In this session, we aim to foster a community among computer science faculty across 2-year and 4-year primarily undergraduate institutions (PUIs). We will foster an inclusive environment through activities that allow for multiple forms of engagement (e.g. shows of hands, small group introductions, and full group discussion). We will facilitate discussions about ways computer science is changing at PUIs, differences seen across institutions, and ways that our community can be sustained outside of the SIGCSE TS. In prior years, discussions have focused on topics such as availability of course staff and tutors, availability of conference funding, organizational infrastructure such as sponsored program offices, and requirements for promotion.

In this session, we aim to foster a community of computer science faculty across many primarily undergraduate institutions. We will foster an inclusive environment through activities that allow for multiple forms of engagement (e.g. shows of hands, small group introductions, and full group discussion). We will facilitate discussions about ways computer science is changing at PUIs and continue to brainstorm ways that our community can be sustained outside of the SIGCSE TS.

In this session, we aim to foster a community of computer science faculty across many primarily undergraduate institutions. We will foster an inclusive environment through activities that allow for multiple forms of engagement (e.g. shows of hands, small group introductions, and full group discussion). We will facilitate discussions about ways computer science is changing at PUIs and brainstorm ways that our community can be sustained outside of the SIGCSE TS.

Improving Computer Science (CS) education requires increasing the meaningful usage of research-supported pedagogy and curriculum. Studies on propagation have largely looked at dissemination and adoption from the perspective of adopters: what motivates them to discover, experiment with, and continue using innovative teaching. This study adds to a growing body of research on approaches to encourage adoption by examining the perspectives and advice of successful propagators-education researchers who have had their innovations widely adopted. Drawing on interviews with fourteen CS education researchers, this paper identifies both points of convergence and unique insights across several broad areas: barriers to adoption, the structure of academia, relevant principles of design and techniques for deployment, and strategies for propagation. Notable findings include: the structure of academia has aspects that both impede and facilitate successful propagation; traditional academic funding sources do not adequately support ongoing propagation; and some successful strategies for getting the word out involve oblique approaches for reaching potential users. This exploration of common successful approaches can serve as a guide for developers and educational advocates when working to attract new users and broaden impact.

This session takes inspiration from the highly successful "Nifty Assignments" special session, but instead highlights high quality multiple-choice questions that can be used for Peer Instruction. Peer Instruction is a pedagogical practice characterized by asking students to answer challenging, conceptual questions in class. For each question, students individually respond, discuss the question in small groups, and respond again based on their new understanding. Peer Instruction has been widely identified as an important instructional technique in teaching computing. In this session, members of the community will present some of their best Peer Instruction questions along with a short explanation that provides the pedagogical content knowledge indicating why the question is a good question. If you are interested in learning more about Peer Instruction or finding new questions for your course(s), this session is for you.

A Concept Inventory (CI) is an assessment to measure student conceptual understanding of a particular topic. This article presents the results of a CI for basic data structures (BDSI) that has been previously shown to have strong evidence for validity. The goal of this work is to help researchers or instructors who administer the BDSI in their own courses to better understand their results. In support of this goal, we discuss our findings for each question of the CI using data gathered from 1,963 students across seven institutions.

Computer Science now has a number of validated instruments available for measuring student knowledge or interest in computing including the Second CS1 Assessment (SCS1), The Basic Data Structures Inventory (BDSI), the Computing Attitudes Survey (CAS), and the Digital Logic CI. These instruments can be used by instructors to assess their students and/or their own teaching. They can also be used by researchers to measure students' learning or attitudes. The goal of this BOF is to help instructors and researchers gain a better understanding of how to use these instruments, whether that be to get started in education research, to compare student learning across terms/curricular revisions, or just to learn more about student misconceptions. We will begin by discussing the available instruments, their purpose, and how to obtain them. Then we will open the discussion to the group on what they would like to measure, how these instruments might work for them, and how to best employ them with their students.

