This full paper in the innovative practice category introduces a uniquely novel visual privacy themed game, which is meant to be used as an experiential learning tool for teaching plus demonstration of fundamental data privacy concepts and basic security concepts. To our knowledge, this new, innovative visual privacy themed game, as presented in this paper, is the first of its kind gamified educational tool, which makes use of the privacy through visual anonymity i.e. VPET (Visual Privacy Enhancing Technology) theme for effective illustration of privacy concepts along with basic security concepts. This paper describes our nifty, visually interactive VPET game, which teaches privacy plus security concepts through the PET illustration and demonstrates applied cryptography for privacy-driven de-identification through obscuration-based disguise tasks during the game play. It also discusses how we have successfully used a pilot, proof of concept prototype version of this game over the last few years for cybersecurity education and outreach primarily at the K-12 level. Over the last few years, we have surveyed several VPET game players, who are from a large, diverse group of K-12 community members, consisting mainly of high school students and teachers, who have played the VPET game, as part of several cybersecurity training camps and outreach workshop sessions, and have benefited from this exercise in terms of learning, as well as developing awareness plus interest in privacy and security topics. This paper shares and analyze the preliminary data collected from all these survey responses to evaluate the prospects of our unique VPET game as a potential educational and outreach tool for engaging K-12 learners, for teaching privacy plus security concepts, and for creating awareness plus interest in cybersecurity. In summary, we demonstrate how our unique VPET gamification approach for educational purposes can successfully engage students for effective learning of data privacy and cybersecurity concepts.

This full paper in the research track evaluates the usage of data logged from cybersecurity exercises in order to predict students who are potentially at risk of performing poorly. Hands-on exercises are essential for learning since they enable students to practice their skills. In cybersecurity, hands-on exercises are often complex and require knowledge of many topics. Therefore, students may miss solutions due to gaps in their knowledge and become frustrated, which impedes their learning. Targeted aid by the instructor helps, but since the instructor's time is limited, efficient ways to detect struggling students are needed. This paper develops automated tools to predict when a student is having difficulty. We formed a dataset with the actions of 313 students from two countries and two learning environments: KYPO CRP and EDURange. These data are used in machine learning algorithms to predict the success of students in exercises deployed in these environments. After extracting features from the data, we trained and cross-validated eight classifiers for predicting the exercise outcome and evaluated their predictive power. The contribution of this paper is comparing two approaches to feature engineering, modeling, and classification performance on data from two learning environments. Using the features from either learning environment, we were able to detect and distinguish between successful and struggling students. A decision tree classifier achieved the highest balanced accuracy and sensitivity with data from both learning environments. The results show that activity data from cybersecurity exercises are suitable for predicting student success. In a potential application, such models can aid instructors in detecting struggling students and providing targeted help. We publish data and code for building these models so that others can adopt or adapt them.

This Full paper in the Innovative Practice Category describes a novel research study that is based upon an experimental scaffolding of live coding techniques used towards teaching a traditional face to face undergrad computer programming class. It discusses our hybrid pedagogical model, which comprises of a scaffolded collection of our class instructional methods that include fine blend of live coding-based teaching strategies, and traditional lectures. Our combination of live coding styles, as used in this study, consists of the standard live coding technique and our live secure coding demonstrations, which lead to a uniquely blended and integrated live coding approach for teaching coding along with software security concepts. To our knowledge, this is a new research study based upon a hybrid, integrated live coding approach that represents a scaffolding of distinct teaching styles, which combines coding instructions with teaching of secure coding components. We demonstrate an improvised teaching model that enhances the classical live coding pedagogy by adding the live secure coding components, which holistically represent a new variant in a traditional undergrad coding class, for an engaged and enhanced learning experience. Existing literature indicates that there is limited number of prior educational research studies on the usage of a hybrid, non-traditional live secure coding approach blended with the traditional live coding style. Thus, this paper discusses a fresh, nifty teaching strategy that involves new variants of the standard live coding instructional method and forms a hybrid pedagogical model for a more effective and relatable learning of coding skills. We discuss the results of our experimental study in the form of data obtained over a couple of semesters from an upper-level undergrad coding class through learning assessments and collected survey data on learner experiences. We have analyzed the overall gathered learner data to evaluate the performance of our new hybrid model of scaffolded live coding techniques. This paper discusses our overall hybrid pedagogical approach through a scaffolding of traditional and non-traditional live coding styles for teaching coding plus software security topics. It analyzes our obtained learner assessment data plus enhanced student learning experiences, based upon the inclusion of secure code design lessons and code vulnerability hacking plus exploitation demos.

