LogicWriter Actual (https://tinyurl.com/logicwriteractual) is a web app that helps early undergraduate CS students write with symbolic logic notation (↔, ∃, ∧, Greek letters, etc.). It designed with a quick start easy-to-use interface and is compatible with most writing programs. LogicWriter Actual is designed to minimize cognitive demands on software operation so that students can focus on mathematical writing.

Mathematics is often considered the foundation of computer science, with rigorous, mathematical reasoning, i.e., proof, at the heart of this foundation. Mathematical proof is the backbone of virtually all introductory mathematics courses within any computer science major. However, the degree to which rigorous reasoning is required of students in subsequent courses is highly variable across institutions. At some institutions, proof is a tool used to deepen material, whereas, at other places, proof is set aside in favor of increased topic coverage. Consequently, many students do not see the purpose of proof in computing. Furthermore, the demands of rigorous mathematical reasoning dissuade many students from continuing in the field.

"Proof Buddy" is an online browser based tool designed to teach proof writing to beginning computer science students. It has been designed from the ground up with educational purposes in mind and has been used successfully with hundreds of students since January 2022 at Drexel University. The tool helps students build and check proofs in a variety of systems. It is capable of doing Natural Deduction, both Boolean logic and first order logic, and is being extended to Equational Reasoning. Important instructor-centered features include that the teacher can create assignments of proof problems, which the software can auto score and have results uploaded into their school's LMS. Additionally, the tool allows proofs to be saved and exported and used as new rules. When this feature is used by the instructor, it permits a customization of the allowable rules. When this feature is used by the students, it allows them to create their own lemmas which reduces the cognitive load of a more intricate proof.

Mathematics instruction in computer science goes beyond prescribed topic coverage. It should build proficiency and willingness to engage in mathematical thought whenever appropriate: knowledge retention (across multiple years), and knowledge transfer across multiple application/course contexts. This evergreen subject has seen significant changes recently: the CS enrollment explosion; on-line instruction; active learning; greater diversity in background, interests, and goals among students; and expanded use of lookup technology for student work. Additionally, mainstream software development now encompasses mathematical ideas such as functional programming; cryptography; statistical inference; and mathematical certification of software. Retention and transfer (and their relative, "mathematical maturity") can be supported by well-considered and well-timed instructional action, supplementing the student realizations that may happen naturally. Cultivating authentic student engagement can help seeing course activity as building mathematical understanding for career use rather than an ephemeral game played for points. BoF participants will collaboratively discuss observations, reactions, thorny situations, and suggested practices for knowledge retention and transfer, in order to establish understanding for future directions.

This article focuses ontracing player knowledgein educational games. Specifically, given a set of concepts or skills required to master a game, the goal is to estimate the likelihood with which the current player has mastery of each of those concepts or skills. The main contribution of the work is an approach that integrates machine learning and domain knowledge rules to find when the player applied a certain skill and either succeeded or failed. This is then given as input to a standard knowledge tracing module (such as those from intelligent tutoring systems) to perform knowledge tracing. We evaluate our approach in the context of an educational game calledParallelto teach parallel and concurrent programming with data collected from real users, showing our approach can predict students skills with a low mean-squared error. We also provide results from deployment of our system in a classroom environment.

We investigated the impact of assigning specific roles in Process Oriented Guided Inquiry Learning (POGIL) activities versus giving the same group activities without pre-assigned roles. We hoped to show that the group with additional structure would receive tangible benefits: more engagement with partners, greater comprehension of material, heightened content interest, and increased retention. Preliminary results suggest that the proportion of minimally participating students was not statistically significantly different, and neither were the individual assessments. The roled section did have higher scores overall in the course, both in the group activities and also in the final exam; however, the difference was small and not clearly statistically significant. Unexpectedly, disciplinary actions and post course surveys indicate a greater rate of plagiarism on both shared lab reports and individual homework assignments in the free-form group and this may be a factor for instructors to bear in mind when utilizing group activities.