Computer Science now has a number of validated instruments available for measuring student knowledge or interest in computing (SCS1, BDSI, CAS, Digital Logic CI, etc.). But when and how should instructors and researchers use these instruments? In this BOF, we will begin by discussing the available instruments, their purpose, and how to obtain them. Then we will open the discussion to the group on what they would like to measure, how these instruments might work for them, and how to best employ them with their students.

Concept inventories (CIs) allow researchers and practitioners to measure student conceptual learning within a course or topic area. While they have enabled meaningful pedagogical change in other disciplines, there are relatively few CIs in computer science. In this paper, we report on our experiences as recent developers of a CI for basic data structures. We discuss each step along the route to a CI and offer tips based on what we have learned. We encourage others to create CIs, and we hope that this paper will serve as a practical guide through the process.

A Concept Inventory (CI) is a validated assessment to measure student conceptual understanding of a particular topic. This work presents a CI for Basic Data Structures (BDSI) and the process by which the CI was designed and validated. We discuss: 1) the collection of faculty opinions from diverse institutions on what belongs on the instrument, 2) a series of interviews with students to identify their conceptions and misconceptions of the content, 3) an iterative design process of developing draft questions, conducting interviews with students to ensure the questions on the instrument are interpreted properly, and collecting faculty feedback on the questions themselves, and 4) a statistical evaluation of final versions of the instrument to ensure its internal validity. We also provide initial results from pilot runs of the CI.

Many great teaching techniques are presented every year at SIGCSE and other CS education conferences. Unfortunately, most of them achieve very limited adoption, with few instructors incorporating these ideas into their classrooms. There is significant literature on how to encourage instructors to adopt educational innovations in other STEM fields, but the CS education community has made only limited strides in this area. This session will feature an interactive discussion of some of the barriers that prevent the adoption of good ideas, what solutions are available, and a brief presentation of the results of an ITiCSE working group on this topic. Attendees will leave the session better equipped to promote the adoption of educational innovations, either their own or ones that they have decided to champion.

In computer science, educational innovation is constant, but many great ideas never achieve the type of widespread adoption necessary to make lasting and effective change to the way we teach and learn. Research across STEM education has shown that propagation planning is often an overlooked or undervalued part of educational innovation. Whether promoting our own projects or an outside innovation, barriers to success are more difficult to overcome when encountered without sufficient preparation. Plans for adoption and scaling of innovations are not one-size-fits-all, but there are lessons we can learn from both successful and unsuccessful previous projects. We will present a summary of these lessons based on our recent ITiCSE working group research experience on the topic. This writing workshop will focus on building propagation plans informed by best practices, within the context of individual project definitions of success. We will work in small groups to identify potential barriers to the success of our projects, learn about best practices for overcoming those barriers, and put in place a measurable and actionable plan for adoption and propagation. Participants will work toward a better plan for propagation while garnering advice from their peers, learning and generating new ideas about and methods for dissemination and adoption, and building a community of resources for future collaboration, champions for change, and peer feedback. Bringing a laptop is recommended.

In this position paper, we look at the representation of SQL injection within undergraduate database textbooks, and argue that both discussion of security issues and security of example code must be improved. SQL injection is a common database exploit which takes advantage of programs that incorrectly incorporate user input into SQL statements. Teaching students how to write parameterized SQL statements is key to preventing this wide-spread attack. We look at the current editions of seven textbooks used at the top 50 US CS programs, and analyze their coverage of SQL injection, use of parameterized queries, and correctness of examples. We find a wide variety in the amount of coverage given to the topic, from none at all to in-depth coverage of defenses. Additionally, we find cases of SQL injectable code given as examples of how to correctly write queries in two of seven textbooks.

