Interactive Petri net simulation

Aim/Purpose: The purpose of this study is to identify how Advanced level Mathematics and Mathematics course units offered at university level do impact on the academic performance of theoretical Computer Science course units. Background: In Sri Lankan state universities, students have been enrolled only from the Physical Science stream to do a degree program in Computer Science. In addition to that, universities have been offering some course units in Mathematics to provide the required mathematical maturity to Computer Science undergraduates. Despite of this it is observed that the failure rates in fundamental theoretical Computer Science course units are much higher than other course units offered in the general degree program every year. Methodology : Academic records comprised of all 459 undergraduates from three consecutive batches admitted to the degree program in Computer Science from a university were considered for this study. Contribution: This study helps academics in identifying suitable curricula for Mathematics course units to improve students’ performance in theoretical Computer Science courses. Findings: Advanced level Mathematics does not have any significant effect on the academic performance of theoretical Computer Science course units. Even though all Mathematics course units offered were significantly correlated with academic performance of every theoretical Computer Science course unit, only the Discrete Mathematics course unit highly impacted on the academic performance of all three theoretical Computer Science course units. Further this study indicates that the academic performance of female undergraduates is better than males in all theoretical Computer Science and Mathematics course units. Future Research: Identifying other critical success factors contributing to the students’ academic performance of the theoretical Computer Science through empirical studies

Teaching a hardware-based course for computer science students is a very challenging task. Students need to do a lot of practical work in the laboratory, usually do some practical project, learn theory and finally take the exam. This is a very hard task for the first hardware-based course — Computer architecture and organization (CAO), especially if it is offered in the first year of studies. Many successful examples report introducing some online learning tools, such as distance laboratories or visual simulators, which help students easier to learn the required learning objectives. In this paper, we introduce a brand new approach of reorganizing the curriculum of the course of Discrete Mathematics (DM). This approach transfers the fundamentals of logic design earlier in the DM course. Since both DM and CAO courses are scheduled in parallel, this transfer and reorganization offers necessary background for topics learned in the CAO course. This change prepares the students with relevant content about digital logic part of the CAO course and results with an improvement of 50% of those who had passed the midterm exam compared to the previous years.

Google Classroom is a platform in the form of an LMS (learning management system) which is provided free or unpaid by Google. Google classroom is integrated with email, so it's easy to use (user friendly). Google classroom makes it easy for teachers and lecturers to do distance learning, so that learning becomes efficient, effective and interactive. This study uses a quantitative descriptive research method (Maolani & Cahyana, 2016). The quantitative approach used is in the form of questionnaires and interviews. The purpose of this study is to describe student learning using the Google Classroom Application in Discrete Mathematics courses during the Covid-19 pandemic. This research carried out from the odd semester of the 2021/2022 academic year to 10 students in the fifth semester of the Discrete Mathematics course, the Mathematics Education Study Program. useful for helping plan events, send surveys, give students or others quizzes, or gather simple information in an efficient way. Interviews were conducted at the end of online teaching and learning activities. Data analysis was performed using excel to calculate the percentage and average value. Based on the indicators of the application of the Google Classroom Application, it shows that the average student answer is 75.5% agree and 25.5% disagree. These results show that the application of Google Classroom gets good responses from students, so that it can be used for learning in Discrete Mathematics courses.

We are concerned about a view in undergraduate computer science education, especially in the early courses, that it's okay to be math-phobic and still prepare oneself to become a computer scientist. Our view is the contrary: that any serious study of computer science requires students to achieve mathematical maturity (especially in discrete mathematics) early in their undergraduate studies, thus becoming well-prepared to integrate mathematical ideas, notations, and methodologies throughout their study of computer science. A major curricular implication of this theme is that the prerequisite expectations and conceptual level of the first discrete mathematics course should be the same as it is for the first calculus course --- secondary school pre-calculus and trigonometry. Ultimately, calculus, linear algebra, and statistics are also essential for computer science majors, but none should occur earlier than discrete mathematics. This paper explains our concerns and outlines our response as a series of examples and recommendations for future action.