Cybersecurity students need to develop practical skills such as using command-line tools. Hands-on exercises are the most direct way to assess these skills, but assessing students' mastery is a challenging task for instructors. We aim to alleviate this issue by modeling and visualizing student progress automatically throughout the exercise. The progress is summarized by graph models based on the shell commands students typed to achieve discrete tasks within the exercise. We implemented two types of models and compared them using data from 46 students at two universities. To evaluate our models, we surveyed 22 experienced computing instructors and qualitatively analyzed their responses. The majority of instructors interpreted the graph models effectively and identified strengths, weaknesses, and assessment use cases for each model. Based on the evaluation, we provide recommendations to instructors and explain how our graph models innovate teaching and promote further research. The impact of this paper is threefold. First, it demonstrates how multiple institutions can collaborate to share approaches to modeling student progress in hands-on exercises. Second, our modeling techniques generalize to data from different environments to support student assessment, even outside the cybersecurity domain. Third, we share the acquired data and open-source software so that others can use the models in their classes or research.

Prior research literature shows that there has been considerable work done in the last decade in the area of image de-identification (DeID) for privacy protection. With the advances made in privacy enhancing image DeID techniques, there have been research studies on different DeID performance evaluation approaches for determining the effectiveness of these methods. Existing approaches for evaluating DeID methods can be classified into three separate categories - analysis of privacy versus utility, analysis of viewer experience-based user studies, and analysis of robustness against adversarial attacks. However, none of these categorized approaches have utilized person re-identification (ReID) for evaluating DeID. Additionally, there are no previous research studies that have analyzed the threat of ReID to DeID. In this paper, we present a unique experimental case study that demonstrates how ReID can be used successfully for evaluating the efficacy of DeID techniques, and how, in the process, we can assess the threat of ReID to DeID. We describe a novel approach, in which a selected ReID algorithm is pitted against multiple DeID techniques to test the robustness of these DeID methods, and to determine if ReID can pose a threat to DeID as an adversary. Through this approach, we compare the DeID performances based upon how effectively they can deter successful ReID in the privacy enhanced versions of the ReID image dataset. Our preliminary results show how we can potentially evaluate DeID and compare DeID performances by analyzing the extents to which they are able to successfully resist re-identification i.e., by studying the impact of DeID on the ReID performances.

The last few years have seen a strong movement supporting the need of having intelligent consumer products align with specific design guidelines for trustworthy artificial intelligence (AI). This global movement has led to multiple institutional recommendations for ethically aligned trustworthy design of the AI driven technologies, like consumer robots and autonomous vehicles. There has been prior research towards finding security and privacy related vulnerabilities within various types of social robots. However, none of these previous works has studied the implications of these vulnerabilities in terms of the robot design aligning with trustworthy AI. In an attempt to address this gap in existing literature, we have performed a unique research study with two social robots - Zümi and Cozmo. In this study, we have explored flaws within the robot's system, and have analyzed these flaws to assess the overall alignment of the robot system design with the IEEE global standards on the design of ethically aligned trustworthy autonomous intelligent systems (IEEE A/IS Standards). Our initial research shows that the vulnerabilities and design weaknesses, which we found in these robots, can lead to hacking, injection attacks, and other malfunctions that might affect the technology users negatively. We test the intelligent functionalities in these robots to find faults, and conduct a preliminary examination of how these flaws can potentially result in non-adherence with the IEEE A/IS principles. Through this novel study, we demonstrate our approach towards determining alignment of social robots with benchmarks for trustworthy AI, thereby creating a case for prospective design improvements to address unique risks leading to issues with robot ethics and trust.