Developers spend a significant portion of their time searching for solutions and methods online. While numerous tools have been developed to support this exploratory process, in many cases the answers to developers' questions involve trade-offs among multiple valid options and not just a single solution. Through interviews, we discovered that developers express a desire for help with decision-making and understanding trade-offs. Through an analysis of Stack Overflow posts, we observed that many answers describe such trade-offs. These findings suggest that tools designed to help a developer capture information and make decisions about trade-offs can provide crucial benefits for both the developers and others who want to understand their design rationale. In this work, we probe this hypothesis with a prototype system named Unakite that collects, organizes, and keeps track of information about trade-offs and builds a comparison table, which can be saved as a design rationale for later use. Our evaluation results show that Unakite reduces the cost of capturing tradeoff-related information by 45%, and that the resulting comparison table speeds up a subsequent developer's ability to understand the trade-offs by about a factor of three.

To be effective instructors and CS education researchers, we must identify and understand student difficulties surrounding core computing topics. This study examines student difficulties with the basic data structures commonly found in CS2 courses. Initial exploration of student thinking began with think-aloud interviews with students. These interviews centered on open-ended questions that were iteratively improved upon based on analysis of interview transcripts. The revised open-ended questions were then posed to 249 students during an end-of-term final exam study session. Using the explanations and justifications included by students, responses to the questions were coded and summarized. This work characterizes the difficulties revealed by student responses, and provides details of their prevalence among the examined student population.

Peer Instruction (PI) is an active learning pedagogy that has been shown to improve student outcomes in computing, including lower failure rates, higher exam scores, and better retention in the CS major. PI's key classroom mechanism is the PI question: a formative multiple choice question on which students vote, then discuss, then vote again. While research indicates that PI questions lead to learning gains for students, relatively little is known about the questions themselves and how faculty employ them. Additionally, much of the work has examined PI data collected by researchers operating in a quasi-experimental setting. We examine data collected incidentally by multiple instructors using PI as a pedagogical technique in their classroom. We look at how many questions instructors use in their courses, the difficulty level of the questions, and normalized gain, a metric that looks at increases in student correctness between individual and group votes. We find normalized gain levels similar to those in existing literature, indicating that students are learning, and that most questions, even those developed by instructors new to PI, fall within recommended difficulty levels, indicating instructors can create good PI questions with little training. We also find that instructors add PI questions over the first several iterations of a new PI course, showing that they find PI questions valuable and suggesting that full development of PI materials for a course may take multiple semesters.

Most projects that create innovations in Computer Science education, whether they be changes to content or pedagogy, focus on first developing materials and then proving effectiveness. For educational innovations to have impact, however, they must be adopted by other instructors. Getting instructors to use new educational strategies is a significant challenge, with most new techniques never obtaining widespread adoption. Researchers who do consider dissemination of their research frequently use techniques such as publications and workshops, which are known to be insufficient.

We present the curriculum and evaluation of a pilot Biology-themed CS1 course offering at a large public university. Inspired by Harvey Mudd's CS 5 Green, we adapt CS1 + Bio to fit the needs of our student body, which is much more typical for those US institutions that produce the bulk of the nation's CS undergraduate degrees. This course was team-taught by a computer science professor and a biology professor, and combined typical CS1 topics with relevant biology content. Our initial offering attracted students who would not otherwise have taken CS1, and was the only one of our three CS1 courses where more students reported planning to major in CS after the course than before it.

Peer Instruction is an active learning pedagogy that has been shown to improve student outcomes in computing, including lower failure rates, higher exam scores, and better retention in the CS major. A key classroom mechanism for Peer Instruction is the "clicker question": a formative multiple-choice question on which students vote, then discuss, then vote again. While research indicates that clicker questions lead to learning gains for students, relatively little is known about the questions themselves and how faculty employ them. Additionally, much of the work has examined clicker data collected by CS Education researchers operating in a quasi-experimental setting. In this project, we examine clicker data collected incidentally by multiple instructors using clickers as a pedagogical technique in their classroom. This work represents a first effort to systematically evaluate how instructors use clicker questions, including how many clicker questions are used in a course, how difficult the questions used are, and whether instructors add or modify questions over time.

