to CS teaching positions but without adequate preparation, which can lead to lack of confidence and feelings of isolation [35, 54]. In response to these issues, the purpose of this study was to determine the effectiveness of a newly developed summer professional development program with follow-up support with the goal of improving teacher confidence and informing teacher beliefs about computer science. This training featured peer instruction and an emphasis on computer science principles. It took place over three years, and was used to prepare teachers from over 50 schools across a midwestern state. Using Hierarchical Linear Modeling, data analysis from 57 teachers and 871 students showed that teacher confidence and content knowledge increased significantly, and to a greater extent for those who began with the lowest levels of confidence. Students also made significant knowledge gains from before to after taking the class. Student gains were higher for those whose teachers were more confident in their ability to teach computer science.

Instrument development is an important step towards unlocking the analytical power of teacher attitudes and beliefs towards Computer Science (CS). Teacher dispositions have strong empirical and theoretical ties to teacher motivation, professional choices, and classroom practices. To determine consensus desirable attitudes and beliefs, we analyzed 17 key documents produced by 12 national and international organizations associated with CS and the CS education reform movement. An analysis of 98 relevant coded segments yielded four dispositional targets: an equity orientation, a teacher growth mindset, and key beliefs regarding (career) outcomes and epistemology of CS. Statements crafted for these targets as well as self-efficacy were reviewed through an expert panel (N = 5) and a pilot study (N = 22) before the T-ABC was administered to elementary teachers in a large grant-funded outreach project (N = 772). Psychometric analysis demonstrates high reliability (Cronbach's alpha = 0.89) and satisfactory extraction and loading onto a three factor model, with CS beliefs, growth mindset, and self-efficacy as major factors. Identification and measurements of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences.

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.

Gen Z stands out as a new age learner group in the context of open and distance learning. Research shows that Gen Z has different needs and expectations form their predecessors; therefore, new educational interventions are required. The purpose of this study is to examine the suggestions of the scientific articles on Gen Z to draw educational conclusions. This systematic review includes educational suggestions (n = 77) of 59 articles selected from search results on Scopus, Google Scholar and ULAKBIM. The suggestions were coded and themed. Then, percentage and frequency analyses were made with the codes obtained. The main categories that emerged were speed, motivation, content, learning environment and active learning. Highlights of these suggestion categories are: rapid delivery of student feedback under the speed category, job-oriented education under the motivation category, use of student-produced content under the content category, paying attention to updating and following the digital contents under the learning environment category, learning autonomy acquisition practices under the active learning category. These educational suggestions are thought to help researchers and educational specialists who try to understand the generational differences and especially the features of Gen Z.

The aim of this study is to compare computational thinking skills of teacher candidates who are educated in Turkey and India. For this purpose, 555 male and 212 female who are students in the Faculty of Education at a University in Turkey and, 239 male and 493 female who are students in Faculty of Education at University of Madras in India. Within the scope of the research, the "computer thinking skill levels scale" developed by Korkmaz, Çakir and Özden (2017) to measure the computer thinking skills of university students in Turkey was used. The scale consists of 29 items and five factors. The Cronbach alpha of Scale' Turkish form is 0.822, and the Indian form is 0.769. Mean, standard deviation, t-test and ANOVA analyses were run on the collected data. According to the results, computational thinking skills of Indian teacher candidates are generally quite high, whereas Turkish teacher candidates are moderately high, and in both groups the students' highest level in term of factors is creativity, and the lowest one is problem-solving skill.

Bachelors and graduate students are offered in the course of teaching computational informatics, the ability to solve nonstandard mathematical problems, which, as a rule, are not included in the content of teaching computational informatics. The article aimed to analyze the application effectiveness of non-standard mathematical problems in the course of teaching computational informatics, elaboration of constructive computational solution algorithms of inverse problems for differential equations, during which the bachelors and graduate students develop own professional competencies. The research conducted a review of previous literature on the topic. Formulation of the inverse problem for differential equations for the investigation of which the computational mathematics finite difference methods are applied, is presented. In the course of investigation, it was revealed that at elaborating the constructive computational algorithms of its solution, the bachelors and graduate students develop not only fundamental knowledge in the field of applied and computational mathematics, computational informatics methods, but also develop the professional competences, including computational thinking.