Cybersecurity educational games are capable of meeting a variety of goals, including learning of fundamental cybersecurity concepts, exposure to cybersecurity literacy, basic awareness, experiential learning plus situational awareness, and being a medium for K-12 outreach, college level learning plus corporate training. Existing literature shows that there have been several prior research surveys focused on analyzing cybersecurity educational games from various viewpoints. However, to our knowledge, there has been no previous work that has analyzed cybersecurity educational games in terms of their alignment with the current benchmarks in academic and industry standards that include the cybersecurity curriculum plus assessment guidelines in higher education, the K-12 standardized cybersecurity concepts, and the cybersecurity job-related functions. In an effort to address this research gap, we use the CSEC2017 curricular guidelines, the Cybersecurity Assessment Tools (CATS) model, the National Security Agency (NSA) GenCyber concepts and the National Initiative for Cybersecurity Education (NICE) framework for performing a unique analysis of a list of popular cybersecurity educational games, plus a few Capture the Flag (CTF) instances. The list of cyber educational games, which we study, comprises of Anti-Phishing Phil, Cyber Awareness Challenge, Cyber CIEGE, Cyber Protect, Nsteens, NOVA Labs, What.Hack, PASDJO, CyberStart Go, OnGuardOnline, Safe Online Surfing, and Interland. This non-traditional survey-based research work demonstrates a novel, multi-faceted approach for analyzing popular opensource cybersecurity educational games in terms of their alignment with the standard academic and industry benchmarks. Our survey results include conceptual mapping of these cyber educational games to (1) the CSEC2017 curricular knowledge areas (Data Security, Software Security, Component Security, Connection Security, System Security, Human Security, Organizational Security and Societal Security), (2) the CATS concept inventory topics, including the Cybersecurity Concept Inventory (CCI), which pertains to basic first year college concepts, and the Cybersecurity Curriculum Assessment (CCA), which contains core concepts and learning outcomes for a college graduate, (3) the NSA GenCyber concepts (Defense in Depth, Confidentiality, Integrity, Availability, Think Like an Adversary and Keep It Simple), and (4) NICE framework-based specialized skill sets (Analyze, Collect & Operate, Investigate, Operate & Maintain, Oversee & Govern, Protect & Defend and Securely Provision). Our research provides a first-of its kind study and a user-friendly analysis of open-source cybersecurity educational games that can serve as an insightful reference for cybersecurity educators and other audiences for using these games. Additionally, in this full research paper, we exhibit how the results of our study can be used for performing an overall gap analysis with cybersecurity educational games in terms which benchmarks they cover and which they do not.

The critical shortage of cyber security professionals remains an unsolved problem. We need to greatly expand the community of faculty teaching in cybersecurity in order to meet the increasing demand for security professionals. The number of security-focused competitions and exercises has increased in recent years. As faculty we need to integrate them into our courses. Having a more unified environment and contributing to each other's educational projects will help. By bringing together new and experienced faculty we can build a community to engage in this work. We need to develop a critical mass of faculty, asking each other what we want from this learning community. As a learning community we can provide support for new members to learn about resources and help each other. These resources include exercises, webinars, and slides. We will share experiences, practices and ongoing efforts. The BoF also benefits experienced members, helping them to disseminate their work and reach other faculty with similar interests. As a community we have begun to discuss what works and what problems students and instructors have. The questions we will ask are, "What exercises have you tried? What are your experiences? What are you looking for from the community?"

This lightning-talk will discuss our novel work towards making undergraduate research a required part of our CS freshmen classes as a High-Impact-Practice (HIP) activity. We have developed a nifty undergrad-scholarly-creative-activity (URSCA) as a mandatory assignment for CS freshmen in this pilot experiment. We are investigating whether undergrad research can be included in an equitable and inclusive manner at the freshmen level so that it is accessible to all students for enhanced learning, better experience and more impactful professional development. Thus, this project is an initiative towards bringing URSCA to CS freshmen in a user-friendly and accessible form, so that the opportunity to taste URSCA is not limited to a few i.e. only the talented, self-motivated and selected CS students. The goal of this project is to discover a user-friendly and an equity-focused way for exposing CS freshmen to the essence of URSCA, which includes understanding the notion of a research-question, how to read and analyze research-articles, how to identify research-questions and think out-of-the-box, and how to develop writing-skills. Our innovative URSCA-HIP assignment has been designed as a team project for CS freshmen, with each team being assigned a senior CS student as a peer research mentor. We are collecting survey-data from the freshmen research-mentees and their corresponding senior research-mentors in order to evaluate our unique URSCA-HIP experiential-learning model, and gauge its overall efficacy. To our knowledge, this is a first-of-its-kind initiative of engaging CS freshmen in an inclusive, equity-focused URSCA-HIP experience through a user-friendly but required class project.

