Multi-disciplinary Pathways to Computing:A Scalable and Col aborative Approach to Capitalize on the Demand for Computer Science Education

The number of students demanding computer science(CS)education is rapidly rising,and while faculty sizes are also growing,the traditional pipeline consisting of a CS major,a CS master’s,and then a move to industry or a Ph.D.program is simply not scalable.To address this problem,the Department of Computing at the University of Illinois has introduced a multidisciplinary approach to computing,which is a scalable and collaborative approach to capitalize on the tremendous demand for computer science education.The key component of the approach is the blended major,also referred to as“CS+X”,where CS denotes computer science and X denotes a non-computing field.These CS+X blended degrees enable win-win partnerships among multiple subject areas,distributing the educational responsibilities while growing the entire university.To meet the demand from non-CS majors,another pathway that is offered is a graduate certificate program in addition to the traditional minor program.To accommodate the large number of students,scalable teaching tools,such as automatic graders,have also been developed.

Panel Discussion on“Development Trends of Computer Science in the New Era”

At the panel session of the 3rd Global Forum on the Development of Computer Science,attendees had an opportunity to deliberate recent issues affecting computer science departments as a result of the recent growth in the field.6 heads of university computer science departments participated in the discussions,including the moderator,Professor Andrew Yao.The first issue was how universities are managing the growing number of applicants in addition to swelling class sizes.Several approaches were suggested,including increasing faculty hiring,implementing scalable teaching tools,and working closer with other departments through degree programs that integrate computer science with other fields.The second issue was about the position and role of computer science within broader science.Participants generally agreed that all fields are increasingly relying on computer science techniques,and that effectively disseminating these techniques to others is a key to unlocking broader scientific progress.

A Review of the Status and Development Strategies of Computer Science and Technology Under the Background of Big Data

This article discusses the current status and development strategies of computer science and technology in the context of big data.Firstly,it explains the relationship between big data and computer science and technology,focusing on analyzing the current application status of computer science and technology in big data,including data storage,data processing,and data analysis.Then,it proposes development strategies for big data processing.Computer science and technology play a vital role in big data processing by providing strong technical support.

Reform and Practice of the Course“Introduction to Computer Science”in Universities Based on the Cultivation of Computational Thinking and Systematic Abilities

Introduction to Computer Science,as one of the fundamental courses in computer-related majors,plays an important role in the cultivation of computer professionals.However,traditional teaching models and content can no longer fully meet the needs of modern information technology development.In response to these issues,this article introduces the concept of computational creative thinking,optimizes course content,adopts exploratory teaching methods,and innovates course assessment methods,aiming to comprehensively enhance students’computational thinking and innovative abilities.By continuously improving and promoting this teaching model,it will undoubtedly promote computer education in universities to a new level.

Differences between journal and conference in computer science:a bibliometric view based on Bayesian network

Purpose:This paper aims to investigate the differences between conference papers and journal papers in the field of computer science based on Bayesian network.Design/methodology/approach:This paper investigated the differences between conference papers and journal papers in the field of computer science based on Bayesian network,a knowledge-representative framework that can model relationships among all variables in the network.We defined the variables required for Bayesian networks modeling,calculated the values of each variable based Aminer dataset(a literature data set in the field of computer science),learned the Bayesian network and derived some findings based on network inference.Findings:The study found that conferences are more attractive to senior scholars,the academic impact of conference papers is slightly higher than journal papers,and it is uncertain whether conference papers are more innovative than journal papers.Research limitations:The study was limited to the field of computer science and employed Aminer dataset as the sample.Further studies involving more diverse datasets and different fields could provide a more complete picture of the matter.Practical implications:By demonstrating that Bayesian networks can effectively analyze issues in Scientometrics,the study offers valuable insights that may enhance researchers’understanding of the differences between journal and conference in computer science.Originality/value:Academic conferences play a crucial role in facilitating scholarly exchange and knowledge dissemination within the field of computer science.Several studies have been conducted to examine the distinctions between conference papers and journal papers in terms of various factors,such as authors,citations,h-index and others.Those studies were carried out from different(independent)perspectives,lacking a systematic examination of the connections and interactions between multiple perspectives.This paper supplements this deficiency based on Bayesian network modeling.

Computer Science at University 2.0: What the Future Holds and How We Can Shape It

Alongside the development of computer science,many fields like engineering,finance and the natural sciences increasingly leverage computer science techniques to facilitate their own evolution.As a result,students now need to have a good grasp of computer science skills in order to keep pace with the new forms of working in these other fields.Therefore,higher education need to change to support this transformation.Computer Science 2.0 refers to this new way of educating that facilitates these interdisciplinary connections.This creates exciting opportunities for students and staff to interact across disciplines in teaching,research,and transfer to create the so-called University 2.0.