Over its short disciplinary history, computing has seen a stunning number of descriptions of the field's characteristic ways of thinking and practicing, under a large number of different labels. One of the more recent variants, notably in the context of K-12 education, is "computational thinking", which became popular in the early 2000s, and which has given rise to many competing views of the essential character of CT. This article analyzes CT from the perspective of computing's disciplinary ways of thinking and practicing, as expressed in writings of computing's pioneers. The article describes six windows into CT from a computing perspective: its intellectual origins and justification, its aims, and the central concepts, techniques, and ways of thinking in CT that arise from those different origins. The article also presents a way of analyzing CT over different dimensions, such as in terms of breadth vs. depth, specialization vs. generalization, and in terms of skill progression from beginner to expert. Those different views have different aims, theoretical references, conceptual frameworks, and origin stories, and they justify their intellectual essence in different ways. [Note: The issue number (1) shown on the PDF is incorrect. The correct citation for this article is v20 n3.]

This study aimed to determine the views of thirty preservice preschool teachers recruited using convenience sampling on STEM education and engineering. Phenomenology was the design of choice. Data were collected using a semi-structured interview form and analyzed using inductive content analysis. Participants offered different definitions of STEM education and thought that it could have contributions in numerous aspects. They also remarked that preschool STEM education on civil and computer engineering skills made teachers better equipped. They mentioned designs and projects for preschool STEM education as well. However, they had the stereotypical image of engineering as a dirty job for men working in construction sites and carrying sand. Results suggest that preschool undergraduate education should integrate STEM activities and offer workshops and trainings to change preservice preschool teachers' misconceptions about engineering.

The present study aimed to determine the effect of Scratch-assisted expressions and applications on the Computational Thinking skills of pre-service teachers. For this purpose, the research was designed with an exploratory sequential design, a mixed research method. Thirty-three pre-service teachers participated in the study. Data were collected with Computational Thinking Scale before and after the applications conducted in the Instructional Technologies course, and with a survey form developed by the author and face-to-face interviews conducted with the participants at the end of the course. Based on the data obtained, it was determined that the applications conducted in the course improved the Computational Thinking skills of the participants. Although the improvement did not differ based on gender, it was determined that the differences were significant based on creativity, algorithmic thinking, and critical thinking sub-dimensions. Furthermore, it was observed that there was a positive and significant correlation between Computational Thinking and academic achievement. Also, pre-service teachers stated that Scratch applications contributed to the acquisition of Computational Thinking skills. It was suggested that the present study findings would contribute to future studies on Computational Thinking acquisition in similar courses.

Lexical bundles are two or more string of words that co-occur frequently in a corpus. Hence, this corpus-based research design study examines the effects of lexical bundles on English as a foreign language learner's abstract genre academic writing skills, and it also investigates students' perception towards lexical bundles instruction to enhance their academic writing skills. Hence, frequent lexical bundles were selected from 70 computer science articles. These articles were selected from 7 journals that were published in reputable, indexed, and through representative criteria. Accordingly, sixteen frequent lexical bundles were selected through corpus analysis software (Laurence Anthony's Antconc software) for the purpose of classroom instruction. The bundles are intended to help computer science students to develop their abstract genre academic writing skills. Students have instructed their academic writing through corpus informed instruction for two months, and the data were gathered through pre and post-tests and questionnaire. The findings indicated that lexical bundles have a positive effect on students' academic writing skills, particularly abstract genre writing. Besides, the students have a positive perception of the lexical bundle and the instruction to enhance their academic writing skills. Finally, this research calls attention to discipline-oriented lexical bundles since they are crucial for academic writing.

Societal stereotypes depict girls as less interested than boys in computer science and engineering. We demonstrate the existence of these stereotypes among children and adolescents from first to 12th grade and their potential negative consequences for girls' subsequent participation in these fields. Studies 1 and 2 (n = 2,277; one preregistered) reveal that children as young as age six (first grade) and adolescents across multiple racial/ethnic and gender intersections (Black, Latinx, Asian, and White girls and boys) endorse stereotypes that girls are less interested than boys in computer science and engineering. The more that individual girls endorse gender-interest stereotypes favoring boys in computer science and engineering, the lower their own interest and sense of belonging in these fields. These gender-interest stereotypes are endorsed even more strongly than gender stereotypes about computer science and engineering abilities. Studies 3 and 4 (n = 172; both preregistered) experimentally demonstrate that 8- to 9-y-old girls are significantly less interested in an activity marked with a gender stereotype ("girls are less interested in this activity than boys") compared to an activity with no such stereotype ("girls and boys are equally interested in this activity"). Taken together, both ecologically valid real-world studies (Studies 1 and 2) and controlled preregistered laboratory experiments (Studies 3 and 4) reveal that stereotypes that girls are less interested than boys in computer science and engineering emerge early and may contribute to gender disparities.