This poster will present a novel experimental case-study that focuses on the merits of teaching software-security to CS0 and CS1 learners by demonstration of how vulnerable programming of the Cozmo robot can lead to unexpected robot-behavior. It will introduce our unique Cozmo secure-coding lesson-plan, as a new experiential-learning model, which combines learning of software-security concepts with educational-robotics (ER) in the form of hands-on, interactive coding. It will compare a conventional approach of teaching software-security via secure-coding lessons with our unconventional technique of teaching secure-coding using Cozmo. It will present student-survey based learning-assessment data collected from our experiment of offering secure-coding lessons to a diverse group of CS0 and CS1 learners through traditional secure-coding training-modules, which involve no ER. It will, then, compare these data with the student-survey based learning-assessment data gathered from our Cozmo secure-coding sessions. It will analyze these comparative-results in an effort to show preliminary evidence of the effectiveness and potential of our approach for more enhanced and engaging learning of software-security via defensive programming of Cozmo. Prior research in ER indicates that a social-robot can be an effective platform for teaching coding and cyber concepts. However, there is very limited work on the efficacy of teaching secure-coding using social-robots. Hence, our fresh, non-traditional approach of making CS0 and CS1 learners explore hands-on secure-coding through Cozmo is a first-of-its-kind research case-study in an attempt to fill this gap.

We need to greatly expand the number of students studying cybersecurity in order to meet the increasing demand for security professionals. As a community, we can use our expertise and alliances with other fields to create interdisciplinary courses and modules to attract diverse students into cybersecurity. For example, Liberal Arts Colleges have a strong core general education curriculum that can be enhanced with cybersecurity concepts. On one hand, students from non-CS majors are important for the cybersecurity workforce as they will be shaping the policies and business processes that affect cybersecurity decisions. On the other hand, well rounded CS students that take interdisciplinary security courses and CS1 will be able to apply the concepts and solve today's complex security problems. This BoF will explore ideas for integrating the technical content of cybersecurity with political science, business, law, psychology, philosophy, international affairs, and others. Participants from colleges, universities and K-12 will be able to co-create plans for these interdisciplinary experiences.

This Full-paper in the Innovative-Practice Category introduces an innovative visual-privacy themed experiential-learning tool, and discusses how it is used for building human-privacy plus societal-security awareness in middle-school and high-school youth. The new GDPR driven business-communications are touching the lives of worldwide-consumers, including youth, who use technology-services, like internet and email, from an early age. A lack of privacy-security awareness in this context may expose youth. The new CSTA-standards advocate for inclusion of privacy, safety, ethics, societal-security and human-privacy topics in K-12. Existing literature show multiple instances of K-12 research-studies on data-privacy education and cybersecurity awareness. However, very few of these explore the visual-privacy theme in a way that middle-school and high-school youth can learn privacy, security and ethics through the lens of privacy-enhancing video-surveillance. This paper presents our simple but novel, visually interactive experiential-learning tool, which is based upon the PVA theme as applicable to visual-media contents. Our unique tool introduces young learners to privacy-security concepts, illustrates applied-cryptography and discusses privacy-security tradeoffs in surveillance-space. The educational application of this tool addresses the gap within the current K-12 educational-research work in societal-security implications and human-privacy domain. We discuss our experimental-studies with this tool, including piloting the tool-based hands-on workshop sessions with middle-school and high-school learners, as part of GICS and NSA-GenCyber projects. Additionally, we share and analyze the learning-assessment data and survey-responses collected from participants, in an effort to evaluate the prospects of our experiential-learning model as a potential educational and outreach medium for engaging and recruiting K-12 students in computing-disciplines.

