Search

Soft skills development, such as communication, teamwork, and problem-solving, is critical for computer students as they enter the profession. Students may be able to practice these skills in a virtual setting through an online task-based course. In this study, we investigated how successfully an online task-based course encouraged the development of soft skills among computing students. The course was designed to give students real-world challenges that required them to work in groups and communicate effectively with their classmates and instructors. The inquiry was based on a qualitative examination of the students' final reports. It gave data from two semesters (Fall 2020 and Spring 2021) of students who studied a course named Technical Communication. In total, 216 students' final reports were ready for investigation. A sample of 97 reports, representing 45%, was selected based on certain criteria to ensure a high-quality investigation. According to the findings of our study, the online task-based course helped boost the development of certain soft skills among students. Students noted an improvement in their ability to communicate effectively, cooperate successfully with team members, and identify professional responsibilities, as well as a rise in their self-confidence. Overall, this study emphasizes the necessity of introducing online task-based courses into computing students' curricula, giving them a valuable opportunity to develop critical soft skills. The present design of the Technical Communication Course is believed to be efficient regardless of the education delivery method (traditional/online).

Integrating computational thinking (CT) into various disciplines via computer science (CS) methods such as unplugged, block-based, text-based, and physical programming is a trending topic in educational sciences. This study presents a perspective on implementing an unplugged computer science activity to integrate CT into mathematics education. This study aims to examine the integration of CT into mathematics education, its classroom practice, and the opinions of students and pre-service teachers towards the unplugged CS activity. For this purpose, we developed an unplugged CS activity, which includes CT components, computer science and mathematics education achievements. The unplugged CS activity is a problem of transmitting data most efficiently and accurately between transmitter and receiver. The researchers trained twelve pre-service mathematics teachers to implement this activity in realclassroom environments. The pre-service teachers implemented the unplugged CS activity with 80 students in four classes. CT components were considered in the activity design. The students performed data collection, data analysis, decomposition, pattern recognition, algorithm design, and testing and debugging, which are components of CT, during the activity. Middle school students stated that they had enjoyed the activity and that this activity made the mathematics learning process satisfying. They established a relationship between the activity and mathematics education, besides, they needed help connecting it with CS concepts. Pre-service teachers stated that they had challenges in classroom management during the activity. Classroom management should be a part of teacher education in designing and implementing CT-integrated lessons. Courses containing classroom management, CS activity design and implementation should be developed for pre-service teachers based on theory and practice within their discipline.

As we move further into the digital age, the acquisition of digital literacy (DL) and computational thinking (CT) skills is emerging internationally as an essential goal for students in contemporary school curricula. As the world becomes more uncertain and volatile due to impacts of artificial intelligence (AI), international unrest, climate change, global economic instability and unforeseen catastrophes such as the Coronavirus (COVID-19) pandemic, it is necessary to review, revise and refine school education curricula and policies. The issue of what is essential for students to learn, and how they learn it, is of growing importance to international organisations such as the Organisation for Economic Co-operation and Development (OECD) and the United Nations Educational, Scientific and Cultural Organisation (UNESCO) and is emerging as a significant driver for educational reform across the globe. The growing prominence of CT and DL skills across many industry sectors has prompted recent changes to international assessment frameworks such as the Programme for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS). This paper will briefly discuss specific examples of alternative approaches to addressing CT in national curricula for the compulsory years of schooling and explain how CT has been adopted as a driver for mathematics curriculum change in Australia.

This study examined the effectiveness of guided data-driven learning (DDL) activities on helping technological university students with a lower-intermediate proficiency level to learn grammar and vocabulary topics for the TOEIC test. The question of whether inductive learners make more progress than deductive learners was also addressed. A total of fifty-one non-English majors in a freshman English class participated in the study. Five computer-based and four paper-based DDL lessons were developed to increase students' awareness of the usage of particular grammar items and the distinction between three sets of synonyms. In order to determine the effects of the treatments, all the participants took pre-tests and immediate posttests. The results showed that there was a statistically significant difference between pre- and post-tests on grammar and vocabulary. However, inductive learners did not outperform deductive learners. As for students' perception of the treatments, it is noteworthy that they tended to take a neutral to less than positive attitude towards this DDL experience even though such an experience helped them significantly improve. The results suggested the existence of a gap between students' perceived satisfaction and their actual achievement. Pedagogical implications of these findings were discussed to improve the efficacy of DDL in Taiwan's EFL context.

