We started with an idea for something new. We saw it evolve. There is every indication that it has a bright future. What more could we ask?

Gamification, the use of game elements in non-game contexts, is already widely used to enhance learner engagement and motivation. Gamification motivates by adding gamefulness to the learning tasks. It is largely agreed that the success of applying gamification to educational contexts strongly depends on the way the gamification is designed & implemented. The goal of this BOF will be to provide a platform for discussing and brainstorming of different ways in which Computer Science courses could be gamified. BOF participants will form groups which will be tasked with developing scenarios of gamification design for a CS course. The groups will be led by the BOF organizers & other participating colleagues who are experienced in applying gamification in their courses. The guiding questions will include: What should be the steps in the gamification design process, where do we start? What are the goals? Which learning activities are suited for gamifying? Which game elements - the building blocks that are used for creating gameful experiences - could be used in the selected contexts? What gamification platforms or tools can be used to implement the designed gamification? At the end, the groups will be invited to present their gamification scenarios. We hope that in this BOF we will collectively identify new and interesting strategies for creating successful and sustainable gameful experiences in CS courses which will contribute to learners' engagement & motivation.

This Full Paper in the Research-to-Practice track builds on research in gamification of instruction. A primary objective of gamifying learning is to encourage and sustain students' engagement in activities by making them more gamelike. However, it is still unclear what structures borrowed from games could afford such a “game-like” experience and in what contexts. Embedding classmates' duels in learning settings seems a promising gamification strategy for exploration due to its potential of increasing motivation and engagement through a “game-like” experience. Similar effects are expected from using virtual currency, another design element popular in video games. Accordingly, the goal of this study is to empirically investigate whether the incorporation of dueling leads to increased interest in out-of-class practicing. In addition, we were interested in investigating to what an extent adding virtual currency can boost students' interest in dueling. An introductory class in Python programming served as the experimental environment. Unlike most studies in which the control group works in a non-gamified condition and the experimental group works in a gamified condition, this experiment uses a different approach. We investigated the impact on learners' engagement of adding duels to an ongoing gamified activity. Engagement indicators were measured and logged throughout the semester while student motivation was examined through surveys. The opportunity to challenge classmates appeared after the first exam (around one-third of the semester) and continued for the remaining two thirds of the class time. Thus, the same students in the new condition served as the experimental group. After the third exam, we added virtual currency. Students were able to earn virtual currency by issuing and responding to duel requests as well as by doing extra practice. This had a noticeable effect on the use of dueling. The empirical results of the study show that overall, for this group of students, adding duels alone had no positive effect on students' engagement with the gamified practicing system. However, evidence from the survey suggests that the studied combination of gamification elements (points, badges, leaderboard, avatars, duels, and virtual currency) did increase student intrinsic motivation.

There has been an increasing effort to make activities that are not inherently interesting for all learners more attractive through gamification. Although the research on the effectiveness of educational gamification has been growing, the effects of some gamification elements on learners' motivation and engagement are not well understood. In response to this gap, in this paper we describe an experience of gamifying out-of-class practicing with Virtual Currency (VC) in a Computer Networking course. The results of our study show that the VC-based gamification (without interactions with any other gamification elements) had a positive impact on student engagement compared to non-gamified online practicing. The learners' VC earning and spending behaviors indicate also that Virtual Currency brings additional objectives for students to strive for, besides grades.

In this session, members of the ACM Data Science (DS) Task Force will present the final draft of Computing Competencies for Undergraduate Data Science Programs. Drafting this document has been a three-year process, in which the task force has released preliminary drafts, sought input from the community, and responded to the community's helpful feedback. Our intent is that the session be an exchange that will clarify the contents of the report and provide participants with ways to put the report into practice at their own institutions. This session should be of interest to all SIGCSE attendees, but especially to faculty developing college-level curricula in Data Science.