The critical shortage of cyber security professionals remains an unsolved problem. We need to greatly expand the community in order to meet the increasing demand. The number of security-focused competitions and exercises has increased in recent years. As faculty we need to choose those that we can best integrate into our courses. As a community, we can think about how to create a more unified environment to contribute to each other's projects. We would like to bring together new and experienced faculty to build community and engage in this work. We have set up a dedicated Facebook to allow us to work together outside of SIGCSE events. During the BoF, we will encourage participants to sign up for the closed group, and we will ask the questions, 'What do you want from this learning community? What exercises have you heard about or tried?" One benefit of having a learning community is that it will be easier to provide support for new members to learn about resources and get help. These resources include exercises, webinars, and slides. We will share experiences, practices and ongoing efforts (NSA's National Cybersecurity Curriculum Program), including our own (e.g. Security Injections, Security Knitting Kit, EDURange and UWGB GenCyber). The BoF also benefits experienced members, helping them to disseminate their work and reach other faculty with similar interests. We will discuss what works and what problems students and instructors have encountered. We will discuss ways to integrate security-related exercises into existing courses.

This Work-In-Progress paper in the Innovative Practice Category presents an innovative model of inter-class peer collaboration that enhances student learning in computing education, and addresses student conceptual gaps. It expands the scope of traditional peer learning beyond the usual classroom setting and motivates student creativity leading to interests in co-curricular professional development. This nifty peer learning model connects computing students from an upper level class with students of a lower level class, so that they can aid each other in a mentor-mentee relationship to address conceptual learning gaps. Existing literature on computing educational research show that several peer learning models have been used in a typical classroom setting for reinforcing learning. However, very few peer learning models have been used in an inter-class setting, and none have been driven by student conceptual gaps in order to create an enhanced learning environment. Our model focuses on developing student interests in further co-curricular professional development opportunities in the form of peer mentoring, tutoring and instruction. Currently, student retention is a significant challenge for computing educators, given the demand of the computing disciplines for an all-round solid knowledge base, including grasping of complex technical concepts. Our approach of inter-class peer collaboration strengthens the learning environment of both lower level and upper level computing courses, and provides much needed support to students, whose knowledge base is still underdeveloped and conceptual understanding is undercooked. This unique form of inter-class peer learning provides upper level students with an exclusive opportunity to reinforce their conceptual grasps by mentoring lower level students. It also enables the lower level students to receive peer guidance for addressing their conceptual gaps. Our improvised peer networking model adds a different dimension to the practice of intra-class peer learning and extends peer learning beyond the traditional bounds. It promotes a new kind of service learning project in classes by encouraging peer mentoring that leads to peer connections across classes. It aids student retention by helping lower level student mentees get over their knowledge limitations. Our work-in-progress research case study indicates that this model inspires peer mentors to engage in out-of-box thinking by challenging them to find creative ways for overcoming conceptual shortcomings of mentees. This, in turn, generates student interests in enhanced co-curricular professional development. Additionally, our ongoing experimental study results show that this model can help in producing a sustainable pool of peer mentors, tutors and teaching assistants, who can become resources plus role-models for other students, and for helping student retention. As part of our in-progress experiments, this model has been deployed within our computer programming classes, where CS2 students have been paired with CS1 students based upon conceptual gaps and knowledge shortcomings. As we conduct these teaching experiments, we analyze the performance of our model through data obtained by conducting student surveys. We discuss these initial collected data and cite them as preliminary evidence in the process of evaluating our model in terms of the improved learning, and generated student interests plus engagement in professional development.

