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As societies rely increasingly on computers for critical functions, the importance of cybersecurity becomes ever more paramount. Even in recent months there have been attacks that halted oil production, disrupted online learning at the height of COVID, and put medical records at risk at prominent hospitals. This constant threat of privacy leaks and infrastructure disruption has led to an increase in the adoption of artificial intelligence (AI) techniques, mainly machine learning (ML), in state-of-the-art cybersecurity approaches. Oftentimes, these techniques are borrowed from other disciplines without context and devoid of the depth of understanding as to why such techniques are best suited to solve the problem at hand. This is largely due to the fact that in many ways cybersecurity curricula have failed to keep up with advances in cybersecurity research and integrating AI and ML into cybersecurity curricula is extremely difficult. To address this gap, we propose a new methodology to integrate AI and ML techniques into cybersecurity education curricula. Our methodology consists of four components: i) Analysis of Literature which aims to understand the prevalence of AI and ML in cybersecurity research, ii) Analysis of Cybersecurity Curriculum that intends to determine the materials already present in the curriculum and the possible intersection points in the curricula for the new AI material, iii) Design of Adaptable Modules that aims to design highly adaptable modules that can be directly used by cybersecurity educators where new AI material can naturally supplement/substitute for concepts or material already present in the cybersecurity curriculum, and iv) Curriculum Level Evaluation that aims to evaluate the effectiveness of the proposed methodology from both student and instructor perspectives. In this paper, we focus on the first component of our methodology - Analysis of Literature and systematically analyze over 5000 papers that were published in the top cybersecurity conferences during the last five years. Our results clearly indicate that more than 78% of the cybersecurity papers mention AI terminology. To determine the prevalence of the use of AI, we randomly selected 300 papers and performed a thorough analysis. Our results show that more than 19% of the papers implement ML techniques. These findings suggest that AI and ML techniques should be considered for future integration into cybersecurity curriculum to better align with advancements in the field. [ABSTRACT FROM AUTHOR]

Challenges remain in fulfilling skilled professionals to meet the growing demand for the computing workforce. Computer and information technology occupations are projected to grow at an aboveaverage rate of 13% from 2020 to 2030. To meet the need for computer science jobs, the computer science education research (CSER) community has explored pedagogical theories and practices to prepare students for careers in the field. However, the focus has been on populations of students at K-12 and/or college levels who have gone through several years of development before they can enter the workforce. The study of alternative pathways to computer science is facing an urgent need and presents a faster solution to allow the working-age population to advance careers in this field. This is especially true for women, who have traditionally been underrepresented in this area due to the prevalence of gender disparities in computing. Therefore, this article presents a review of the literature on pathways for women entering computer science (CS) after earning a degree in another discipline. Through this review, we assess the landscape of literature related to pathways for women entering CS at any point after their earned undergraduate degree (in another field) and identify any gaps in current research. Our results suggest that coding bootcamps and second-degree programs are the common alternative pathways presented in the literature. The results indicate that there is a lack of rigorous studies in this area since limited research methods have been applied and very few of the studies included theoretical frameworks. In addition, this review will shed light on the challenges and implications of women's alternative pathways to CS, to better understand and avoid the barriers to broadening participation. [ABSTRACT FROM AUTHOR]

As described in this Complete Research paper, prior research suggests that to diversify the computer science profession, educational scholars need to investigate and explore alternative pathways into the field. The 2-year to 4-year institutional pathway can serve as one such pathway, mainly due to the pragmatic allure of a 2-year program to first-generation college students--including but not limited to Black and Hispanic students. This research inquiry explored the unique and often symbiotic relationship between one 2-year college and one 4-year university. To better understand this alternative pathway, the following research questions were posed: 1) what are the experiences of students at critical transition points from a 2-year college to 4-year computer science programs, 2) what are the strategies invoked by students that help their transitions, and 3) what types of support do students use and benefit from during their transitions? To answer these questions, we leveraged a cross-sectional approach to explore the perspectives at multiple points within the 2-year to 4-year institutional pathway. While a longitudinal study would observe one subject over a period of time, often taking years, a cross-sectional inquiry observes multiple subjects on the same trajectory at different snapshots of time. To further ground the study, we used Anderson, Goodman, and Schlossberg's Transition Theory as the guiding and analytical frameworks. The team identified three critical transition points along the pathway to a bachelor of science in computer science: the start of the 2-year institution, the end of a 2-year institution, and the start of a 4-year institution. We then recruited students who were at each of those transition points, resulting in ten student interviews. We found that students utilized a variety of constructive coping strategies and support structures that enabled them to successfully make their way through a computer science 2-year to 4-year institutional pathway. Strong partnerships, including transfer orientations and bridge advising, between 2-year and 4-year institutions were helpful for computing Hispanic/Latinx transfer students in navigating the transition between the two institutions. The results of this work have implications for policy and procedures at both the 2-year and 4-year institutions to smooth the transition for a more diverse population in computing. [ABSTRACT FROM AUTHOR]