Even though the main purpose of Computer Education and Instructional Technology (CEIT) department is to educate and train computer teachers for K12 level schools in Turkey, the graduates from the department have diverse competencies in different fields like instructional designer, content creator, software developer, etc. However, neither the graduates nor the companies in educational technology or other fields have fully awareness of that competencies essential mostly in non-teaching fields. A small number of studies have worked with CEIT graduates, but more studies are needed to explore those competencies and current job requirements in the companies. In this way the graduates would create better career plans and the companies would hire correct employee. Moreover, the CEIT curriculum would be reconsidered with respect to the experiences or expectations of the graduates or the companies. This study was conducted to investigate the opportunities of CEIT graduates in non-teacher positions in any business sector in Turkey. For this purpose, four research questions were asked: 1) What are the job opportunities of CEIT graduates in non-teaching fields? 2) What are the competencies of CEIT graduates that enable them to work in non-teaching areas? 3) What competencies do CEIT graduates need to have more in order to work in non-teaching areas? 4) What are the changes that CEIT graduates in non-teaching fields suggest in the undergraduate program? To answer the questions a survey research design was used, and data were collected from 41 CEIT graduates who were working in non-teaching jobs, by means of a questionnaire. The questions were analyzed with descriptive statistics and content analysis. The results show that CEIT graduates do and can have professions in many different fields, both due to the courses in their own degree programs and the competencies that can be acquired after graduation. In addition, improvements in CEIT undergraduate curriculum have been discussed and suggested to support certain specializations in different fields.

This research investigates university students' success in their first programming course (CS1) in relation to their motivation, mathematical ability, programming self-efficacy, and initial goal setting. To our knowledge, these constructs have not been measured in a single study before in the Finnish context. The selection of the constructs is in line with the statistical model that predicts student performance ("PreSS") (Quille and Bergin, 2018). The constructs are compared with various demographic and background variables, such as study major, prior programming experience, and average weekly working hours. Some of the main results of this study are as follows: (1) students generally entered with a high interest in programming and high motivation, but these factors did not increase during the course, i.e., interest in programming did not increase. (2) Having prior experience yielded higher initial programming self-efficacy, grade expectations, and spending less time on tasks, but not better grades (although worse neither). While these results can be seen as preliminary (and alarming in some parts), they give rise to future research for investigating possible expectation-performance gaps in CS1 and later CS studies. As our dataset accumulates, we also hope to be able to construct a valid success prediction model.

Programs in bioinformatics, offered in many academic institutes, are assumed to expand women's representation in computer science (CS). Women's enrolment in these programs is high. Our questions are: Do these programs attract different women from those attracted to CS programs? What factors underlie women's decision to enroll in bioinformatics programs? How do these factors differ from those of women who choose CS, if at all? What career opportunities do these women anticipate and pursue? Using questionnaires and interviews, we found a statistically significant difference between the factors that motivate women to choose bioinformatics and others to study CS. Many bioinformatics students did not consider CS as an alternative. Post-facto they learned to love computing, albeit with a biology-oriented purpose. "Computing with purpose" underlies many participants' pursuit of careers in research, CS, and bio-tech. We thus conclude that bioinformatics programs do indeed expand women's representation in CS.

In today's world, the ability to think computationally is essential. The skillset expected of a computer scientist is no longer solely based on the old stereotype but also a crucial skill for adapting to the future. This perspective presents a new educational challenge for society. Everyone must have a positive attitude toward understanding and using these skills daily. One thousand two hundred seven documents about computational thinking (CT) may be found while searching the Scopus database from 1987 to 2023. Data from Scopus were analyzed using VOSviewer software. This study educates academics by delving into the fundamentals of what is known about the CT of visual and quantitative research skills. This approach allows for a more in-depth look at the literature and a better understanding of the research gap in CT. This bibliometrics analysis demonstrates that (1) research on CT is common to all sciences and will develop in the future; (2) the majority of articles on CT are published in journals in the fields of education, engineering, science and technology, computing and the social sciences; (3) the United States is the most dominant country in CT publications with a variety of collaborations; (4) keywords that often appear are CT, engineering, education, and mathematics, and (5) research on CT has developed significantly since 2013. Our investigation reveals the beginnings and progression of the academic field of research into CT. Furthermore, it offers a road map indicating how this study area will expand in the coming years.