This Full paper in the Innovative Practice Category introduces an innovative visual privacy themed pre-university educational module using social media apps for creating privacy awareness as well as teaching societal and human security topics. With the advent of internet (World Wide Web) and social media, and the extensive use of these resources by naïve young users, privacy issues pop up every now and then. The lack of privacy and security awareness may lead to confidential information leaks during the use of online contents, particularly social media. The current IEEE/ACM curricular guidelines in CS, IT and cybersecurity clearly point to a need for inclusion of societal and human security topics at the college level, so that a general awareness can be created regarding today's growing privacy concerns, including privacy issues with media sharing. However, there is still a gap within the K-12 curriculum in regard to these security and privacy topics. Even though there has been some computing educational research work on the topic of data privacy at the K-12 level, the visual privacy theme under the societal and human security domain has hardly been explored within K-12. None of the K-12 cybersecurity educational modules have employed the privacy-enhanced computer vision theme along with a social media platform. This paper intends to address the this gap by presenting a visual privacy themed lesson plan using social media apps for teaching privacy, ethics and machine learning. Its main contribution is a unique visual privacy education based hands-on outreach module that utilizes the PVA (Privacy through Visual Anonymity) notion to teach privacy, ethics and machine learning using media images and videos. Our module uses two freely accessible apps, namely an Obscura Cam and YouTube - Face Blur. These apps are utilized to illustrate the concept of visual privacy and demonstrate PVA in pictures and media clips. Additionally, this paper describes our research case study conducted by piloting our PVA workshop module at the middle-school level. This paper discusses and analyzes the learner data obtained from the workshop participants as part of our Google IgniteCS outreach project. The learning analytics survey data collected during our PVA workshop sessions with various middle-school participants indicate that the described visual privacy module can become a simple yet effective tool for privacy literacy, as it can help build privacy perceptions in young minds. Our acquired results also suggest that that this PVA themed outreach lesson plan can be used as a potential medium for recruiting K-12 students into computing and cybersecurity disciplines.

Today's organizations, including online businesses, use the art of data-driven decision-making i.e. business-intelligence (BI) to benefit from all the data out in the open. Given the current market demand for BI skill-sets, including the knowledge of different sources and tools for data-collection plus processing, today's youth need a basic understanding of data-driven intelligence, and an awareness of big-data related ethics and privacy. However, there has been limited research and development work towards designing an effective educational module in this regard at the K-12 level. We intend to address this particular limitation by presenting a uniquely engaging middle-school learning module based upon a combination of useful topics, like data-mining, predictive-analytics, data-visualization, big-data, ethics and privacy, using the free RapidMiner software-tool. The novelty of our module lies in the use of a GUI-based visual hands-on platform (RapidMiner), a Hollywood movie-theme based educational activity, as well as an added focus on big-data ethics and privacy, and its conceptual mapping to the NSA-GenCyber security-first principles. We discuss and analyze the survey data obtained from over hundred participants through several offerings of our module as an educational workshop through our Google-IgniteCS and NSA-GenCyber programs. The collected learning-analytics data indicate that our module can become a simple yet effective means for introducing data-mining, big-data, ethical and privacy issues, and GenCyber security-first principles at the middle-school level. Our results show prospects of motivating middle-school participants towards further learning of topics in data-science, data-ethics and data-security, which is necessary today in a variety of professions.

With the growing demand for cybersecurity workforce, as we look to prepare our youth in cybersecurity, a lack of basic awareness about mobile device security and limited practical knowledge in securing mobile devices may expose our young generation to data hacks and cyber-attacks. The current IEEE/ACM CS2013 curricular recommendations and the latest CSEC2017 cybersecurity curriculum guidelines clearly point to a need for inclusion of mobile security related topics within the present CS knowledge areas. However, even though there are limited mobile security-based curriculum development initiatives at the K-12 level, none of them focus on the theme of mobile app related permissions, vulnerabilities and exploits. Therefore, in order to address this gap in mobile security based K-12 experiential learning, we have designed and developed a unique Android app-driven information security-based learning module for educating middle-school (fifth to ninth grade) learners about relevant cybersecurity topics, like good password practices, ethics, Android app permissions, vulnerabilities, exploit-based hacking, using an Android device. This poster will describe our creative mobile security theme-driven middle-school educational module, including our original unique Android app, which has been successfully used to conduct several hands-on workshop sessions for middle-school students as part of our Google IgniteCS outreach program and the NSA GenCyber camp program. Our poster will also present the survey data collected from middle-school participants in an effort to evaluate mobile security-based experiential learning model as a potential cybersecurity educational interface for engaging K-12 students.