Establishing learning goals for a course allows instructors to design course content to address those goals, helps students to focus their learning appropriately, and enables researchers to assess learning of those goals. In this work, we propose six learning goals for a topic prevalent in CS2 courses: Basic Data Structures. These learning goals arise from reviewing several CS2 courses at a variety of institutions, surveying faculty experts who commonly teach CS2, and meeting and working closely with these experts. We outline our process for creating learning goals, identify important topics underlying these goals, and provide examples of how the goals developed on the path to consensus. We also document that the term "CS2" does not have a unified interpretation within the CS education community and describe how this hurdle influenced our decision to focus on Basic Data Structures.

Research shows the benefit of using active learning in computer science education; however, only limited resources (such as, prior publications) exist for systems courses (including architecture, networking, operating systems). This BoF brings together practitioners of various levels of experience to discuss ways to augment or replace traditional lecturing. We will discuss different techniques, possible materials available, and results measured. This BoF should benefit both instructors considering adopting techniques and instructors looking to discuss issues with their usage.

Peer Instruction (PI) is an active learning technique with over 25 years of research supporting its efficacy. Documented benefits in CS include lower WDF rates, higher exam scores, and improved retention in the CS major. One key difference between PI and traditional lecture is the use of "clicker questions" in class to challenge students' conceptual understanding. Students discuss and answer these questions in small groups before the instructor goes over the question with the entire class. This BoF is for both those using PI and those interested in starting. Attendees will meet other PI practitioners, discuss tips and tricks, and exchange materials. We will provide pointers to PI materials for a variety of courses, including CS1 & CS2, Machine Organization, Programming Languages, OS and more.

Modern web browsers have accrued an incredibly broad set of features since being invented for hypermedia dissemination in 1990. Many of these features benefit users by enabling new types of web applications. However, some features also bring risk to users' privacy and security, whether through implementation error, unexpected composition, or unintended use. Currently there is no general methodology for weighing these costs and benefits. Restricting access to only the features which are necessary for delivering desired functionality on a given website would allow users to enforce the principle of lease privilege on use of the myriad APIs present in the modern web browser.

We present the curriculum, pilot offering, and initial evaluation of a CS + Law based CS 1 course that was team taught by a Computer Science professor and a law school professor. Relevant legal topics were interwoven through the course.

Peer Instruction (PI) is an active learning technique with over 25 years of research supporting its efficacy in Physics Education. More recently, the CS Education community has found that the benefits of PI are true for CS as well, including lower WDF rates, higher exam scores, and improved retention in the CS major. One of the key differences between PI and traditional lecture is the use of a series of multiple choice "clicker questions" in class to challenge the students' conceptual understanding. Students discuss and answer these questions in small groups, then the instructor reviews why each choice was right or wrong with the entire class. The workshop is a practical look at the kinds of clicker questions used in PI. Attendees with see examples of some of our best and worst questions, and also work to design and improve some of their own questions. In addition, we will provide a demonstration of PI, and share our practical experiences in adopting PI in a wide variety of class sizes.

This paper describes the experience of using a student consultant in a sophomore level computer science course. A student consultant is a student who is not enrolled in the course, but attends selected class sessions and provides feedback on the in-class experience to the instructor, with the goal of improving some aspect of the course. In this paper we describe our experience with such a program from the point of view of both the instructor and the student consultant. We provide our views of the experience with the dual goals of making student consultant programs better known within the computer science education community, and to provide guidance and insight to those who may wish to use such a program themselves.

This session is a chance for researchers studying concept inventories (CIs)--low-cost assessments highlighting student misconceptions in a field--and CS education practitioners to communicate about advances in concept inventories in an engaging and utterly ridiculous way.

Concept Inventories (CIs) are short, multiple-choice exams that evaluate a student's understanding of core concepts of a particular course. CIs are especially useful for evaluating the effects of pedagogical techniques and interventions on student learning, as their focus on core concepts means any student should be able to answer the questions, and their use as a pre- and post-test allows them to measure student learning gains. However, CI development requires significant overhead: the current state of the art calls for an intensive, six step process. As a result, there are few CIs available for Computer Science, despite their effectiveness.