The low performance and drop-outs in Computer Science classes are frequently attributed to lack of student engagement and motivation. Meanwhile, gamification increasingly attracts the interest of educators due to its potential to foster motivation and behavioral changes in learning contexts. This virtual workshop introduces participants to the concept of gamification and the use of OneUp Learning, a platform aimed at gamifying academic courses. OneUp is aimed at encouraging students' out-of-class practicing and increasing their overall engagement in the course through employing game design elements. The platform is course-independent and allows the instructor to turn on and off a number of gamification features, including avatars, points, leaderboards, progress bar, content unlocking, goal-setting, badges, virtual currency, duels, etc. For using OneUp, instructors have to provide practice exercises. Apart from the standard question types, OneUp supports Parson's and programming problems, as well as Flash cards. The workshop offers an interactive tutorial and individual work. The tutorial will introduce the OneUp platform and will demonstrate its use for gamifying a course. Workshop attendees will be engaged in hands-on experience. An OneUp course shell will be created and populated with sample data for each workshop attendee. After the tutorial, the participants will be able to explore and further gamify their own OneUp demo course. We will also demonstrate Quest, a repository for sharing OneUp problems.

The ACM Data Science Taskforce was established in 2017 by the ACM Education Council and tasked with articulating the role of computing discipline-specific contributions to the emerging field of data science. This taskforce is seeking to define what the computing contributions are to this multidisciplinary field, in order to provide guidance for computer science or similar departments offering data science programs of study at the undergraduate level. This panel session will provide an update of the work of the ACM Data Science Taskforce and will engage the ITiCSE international community in this effort. Panelists are members of the taskforce and will report on version 2 of a draft report released Fall 2019, and the activities to-date, including a summary of data science curricular efforts, as well as the current articulation of computing competencies. This session should be of interest to all conference attendees, but especially faculty developing bachelors-level curricula in Data Science.

The ACM Data Science Taskforce was established by the ACM Education Council and tasked with articulating the role of computing discipline-specific contributions to this emerging field. This special session seeks to provide an update of the work of the ACM Data Science Taskforce as well as to engage the SIGCSE community in this effort. Members of the taskforce will report on version 2 of a draft report released Fall 2019, and the activities to-date, including a summary of data science curricular efforts to date, as well as the current articulation of computing competencies. This session should be of interest to all SIGCSE attendees, but especially faculty developing college-level curricula in Data Science.

The low performance and drop-outs in Computer Science classes are frequently attributed to lack of student engagement and motivation. Meanwhile, gamification increasingly attracts the interest of educators due to its potential to foster motivation and behavioral changes in learning contexts. This workshop introduces participants to the concept of gamification and the use of OneUp Learning, a platform aimed at gamifying academic courses. OneUp is aimed at encouraging students' out-of-class practicing and increasing their overall engagement in the course through employing game design elements. The platform is course-independent and highly configurable, allowing the instructor to turn on and off a number of gamification features, such as avatars, points (challenge and skill points), leaderboards, skill boards, a progress bar, content unlocking, goal-setting, badges, virtual currency, duels, chat, etc. For using OneUp, an instructor has to provide practice exercises and to specify the gamification elements to be used. Apart from the standard question types, OneUp supports Parson's problems and dynamic problems (e.g. programming problems). The workshop proceeds in two sessions. In the first session we introduce the OneUp platform and present our experience of gamifying a Data Structures course. In the second, workshop attendees engage in hands-on experience: we show them how to use OneUp in their classes. In particular, we assist them in creating problems and challenges, configuring desired gamification features, defining their own badges and rules for earning and spending virtual currency, and monitoring the engagement and progress of their students. Laptops required.

Gamification in education still lacks systematic studies assessing its impact on learning. This poster will present the design of our empirical studies on the effect of various combination of game elements on student motivation and engagement in CS courses.

The ACM Data Science Task Force was established by the ACM Education Council and tasked with articulating the role of computing discipline-specific contributions to this emerging field. This special session seeks to introduce the work of the ACM Data Science Task Force as well as to engage the SIGCSE community in this effort. Members of the task force will introduce key components of a draft report, including a summary of data science curricular efforts to date, results of ACM academic and industry surveys on data science, as well as the initial articulation of computing competencies for undergraduate programs in data science. This session should be of interest to all SIGCSE attendees, but especially faculty developing college-level curricula in Data Science.