We need to greatly expand the community of faculty teaching cybersecurity using hands-on exercises. The number of security-focused competitions and exercises has increased in recent years so that faculty need to choose those that can best be integrated into their courses. As a community, we can contribute to each other/s projects. We would like to bring together both new and experienced faculty to build community. Our Facebook group (https://www.facebook.com/groups/TeachingCyber/) allows us to work together outside of SIGCSE events, and we are developing a critical mass of users. In the BoF, participants can sign up for the closed group. Participants will discuss answers to specific questions on teaching security. One goal of our BoF is to provide support for new members to learn about resources and get help. These resources include exercises, webinars, and slides. We will share experiences, practices and ongoing efforts, including our own (e.g. Security Injections, the Security Knitting Kit project, and EDURange). The BoF also benefits experienced members, helping them to disseminate their work and reach other faculty with similar interests. As a community we have begun to share exercises and discuss what works and what problems students and instructors have encountered. We will discuss ways to integrate security-related exercises into existing courses. The questions we will ask are, What materials and exercises have you tried? What are your experiences? How do we expand and improve cybersecurity education?

There have been some social constructivist learning approaches used in computing sciences (CS) education, but none of them has actually validated the student reflection process, which is a critical component of the action learning associated with them. The step of reflection within the social constructivist pedagogy has a crucial role in building the learner's mental model and in refining the existing mental model. This paper presents a novel research case study on the employment of an innovative process of student reflection and analysis. This innovative process promotes a unique, non-traditional approach of employing a social interaction based dialogue of inquiry that helps engage each learner in a self-reflective assessment prior to the action learning. The process is in line with the social constructivist model that is based upon inquiry based knowledge building. It helps students debug their conceptual understandings, which make up their respective cognitive models. It also enables them to identify problems or limitations within that mental model before the actual knowledge assimilation or accommodation takes place. The presented case study strives to address a key issue of the social constructivist model i.e. how to ensure that students successfully self-reflect upon what they are learning. In order to so, this research performs a comparative analysis between the results obtained through the presented social constructivist self-reflection assessment and the outcomes of a software based traditional assessment. This paper discusses and analyzes learning analytics data collected over several semesters from multiple instances of social constructivist epistemology conducted for students of two different computer programming classes at the CS1 and CS2 levels respectively. The main contributions of this research experiment are evaluations of the process of student reflection, validations of student assumptions and presentation of an authentic action-learning problem for students in the form of their conceptual gaps. The experimental findings represent evidences of successful validation of student beliefs as well as knowledge discovery process though an epistemic investigation.

Social construction based learning approaches have been employed in computing education, but none of them has actually evaluated the effectiveness of the student reflection mechanism, which plays a key role in the learner's assimilation and accommodation process that builds upon the student's existing knowledge as part of the action learning within these approaches. Adapting the inquiry based knowledge building of the social construction model, this poster presents a process of student reflection that uses a unique, non-traditional method of interactive question-answer dialogue for engaging CS1 and CS2 students in a reflective assessment before the actual action learning cycle begins. This process of reflection helps students analyze their conceptual understandings and identify problems or limitations within their respective cognitive models prior to the actual process of knowledge refining or creation. In order to ensure that students have successfully reflected upon their conceptual beliefs, a software tool based assessment is then carried out. The answers from the social interaction based reflective assessment are compared with the results obtained through the software based traditional assessment in order to validate the student reflection process in the form of a social construction based epistemology. This research experiment also presents an authentic and relevant problem basis in the form of conceptual gaps for students to address within the action learning pedagogy of social construction. Results from the conducted comparative analysis in this case study show encouraging evidences confirming the validity of student comprehensions and assumptions by evaluating the knowledge discovery process through an epistemic investigation.