Concept Inventory (CI) assessments, which target high-level learning goals, have proven highly valuable for higher education research. These assessments have helped to evaluate pedagogical practices among individual instructors, both within and across institutions, and have hence elevated the level of discourse on education within the community. The success of CIs in physics has inspired similar developments in computer science, with a few CIs now developed for computer science courses. However, the development of a CI typically follows a burdensome process, requiring a significant investment to produce a single CI that may be difficult to deploy due to institutional curricular differences. Furthermore, as our field continues to be shaped by technological advances, a path to faster, more modular CI development is critical.

We describe a new enhanced cloud computing architecture, called the Proximal Workspace, to allow access and interaction between lightweight wearable I/O devices, e.g., video glasses, earphones, wrist displays, body sensors, etc., and ubiquitous applications that represent a new generation of comp

Operating systems courses often present students with multiple approaches to solve a problem, often with differing trade-offs. While students are more than capable of memorizing the details of these competing approaches, they often struggle to recommend a specific approach and analyze its implications. In particular, we find that students exhibit difficultly in interpreting text-based scenario descriptions in a way that allows them to correctly choose between potential solutions when presented with a high-level, conceptual scenario.

Peer Instruction (PI) has been shown to be successful at improving pass-rates and improving retention of majors in large classes at large research-intensive institutions. At these institutions, students have been shown to learn from peer discussion in PI and both students and faculty have reported that they value PI in their classrooms. However, little is known about the effectiveness of PI in small classrooms at teaching-focused liberal arts colleges. This study evaluates results from seven lower-division classes and four upper-division classes taught at three different liberal arts institutions using PI. In these classes, PI experienced similar success as that reported at large-research intensive universities, both in terms of student learning from peer discussion and from student attitudinal surveys. Most notably, of 137 surveyed students, 91% recommend more faculty use PI in their classes.

With applications increasingly moving to the cloud, it is becoming common for an application to be separated by the network from the I/O devices with which the user is interacting. Currently this requires modifying the application to receive user input from the network rather than the device. We present a new I/O architecture in which the device driver is split into two parts, with the network between them. This architecture makes the network invisible to both device and application, allowing both of them to work unmodified. Our architecture also supports transformation modules, each of which comes in a pair that operates on each side of the network. Via these module pairs, the resulting system is capable of supporting the modification of the I/O stream in a variety of ways to compensate for the network, while remaining transparent to the application.

We present performance results of a new distributed I/O software architecture to support remote applications interacting with local I/O devices. The architecture emphasizes network transparency and ease of customization/extensibility in support of the vastly different needs of various applications and devices that can benefit from remote I/O. Networked I/O is achieved via a networked device driver that is split into two parts, one on each side of the network. An I/O stream that is sourced at one end and sinked at the other may be modified by a set of pipelined transformation modules. Each module comes in a pair, one on each side of the network, with one side typically applying some operation and the other side applying a corresponding one, such as encoding and decoding the format of the data or pausing and resuming the sending of messages. Because of the paired nature of transformation modules, the system is capable of supporting the modification of the I/O stream in a variety of ways to compensate for network issues, one of the key problems of remote I/O, while remaining transparent to the application. We show that even with an implementation that operates almost entirely at user level (i.e., outside the operating system), good levels of performance that are adequate for even high intensity I/O, both in terms of efficiency and throughput, can be achieved.

The goal of the RUBI project is to accelerate progress in the development of social robots by addressing the problem at multiple levels, including the development of a scientific agenda, research methods, formal approaches, software, and hardware. The project is based on the idea that progress will go hand-in-hand with the emergence of a new scientific discipline that focuses on understanding the organization of adaptive behavior in real-time within the environments in which organisms operate. As such, the RUBI project emphasizes the process of design by immersion, i.e., embedding scientists, engineers and robots in everyday life environments so as to have these environments shape the hardware, software, and scientific questions as early as possible in the development process. The focus of the project so far has been on social robots that interact with 18 to 24 month old toddlers as part of their daily activities at the Early Childhood Education Center at the University of California, San Diego. In this document we present an overall assessment of the lessons and progress through year two of the project.