Having to compete harder than ever for students' attention against cool social media sites, mobile apps, video games, messaging, etc., instructors are struggling to find new ways to motivate and engage learners. Gamification offers a promising framework for educational interventions that can increase students' motivation and engagement. This BOF will bring together instructors who have already explored the use of various game driven strategies and elements to increase the motivation of their students and also those who are looking for promising interventions to do that. The facilitators conducted a similar BOF at SIGCSE 2018, which was well attended, well received and sparked an interesting and lively discussion. This BOF will continue the conversation on what might be useful ways of incorporating game elements in Computer Science courses, what tools might be needed to support such efforts, how can the student experience of gamified learning be personalized, etc. Two NSF sponsored projects related to the use of gamification in STEM courses will seed the discussion. We hope to collectively contribute to the ongoing important discussion on successful strategies for applying of gamification in Computer Science education.

Two faculty teams worked to develop significant content that could be presented in a variety of contexts to students with interests in many areas. This poster reports on the opportunities and the challenges encountered.

Participants in this Birds-of-Feather session will share thoughts and experiences in offering an introductory course in this exploding field. It will be the third consecutive year that these facilitators will conduct a SIGCSE session on a first course in Data Science. The interest in the field has increased greatly over the years, and attendees of varying backgrounds, points of view and experience are welcome. Whether the course will serve as an outreach vehicle to students of all majors, including non-technical ones, or as a first course in a formal program of some sort, we will be exchanging points of view regarding both topic coverage and pedagogical approaches. Regarding topics, we'll raise questions on the relative emphases of statistics, programming (should R be the vehicle? how about Python? other languages?), machine learning (which algorithms?), other tools, and appropriate data sets. Participants who have taught such a course will be invited to describe some of their approaches, especially if they've used such active learning methods as flipped classrooms. The facilitators, PI's on an NSF IUSE grant now winding down, bring experience from two institutions and three departments, including one interdisciplinary course. They hope to expand the community begun through the grant and these sessions, hosted at http://computingportal.org/DataScienceCommunity.

The low performance and drop-outs in Computer Science classes are frequently attributed to lack of engagement and motivation. Meanwhile, gamification - the application of game design principles and game mechanics to a non-game context -- increasingly attracts the interest of educators due to its potential to foster motivation and behavioral changes in learning contexts. Course gamification is about using game elements, such as instant feedback, freedom to fail, freedom of choice, achievements, leveling, progress mechanics, badges, and leaderboards, as interventions in the learning process. This BOF will provide a platform for a discussion of when and how course gamification strategies can be beneficial for improving student motivation, engagement and achievements in Computer Science classes. Questions to be discussed include: What game elements could be useful in gamifying a computer science course? How can an instructor incorporate game elements in the design of their courses? What support the instructor may need for gamifying their courses? Could some game elements have potential drawbacks on student motivation and performance? The discussion leaders and attendees with experience in applying gamification in their courses will share examples of successes or failures, challenges, problems, tips, and techniques for gamifying learning with each other and those new to the use of gamification. Two NSF sponsored projects related to the use of gamification in STEM courses will seed the discussion. As an outcome of the discussion, we hope to collectively identify some lessons learned and challenges to be overcome for a successful application of gamification in Computer Science education.

Data Science, often described at the intersection of computer science, statistical thinking and analysis, and subject matter expertise, has seen an exponential growth in the past few years. Courses (and entire programs) have been appearing at such a fast rate at most institutions of higher education, as well as some high schools, that comparisons between curricular and delivery models and rigorous discipline-based education research are often overlooked in order to gain competitive advantages. This study attempts to rectify that absence by evaluating, comparing, and discussing four different courses offered at two different institutions of higher education. Funded by NSF via a collaborative grant (DUE-1432438), faculty from Computer Science and Statistics departments collaborated on the development and evaluation of introductory courses in Data Science for all students, using a discipline-based education research approach. Data on students were gathered including demographics, curriculum, statistical knowledge, and attitudes towards Data Science. Post-course growth was measured, when available, and compared through formal statistical inference. End-of-course evaluations, with supplemental questions about student learning, were reviewed and will be summarized. Finally, reflections on successes, challenges, and lessons learned will be shared.