Learning programming logic remains an obstacle for students from different academic fields. Considered one of the essential disciplines in the field of Science and Technology, it is vital to investigate the new tools or techniques used in the teaching and learning of Programming Language. This work presents a systematic literature review (SLR) on approaches using Mobile Learning methodology and the process of learning programming in introductory courses, including mobile applications and their evaluation and validation. We consulted three digital libraries, considering articles published from 2011 to 2022 related to Mobile Learning and Programming Learning. As a result, we found twelve mobile tools for learning or teaching programming logic. Most are free and used in universities. In addition, these tools positively affect the learning process, engagement, motivation, and retention, providing a better understanding, and improving content transmission.

The problem-based learning model via cloud technology (PBL model via cloud technology) is a research tool fabricated with the concepts of problem-based learning management, in which students are stimulated and enabled to foresee the problems that will arise. Also, in this learning style, teachers will define the problem situations and encourage students to develop their systematic analytical thinking skill by taking action through the cloud technology. Thus, it is believed that this learning model can be used as a guideline for the instruction management that can promote students to have thinking process and problem-solving process while developing their programming skills. The objectives of this research are (1) to synthesize the conceptual framework of the PBL model via cloud technology, (2) to develop the PBL model via cloud technology, and (3) to study the results of the PBL model via cloud technology. The results of this research show that (1) the overall elements suitability of the PBL model via cloud technology is at the highest level (Mean = 4.77, SD. = 0.44), and (2) the overall suitability of the PBL model via cloud technology is at the highest level (Mean = 4.74, SD. = 0.39). Referring to the research results above, it can be summarized that the PBL model via cloud technology can be employed as a guideline to further develop the PBL systems via cloud technology in order to promote the programming skills among vocational students in Thailand.

Emotions play a crucial role in knowledge acquisition and can significantly impact motivation when studying a new field. Unfortunately, young people, especially girls, are often not drawn to Computer Science. To address this issue, we conducted an analysis of emotions among 8-9-year-old and 12-13-year-old students engaged in Computational Thinking activities, considering educational level, gender, and type of intervention. Our study sought to understand the lack of interest by examining the emotions present in primary and secondary school students. Hour-long in-person classes were conducted, focusing on Computational Thinking activities. We used the Developmental Channels Questionnaire, which includes 13 emotions rated on a Likert scale from 0 to 10, to measure emotions. The results showed that the predominant emotions were mostly positive and ambiguous, with low intensity negative emotions, particularly in primary education. Gender differences were observed only in secondary education, while in primary education, the differences were not significant. Girls demonstrated an emotional evolution when engaging in these activities, unlike boys. These findings provide valuable quantitative insights for primary and secondary school teachers. Understanding the emotions experienced can help guide effective teaching approaches. By addressing emotional factors, educators can enhance students' interest in computer science, thus fostering a more inclusive and engaging learning environment.

The purpose of the current study was to explore the effect of modality (constructionist mBlock, Scratch, and Python interventions) on six-grade students' computational thinking, programming attitude, and achievement. The pre-test and post-test quasi-experimental design was used to explore the research questions. The study group consisted of 105 six grade students from three different classes. A constructionist learning environment was formed for Scratch, mBlock, and Python groups. All groups were given 8 week-instruction. Instruction included two forty-minute sessions each week. The data were collected through the programming achievement test, computational thinking test, and computer programming attitude scale. The results of the study showed that mBlock group outperformed the Scratch and Python groups with respect to computer programming attitude. Students who attended mBlock and Scratch groups had higher levels of programming achievement than those of the students who attended the Python group. No significant differences with respect to computational thinking were observed between the groups. This study has implications for educators who are teaching computational thinking and programming. Further research was recommended to explore the effect of modality.