In this research paper, we describe faculty development as mentors to postdoctoral fellows (postdocs). Postdoctoral fellowships have become a significant step in academic and industry positions, while little research investigates the purpose of a postdoc position, the experiences of postdocs, and how faculty develop as postdoc advisors. As part of a larger project investigating postdoc mentorship, nineteen semi-structured qualitative interviews with faculty advisors uncovered themes about how postdoc advisors learn to mentor and advise postdocs. Faculty from U.S. and Canadian universities completed 60-minute online interviews. Participants had varying experience and expertise in advising postdocs. Observational learning theory provides a framework for identifying the process of learning from observation and the replication of mentors' past experiences. Open and axial coding was used to identify faculty experiences that informed how they mentored their postdoctoral fellows. Faculty who had completed a postdoc as part of their training reflected on their experiences, often identifying positive and negative experiences they used to guide, mentor, and plan the development of the postdocs they advise. Faculty who did not complete a postdoc used doctoral and industry experiences to inform their decisions. This work provides a unique window into postdoctoral training and mentorship, highlighting the need for more explicit expectations and plans for postdoc advisors. [ABSTRACT FROM AUTHOR]

Women are underrepresented in the field of computer science in the United States. However, this is not a new problem as female participation in computer science (CS) has been experiencing a steady decline over the last three decades. Current reporting on women's participation in this field has been published as steadying around 13-17%, depending on the data source. Although, there are varying levels of participation in other countries, particularly in Muslim majority countries. For example, women in Bahrain, Morocco, Palestine, Oman, Saudi Arabia, Iran, and Tunisia earned more than half of the total number of science degrees in their respective nations. This stark contrast between the United States and these other countries has prompted an exploration into the factors that contribute to women's participation in computer science. This study focuses on understanding how cultural environment can affect the participation of women in CS, specifically with respect to individual, household, community, country, and global influences on occupational pursuit. The research question guiding this study is: what cultural factors influence Muslim women's occupational pursuit of computer science? This qualitative study explores, through semi-structured interviews, the experiences and influences of Muslim female students currently pursuing graduate degrees in CS. Leveraging snowball sampling, this research study seeks to better understand Muslim women's pathways to and through computer science. This study will also provide further insight as to how and why certain experiences or cultural influences impact women's choice of computer science. Through thematic analysis leveraging NVivo12, the preliminary findings suggest that micro- and macro-cultural environmental factors are different for Muslim women students across different cultural groups as well as the influence these variables have on their participation and achievement in CS. Our findings suggest that cultural background may influence women in different ways. Understanding the pathways of Muslim women, given their high representation in computer science in their home nations, might provide insight into different ways to engage more women (Muslim or otherwise) in CS in the United States. This study provides a counter-narrative to underrepresentation of women in this field by presenting the pathways of those achieving or exceeding parity in science, technology, engineering and mathematics (STEM) fields outside of the United States. [ABSTRACT FROM AUTHOR]

Despite the projected growth of computer and information technology occupations, many computing students fail to graduate. Studying students' self-beliefs is one way to understand persistence in a school setting. This paper explores how students' disciplinary identity subconstructs including competence/performance, recognition, interest, and sense of belonging contribute to academic persistence. A survey of 1,640 students as part of an NSF grant was conducted at three South Florida metropolitan public universities. A quantitative analysis was performed which included a structural equation model (SEM) and a multigroup SEM. The study examined different groups of students such as male versus female, and freshman versus senior students. Results suggest identity sub-constructs contribute differently to academic persistence among freshman and senior students; however, no significant differences were found between male and female students. The findings, such as the significance of particular aspects of computing identity on academic persistence, can have implications for educators and college administration. [ABSTRACT FROM AUTHOR]

As technology increases in the global arena and the necessity for a more diverse group of individuals to fulfill engineering and computing roles increases, it is important to engage more students in computing majors and roles. Identity has proven to be an important lens through which researchers can better understand how to engage students in these fields. In particular, our framing for computing identity includes students' self-perceptions about recognition, interest, and performance/competence. Using survey data, this study examines the computing identity of high achieving underserved students in computer science (CS), computer engineering (CE), and information technology (IT). For these students, we compare the constructs between men and women, computing fields, and first year students (commonly referred to as freshmen) and postsecond year students (which includes junior and senior students). Based on preliminary data, results show that female participants had less of a computing identity than male students, specifically with respect to computing recognition and overall computing identity. Students in IT programs had less of an overall computing identity than students in CS and CE. Finally, first year students were lower on their overall computing identities and specifically performance/competence beliefs and interest. These results suggest that even within computing programs, students differ in their computing identities. Furthermore, there are different constructs related to computing identity that vary for different subgroups of students. While these results are insightful, future work will compare the computing identities of high achieving underserved students with a larger population of computing students as well as strategies for building their computing identities. [ABSTRACT FROM AUTHOR]