In this poster the authors report on experiences in teaching an introductory course in Data Science at two different institutions. Their approaches were informed by the aims of their NSF-funded project: to provide insight on learning goals, central data science topics, content modules, and a framework for implementing a flipped classroom approach to introduce data science to students with various technical backgrounds. The authors, investigators on the grant mentioned above, are a collaborative team of computer scientists and a statistician working to create flipped material for an introductory data science class. After ITiCSE the materials described in the poster will continue to be available in Ensemble, at http://computingportal.org/datascienceflipped

Recognizing that the changing nature of science and its reliance on massive amounts of data has led to the integral use of machine learning approaches in just about every discipline, we present the results of a multi-year research effort entitled "Broader and Earlier Access to Machine Learning." For this project, we explored teaching strategies for introducing machine learning topics to non-technical students in discipline-relevant ways, culminating in a large collection of ready-to-use learning modules suitable for use in a wide variety of academic fields. We present a roadmap to our online repository of module materials, a detailed walk-thru of the contents of an example module, ideas and approaches for incorporating modules into a class or assisting non-technical colleagues in doing the same, and a summary of results of using these modules in course settings.

The use and analysis of large quantities of data have become ubiquitous in nearly every discipline. We began a discussion of the role of data science across disciplines, and the role of computing in data science programs, at SIGCSE 16. The session was well attended and the discussion was valuable. Since then, more work has been done and more people are engaged. This BOF will continue the discussion, including welcoming new voices. We will distribute copies of the report of the NSF sponsored workshop on Data Science education and discuss a new initiative to develop curriculum guidelines for data science programs. This initiative will be in its earliest stages by the time SIGCSE meets, so it will be an excellent opportunity to gather impressions about what are critical considerations for any such curriculum effort. We developed a mailing list from the SIGCSE 16 attendees and will use that list to promote the BOF. The BOF will engage SIGCSE participants who have views on the content and role of courses and programs in data science. In addition to the workshop report, we will describe results from an NSF IUSE grant to develop modules for use in many types of courses. These expect to make access to fundamentals elements of data science available as widely as possible. With these as a starting point, participants in the Birds of a Feather session will explore the emerging field of data science and its relationship to computer science education. Discussions will be hosted at http://computingportal.org/datascienceflipped

This poster presents the results of an ongoing project that has developed learning modules to provide access to the tools and techniques associated with machine learning to a broad category of undergraduate students. The changing nature of science and its reliance on massive data sets has led to the integral use of machine learning approaches in just about every discipline. Recognizing this shift, flexible teaching materials have been developed to provide educators and students in a wide variety of academic fields with relevant machine learning topics and discipline-ready activities. Goals, module design, example material, dissemination plans and evidence of student learning are presented.

In this poster the authors report the approaches for presenting Data Science topics in Flipped Classroom mode, incorporating topics in Data Science into existing courses as well as in stand-alone courses. It provides an insight on listing of learning goals, central data science topics, content modules, and a framework for implementing a flipped classroom approach to introduce data science to students with limited technical backgrounds. The presenters are NSF-funded investigators on a collaborative team of computer scientists and statistician to create flipped material for an introductory data science class.

Data Science programs are emerging in many areas and are related to many disciplines. This includes sciences, social sciences, business, journalism, history, and any other area dealing with massive amounts of data. Some institutions are establishing majors or minors in data science while others need to incorporate some level of introduction to relevant topics within the context of other coursework. The BOF will engage SIGCSE participants who have views on the content and role of courses and programs in data science. Two existing NSF sponsored projects will seed the discussion. One of the projects investigates the use of flipped classroom instruction for course material in data science, with significant attention to what can be done with a minimum of prerequisites. The other project produced a workshop to elicit opinions from a number of perspectives on what are the core elements of data science and how the subject is seen by different disciplines. Results from the workshop will be available at SIGCSE. With these as a starting point, participants in the Birds of a Feather session will explore the emerging field of data science and its relationship to computer science education.