Panel Discussion on“ The Role of Computer Science in University Development Strategy”

At the end of the keynotes during the second Global Forum of Development of Computer Science,a panel discussion was held to encourage further discussion on ways for universities to adapt to the rapidly changing computer science field.Five deans of top computer science departments participated,including the moderator.The discussions were guided along three topics,namely the role of computer science departments in universities today,the nature of computer science as a fundamental discipline or an applied one,and computer science education.Out of these topics,the panelists mainly focused on the interdisciplinary nature of computer science in teaching,research,and industry.The panelists agreed about ways to prepare for the interdisciplinary future,for example by establishing new research centers,introducing projectbased curricula,and collaborating with industry while keeping the campus vibrant.They also pointed out that universities may be under equipped for preparing future professionals to keep up with rapid new advances,especially in machine learning and artificial intelligence.

Challenges and Opportunities in Computer Science Executive Education

Carrying out executive education in computer science(CS)brings both opportunities and challenges.The major advantages are that it helps research programs with funding,data and reallife cases,and both professors and students can benefit from it by having greater engagement with industry.However,the main challenge is that most CS professors and doctoral students are currently not interested in executive education because they are more interested in their academic work.This paper first introduces the background of the Singapore government’s initiative for lifelong education for public,then presents the response from the National University of Singapore(NUS)that ultimately led to several executive education programs.Particular attention is given to the experience of the NUS School of Computing in carrying out computer science executive education.

CAIE中Computer Science考试对信息技术纳入高考的启示

介绍和分析CAIE英式课程考试中Computer Science学科的课程内容、考试制度、试题模式,借鉴其成功经验与考试制度,以期借他山之石对我国信息技术课程纳入高考选考的相关研究提供助力。

Recent Development of Computer Science Education in USA

Computer science(CS)is a discipline to study the scientific and practical approach to computation and its applications.As we enter into the Internet era,computers and the Internet have become intimate parts of our daily life.Due to its rapid development and wide applications recently,more CS graduates are needed in industries around the world.In USA,this situation is even more severe due to the rapid expansions of several big IT related companies such as Microsoft,Google,Facebook,Amazon,IBM etc.Hence,how to effectively train a large number of

Recent Development of Computer Science Education in Japan

In this special section,two introductive papers from Waseda University and the University of Aizu are selected for the introduction of recent development of computer science education in Japan.Waseda University is one of top and comprehensive private universities in Japan.The University of Aizu is a public university and the first university dedicated to computer science engineering in Japan.The University of Aizu advocates'advancement of knowledge for humanity'and carries out significant research in computer science.

Overview of the Third Global Forum

Computer science continues to grow at a rapid pace,raising the issue of how universities can best adapt to this trend.At the third Global Forum on the Development of Computer Science(GFDCS),five heads of departments of computer science from Asia,Europe,and North America came together to exchange ideas under the theme Challenges and Opportunities of Computer Science in the New Era.Through the discussions,a number of new challenges were explored,including how to meet the growing demand for computer science education,how to manage increased teaching loads,how to foster collaboration between computer science and other disciplines,how to raise ethical awareness,and how to support new“transdisciplinary”modes of education and research.At the same time,there was a consensus on the need to strengthen the role of computer science in other departments,the importance of industrial collaboration,and the need for more scalable approaches to teaching.The evolving role of computer science within the context of broader science was also discussed.

Teaching Mode of Basic Computer Courses Using Theories and Methods of Computational Thinking

In view of the university computer culture foundation of college course,it is proposed that learners use efficient thinking methods to think.They must get rid of the prejudice of traditional teaching"narrow tool theory",based on computing thinking and university computer culture foundation.This paper proposed how to guide learners to use computing thinking to solve related problems in classroom teaching,introduced the application of computing thinking in computer classroom teaching,and proposed a curriculum with"computing thinking"as the core.The teaching method provides a new model for the university computer basic education with the goal of improving students'thinking ability.

How Does a University’s Computer Science Strength and Location Impact Its Total ChatGPT News?

As AI, starting with ChatGPT has become increasingly prevalent in academic discussions, school especially, colleges have become hotspots of AI activities and debates. Colleges have the responsibility of addressing not only the academic, integrity-based concerns of students using AI for their homework, but also as the forebearers of new learning and technology, how AI will change their students’ futures and careers. In this study, we will explore the different factors, such as Computer Science Score and location, that might affect how much a college discusses AI, ChatGPT specifically. To demonstrate the validity of our research, we used self-collected data with our methods detailed below.