This poster presents a potential way of promoting student driven computing educational research that may provide an alternate path or option to the traditional faculty-driven computing education research. We propose a unique model of inter-class student collaboration that motivates creativity, expands the scope of collaborative research and enables handling of conceptual gaps through inter-class peer mentoring. The proposed model engages students from an upper level class with students of a lower level class so that they can connect with each other in a peer mentor-mentee relationship to overcome conceptual gaps in learning. It provides upper level students with an exclusive opportunity to reinforce their conceptual grasps and engage in research for addressing the problems faced by lower level students. This proposed model of improvised peer collaboration promotes a new kind of service-oriented learning project in computing that inspires innovation and leads to research on finding ways to handle common conceptual limitations, thereby helping student retention by assisting lower level peer mentees. It also assists upper level peer mentors in self-driving towards research oriented thinking for inventing methods to solve authentic conceptual issues. The proposed model has been currently implemented in the UWGB computing curriculum, where CS2 students have been collaborating with CS1 students and have been participating in computing educational research as part of the process. These ongoing research experiments have analyzed the performance of the proposed model through data obtained by conducting student surveys. The collected survey data represent insightful evidences from preliminary evaluations of the proposed model.

Given that many modern computing technologies have led to privacy issues in today's digital world, the latest CS curriculum (CS2013 - Ironman Version 1.0) has recommended a strong need for inclusion of privacy topics within the present body of knowledge. According to the above curriculum, there is a requirement for global awareness of today's growing privacy concerns with technology. Our proposed lab caters to the above curricular recommendation. We present a physical security focused lab, which is based on the technology of PVA (Privacy through Visual Anonymity). Through this hands-on PVA lab, we teach pre-university and university students the notion of privacy in images/videos and educate them in the technique of VA (Visual Anonymity), which can help safeguard one's privacy by obscuring the individual identity in pictures/videos captured by cameras. Using this lab, we intend to enhance CS education and outreach by making students aware of the global issue of privacy invasion in today's surveillance and by demonstrating how the issue can be addressed via VA. The lab exercises are based on two open-source applications, namely "ObscuraCam" and "YouTube-FaceBlur". These applications are used as tools for enabling students to learn the concept of PVA. In this process, we show students an innovative aspect of balancing security and privacy in technology, thereby drawing their focus to the humanitarian side of CS applications. Our topic of PVA also enhances the IAS knowledge area in the latest CS curriculum.

Mobile computing and robotics have been used as two separate approaches to engage university and pre-university students in STEM education. We are in the process of developing an innovative learning model that combines these two approaches into an integrated framework, where students would learn to make robots and control them via Android applications. By creating these cellbots, students will learn Android app programming and robot building together. Through CLF, we strive to engage both university and pre-university students in a creative environment that enables joint learning of programming logic and engineering concepts. CLF will also serve as an interdisciplinary tool to interface science with engineering. It will further pave the way for building diverse student communities by bonding different learners. The overall goal is to enhance STEM curriculum and outreach activities for recruiting more STEM majors. As part of implementing CLF, we are developing a STEM workshop for high school students, which will consist of hands-on activities on working with BERO (Be The Robot) and designing cellbots. Our future plans comprise of deploying CLF in introductory STEM courses to promote the diverse and interdisciplinary nature of STEM disciplines.

Considerable research work has been done in the area of surveillance and biometrics, where the goals have always been high performance, robustness in security and cost optimization. With the emergence of more intelligent and complex video surveillance mechanisms, the issue of "privacy invasion" has been looming large. Very little investment or effort has gone into looking after this issue in an efficient and cost-effective way. The process of PICO (privacy through invertible cryptographic obscuration) is a way of using cryptographic techniques and combining them with image processing and video surveillance to provide a practical solution to the critical issue of "privacy invasion". This paper presents the idea and example of a realtime embedded application of the PICO technique, using uCLinux on the tiny Blackfin DSP architecture, along with a small Omnivision camera. It demonstrates how the practical problem of "privacy invasion" can be successfully addressed through DSP hardware in terms of smallness in size and cost optimization. After review of previous applications of "privacy protection", and system components, we discuss the "embedded jpeg-space" detection of regions of interest and the real time application of encryption techniques to improve privacy while allowing general surveillance to continue. The resulting approach permits full access (violation of privacy) only by access to the private-key to recover the decryption key, thereby striking a fine trade-off among privacy, security, cost and space.