Open educational resources - assignments, labs, course notes, and other types of materials made available for anyone interested in using them - have the potential to have a significant positive impact on courses and students at many institutions. Distribution and use of course materials is also an important factor in encouraging the adoption and use of innovative teaching practices. However, the use of open resources is still somewhat uncommon, with most instructors preferring to use their own materials.

This year marks the 19th ITiCSE conference. This panel will provide conference delegates, both frequent attendees and those new to ITiCSE the opportunity to reflect on the conference's success as one of the premier international com- puter science education conferences and to discuss potential future directions for the conference.

The Ensemble computing portal originated under the NSF NSDL program and enjoys the respect and continued interest of the computing education community. The project has reached a maturity level at which it is time to focus on the long-term viability of the activity. The original proposal included a commitment from the Villanova University library to adopt the system and keep in running in perpetuity. However, merely keeping the system running will not preserve nor extend the true promise of the project. That requires an active, engaged community. The leaders of the Ensemble project invite our partner projects and the SIGCSE community to join us in an initial meeting of an organization devoted to the continued development and support of the Ensemble vision: that of a community of educators sharing their best efforts, showcasing the best resources, and archiving materials that deserve long term preservation.

No abstract available.

This session reports on a workshop convened by the ACM Education Board with funding by the US National Science Foundation and invites discussion from the community on the workshop findings. The topic, curricular directions for cybersecurity, is one that resonates in many departments considering how best to prepare graduates to face the challenges of security issues in employment and future research. The session will include presentation of the workshop context and conclusions, but will be open to participant discussion. This will be the first public presentation of the results of the workshop and the first opportunity for significant response.

We summarize the results of our NSF funded exploration of interdisciplinary computing, including the following points: Interdisciplinary computing spans fields as diverse as visual art, music, the humanities and social sciences, health sciences, pure science, engineering, and mathematics. No field of inquiry in the 21st century extends its knowledge without the influence of computing.[1-4]; A bifurcation is occurring: at some institutions this climate of interdisciplinary work is nurtured, while at others it is thwarted by lack of motivation, resource limitations or simple inaccessibility.; Interdisciplinary computing is inherently collaborative between computing specialists and specialists in other fields. It is not merely pair-wise: computational-X or Y-informatics, but often the collaboration draws from a number of fields.; An important question is what is the breadth and depth of knowledge and skill required to engage in this work. Who needs to know what? What is the language of discourse? How is a methodology established and accepted, and how is subsequent work evaluated?; The mundane concerns of intellectual ownership, boundaries on the discipline (e.g. silos), professional advancement, financial support, and institutional buy-in can diminish the pure intellectual joy that is evident in existing interdisciplinary work.; Impediments are encountered in making the effective collaborations that are essential for the advancement of all the disciplines. The computing disciplines are essential to and also dependent on nearly all other branches of intellectual discovery. [5-6]

No abstract available.

Search engines are mostly targeted toward the generic user but educators have specific information needs with specialized information-seeking behaviors. When designing a course, educators may create a syllabus, lecture slides, and use tools as lecture aides. These resources are scattered across a large number of websites and require time and effort in finding them. To design a useful system for educators we must understand the problems they face when they seek, use, and re-use online resources. With that in mind, the Ensemble team conducted focus groups to identify current practices and problems in locating online resources for educational purposes. The data provides better understanding of the information-seeking process of educators that can lead to better educational resource sites.

As the need for multidisciplinary computing education continues to increase, consideration for distributed expertise will become critical to implementing a successful curriculum. A model of cooperative expertise is presented in which faculty maintain responsibility for their own course, creating and evaluating assignments for their students that support learning in their colleagues' courses as well. We present outcomes of an experiment to implement this model at two geographically separated institutions through three courses (two at one institution, one at the other), by faculty in computer science, media and English. Results reported include faculty analysis of student achievement in each course and student surveys of attitudes toward multidisciplinary collaboration. Overall, it appears that student learning and attitudes are enhanced by the experience.

