Most students readily see the value of studying computing as a path to a good job and know that the application of computing can generate business value. At the same time, we now face a world where pervasive computing is enabling a misalignment between business value and social value. However, computing also holds the potential to drive positive social change and to serve the greater good. This talk will discuss how some of the recent revisions to the computer science major at Dickinson College elevate this potential. A thread emphasizing computing for the greater good that now runs through our courses engages students in Free and Open Source Software (FOSS) with explicit humanitarian goals (HFOSS). The missions of these HFOSS communities provide real examples of ways in
which computing can be focused intentionally on creating a positive social impact. At the same time, learning and working with HFOSS tools, processes, artifacts and community members builds the hard and soft skills that students and employers want. Students are exposed to FOSS concepts and examples of HFOSS in our first course. A sequence of two ½ courses at the intermediate level familiarize students with FOSS communities and build their technical skills by engaging them in an authentic HFOSS project. This project is FarmData2, which we manage in collaboration with the Dickinson College organic farm. In a year-long senior capstone students research FOSS and HFOSS projects/communities that are of interest to them. They then form teams, choose projects and engage with their selected project communities “in the wild.” Details on some of the activities that students complete and examples of the types of contributions they have made both to FarmData2 and to the projects they have chosen in the capstone will be given. Analyses of pre/post course survey data and the types of projects selected in the capstone will be presented. These analyses suggest that (1) students gain an appreciation that they can use computing to contribute to the greater good, (2) that they become more likely to continue contributing to FOSS or HFOSS projects and (3) that engaging students in HFOSS holds potential for broadening participation in computing.
more »
« less
Promoting Privacy Considerations in Real-World Projects in Capstone Courses with Ideation Cards
Nearly all software built today impinges upon end-user privacy and needs to comply with relevant regulations. Therefore, there have been increasing calls for integrating considerations of compliance with privacy regulations throughout the software engineering lifecycle. However, software engineers are typically trained in the technical fields and lack sufficient knowledge and support for sociotechnical considerations of privacy. Privacy ideation cards attempt to address this issue by making privacy compliance understandable and actionable for software developers. However, the application of privacy ideation cards in real-world software projects has not yet been systemically investigated. The effectiveness of ideation cards as a pedagogical tool has not yet been examined either. We address these gaps by studying how teams of undergraduate students applied privacy ideation cards in capstone projects that involved building real-world software for industry sponsors. We found that privacy ideation cards fostered greater consideration and understanding of the extent to which the projects aligned with privacy regulations. We identified three main themes from student discussions of privacy compliance: (i) defining personal data; (ii) assigning responsibility for privacy compliance; and (iii) determining and exercising autonomy. The results suggest that application of the cards for real-world projects requires careful consideration of intersecting factors such as the stage at which the cards are used and the autonomy available to the developers. Pedagogically, ideation cards can facilitate low-level cognitive engagement (especially the cognitive processes of meaning construction and interpretation) for specific components within a project. Higher-level cognitive processes were comparatively rare in ideation sessions. These findings provide important insight to help enhance capstone instruction and to improve privacy ideation cards to increase their impact on the privacy properties of the developed software.
more »
« less
- Award ID(s):
- 2221870
- NSF-PAR ID:
- 10357451
- Date Published:
- Journal Name:
- ACM Transactions on Computing Education
- Volume:
- 21
- Issue:
- 4
- ISSN:
- 1946-6226
- Page Range / eLocation ID:
- 1 to 28
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
We are now over four decades into digitally managing the names of Earth's species. As the number of federating (i.e., software that brings together previously disparate projects under a common infrastructure, for example TaxonWorks) and aggregating (e.g., International Plant Name Index, Catalog of Life (CoL)) efforts increase, there remains an unmet need for both the migration forward of old data, and for the production of new, precise and comprehensive nomenclatural catalogs. Given this context, we provide an overview of how TaxonWorks seeks to contribute to this effort, and where it might evolve in the future. In TaxonWorks, when we talk about governed names and relationships, we mean it in the sense of existing international codes of nomenclature (e.g., the International Code of Zoological Nomenclature (ICZN)). More technically, nomenclature is defined as a set of objective assertions that describe the relationships between the names given to biological taxa and the rules that determine how those names are governed. It is critical to note that this is not the same thing as the relationship between a name and a biological entity, but rather nomenclature in TaxonWorks represents the details of the (governed) relationships between names. Rather than thinking of nomenclature as changing (a verb commonly used to express frustration with biological nomenclature), it is useful to think of nomenclature as a set of data points, which grows over time. For example, when synonymy happens, we do not erase the past, but rather record a new context for the name(s) in question. The biological concept changes, but the nomenclature (names) simply keeps adding up. Behind the scenes, nomenclature in TaxonWorks is represented by a set of nodes and edges, i.e., a mathematical graph, or network (e.g., Fig. 1). Most names (i.e., nodes in the network) are what TaxonWorks calls "protonyms," monomial epithets that are used to construct, for example, bionomial names (not to be confused with "protonym" sensu the ICZN). Protonyms are linked to other protonyms via relationships defined in NOMEN, an ontology that encodes governed rules of nomenclature. Within the system, all data, nodes and edges, can be cited, i.e., linked to a source and therefore anchored in time and tied to authorship, and annotated with a variety of annotation types (e.g., notes, confidence levels, tags). The actual building of the graphs is greatly simplified by multiple user-interfaces that allow scientists to review (e.g. Fig. 2), create, filter, and add to (again, not "change") the nomenclatural history. As in any complex knowledge-representation model, there are outlying