Given the increasing needs of employees with computational skills, understanding the core competencies of K-12 computer science (CS) education is vital. This phenomenological research aims to identify critical factors of CS education in K-12 schools from the perspectives and visions of CS faculties in higher education and teachers in K-12 schools. This study adopted a phenomenological research design. The researchers conducted a semi-structured interview with 13 CS faculties and K-12 CS teachers in Michigan and analyzed the data using thematic analysis. The findings indicated that: (1) the core competencies for K-12 CS education include problem-solving through computational thinking, math background, and foundational programming skills, and (2) what is essential is not the programming languages taught in K-12 schools but computational thinking, which enables the learners to easily transfer from one language environment to another. The findings provide important implications for K-12 CS education regarding the core competencies and programming languages to be taught.

Computer science (CS) has become a critical part of K-12 education worldwide. Computational thinking (CT) skills are a key set of competencies in CS education that can solve problems and use computational design to create useful solutions. However, preservice and in-service teachers are not fully prepared to integrate CS and CT into their curricula. Furthermore, there are limited special topic courses and educational research on how to facilitate in-service teachers' professional learning of CS and CT, as well as their content specific integration. Therefore, this study investigated in service teachers' perceptions and development of CT skills in an online graduate emerging technologies course. Theoretically framed by the four cornerstones of CT (i.e., abstraction, algorithms, decomposition, and pattern recognition), participants perceived that they increased their CT problem-solving and creativity skills but decreased their collaborative learning and critical thinking skills. Additionally, teachers increased their CT test scores after taking the course. Most teachers used CT terminology correctly (i.e., algorithms and decomposition). However, only 59% correctly described abstraction and pattern recognition, while most teachers did not mention debugging. The authors call on teacher educators to address in-service teachers' CS knowledge gaps, increase their CT skills, and select appropriate strategies for CT professional learning.

Computer Science (CS) stereotypes promote the mindset that nerdy White males who have a high IQ and are technology enthusiasts are the ones to succeed in the field, leading to gender and racial disparities. This quasi-experimental study investigated if exposing teacher candidates to a stereotypical vs. counter-stereotypical CS role model affects their stereotypes and attitudes toward teaching CS. Participants exposed to a counter-stereotypical role model reported a statistically significant decrease in stereotypes about social skills, and slightly weaker stereotypes about appearance, cognitive skills, and work preferences. Participants exposed to a stereotypical role model reported no changes in stereotypes. Participants in both groups showed increasingly positive attitudes toward teaching CS. Implications for CS teacher education are discussed.

This paper reports on the findings of a Design-Based Research (DBR) study that investigated the transformative learning of six high school computer science teachers after they participated in a professional development (PD) training with a focus on Culturally Responsive Computing (CRC). Findings from the statistical analysis of pre-and post-surveys reveal ways in which teachers' understanding and enactment of CRC in their classrooms led to a reporting of increased student engagement, a deeper understanding of diverse learning needs, and improved access to cultural resources to specifically meet girls' needs. Findings from interviews and focus groups further reveal that after engaging in the PD, teachers qualitatively adapted their classroom strategies in order to uplift the cultural practices and gender identities of historically marginalized students. This study has implications for how teachers' professional development is designed and how they are guided to enact culturally responsive computing in ways that help recruit and retain racial and ethnic minority girls in CS courses.

The Cross Industry Standard Process for Data Mining (CRISP-DM) framework was developed in the 1990s and has been widely used as the most relevant and comprehensive leading principle for conducting analytics projects. Despite the wide acceptance and adoption of the CRISP-DM framework, the current business analytics discipline often focuses on the modeling phase and overlooks the interplays between the phases. Consequently, students often lack a comprehensive understanding of the entire analytics process. This teaching case is created to demonstrate the importance of the data analytics life cycle and how six phases collectively contribute to the success of analytics projects using R. This case collects real-life data and follows the six CRISP-DM phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. At the end of the project, students will learn the importance of the data analytics life cycle, especially the data understanding and preparation phases, which often receive minimal attention in business analytics projects. This project will also demonstrate the importance of storytelling, ensuring that critical insights are conveyed to the audience.

Organizations are keenly interested in employees trained in business analysis and robotic process automation. This is because those methods are growing in demand for improving efficiency in business processes. Business students exiting college must understand how to map out business processes and implement automation fundamentals to be competitive in the job market. In this hands-on project, students will analyze a real-world situation and utilize NICE Automation Studios to automate the process.

