Molecular computation at equilibrium via programmable entropy

In the universities where undergraduate Computer Engineering (CE) and Computer Science (CS) programs are offered, people often wrongly argue that the CE program should be offered under College of Engineering instead of under the college where CS program is offered, this is mostly because they think CE program has “Engineering” word in it. This school of thought does not realize that by this, it will take CE program apart from CS program, which will break the natural alliance of both of these programs. In this paper, this natural alliance of CE and CS programs is discussed, which gives strong argument that both CE and CS programs should be put together under the same college. To further support these arguments of putting CE and CS programs together, the best practices adopted in this regards by the top 10 universities in KSA, USA, UK and other European Universities are studied and results are provided to prove that CE and CS programs should be put together under the same college. Since, this is the current debate at AlBaha University in Saudi Arabia (KSA), therefore the case of AlBaha University is presented to settle the argument.

Mirroring the trend of the growth of Computer Science (CS) programs nation and worldwide, the CS program in the College of Engineering at Tennessee Technological University has experienced similar growth in the number of students enrolling in its B.S., M.S., and Ph.D. programs. This growth of enrollment in CS has been accompanied by a growth in another student population at the university that is often overlooked: Interdisciplinary Studies - Interest in Computer Science (ICSC) majors. This population represents students who have qualified for admission at Tennessee Tech, but have not qualified for entry into the CS program. Indeed, just as the freshman class of CS has grown 44%, the ICSC program has grown 63%. To address the problem of retention and migration into CS from ICSC, we have developed the pre-CS Redshirt program, which is aimed at providing increased advising, peer mentoring, tutoring, and connections to faculty. Launched in Fall 2020, the challenges facing these students have been compounded by COVID-19. In order to study initial effectiveness, we measured Fall-Spring retention, comparative GPAs for students in the CS and ICSC programs, and conducted a survey of students to measure students' sense of belongingness with the measured population including students of all levels currently enrolled in the CS program as well as the pre-CS Redshirt students.

How can we retain computer information systems (CIS) students? A decline in enrollment similar to that which occurred in the 80’s (Mawhinney, Callaghan, & Cale, 1989) is the motivating factor for this question. A google™ search on declining enrollments in information systems brings up reports supporting this trend. DePaul University, for example, had increased undergraduate enrollments “in all colleges but the School for New Learning and the School of Computer Science, Telecommunications and Information Systems” (DePaul University, 2003). A report from the California Community College system listed the top 15 curricular areas of declining FTE’s (Perry, 2003); Computer and Information Science and Computer programming made the list. Our own Computer Information Systems (CIS) and Computer Science programs have fewer students enrolled.

A national web-based survey was administered to 700 undergraduate computer science (CS) programs in the United States as part of a stratified random sample of 797 undergraduate CS programs. The 251 program responses (36% response rate) regarding social and professional issues are presented. This article describes the demographics of the respondents, presents results concerning whether programs teach social and professional issues, how social and professional issues are integrated, perceptions of CS faculty regarding the importance of social and professional issues, pedagogies used to teach social and professional issues, and what specific social and professional topics have been included in the CS curriculum. Additionally, we (a) provide suggestions for CS programs regarding the integration of social and professional issues into the CS curriculum, (b) suggest ways to encourage more social and professional coverage in CS programs, pedagogy, and (c) recommend what social and professional topics should be included in future CS curriculum reports.

The need for graduates from master's programs in computer science and related areas is well recognized [19, 20]. Indeed, some companies have a policy of extensively utilizing master's programs at universities for the continuing education of their employees. The Graduate Study Program of Bell Laboratories is well known. At Honeywell Information Systems it has been found that support of continuing studies at the master's level helps in hiring and retaining personnel, and is beneficial to the dissemination of new technology through the organization [29]. It has been demonstrated that programmers acquire new knowledge primarily from other programmers [17]; periodic influx into an organization of graduates of programs of advanced study is therefore essential if the organization is to retain technical soundness.Universities have responded to this need, but in a rather haphazard manner, with the result that we have today a variety of programs, some of which have very little to do with computer science. Some of the programs are no more than, to use Smoliar's [41] words, “undergraduate programs for grown-ups.” Others are viewed as a first stage in the preparation for research careers of narrow specialization. Late in 1972 Terry Walker [45] conducted a poll of master's degree granting departments. The four primary objectives of a master's program given by the 93 respondents were: prepare a person for a job designing computer software systems, prepare a person for a job as a systems analyst, prepare a person to pursue a doctoral degree in computer science, prepare a person for a job as a scientific programmer. Today one would add a fifth objective: prepare a person for teaching computer science at the junior college level. There is clearly a need to reconcile these different objectives with a unified view of computer science.