A Defect Detection Method for the Primary Stage of Software Development

In the early stage of software development,a software requirements specification(SRS)is essential,and whether the requirements are clear and explicit is the key.However,due to various reasons,there may be a large number of misunderstandings.To generate high-quality software requirements specifications,numerous researchers have developed a variety of ways to improve the quality of SRS.In this paper,we propose a questions extraction method based on SRS elements decomposition,which evaluates the quality of SRS in the form of numerical indicators.The proposed method not only evaluates the quality of SRSs but also helps in the detection of defects,especially the description problem and omission defects in SRSs.To verify the effectiveness of the proposed method,we conducted a controlled experiment to compare the ability of checklist-based review(CBR)and the proposed method in the SRS review.The CBR is a classicmethod of reviewing SRS defects.After a lot of practice and improvement for a long time,CBR has excellent review ability in improving the quality of software requirements specifications.The experimental results with 40 graduate studentsmajoring in software engineering confirmed the effectiveness and advantages of the proposed method.However,the shortcomings and deficiencies of the proposed method are also observed through the experiment.Furthermore,the proposed method has been tried out by engineers with practical work experience in software development industry and received good feedback.

DEBRA: On the Unsupervised Learning of Concept Hierarchies from (Literary) Text

With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such distinguishing itself from the majority of research literature on the topic which is primarily focused on building ontologies from a vast array of different types of data sources, both structured and unstructured, to support various forms of AI, in particular, the Semantic Web as envisioned by Tim Berners-Lee. We first elaborate on mutually informing disciplines of philosophy and computer science, or more specifically the relationship between metaphysics, epistemology, ontology, computing and AI, followed by a technically in-depth discussion of DEBRA, our dependency tree based concept hierarchy constructor, which as its name alludes to, constructs a conceptual map in the form of a directed graph which illustrates the concepts, their respective relations, and the implied ontological structure of the concepts as encoded in the text, decoded with standard Python NLP libraries such as spaCy and NLTK. With this work we hope to both augment the Knowledge Representation literature with opportunities for intellectual advancement in AI with more intuitive, less analytical, and well-known forms of knowledge representation from the cognitive science community, as well as open up new areas of research between Computer Science and the Humanities with respect to the application of the latest in NLP tools and techniques upon literature of cultural significance, shedding light on existing methods of computation with respect to documents in semantic space that effectively allows for, at the very least, the comparison and evolution of texts through time, using vector space math.

Large-scale data archiving: At the interface of archive science and computer science

Both computer science and archival science are concerned with archiving large-scale data,but they have different focuses.Large-scale data archiving in computer science focuses on technical aspects that can reduce the cost of data storage and improve the reliability and efficiency of Big Data management.Its weaknesses lie in inadequate and non-standardized management.Archiving in archival science focuses on the management aspects and neglects the necessary technical considerations,resulting in high storage and retention costs and poor ability to manage Big Data.Therefore,the integration of large-scale data archiving and archival theory can balance the existing research limitations of the two fields and propose two research topics for related research-archival management of Big Data and large-scale management of archived Big Data.

The 3x + 1 Conjecture, a Direct Path

The 3x + 1 problem, is a math problem that has baffled mathematicians for over 50 years. It’s easy to explain: take any positive number, if it’s even, divide it by 2;if it’s odd, multiply it by 3 and add 1. Repeat this process with the resulting number, and the conjecture says that you will eventually reach 1. Despite testing all starting values up to an enormous number, no one has proved the conjecture is true for all possible starting values. The problem’s importance lies in its simplicity and difficulty, inspiring new ideas in mathematics and advancing fields like number theory, dynamical systems, and computer science. Proving or disproving the conjecture would revolutionize our understanding of math. The presence of infinite sequences is a matter of question. To investigate and solve this conjecture, we are utilizing a novel approach involving the fields of number theory and computer science.

Building the MIT Schwarzman College of Computing

Broad multidisciplinary computing is transforming our modern life in many aspects,and computer science itself is also broadening.In response to these trends,the Massachusetts Institute of Technology(MIT)recently built a new college,the Schwarzman College of Computing.The missions of the College are to support rapid growth of computing fields,facilitate computing collaborations across departments and disciplines,and to focus on social,ethical,and policy issues in computing.This paper begins by introducing the history and design of the Schwarzman College.Then,it discusses the new opportunities that the College of computing has created at MIT,specifically the common ground for computing education and the social and ethical responsibilities of computing programs.

Translating Linear Temporal Logic Formula s into Automata

To combat the well-known state-space explosion problem in Prop ositional Linear T emp o- ral Logic （PLTL） model checking, a novel algo- rithm capable of translating PLTL formulas into Nondeterministic Automata （NA） in an efficient way is proposed. The algorithm firstly transforms PLTL formulas into their non-free forms, then it further translates the non-free formulas into their Normal Forms （NFs）, next constructs Normal Form Graphs （NFGs） for NF formulas, and it fi- nally transforms NFGs into the NA which ac- cepts both finite words and int-mite words. The experimental data show that the new algorithm re- duces the average number of nodes of target NA for a benchmark formula set and selected formulas in the literature, respectively. These results indi- cate that the PLTL model checking technique em- ploying the new algorithm generates a smaller state space in verification of concurrent systems.