The overall aim of this article is to stimulate discussion about the activities within CER, and to develop a more thoughtful and explicit perspective on the different types of research activity within CER, and their relationships with each other. While theories may be the most valuable outputs of research to those wishing to apply them, for researchers themselves there are other kinds of contributions important to progress in the field. This is what relates it to the immediate subject of this special journal issue on theory in CER. We adopt as our criterion for value "contribution to knowledge". This article's main contributions are: (1) A set of 12 categories of contributions which together indicate the extent of this terrain of contributions to research; and (2) Leading into that is a collection of ideas and misconceptions which are drawn on in defining and motivating "ground rules", which are hints and guidance on the need for various often neglected categories. These are also helpful in justifying some additional categories which make the set as a whole more useful in combination. These are followed by some suggested uses for the categories, and a discussion assessing how the success of the article might be judged.

Computationally intensive science (CIS)-related disciplines and careers are predicted to be among the cutting-edge fields and high-demand jobs. Such disciplines and careers demand expertise in both traditional scientific knowledge and computer science (CS)-related understanding and skills. Preparing educational systems for developing interest and abilities for such career paths require a new set of research tools. In this study, we developed and validated a multidimensional instrument called computationally intensive science career interests (CISCI) to measure middle school students' interests in CIS careers. We also explored several predictors of students' interests in such careers and examined the impact of a 4-day online synchronous scientific computational modeling activity on students' career interests. A total of 934 Indonesian middle school students (aged 11-14) participated in this study. A combination of the classical test theory and item response theory approaches was used to validate the CISCI instrument. Multiple linear regression tests were run to identify the predictors of students' career interests, and paired-sample t-tests were used to examine a scientific computational modeling activity's impact on students' career interests. The results revealed that CISCI was a psychometrically valid and reliable instrument to measure students' career interests. We also found that science and CS attitudes, computational thinking, and prior experience in CS-related activities were significant predictors of students' career interests. In addition, computational modeling activity significantly influenced the frequency of students discussing such career paths with their parents. This study underscores the importance of engaging students in CS-integrated science learning activities to help develop their interests in CIS jobs.

Disciplines in Higher Education have their own interpretations of what is essential knowledge that influences what is taught, how teaching occurs, and the role of digital tools. Disciplinary culture is dynamic and evolving, informed by disciplinary research and technology improvement. During the COVID-19 pandemic, digital solutions enabled ongoing teaching when undergraduate courses could not be taught on campus, in lecture theatres, seminar rooms, laboratories, or in the field. Using digital tools and changes in teaching practices has created a context where Higher Education teachers must consider how future learning and teaching should occur. To explore this, a cross-discipline team used appreciative inquiry framed in complexity theory to examine how teaching in undergraduate programmes is changing in the digital age and implications for Higher Education teachers. The research identifies how digital technologies influence undergraduate programmes in Applied Statistics, Computer Science, Critical Indigenous Studies, Geography, and Information Systems. Analysis of the case studies identified how disciplinary culture, context, and technology combine to influence pedagogical practice and digital capabilities needed to teach in undergraduate programmes. We conclude that Higher Education teachers require capability in appropriate pedagogical practice that aligns with disciplinary culture and the technologies available.

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.

When pressing societal challenges (e.g., COVID-19, access to clean water) are sidelined in science classrooms, science education fails to leverage the knowledge and experiences of minoritized students in school, thus reproducing injustices in society. Our conceptual framework for "justice-centered STEM education" engages all students in multiple STEM subjects, including data science and computer science, to explain and design solutions to pressing societal challenges and their disproportionate impact on minoritized groups. In the first part of this article, we extend our conceptual framework by articulating the affordances of justice-centered STEM education for one minoritized student group that has been traditionally denied meaningful STEM learning experiences: multilingual learners (MLs). Justice-centered STEM education with MLs leverages the assets that MLs bring to STEM learning, including their transnational knowledge and experiences as well as their rich repertoire of meaning-making resources, thus refuting deficit narratives of these students. To illustrate the affordances of justice-centered STEM education with MLs, we draw on examples from our instructional unit that engages students in the pressing societal challenge of the COVID-19 pandemic. In the second part of the article, we report on an initial inquiry into how 14 undergraduate pre-service teachers made sense of our conceptual framework after participating in lessons from our COVID-19 instructional unit. Findings indicated that pre-service teachers perceived both opportunities and obstacles of justice-centered STEM education with MLs. We close by discussing what it might take to prepare the next generation of teachers to disrupt systemic injustices in and out of school.