Course-based Undergraduate Research Experiences (CUREs) have been well developed in the hard sciences, but math CUREs are all but absent from the literature. Like biology and chemistry, math programs suffer from a lack of research experiences and many students are not able to participate in programs like REUs (Research Experiences for Undergraduates). CUREs are a great alternative, but the current definition of CURE (see [1]) has potential barriers when applied to mathematics (e.g. time, novelty of project). Our solution to these barriers was to develop a math CURE pathway in which students complete "Math CUREs" in targeted courses. After finishing the pathway (or part of the pathway), students complete a research project in at least one of the following areas: Lie theory, representation theory, or combinatorics. The focus of this paper is the math CURE implemented in a discrete mathematics course for math and computer science majors. We share our experiences with the development and implementation of this CURE over several iterations as well as the impact of the CURE on students experiences through participant survey data obtained from this CURE.

Teaching formal methods in software construction has often been a concern of several computer science educators. In our opinion, the origin of most of the difficulties in learning formal methods in computer science and software engineering does not lie in computer science courses but in the mathematical background of the students. Moreover, there are numerous obstacles to learning basic concepts noted by both computer science and mathematics educators. To change this situation it is necessary to integrate the work of mathematics and computer science educators. That is, the main focus should be the creation of new educational approachs nourished by two components: a theoretical one (formally introducing discrete mathematics concepts) and an experimental one (implementing those concepts in a suitable programming language). In this paper, using examples from a discrete mathematics course for high school teachers, we describe the main characteristics of our approach.

This experience report documents an attempt at embracing the "A's for all" and equitable grading frameworks in an introductory, proof writing-based discrete mathematics course for computer science majors (with N=138 students) at a medium-sized research-oriented university in the US. Unlike in introductory programming contexts, there is so far no reliable automated grading system that gives formative and adaptive feedback supporting the scope of a proof-based discrete mathematics course. We therefore faced the unique challenge of being unable to automate all assessments and directly offer all students unlimited attempts toward mastery.

Discrete Mathematics is a new course that has emerged in recent decades. It is an important branch of modern mathematics and the main course of professional basic theory in computer science. Its whole system is centered around the data objects that computers can accept and process, and discrete mathematics has gradually developed, improved and deepened with the development of computer science. This paper considers how to improve the level and quality of teaching discrete mathematics courses in terms of content, methods and teaching resources, so as to facilitate students’ learning of subsequent courses and future scientific research.

This session is a progress report from the first committee created under the SIGCSE Committee Initiative. The Committee on Implementation of a Discrete Mathematics Course is charged with developing implementation models and materials for the one-semester discrete math course proposed in Computing Curriculum 2001. At the time of the session, the Committee will have completed about three-fourths of its task. In this session the committee will present a number of course models which, for each, will include a syllabus/course outline and a list of possible applications which connect the mathematics to fundamental ideas in computer science. Comments and additional input from the SIGCSE community will be solicited. Presentation will by Bill Marion, one of the two committee co-facilitators and two other committee members.

Several factors, including grade-point average, math SAT scores, performance in calculus and programming courses, and results from a short pre-test were used in an effort to predict student grades a discrete mathematics course offered to computing science students. Two factors, SAT and average programming grade, were found to be significantly associated with the final grade for the discrete math course. Additionally, performance in the discrete math course was positively correlated with performance in the automata course required for computer science students.

Critical thinking skills greatly affect the solving of mathematical problems. Therefore this study aims to develop a test instrument for students' critical thinking skills based on Higher Order Thinking Skills (HOTS) in discrete mathematics courses. The type of instrument developed is a work breakdown test equipped with an assessment rubric. Instrument development uses the Research and Development (R&D) method. Critical thinking skills are determined using four indicators, namely: analyzing problems, concluding and providing explanations, evaluating, and selecting problem-solving strategies. Development of Higher Order Thinking Skills (HOTS) type instruments adapted to discrete mathematics course material. This study consisted of three stages: designing the instrument, validating the contents of the instrument, and validating the construction of the instrument. The results showed that the results of content validity were 0.84 with a very high category, then ten job description test items were tested for validity using the ratter test. The results of the reliability rater showed a value of 0.994. So, based on the reliability criteria developed by Guilford, the reliability rater obtained, namely 0.994, is classified as very high. The HOTS type test refers to the top three dimensions of cognitive processes from the revised Bloom's taxonomy, namely analyzing (C4), evaluating (C5), and creating (C6).