Research has shown that e-learning games do not have the same level of appeal to girls, as they do to boys; particularly in the crucial 11-14 age group. In the United Kingdom, this is typically when they start to make subject choices that impact their future studies and careers. Given the shortage of females who choose computer science as a career, this study explores how e-learning games can be designed to be motivationally appealing to young learners. It further explores the role of game representations and its appeal to this age group. This empirical study addresses the research question: "Can we develop e-learning games which appeal and motivate girls of age 11-14 to study computer science concepts?" Two e-learning games were developed: one included game representations such as game colour, graphics, character, age appropriateness, storyline, number of players, violence, identified as appealing to young females and the other game included antithetical or neutral representations. The two developed prototypes were used to explore key e-learning game representations as used to teach computer science concepts. A total of 304 participants, comprising of 152 girls and 152 boys from a combination of same sex and mixed secondary schools in Southeast England, engaged with both experimental games. The experiment also elicited information on how learners interact with these games and the resulting game appeal, motivation and learning. The insight gained from the analysis of data captured during the experiments, provide the evidence to demonstrate that inclusive e-learning games which motivate and appeal to girls of age 11-14 can be developed. This can have a positive influence on their willingness to use such games to learn computer science concepts. This implies that the study found positive outcomes related to e-learning game appeal, motivation and the learning of girls of this age group. A follow-up longitudinal study could investigate the impact of significant e-learning game representations that appeal to the target group. This could provide additional evidence on the changes in the appeal of the investigated significant game representations over time, due to the influence of other factors such as socio-economic and socio-cultural differences. This understanding can further enhance inclusive e-learning strategies to improve diversity in computer science education and consequently the career pipeline.

Mentorship is vital to increasing graduate school access in computing; however, mentorship must be structured in power-conscious, developmental ways to ensure equitable access to and support within computing graduate pathways. I engage a critical quantitative lens to examine mentoring support among undergraduates with reported graduate aspirations, taking a nuanced look at departmental mentorship to investigate how organizational power in computing may maintain inequitable mentoring outcomes. Descriptive and regression analyses draw from a longitudinal sample of 442 graduate aspirants in computing who completed an introductory course survey (between 2015-2017) and a follow-up survey (fall 2019). Results document significant variation in forms of mentoring support and disciplinary psychosocial beliefs (i.e., computing identity and self-efficacy), with key patterns across graduate aspirants' social identities and mentors' organizational power (via their departmental roles). I conclude by discussing structural and social inequities in mentorship, which may underscore disparities in students' realization of their computing graduate aspirations.

The use of computer applications as learning media has been widely used in the learning process. One such computer application is Augmented Reality. Augmented Reality has advantages in ease of use, media appeal, and mobility because it can be used on cell phones and tablets. Creative thinking is a skill that students need in solving problems in a learning process in the classroom. The research objective is to investigate the effect of augmented Reality on students' academic achievement viewed from the creative thinking level. MANOVA was used to analyze differences in cognitive and psychomotor learning outcomes between the experimental class using AR and the control class using PowerPoint. The results showed that learning media and creative thinking levels affect cognitive and psychomotor learning outcomes. Cognitive learning outcomes of students using AR are higher than student learning outcomes using PowerPoint. Meanwhile, the psychomotor learning outcomes of students using AR are higher than those using PowerPoint. The learning media significantly affects cognitive learning outcomes with a p-value = 0.007, while the creative thinking level significantly affects psychomotor learning outcomes with a p-value = 0.016.

The teaching and learning of programming has proven to be a challenge for students of computer courses, since it presents challenges and requires complex skills for the good development of students. The traditional teaching model is not able to motivate students and arouse their interest in the topic. The tool proposed herein, the REA-LP, aims to facilitate the study and retention of content related to the discipline of programming logic at the technical level by presenting its content through various types of media, in addition to allowing students to actively participate in the construction of their knowledge, favoring engagement and motivation. From the results of an empirical study with 39 students, it can be concluded that the tool was very well accepted, being effective in facilitating and assisting participants in their learning, motivation, and interest in classes, mainly due to the way in which the content is presented by REA-LP.