The national imperative to increase the production of computer science and engineering professionals has garnered the attention of both public and private sectors of the economy. As such, private companies, such as Verizon have begun to fund what they call Innovation in Learning (VIL) initiatives that aim to increase participation in these fields. Initiatives such as these, also recognize the need to diversify the engineering workplace by focusing specifically on engaging, inspiring, and motivating underrepresented minority (URM) youth by exposing them to engineering and other STEM concepts. During summer 2017, a southeastern university participated in hosting one of the seventeen Verizon sponsored STEM Camps. The university hosted 144 URM middle school boys for three weeks on campus to explore engineering habits of mind, engineering design principles, and computer science application development fundamentals. The camp was primarily facilitated by fourteen student mentors. One of the principle elements of the camp was to have mentors that reflected the demographics of the student population. As such, the mentor demographics consisted of 12 URM male mentors and 2 URM female mentors. Upon conclusion of the summer camp all of the student mentors were asked to participate in an open-ended survey that inquired about their experiences as studentmentors. The research questions guiding this study were: What role does race and gender have on the development of student mentor relationships? What are the implications of those mentor relationships on STEM identity development of the student-mentors? These research questions were answered through the use of thematic analysis, yielding two main themes: 1) barriers and connections associated with race and gender and 2) development of role identity - specifically the sub-constructs of performance/competence and interest. The results of this study suggest that engaging in mentoring relationships, while motivated by altruistic desires, strengthened STEM role identity development of the student-mentors. Previous literature has demonstrated that salient STEM identity development can contribute to persistence in these fields. Promoting engagement in mentoring opportunities, like summer camps, could aid in increasing and sustaining URM STEM majors. [ABSTRACT FROM AUTHOR]

To help address the issue of underrepresentation of African Americans obtaining engineering degrees and matriculating into engineering industry, the National Society of Black Engineers (NSBE) launched the Summer Engineering Experience for Kids (SEEK) program in 2007. As of 2015, the program had 17 sites across 16 major U.S. cities. The free 3-week summer camp provides access to engineering education activities through competition based, hands-on curriculum. At each of the locations, four individuals were hired to serve as site leaders to oversee all operations and logistics at the program: 1) Site Director 2) Assistant Site Director 3) Operations Specialist and 4) Data Specialist. Classroom instructors, who are referred to as mentors, were hired at a 6:1 ratio with a total of 3 per class. The site leaders and classroom mentors were primarily comprised of undergraduate and graduate engineering, STEM nonengineering and education majors. During the summer of 2015, instructor surveys and student pre and post assessments were distributed, collected and analyzed by the external evaluator. The instructor survey data was analyzed and findings were shared within one of the three reports provided to NSBE by the external evaluator including the overall, all-sites report, site-specific reports and an internal report. However, several of the 34 questions within the instructor post-program survey, a mix of open-ended and likert scale, were not analyzed by the external evaluator. A quantitative analysis will be conducted using raw data from questions related to classroom instructors' feedback on site leadership performance including areas of management, supervision, their ability to give feedback, professionalism, work ethic and problem solving skills. These results will then be compared to the classroom instructors interest outcomes on the SEEK program. The implications of this research include better understanding the role of leadership during short-term, out-ofschool (OST) engineering programs such as training and professional development and other potential best practices. [ABSTRACT FROM AUTHOR]

College enrollment is on the rise. Universities have experienced a 37% increase from 2000 to 2010; this includes a rise in underrepresented minority (URM) students from 1976 to 2010. Hispanic student numbers rose from 3 percent to 13 percent, Asian/Pacific Islander students rose from 2 percent to 6 percent, and the percentage of Black students rose from 9 percent to 14 percent. However, the faculty demographic has not kept pace with the increase in URM enrollment. The percentage of URM faculty has remained flat over the last 20 years, hovering at just a little over 5 percent. Researchers, educators, and practitioners believe that in order for students to succeed academically, they need role models and mentors with whom they can identify. Racial and ethnic diversity has both direct and indirect positive effects on the educational outcomes and experiences of students. The campus climate improves when the diversity of the student population matches that of the faculty. Students from majority groups equally benefit from learning and exchanging ideas in a multicultural environment, offering a wider range of research and a broader representation of alternative perspectives. Therefore, the shift in American demographics over the next ten years changes the question from whether colleges and universities want to support diversity in their faculty distribution to how colleges and universities will accommodate this necessity. Thus, this is a review of the literature on one demographic in engineering academe, the African American woman. African American women are at the intersection of two of the most pervasive prejudices in this country: racism and sexism. This review will unveil some of the unique challenges African American female engineering faculty due to the intersectionality of race and gender. In order, to increase the numbers, the engineering education community must first fully understand the barriers these women face. [ABSTRACT FROM AUTHOR]