The heterogeneous data acquired by educational institutes about students' careers (e.g., performance scores, course preferences, attendance record, demographics, etc.) has been a source of investigation for Educational Data Mining (EDM) researchers for over two decades. EDM researchers have primarily focused on course-specific data analyses of students' performances, and rare attempts are made at the domain level that may benefit the educational institutes at large to gauge and improve their institutional effectiveness. Our work aims to fill this gap by examining students' transcripts data for identifying similar groups of students and patterns that might associate with these different cohorts of students based on: (a) difficulty level of a course category, (b) formation of course trajectories, and, (c) transitioning of students between different performance groups. We have exploited descriptive data mining and visualization methods to analyze transcript data of 1398 undergraduate Computer Science students of a private university in Pakistan. The dataset includes students' transcript data of 124 courses from nine distinct course categories. In the end, we have discussed our findings in detail, challenges, and, future work directions.

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.

Coding is increasingly popular in schools around the world and is often taught by non-specialist teachers as an integrated task with other subject areas. In this article, we explore the relationship between computer science (CS) concepts and students' multimodal expression in a coding animated narrative (CAN) task in the context of an integrated English-Technology unit of learning. Through this collective case study, we explore how CS concepts underpin semiotic elements of an animated narrative, analyse the factors that influence the extent to which students exercise those concepts, and reveal the tensions and opportunities that a CAN task may present for learning computer science concepts in regular, non-specialist, cross-curricular classrooms. The findings suggest that CAN tasks are unique in presenting opportunities for students to learn challenging CS concepts such as synchronisation and parallelism. At the same time, CAN tasks present tensions for teaching CS concepts in non-specialist classrooms, where student projects are often judged on their visual qualities. In such settings, procedural, rather than conceptual knowledge, may be a more efficient route to creative outcomes. It also means that drawing skills need to be prioritised. Role specialisation often led to better quality projects but at the expense of individual students' conceptual development in computer science.

This study offers a review of existing research on translanguaging, inclusion, and computational literacies. It assesses existing school statistics and a student opinion survey released by the New York City Department of Education in Spring 2019 to investigate the attitudes and experiences of students at a public secondary school in the South Bronx that incorporates translanguaging into grades 6-8 computer science and Spanish courses given to most students. The findings of this study indicated that both Language Heritage Learner (LHL) and Non-Language Heritage Learner (NLHL) and perceived overall positive cultural responsiveness from the school community regarding their language identity in a setting where translanguaging exists (most notably in the Dual Language programme), but a minority of staff felt that they did not sufficiently incorporate considerations for cultural heritage and linguistic background into instruction. This study concludes with implications to further improve cultural responsiveness at the staff and administrative levels, the limitations of the study, and thoughts on further research on the issue of assessing whether culturally responsive education is accessible to neoindigenous student populations, particularly given that a citywide survey instrument facing hundreds of thousands of students throughout New York City does not specifically ask about language inclusivity.

We present the results of an ongoing collaboration between computer science and psychology researchers that employs Natural Language Processing (NLP) methods to examine the trajectory of semantic space used during group idea generation sessions. Specifically, we track and estimate the region of semantic space being used and the degree to which new ideas expand that space. We present a visualization of this space mapping endeavor and compare human ratings of creativity dimensions (i.e., novelty, task-relevance, and elaboration) to algorithm-based estimations of those same dimensions. The semantic space mapping and algorithm development projects can be used to deliver real-time feedback to human creative groups in order to optimize the collaborative creativity process. The overall goal of this research is to increase the "survival" of novel ideas and their elaboration in the collaborative ideation and subsequent decision processes.

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.

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.