The ACM Education Board, the Education Activities Board of the IEEE Computer Society, representatives of the Association for Information Systems and the British Computer Society have joined forces to investigate the state of Masters degree programs in computing. This joint effort intends to document the variety and common features of programs throughout the United States and Europe. This poster is a status report on that project and an opportunity for interested individuals to add information about their programs to this work.

Ensemble is a new NSF NSDL Pathways project working to establish a distributed digital library for computing education. This project is funded by the National Science Foundation. The project includes the CSTA portal for teaching materials for teachers in schools.

This poster will describe ongoing work to modify the Computing Ontology to incorporate issues of parallelism and concurrency, motivated by recent developments in computer hardware design.

This project tries to provide a clarified and comprehensive understanding of the computing disciplines that allows shared experiences and expertise within and across the community. This collective sharing enables computing faculty to collaborate with other disciplines that use computing to enhance groups, and to create new cross-disciplinary areas of study and research. This involves the integration of computing with other disciplines like engineering, sciences, business, and arts and explores the challenge by bringing together instructors and researchers across the disciplinary boundaries. Distributed Expertise enhances teaching and learning experiences for students of computing and other disciplines in which computational thinking and computing models contribute to a variety of applications. This project is a collaboration by Villanova University, Virginia Technology University, and The College of New Jersey (TCNJ).

This session proposal is part of the recognition of 40 years of SIGCSE. We will look at the organization itself, how it came to be and where it might be going. It will be an interactive session with the participation of the audience informing the SIGCSE leadership of appropriate directions for the future of this group that has been so important to computing education.

This special session will proved information about the status of work related to Masters programs in Computing. Specifically, the session will describe work completed in the following areas: the categorization of masters programs in computing, the development of curriculum recommendations for masters programs in software engineering, the collaborative work with the Association for Information Systems on the Masters program in Information Systems

Adoption of the Bologna Accord in the European Higher Ed-ucation Area (EHEA) represents a concerted move towards harmonisation of educational outcomes in higher education at the Bachelor, Masters and PhD levels. At a time when European systems are undergoing signif-icant examination and modification, this project addresses the need for greater understanding of the nature of Mas-ters level education in the Informatics disciplines across Eu-rope and the United States. The poster presents the cur-rent findings of the project, and is intended to prompt dis-cussion about the content and expected outcomes of such programmes world-wide.

Now that ITiCSE has reached its teenage years, it's time to take a look at where we've been, where we are, and where we'd like to go. The panelists will offer a historical perspective of the conference, what makes it stand out from other conferences, and give some ideas of how they would like to see ITiCSE mature. Come hear what they have to say, and there will be plenty of time for the audience to offer their own suggestions of where they would like to see ITiCSE go.

No abstract available.

Wikis may be on track to take the academic world by storm. Though researchers have used them as collaborative tools for more than a decade, it is only in the past year or two that they have become widespread in education. Of the articles published by SIGCSE on wikis, nearly two-thirds (30 out of 46) of them gave appeared since the beginning of 2006. References to wikis in the educational database ERIC are approximately doubling each year. What is it about wikis that has suddenly made them so attractive? Among other things, it is the fact that collaboration becomes so easy. Students have the opportunity to revise each other’s work without the need to send documents back and forth. Because an edit history is kept, it is easy to see how much work each student has done—and to verify that it has not been downloaded from a third-party source on the eve of the due date. Wikis have been used for a wide variety of assignments, from discussion boards to writing a textbook from student contributions. This panel will present several collaborativelearning exercises that have been carried out with wikis, and give advice to instructors who want to use wikis in their classes.

No abstract available.

No abstract available.