scenarios, or edge cases that emerge, making certain human tasks more complex than others. TaxonWorks is no exception, it has limitations in terms of what and how some things can be represented. While many complex representations are hidden by simplified user-interfaces, some, for example, the handling of the ICZN's Family-group name, batch-loading of invalid relationships, and comparative syncing against external resources need more work to simplify the processes presently required to meet catalogers' needs. The depth at which TaxonWorks can capture nomenclature is only really valuable if it can be used by others. This is facilitated by the application programming interface (API) serving its data (https://api.taxonworks.org), serving text files, and by exports to standards like the emerging Catalog of Life Data Package. With reference to real-world problems, we illustrate different ways in which the API can be used, for example, as integrated into spreadsheets, through the use of command line scripts, and serve in the generation of public-facing websites. Behind all this effort are an increasing number of people recording help videos, developing documentation, and troubleshooting software and technical issues. Major contributions have come from developers at many skill levels, from high school to senior software engineers, illustrating that TaxonWorks leads in enabling both technical and domain-based contributions. The health and growth of this community is a key factor in TaxonWork's potential long-term impact in the effort to unify the names of Earth's species.more » « less
-
Nowadays, cyberattack incidents are happening on a daily basis. As a result, the demand for a larger and more challenging workforce is increasing. To handle this demand, academic institutions offer cybersecurity courses and degree programs into their curricula; however, more efforts are needed to address the high demand of the cybersecurity workforce. This work aims to bridge the gap between workforce shortage and the number of qualified graduates to fill the positions. We approach this by introducing cybersecurity concepts at the early stage of undergraduate curricula of computer science and engineering programs. Secure programming is critical as many cybersecurity incidents happen due to software vulnerabilities. However, most UG-level programming courses pay little attention to secure programming practices. As a result, many students graduate with limited knowledge of security vulnerabilities that might plague the developed software. Our goal in this work is to introduce secure programming at introductory level programming courses so that students should be aware of cybersecurity issues and use this security mindset in advanced level courses and projects in their degree programs. To accomplish this goal, we developed intuitive and interactive modules emphasizing secure programming in C++ and Java courses to help students become secure software developers. These modules will be used alongside the coursework to emphasize certain vulnerabilities within the programming environment of a specific language and allow students to learn cybersecurity topics, enforcing a solid foundation and understanding. We developed cybersecurity educational modules for C++ and Java as they are amongst the popular languages and used in introductory programming courses. While designing these modules, we kept in mind that the topics must be relevant to real-world issues in the software industry. We used a variety of resources and benchmarks to ensure the authenticity of our chosen topics, including Common Weakness Enumeration (CWE) and Common Vulnerability and Exposures (CVE). While choosing module topics to develop, we had some restrictions. For example, the topics must be introductory and easy to understand. These modules are geared towards freshman or sophomore-level UG students who have just started programming. The developed security modules have four components: power-point slides, lab description, code template for the lab, and complete solution. The complete solution for each module will be provided to the instructors to check students’ work if they adopt the modules in their courses. The modules developed for a C++ programming course include labs on input validation, integer overflow, random number generation, function call with incorrect argument type, and dangling pointers. In Java, we developed lab modules for input validation, integer overflow, null object reference, random number generator, and data encapsulation.more » « less
-
Concurrent programs are difficult to test due to their inherent non-determinism. To address this problem, testing often requires the exploration of thread schedules of a program; this can be time-consuming when applied to real-world programs. Software defect prediction has been used to help developers find faults and prioritize their testing efforts. Prior studies have used machine learning to build such predicting models based on designed features that encode the characteristics of programs. However, research has focused on sequential programs; to date, no work has considered defect prediction for concurrent programs, with program characteristics distinguished from sequential programs. In this paper, we present ConPredictor, an approach to predict defects specific to concurrent programs by combining both static and dynamic program metrics. Specifically, we propose a set of novel static code metrics based on the unique properties of concurrent programs. We also leverage additional guidance from dynamic metrics constructed based on mutation analysis. Our evaluation on four large open source projects shows that ConPredictor improved both within-project defect prediction and cross-project defect prediction compared to traditional features.more » « less
-
Mentoring has been a subject of study for 50 years. Most studies of mentoring programs evaluate the effect of the program on the participants but do not evaluate if different mentors have different effects on mentees. Open-source software (OSS) is software with a license that allows it to be freely used by other people. Such software has become foundational to the world economy. However, many OSS projects get abandoned by their creators. Various nonprofit organizations have arisen to help OSS projects become sustainable. One of the key services offered by many of these nonprofit organizations is a mentorship program where experienced OSS developers advise nascent projects on how to achieve sustainability. We use data from the Apache Software Foundation Incubator program where 303 mentors have mentored 286 projects, with most mentoring more than one project, to address this question: Is who a project has as a mentor associated with variation in project success? Who a project has as a mentor accounts for 45% of the variation in project outcomes, with some mentors being associated with positive and some with negative outcomes. These mentors could offer insights into how to improve the mentoring program. This result also demonstrates, more broadly, that the nature of specific mentoring relationships may be important to understanding how mentors impact outcomes in other mentoring programs.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3458038