This research aims to design Student Worksheets (LKM) for the Discrete Mathematics course, where the LKM design is structured so that the LKM can be used in the Rigorous Teaching and Learning (RTL) learning model. The results of the lecturers' reflections found that the main problem lies in the content of the material in textbooks which is not interesting, students are often unable to understand the textbooks they own, especially in solving the questions given. This has implications for 1) lack of motivation to learn, 2) lack of understanding of the material, 3) fear of expressing opinions, and 4) lectures are less effective and less enjoyable. Therefore, teaching materials need to be packaged appropriately according to the substance and conditions of students in LKM. The research design used in this research is Thiagarajan's 4-D development model. This model is a system of educational development approaches that are carried out in 4 sessions, namely Define or Introduction where in this session preliminary analysis, student analysis, and needs analysis are carried out, Design or Planning where in this session what is done is format selection, initial design and design preparation, Develop or Development where in this session validation and limited trials are carried out, as well as Disseminate or Disseminate where in this session the LKM is given to the teaching lecturers. This research produces an LKM that is used in Discrete Mathematics courses.

Programming assignments in my discrete mathematics course have changed recently due to an influx of non-computer science students with little or no programming experience. Programming problems are now assigned in a simple to learn, easy to write, mathematical-like functional programming language that requires no previous programming experience. In theory, all students begin on the same basis. Exposure to the concepts of functional programming is an essential part of computer science and mathematics curricula. For most students this is the only exposure to functional programming. Functional programming and discrete mathematics are a natural combination. One week of lectures and perhaps a small monetary investment is all that is required. An instructor totally unfamiliar with functional programming can easily learn enough in a week or so to present a simple introduction to the topic. Introducing functional programming concepts in discrete mathematics was very successful. Students found the exposure to functional programming to be an insight they had never experienced before and enthusiastically recommended an introduction to functional programming be a permanent part of the course.

This study aims to determine the interest of Informatics students about the material in discrete mathematics that is most in demand. The population of this study was 20 students from the Informatics Department at Amikom University Yogyakarta. Data collection techniques using the interview method. The interview method is used to determine student interest in discrete mathematics course material that is in accordance with the actual conditions. In the discussion the author uses functions in discrete mathematics, namely with domain functions, codomain, and range. The results of this study indicate that the interests of Informatics students about matter have discrete mathematics in sufficient categories

Graph materials contains declarative knowledge and procedural knowledge. In Graph subject included declarative knowledge is the graph terminology while those included procedural knowledge is how to determine the settlement of problems by using the algorithm methods associated with Graph. Dirrect instruction that relies on principles of behavioral and social learning theory, has been specifically designed to support students' learning processes associated with procedural knowledge and declarative knowledge is well structured and can be taught with the pattern of activity that gradually, step by step. ARSC motivation strategies (Attention, Relevance, Confidence, Satisfaction) is a strategy that can increase the motivation on learning materials and learning activities of students. Application of direct instruction model with ARCS motivational strategies is one solution to resolve the issue. The purpose of this study was to determine whether the aplication of direct istruction model using ARCS strategy on graph materials subject (1) the mastery learning is achieved, (2) students' learning activities are effective, (3) students' responses are positive, and (4) the effectiveness of model is reached. This research is a qualitative descriptive research. The subjects of this research are students who take Discrete Mathematics course in Educational Mathematics Program, Department of Educational Mathematics and Science, FKIP, Sebelas Maret University Surakarta. The results is (1) mastery learning achieved, (2) learning activities are effective, (3) students' response considered positive, (4) the effectiveness of interactive learning on graph is achieved. Keywords: Dirrect Instruction Model, Motivation Strategies ARCS, Discrete Mathematics, Graph