This research discusses the use of a gamified web platform for studying software modeling with Unified Modeling Language (UML). Although UML is constantly being improved and studied, many works show that there is difficulty in teaching and learning the subject, due to the complexity of its concepts and the students' cognitive difficulties with abstraction. There are challenges for instructors to find different pedagogical strategies to teach modeling. The platform proposed allowed students to complement their UML knowledge in an environment with game elements. From the results, it can be concluded that the platform obtained great acceptance and satisfaction of use. Most of the students participating in the research were satisfied with the usability of the platform, reporting a feeling of contribution of the tool to studying the content, in addition to pointing out the satisfaction of using gamification as a pedagogical strategy.

This paper presents an educational setting that attempts to enhance students' understanding and facilitate students' linking-inferencing skills. The proposed setting is structured in three stages. The first stage intends to explore students' prior knowledge. The second stage aims to help students tackle their difficulties and misconceptions and deepen their understanding of the topics under study. This is attempted through individual student engagement in suitably-designed activities and relative feedback. As recorded in previous research, students' difficulties feedback on the material development. The third stage of the educational setting exploits social interaction to help students reorganize their knowledge of the concepts under study. The web-based application of the proposed educational setting indicated improvement in first-year Computer Science (CS) students' understanding of fundamental Computer Architecture concepts and progress in students' linking-inference skills. These results encourage integration in the instructional process of interventions designed according to the proposed setting in order to support and enhance students' understanding of troublesome concepts and their interrelations.

Nowadays, the rapid development of ICT has brought more flexible forms that push the boundaries of classic teaching methodology. This paper is an analysis of online teaching and learning forced by the COVID-19 pandemic, as compared with traditional education approaches. In this regard, we assessed the performance of students studying in the face-to-face, online and hybrid mode for an engineering degree in Computer Science at the Lublin University of Technology during the years 2019-2022. A total of 1827 final test scores were examined using machine learning models and the Shapley additive explanations method. The results show an average increase in performance on final tests scores for students using online and hybrid modes, but the difference did not exceed 10% of the point maximum. Moreover, the students' work had a much higher impact on the final test scores than did the study system and their profile features.

The global spread of the COVID-19 pandemic posed unprecedented challenges to higher education institutions worldwide. As governments announced lockdown measures that placed restrictions and mandatory closures on establishments that traditionally required gatherings, universities worldwide cancelled face-to-face classes and adapted their mode of offering to online teaching and learning. Using an interpretive study based on a single case, this paper presents the author's most profound experiences with online teaching and learning of the Data Structures and Algorithms course at the University of Namibia (UNAM). Throughout the teaching of this course, the author kept an up-to-date reflective practice journal, and required her students to engage in reflective practice. The author also had an opportunity to engage and discuss her experiences with other lecturers in the School of Computing. The paper therefore presents a narrative of reflections on the meaning of teaching and learning as adapted to emergency online teaching during the COVID-19 pandemic. Findings suggest that reflective practice during emergency online teaching presents an opportunity for educators to experiment with new delivery approaches, as well as to monitor how their interventions can impact the achievement of learning outcomes.

Increased exposure to technologies has lately emerged as one of the everyday realities of digital natives, especially K-12 students, and teachers, the digital immigrants. Protection from cybersecurity risks in digital learning spaces is a human right, but students are increasingly exposed to high-risk cyberspace without time to cope with cybersecurity risks. This study, using a survey (N-891 students and 157 teachers) and in-depth interviews (27 students and 14 teachers), described the students' cybersecurity-related experiences and challenges in Nepal. This study revealed that the school's cybersecurity support system is poor and teachers has very low awareness and competencies to protect students from cybersecurity-related challenges. To create a safe cyberspace for learners, it is urgent to enhance the cybersecurity awareness and skills of teachers, as the existing infrastructure is weak and there is a significant gap related to the cybersecurity awareness between students and teachers. Poor cybersecurity is one of the significant barriers to the quality of education in Nepal. In the age of information and technology, effective collaboration among parents, teachers, and students, the multigenerational learners, is the prerequisite for ensuring children's rights to learn in all settings including cyberspace.