A syllabus defines the contents of a course, as well as other information such as resources and assignments. In this paper, we report on our work towards creating a syllabus repository of Computer Science courses across universities in the USA. We present some statistics from our initial collection of 8000+ syllabi. We show a syllabus creator that is integrated with Moodle [5] moodle_2006_moodle, an open-source course management system, which allows for the creation of a syllabus for a particular course. Among other information, it includes knowledge units from the Computing Curricula 2001 body of knowledge. The goal of the syllabus repository is to provide added value to the Computer Science Education community, and we present some such offerings. We conclude by presenting our future plans for the syllabus repository. These include using automated techniques to collect and classify syllabi, providing recommendations to instructors when creating a syllabus, and allowing the community to share their syllabi automatically. The syllabus collection will be part of the Computing and Information Technology Interactive Digital Educational Library (CITIDEL), a collection of the National Science Digital Library (NSDL).

Search engines are an integral part of web information gathering and retrieval process, but they are significantly dependent upon the words or word phrases input by the end user. The search engine usually contributes no additional semantic data toward the information acquisition process. This paper presents an intelligent search agent "Web host access tool" (WHAT) based on support vector machines (SVM), which introduces the notion of queries conducted within a specific contextual meaning. Given a context and associated keywords that personalize the search history and preferences of the user, WHAT performs more intelligent resource filtering than conventional search engines, providing more relevant results while filtering the irrelevant references. Search results obtained in the form of text from different search engines are processed by the SVM based word classifier that arrange the results obtained according to user preference obtained from previous search processes. The text materials are processed by Latent Semantic Indexing (LSI) for creating a document matrix that gives the probability of a word occurrence in a specified context. For simplicity, this paper considers 5 different contexts: business, education, entertainment, news and information and tourism. The LSI coefficients were used by SVM to yield confidence levels for each search result and according to that the results were sorted and presented to the end user. As an alternative, least square support vector machines (LS-SVM) are also studied in this paper. The system is updated by the user that provides feedback regarding the search relevance, based on which the LSI coefficients are updated to ensure increased relevance in future searches. Three different types of kernel function were considered in this paper -Linear. Radial basis function (RBF) and polynomial kernel. Results claim that Linear SVM perform better than the others, not only in terms of classification accuracy but also in terms of training speed.

This poster describes the publication of educational resources in ACM's online Journal for Educational Resources in Computing (JERIC) and the US National Science Foundation's National STEM Digital Library (NSDL).

The poster session will describe the development of an ontology of computing and suggest questions to be answered by use of the ontology.

No abstract available.

This poster describes the publication of educational resources in ACM's online Journal for Educational Resources in Computing (JERIC) and the US National Science Foundation's National STEM Digital Library (NSDL).

This demonstration will illustrate the use of existing and proposed tools in CITIDEL for finding existing resources to integrate into a course and for developing well structured descriptions of class and laboratory activities for sharing with the computing community.

This poster demonstrates connecting objectives, outcomes and CITIDEL resources to improve course preparation. The example used is mobile computing.

This demonstration allows conference attendees to gain experience in using the facilities of the NSF National Science Technology Engineering and Mathematics Education Digital Library (NSDL) to prepare and present College or university level classes.

We present an overview of the National Science Digital Library, NSDL, and focus on one of the partner projects it supports. The computing and Information Technology Interactive Digital Educational Library (CITIDEL) harvests metadata from repositories and collections, and provides tools to customize learning with these resources. CITIDEL's integrated tools guide the user to create instructional environments that enhance the learning experience. Additional tools available from NSDL are included in this presentation to complete the picture. Information on integrating new collections and materials into CITIDEL is included.

The NSDL consists of collections of materials accessible online, as well as many tools and services intended to enhance learning. Tools and services will support students and as well as faculty. This session will provide a status report on the state of the NSDL, its content, tools, and services. The session includes specific presentations of several services included in the NSDL. Session attendees discuss current and proposed initiatives, and offer suggestions about needs of highest priority.

Active learning promises students will really own what they have learned because they have done something rather than only read or listen. The following classroom exercise has been used at both the undergraduate and graduate level Computer Networks courses. There has been no formal study of its effectiveness, but an informal result is telling: Two routing algorithms presented in class. On an exam, students are asked to choose one of them and describe it. In several years of using this classroom exercise, nearly all the students chose the method we did with this exercise and they all explained the algorithm correctly.