The need for graduates from master's programs in computer science and related areas is well recognized [19, 20]. Indeed, some companies have a policy of extensively utilizing master's programs at universities for the continuing education of their employees. The Graduate Study Program of Bell Laboratories is well known. At Honeywell Information Systems it has been found that support of continuing studies at the master's level helps in hiring and retaining personnel, and is beneficial to the dissemination of new technology through the organization [29]. It has been demonstrated that programmers acquire new knowledge primarily from other programmers [17]; periodic influx into an organization of graduates of programs of advanced study is therefore essential if the organization is to retain technical soundness. Universities have responded to this need, but in a rather haphazard manner, with the result that we have today a variety of programs, some of which have very little to do with computer science. Some of the programs are no more than, to use Smoliar's [41] words, “undergraduate programs for grown-ups.” Others are viewed as a first stage in the preparation for research careers of narrow specialization. Late in 1972 Terry Walker [45] conducted a poll of master's degree granting departments. The four primary objectives of a master's program given by the 93 respondents were: prepare a person for a job designing computer software systems, prepare a person for a job as a systems analyst, prepare a person to pursue a doctoral degree in computer science, prepare a person for a job as a scientific programmer. Today one would add a fifth objective: prepare a person for teaching computer science at the junior college level. There is clearly a need to reconcile these different objectives with a unified view of computer science.

Background The last 20 years or so has seen a dramatic growth in the demand for professionals trained in information and communication technologies. This growth was partly driven by tremendous technological advances, such as the emergence of computer networking, including wireless networking, graphical user interfaces, and the Internet, the World-Wide Web, and their applications. But the growth in demand was also driven by a much greater realization on the part of many organizations and individuals of the importance of information and communication technologies for their well being, and the more widespread use of these technologies by individuals whose primary area of expertise was not in information technology (Dalhom & Mathiassen, 1977; Denning, 2001a; Denning 2001b). While programs in traditional computing disciplines such as computer engineering and computer science responded to these new trends, albeit often slowly, employers started to demand skills that graduates typically did not get out of a traditional computer science or computer engineering program. For example, many traditional computer science programs did not equip their graduates with the practical network or system administration skills that organizations needed to expand and maintain their IT infrastructures, or the web development skills required to take advantage of the many opportunities opened up by the Internet. Moreover, because of the more theoretical emphasis of computer science programs, graduates often did not acquire a sufficient understanding of organizational processes to be able to support IT applications from a user or organizational perspective (Denning, 2004). While programs in Information Systems are able to offer material to their students that allow them to develop a better understanding of organizations and the way in which IT applications can support them, they often do so at the expense of a sufficiently thorough coverage of the technology. This has been exacerbated by the fact that a good number of programs in Information Systems were offered in business schools and were limited in the number of courses they could offer in IT because of accreditation standards for business schools in place at the time. It was in this environment that a number of universities started to offer undergraduate programs in IT. While there was, and still is, far less homogeneity among undergraduate programs in IT than there is among programs in computer science or information systems, all IT programs show a family resemblance to each other. Most cover areas such as networking, web development and system administration in some detail, while very few pay particular attention to the theoretical foundations in complexity theory that is so prevalent in computer science programs. Until fairly recently, most IT programs arose in isolation from each other, often evolving out of existing programs in computer science, computer engineering or computer engineering technology, or information systems (Lunt et al., 2003a; Reichgelt et al., 2004). However, there was also a growing realization on the part of those programs that were aware of each other's existence that a forum was needed in which they could discuss the various features of their programs, and improve their programs based on the experiences of IT programs at other institutions (Lunt et al., 2003b). Thus, in early 2001, a steering committee composed of five universities offering or getting ready to offer IT programs compiled a list of IT programs across the United States with the intention of organizing an invitation-only conference. These efforts came to fruition in December 2001, when representatives from 15 colleges/universities attended the first Conference for IT Curriculum (CITC-1) in Provo, Utah. The primary aims of this conference were to establish a national organization of IT educators and begin to establish academic standards for this rapidly emerging discipline (Lunt et al. …

Recent years have seen much debate about the appropriate content of software engineering (SE) programs and how they relate to computer science (CS) programs, culminating in the distinguishing knowledge areas identified in the ACM/IEEE CS and SE curricula. Given these publications, a reasonable question to ask is: how do current SE programs differ from CS programs and to what extent do the differences reflect the characterizing features given in the ACM/IEEE curricula? We aim to answer these questions for SE programs offered in England. The content of a third of the SE programs in England are analyzed and summarized with respect to the knowledge areas of both the ACM/IEEE CS and SE curricula. The results reveal interesting features; such as intelligent systems is a more distinguishing feature between the CS and SE programs than the expected knowledge areas given in the SE curriculum. The main finding is that there are relatively few differences between existing SE and CS programs offered in England. We conclude with a discussion of the reasons for this situation and its likely implications.