The study aimed to investigate students' perceptions of undergraduate programs in relation to exit examinations, employing a mixed research design. A total of 145 students participated in the study. Deans, Department Heads, and College Quality Assurance Coordinators were selected based on availability and purposive sampling methods. The study focused on three colleges each with four years program durations, including Colleges of Social Sciences and Humanities (CSSH), Business and Economics (CBE), and Natural and Computational Sciences (CNCS). Two departments were randomly selected from each college, ensuring equal representation. Survey data was analyzed using mean, stepwise regression, and one-way ANOVA, while interview data was directly cited from respondents. Results of the study revealed that students' perceptions of exit exams varied across colleges, with CBE students demonstrating a more positive perception compared to CSSH and CNCS. Stepwise regression analysis identified significant predictor variables, including anxiety, stress, risk of exclusion, and resource scarcity, all of which influenced students' perceptions of exit examinations. Overall, the study found that students generally held negative perceptions of exit exams. It was evident that factors such as anxiety, stress, unknown content of the exam, risk of exclusion, and resource constraints contributed to the undesirable perceptions. A collaborative approach involving various stakeholders, including the Ministry of Education (MoE), educational institutions, and departments is necessary to reduce excessive stress and anxiety levels, emphasize the importance of exit examinations, address resource deficiencies, and undertake a nationwide study. MoE needs to formulate a well-defined policy concerning students who do not successfully pass their exit exams.

The purpose of the current study was to evaluate the undergraduate program of the Computer Education and Instructional Technology (CEIT) Department. CEIT department is an undergraduate program that trains information technology teachers. The study group of the study, which was designed according to the descriptive research model, was consisted of 461 CEIT graduates, who were selected by using the convenience sampling methods. Three instruments were used to collect data; a "Personal Information Form," the "Pedagogical Competence Perception Scale for the CEIT Graduates," the "Technological Competence Perception Scale for the CEIT Graduates." The data collection tools were developed by the researchers. When the results of the study are evaluated it is seen that the CEIT curriculum supports the participants in the acquisition of pedagogical competence more than the acquisition of the technological competence. When the pedagogical competence perceptions of the graduates are considered, it is seen that the graduates have high level competence perceptions about "Educational Planning and implementation, developing educational software and materials, educational communication competences, security and ethics in the use of information and communication technologies during the educational process, planning and implementation of the projects." When their perceptions of their technological competence are examined, it is seen that the graduates have moderate level of competence perceptions about "ability to solve problems in relation to the hardware installation and using visual software," while they have low level of competence perceptions about "ability to use system software and security of network and system." In this study, it was understood that the undergraduate program of the CEIT department, which trains future teachers of information technologies courses, is more sufficient in terms of developing pedagogical competence and less sufficient in terms of developing technological competence in students. In this context, the contents of the courses in the CEIT undergraduate program should be updated. Additionally, some studies should be conducted in order to develop the technological competence skills of the students attending the department.

In this study, a mobile Blackboard blended learning (BL) environment was implemented to teach the introductory computer course by integrating a learning management system with supplementary video lectures into BL provided through mobile technologies. The purpose of the study was to explore the impact of the mobile Blackboard BL environment on student satisfaction and learning achievement. The quantitative collection method was employed through a quasi-experimental design with a pretest and posttest control group. For seven consecutive weeks, the experimental group of students was taught in the mobile Blackboard BL environment and the control group of students was taught in the traditional learning environment. The students were asked to complete the instructional materials motivation survey to gauge their satisfaction level and given an achievement test at the end of the learning process. The study's findings revealed that the satisfaction level was significantly higher in the experimental group of students than in the control group of students. However, there was no statistical difference between students in the experimental and control groups in terms of learning achievement although students in the experimental group obtained slightly better results from the achievement test.

This study aimed to evaluate the Online Flipped Classroom (OFC) instruction process in the context of Transactional Distance (TD) and Cognitive Load (CL). The study was conducted using a mixed-methods design. The participants were nine graduate students. One of them participated in the process asynchronously and seven of them participated synchronously, and the one member was irregular. Transactional Distance Scale and Subjective Rating Scale were used to collect quantitative data. Interviews were conducted to gather qualitative data related to OFC instruction process. All of the TD measurements for the asynchronous and irregular students were low. The synchronous students' TD measurements were low when OFC began, becoming very low later on. The asynchronous student felt cognitive load during some of the OFC activities. Synchronous and irregular students felt the cognitive load during almost all the OFC stages. The future studies may focus on measuring the types of CL and collecting qualitative data to determine the CL type may contribute to the literature.