The current study compared American, Korean, and Indonesian middle and high school students' CS attitudes. Concurrently, this study also examined whether the items in the CS attitudes scale exhibit country and gender measurement biases. We gathered data on CS attitudes from middle and high school students in the US, Korea, and Indonesia. The participating students took the same (translated) previously validated CS attitudes scale. We ran a unidimensional IRT, differential item functioning (DIF), a two-way ANOVA, and the Kruskal-Wallis H test. Despite the valid instrument, we found it inappropriate as is for international comparison studies because students from different countries interpreted some items differently. We then compared gender-based differences in CS attitudes across countries. The results revealed no significant differences between males and females in the Indonesian middle school data, whereas male students had significantly higher CS attitudes than female students in both American and Korean student data. Furthermore, we found the same pattern in gender differences in Korean and Indonesian high school students' CS attitudes scores as in the middle school study. These findings underscore the importance of a country's sociocultural context in influencing gap and diversity in secondary school students' CS attitudes.

Journal coverage is an important factor to consider when evaluating a database. In this study, we counted the number of articles (including early access articles) in newly-launched journals (2018-2022) from two major association publishers in engineering and computer science: the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). We then compared these numbers with the number of articles from these journals in Web of Science (WOS) Core Collection, Scopus, and Google Scholar (GS). Results indicated that GS had higher percentages for coverage for all the journals that were assessed and outperformed WOS and Scopus in terms of how fast newly-launched journals were indexed. Findings from this study will help librarians evaluate each database in reference, instruction, and collection development.

The disciplinary identity as a computer science student has recently received increasing attention as a well-developed subject identity can help with increasing retention, interest, and motivation. Besides, identity theory can serve as an analytical lens for issues around diversity. However, identity is also often perceived as a vague, overused concept with a variety of theories to build upon. In addition, connections to other topics, such as computer science conceptions, remain unclear and there seems to be little intra-disciplinary exchange about the concept. This article, therefore, attempts to provide a starting point by presenting a so far missing systematic literature review of identity in Computing Education Research (CER). We analyzed a corpus of 41 articles published since 2005 with a focus on the variety of identity theories that are used, the reasons for using them, and the overall theoretical framing of the concept in the CER literature up to this point. We use content analysis with both inductive and deductive coding to derive categories from the corpus to answer our research questions. The results show that there is less variety in the theories than originally expected, most publications refer to the theory of "Communities of Practice". The reasons for employing identity theory are also rather canonical, in particular, there is only little theoretical development of the theories within CER and also only little empirical work. Finally, we also present an extended version of a computing identity that can be theoretically derived from the work in our corpus.

Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an educational context such information may be deemed insufficient, it would be beneficial for both the student and the instructor to receive additional feedback about the overall development of the task. This work aims to tackle this limitation by considering the further exploitation of the information gathered by the OJ and automatically inferring feedback for both the student and the instructor. More precisely, we consider the use of learning-based schemes--particularly, multi-instance learning (MIL) and classical machine learning formulations--to model student behavior. Besides, explainable artificial intelligence (XAI) is contemplated to provide human-understandable feedback. The proposal has been evaluated considering a case of study comprising 2500 submissions from roughly 90 different students from a programming-related course in a computer science degree. The results obtained validate the proposal: The model is capable of significantly predicting the user outcome (either passing or failing the assignment) solely based on the behavioral pattern inferred by the submissions provided to the OJ. Moreover, the proposal is able to identify prone-to-fail student groups and profiles as well as other relevant information, which eventually serves as feedback to both the student and the instructor.

The under-representation of women in the field of Science, Technology, Engineering, and Maths (STEM) is of great concern in South Africa. Despite the efforts made by the government to improve access to education for learners from previously disadvantaged communities, South African Black women are still under-represented in STEM fields. The present study aimed to understand the experiences and challenges that limited the success of Black South African women in STEM courses. The study adopted a qualitative approach and was descriptive in nature. The purposive sampling technique was used to select a sample of eight students studying towards an undergraduate degree in Computer Science at a South African public university. Data was collected using in-depth one-on-one interviews and thematic analysis was deployed to analyze the data. The findings revealed that the majority of the students attended public schools with limited resources (e.g. computer access), as a result struggled to cope with the course workload and language of tuition (English). The absence of relevant mentorship programmes also contributed to the challenges the students experienced in the field. The findings underscore the need for policy that utilizes an intersectionality approach to understanding the multiple interconnected challenges that Black women students experience in STEM courses in South African universities.