Concurrent and parallel programming (CPP) skills are increasingly important in today's world of parallel hardware. However, the conceptual leap from deterministic sequential programming to CPP is notoriously challenging to make. Our educational game Parallel is designed to support the learning of CPP core concepts through a game-based learning approach, focusing on the connection between gameplay and CPP. Through a 10-week user study (n 25) in an undergraduate concurrent programming course, the first empirical study for a CPP educational game, our results show that Parallel offers both CPP knowledge and student engagement. Furthermore, we provide a new framework to describe the design space for programming games in general.

In parallel programming, there is a shift away from the single execution path of sequential programming to situations where non-deterministic operation force consideration of multiple paths of execution. Compared to the substantial computer science education literature on helping students to learn sequential programming, there are fewer studies of the cognitive difficulties that students follow when learning parallel programming. To address this, we created a computer game, Parallel involving concurrent situations. The game is an abstract representation of concurrency problems where players are asked to solve a progression of puzzles involving arrows moving concurrently on tracks. Play does not require coding. The goals of our research were to 1) explore how students acquire skills in the design of solutions with parallelism, and 2) explore how interactive games can substitute or compliment conventional parallel programming courses. Through two user studies of the game (n=7) where students played the game and used a talk-aloud protocol alongside a researcher, three major themes emerged, that of non-determinism where students were able to make the connection of non-deterministic behavior in parallel programming to the game, self-efficacy where students were stating they felt their knowledge of parallel programming increased after playing the game, and expertise where researchers learned that expertise was important to successful connection of the game to parallel programming concepts These findings show that students are beginning to see the connection between the game/s presentation of concurrency to programming concepts such as non-determinism.

This session invites educators interested in sharing and/or learning about experiences with tools for automatic feedback on technical work: the "if", "why" and "how". This includes experiences with program testing, problem-solving exercises, or quizzes, generated or checked with engines with expert-level technical capabilities, to scale up feedback to cope with burgeoning enrollment in CS courses while maintaining or improving student learning outcomes. Commercial, free and open-source tools now exist to assist in this endeavor.

This is work-in-progress on an entry-level course on computational problem-solving and programming for engineering students. It has been run since 2006 at our institution at a scale of 800 students/term, as a hybrid in-person lab and out-of-class on-line autograded exercises using Maple TA. The course is in the process of changing languages (from Maple to Matlab), with upgraded resources: a lecture period, some manually graded assignments, projects, and automatic code testing. To date the assessment of the impact of the course has been through conventional means: assigning grades and indications as to whether student grades are consistent with those obtained in other courses taken. During the transition from Maple to Matlab more detailed and individualized performance assessment plans are being developed which are intended to enable the staff and students to better judge weaknesses in program knowledge and who would benefit from additional personal contact.

We model on-line ink traces for a set of 219 symbols to "best fit" low-degree polynomial series. Using a collection of mathematical writing samples, we find that in many cases this provides a succinct way to model the stylus movements of actual test users. Furthermore, even without further similarity-processing, the polynomial coefficients from the writing samples form clusters which often contain the same character as written by different users. We find this style of characterization to be an attractive tool due to the suitability of the representation to computation and mathematical analysis.

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We report here on an extensive redesign and unification of the Introductory Computer Programming sequences offered to computer science, computer engineering, information science and digital media majors. The redesign is intended to improve student learning while reducing costs. The approach makes use of substantial Web-based course material and course management tools, including multi-level online modules that individualize instruction and enable students to self-schedule learning each week. Each module covers a particular aspect of computer programming at different levels of knowledge. Students are assigned work and reading from the module at a level appropriate to the objectives of the long-term goals of their major. This allows students in different majors to acquire the appropriate skill level for each technique and concept. Peer mentors and teaching assistants provide assistance online or in person. In the future, we plan to expand the self-scheduling aspect of the course to allow students to enter the course at different modules, depending on their previous knowledge.