How can we engage new engineering and computer science graduate students in meaningful conversations about research and publication ethics without establishing a common understanding of the issues and expectations? Most universities offer extensive responsible conduct of research (RCR) training programs, which are usually a semester-long. Absent a requirement, it is unlikely that engineering and computer graduate students and their advisors would prioritize a lengthy training during the student's first semester. Recognizing this, the University of Nevada, Las Vegas' Howard R. Hughes College of Engineering designed and implemented an introductory research ethics workshop for all graduate students entering engineering and computer science. We engaged an interdisciplinary team of faculty and staff in the workshop's design and implementation, and approached our design within the sensemaking framework for ethical decision-making. Each workshop included lecture content in four priority topic areas identified by the college faculty: research design and data ethics, publication ethics, computer coding ethics, and intellectual property. The workshops also included a face-to-face panel discussion with experts including engineering, computer science, and law professors; librarians; and technical writers. Our assessment showed that after completing the workshop, students demonstrated increased content knowledge, and their self-assessed expertise ratings were better aligned with their content knowledge.

In this case study, we present our findings regarding a massive open online Scratch programming course. The course, which followed a project-based learning approach, was delivered from July 4 to 30, 2022 to 186 students in Brazil. The students were challenged to develop individual coding projects. Our research goal was to investigate teaching and learning course dynamics. We followed a convergent parallel mixed-method approach. We collected quantitative and qualitative data by means of questionnaires. We were able to identify five intertwined feedback loops that drove the educational process. Our main findings are as follows: 1) The development of coding skills was driven by the effort of watching video-lectures, remixing of peers' codes, and by sharing knowledge between the students. 2) The project-based learning approach created opportunities for the students to collaborate and exchange ideas.

A robust cybersecurity workforce is critical for protection against a range of malicious attacks. However, it has been noted that there are many vacancies and a shortage of individuals entering the cybersecurity workforce. This workforce shortage has partly been attributed to the lack of diversity in the cybersecurity field, with women, African Americans, and Hispanics remaining underrepresented in educational and professional settings. Using a qualitative approach, this work sought to investigate what led underrepresented minorities currently involved in cybersecurity to the industry, with the goal of determining methods to attract and diversify the workforce. A thematic analysis was conducted using data collected during interviews with 23 participants including underrepresented minority students, underrepresented minority professionals, college instructors, and a high school administrator. The interview questions aimed to address (a) what attracted minorities to the field, (b) how they overcame educational and professional roadblocks, (c) how they built non-technical knowledge, skills, and attitudes, and (d) how they maintained engagement. Findings revealed 17 themes that were related to characteristics of (a) the learner, (b) the instruction, and (c) the environment. Based on these findings, recommendations are presented to illustrate how these themes can be implemented by instructors with the goal of increasing the participation and involvement of underrepresented minorities and fostering diversity in the cybersecurity field.

It is critical for nations to have trained professionals in network security who can safeguard hardware, information systems, and electronic data. Network security education is a key knowledge unit of the National Centers of Academic Excellence in Cybersecurity and various information systems security curricula at the master's and bachelor's levels in higher education. Network security units are components of computer science curricula in high school contexts as well. Educators who teach these concepts play a significant role in developing a skilled workforce of network security experts for both governmental and non-governmental organizations. Understanding the necessary knowledge and skills of network security educators serve to better inform institutes of higher education, educator preparation programs, and others who support educators in the field. This study describes knowledge constructs of a higher education faculty member who teaches networking and network security and was developing, and piloting innovative network security curriculum embedded in both undergraduate and graduate courses. Data were transcripts of recorded monthly meetings with the educator, fieldnotes taken during the meetings, and course artifacts. Existing teacher knowledge frameworks that have been applied in both K-12 and higher education contexts were used to deductively code the data. Examples of curricular knowledge and pedagogical content knowledge specific to the teaching of network security are provided. The affordances of using engagement within curriculum development to understand educator knowledge constructs and the existing teacher knowledge frameworks as tools for analyses are highlighted.