We present a "state of the course" report on a core computer science topic: Computer Organization & Architecture. Our report is based on a survey of over 80 faculty, at colleges and universities around the world, who teach this topic. Based on the responses in the survey, we present our conclusions on the confidence levels of faculty in teaching various core components of the topic. We will present our results in the context of the identified core body of knowledge as defined in the Curriculum 2001. These conclusions can be of help to experts who are willing to provide training and/or pedagogical materials in order to assist those with low confidence levels.

The National Science Foundation has recently funded a variety of projects through its NSDL digital library initiative. One such project is the Computing and Information Technology Interactive Digital Educational Library project, also known as CITIDEL, which is part of NSDL’s Collection Track activities. CITIDEL is a consortium of five universities that includes Virginia Tech (the lead institution), Hofstra University, Penn State University, The College of New Jersey, and Villanova University. CITIDEL will establish, operate, and maintain part of the digital library that includes information systems, computer science, information science, information technology, software engineering, computer engineering, and other computing-related fields. It will manage a front-end portal to all educational activities related to computing and information technology, harvest metadata from applicable repositories, provide an integrated access and linking process to related collections, and encourage and actively support content developers to make new resources available to others. CITIDEL will also address the need to develop and disseminate quality courseware by providing a mechanism for the preservation of educational prototypes. Additionally, it will provide a single location where searches conducted by educators and students can link them educational websites.

No abstract available.

No abstract available.

No abstract available.

An overview is presented of the statistical sampling of measurements from a computer network, a necessary task in all five facilities of the proposed ISO network management architecture. Network measurement, viewed from the standpoint of real-time status reporting, is performed either to approximate the condition of a network parameter over a given interval or to detect a significant change in system behavior over consecutive intervals. Appropriate statistical tools for sampling and analyzing traffic in real time are presented.>

article Free Access Share on Computer science: a core discipline of liberal arts and sciences Authors: Robert E. Beck Villanova Univ., Villanova, PA Villanova Univ., Villanova, PAView Profile , Lillian N. Cassel Villanova Univ., Villanova, PA Villanova Univ., Villanova, PAView Profile , Richard H. Austing Univ. of Maryland, College Park Univ. of Maryland, College ParkView Profile Authors Info & Claims ACM SIGCSE BulletinVolume 21Issue 1Feb. 1989 pp 56–60https://doi.org/10.1145/65294.65300Online:01 February 1989Publication History 6citation294DownloadsMetricsTotal Citations6Total Downloads294Last 12 Months13Last 6 weeks6 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

Key areas of agreement and disagreement in the network management community are presented using the evolving open systems interconnection network management architecture as an informal guide. A key observation is that the open-networking community has apparently settled on a management model that places management information base (MIB) on each network node and manages these MIBs remotely with application level protocols. Various network systems based on this model are examined, along with some systems that use alternative management architectures.>

Courses in Computer Science and Information Systems are constantly in need of revision to remain relevant. Often entire new courses become needed as an area develops. These can be the most challenging alterations to a curriculum. In some cases, while provisions are being made to introduce a new course, key components of the course can be introduced as modules of already existing courses. An example is considered in which seemingly dissimilar courses meet, and new material is given a forum in a standard curriculum. An extension to a standard file processing course to include the files-affecting impact of computer networks is proposed.

No abstract available.

The Curriculum Committee of the Education Board of ACM has established as an ongoing committee a Small College Group. This committee will make a presentation of its report at this symposium and will provide an opportunity for attendees to comment. Various aspects of computing programs will be considered, including obtaining qualified faculty, providing appropriate equipment and the selection of a suitable and manageable set of courses.

The course ca8 "Organization of Programming Languages" of Curriculum '78 is presented in the context of a program for Business Information Systems at a small business college.The applicability of this course to the Information Systems curriculum is considered.It is asserted that the successful inclusion of this course suggests the desirability of including the other core computer science material, as defined in Curriculum '78, in a program for Information Systems.

Panelists will report on the work of the ACM Education Board's ad hoc committee to revise and update the Small College curriculum recommendations published by ACM in 1973. The revised report's completion is expected by the end of 1983.