Advances in computing and telecommunication technology provide abundant new opportunities for academic dishonesty. Anecdotal evidence suggests that students are far more aware than faculty of various mechanisms for cheating on exams, plagiarizing assignments, and soliciting work for pay. Fortunately, technological advances also provide the alert instructor with some tools for combating such academic dishonesty.In this session, we will present information on how calculators, cell phones, beepers, and other handheld technology may be used to cheat on exams; how the Internet is used to match students with sources for solutions to their assignments; and existing tools and services for the faculty member.The intention of this session is to inform faculty about various ways that students may commit academic fraud; and tools and approaches that are available to reduce their effectiveness. We also hope to gain further information from other faculty and/or students in attendance. We do not intend to debate whether these activities should be allowed due to the ease with which they are committed, as is often discussed.We will provide a bibliography of articles about high-tech academic dishonesty, software tools and services for detecting plagiarism (including shared code in programming assignments), and Internet resources.

Article Free Access Share on Symbolic computation in Java: an appraisement Authors: Laurent Bernardin Institut für Wissenschaftliches Rechnen, Eidgenössische Technische Hochschule, Zurich, Switzerland Institut für Wissenschaftliches Rechnen, Eidgenössische Technische Hochschule, Zurich, SwitzerlandView Profile , Bruce Char Department of Mathematics and Computer Science, Drexel University, Philadelphia, Pennsylvania Department of Mathematics and Computer Science, Drexel University, Philadelphia, PennsylvaniaView Profile , Erich Kaltofen Department of Mathematics, North Carolina State University, Raleigh, North Carolina Department of Mathematics, North Carolina State University, Raleigh, North CarolinaView Profile Authors Info & Claims ISSAC '99: Proceedings of the 1999 international symposium on Symbolic and algebraic computationJuly 1999 Pages 237–244https://doi.org/10.1145/309831.309946Published:01 July 1999Publication History 14citation450DownloadsMetricsTotal Citations14Total Downloads450Last 12 Months23Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Article Software components using symbolic computation for problem solving environments Share on Authors: Y. N. Lakshman Department of Mathematics and Computer Science, Drexel University, Philadelphia, PA Department of Mathematics and Computer Science, Drexel University, Philadelphia, PAView Profile , Bruce Char Department of Mathematics and Computer Science, Drexel University, Philadelphia, PA Department of Mathematics and Computer Science, Drexel University, Philadelphia, PAView Profile , Jeremy Johnson Department of Mathematics and Computer Science, Drexel University, Philadelphia, PA Department of Mathematics and Computer Science, Drexel University, Philadelphia, PAView Profile Authors Info & Claims ISSAC '98: Proceedings of the 1998 international symposium on Symbolic and algebraic computationAugust 1998 Pages 46–53https://doi.org/10.1145/281508.281542Online:01 August 1998Publication History 9citation341DownloadsMetricsTotal Citations9Total Downloads341Last 12 Months2Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Many chemical reaction systems studied in the Future work includes extension of the procedure to handle systems with more than two time scales, and development of the mathematical foundations to add to the robustness of the procedure.

We have investigated the use of computer algebra as the basis for software tools for floating-point error

We discuss on-going work on large-grained parallel symbolic computation using a system based on Maple and Linda. The prototype runs on a Sequent Balance. The approach can be used with most existing algebra/symbol manipulation systems, and provides the potential to deliver of parallel symbolic computation on a variety of architectures (e.g. shared memory, hypercubes, networked workstations). Parallel speedup was achieved on a variety of algebraic problems, although many significant improvements in efficiency remain to be achieved.

While numerical (e.g. Fortran) code generation from computer algebra is nowadays relatively easy to do, the expressions as they are produced via computer algebra typically benefit from non-trivial reformulation for efficiency and numerical stability. To assist in automatic “expert reformulation”, we desire good automated tools to assess the stability of a particular form of an expression. In this paper, we discuss an approach to proofs of numerical stability (with respect to roundoff error) of rational expressions. The proof technique is based upon the ability to propagate properties such as sign, exact representability, or a certain kind of numerical stability, to floating point results from properties of their antecedents.