Computer Science Education courses concentrate on the scientific education of computer science, while the Computer Science Program concentrates on computer science. Both of these study programs have a close relationship to complement and improve each other in the domain of science and education in the field of computer science (cross-fertilization principle). Knowledge management nowadays is still in concept level that hard to implement and still requires exploration and improvement to develop. Failure level in implementation of Knowledge Management System (KMS) high enough that should be measured with KMS Readiness Levels. This research uses analytical hierarchy process (AHP) weighting method and Aydin/Tasci scales to find out the research objective which is priority weighting from each of concepts that has been studied and to find out readiness category based on Aydin/Tasci Scale. The initial phase is to design a scale of measurement using AHP method with normalization weight and priority values as final results the next phase is to analyze the processing values using Aydin/Tasci Scale to see readiness scale of knowledge management system in computer science program. As measured from the readiness level of KMS are knowledge manager, technology and culture. Based on that, AHP weight values for each concept which chosen for this KMS readiness research in Computer Science Program. The highest score is 3.176 from culture dimension. Average value KMS readiness in Computer Science Program is 2,863 which means Computer Science Program is not ready yet for KMS implementation.

Contained in this report are the recommendations for the undergraduate degree program in Computer Science of the Curriculum Committee on Computer Science (C 3 S) of the Association for Computing Machinery (ACM). The core curriculum common to all computer science undergraduate programs is presented in terms of elementary level topics and courses, and intermediate level courses. Elective courses, used to round out an undergraduate program, are then discussed, and the entire program including the computer science component and other material is presented. Issues related to undergraduate computer science education, such as service courses, supporting areas, continuing education, facilities, staff, and articulation are presented.

[This Proceedings paper was revised and published in the 2018 issue of the journal Issues in Informing Science and Information Technology, Volume 15] ABSTRACT Mathematics is fundamental to the study of Computer Science. In Sri Lankan state universities, students have been enrolled only from the Physical Science stream with minimum ‘C’ grade in Mathematics in the advanced level examination to do a degree program in Computer Science. In addition to that universities have been offering some course units in Mathematics covering basis in Discrete Mathematics, Calculus, and Algebra to provide the required mathematical maturity to Computer Science under-graduates. Despite of this it is observed that the failure rate in fundamental theoretical Computer Science course units are much higher than other course units offered in the general degree program every year. 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 and to make appropriate recommendations based on our findings. Academic records comprised of 459 undergraduates from three consecutive batches admitted to the degree program in Computer Science from a university was considered for this study. Results indicated that 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 in the first and second year of studies were significantly correlated with academic performance of every theoretical Computer Science course unit, only the Discrete Mathematics course unit highly impact-ed 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.

The use of computation alongside the natural sciences is moving research forward at unprecedented rates. Computational scientists are in high demand, and the undergraduate level is a great place to begin training students for work in this area. Furthermore, studies have shown that applied programs such as computational science are attractive to students and aid in retention. Yet, the number of undergraduate computational science programs remains very limited. Throughout informal conversations with colleagues who were interested in combining computing and science, we repeatedly heard 2 reasons why a computational science program was missing from their institution: 1) they lacked counterparts in the natural sciences who were interested in working with them and 2) their department couldn't support the change in personnel or curriculum that they thought was required to introduce and maintain a computational science program. Addressing the first concern, this poster displays some of what was learned from interviews with 20 natural scientists regarding how they currently or might work with a computational counterpart. Our hope is that this information might be used in conversations with reluctant natural scientists. Addressing the second concern, this poster summarizes the content of computational science programs that currently exist for undergraduates, including majors, minors, computational tracks in science majors or science tracks in computational majors, and science or computational courses with complementary material. Our hope is that this summary will encourage colleagues that, given such variety, there is a place for some form of computational science at their institution.

Introduction The computing sciences are complex fields that combine both theoretical and practical components. Students successfully completing an undergraduate computer science program should have instruction in both the mathematical and theoretical foundations of computing as well as the more practical aspects of how to effectively use computers to solve problems. Software engineering, as its name implies, is more directed toward the practical aspects of how to successfully develop complex systems that meet user requirements and are reliable, usable, and maintainable. Computing Curricula 2005 recognizes the need for more extensive education to produce professional engineers than what can be reasonably provided in a typical computer science program (ACM, 2005). As such, they propose engineering be treated as a totally separate discipline within computer science education. However, while there has been some debate about the exact role engineering should have in a computer science program (Curran, 2003), the ACM Curricula has maintained the importance of engineering to all computer science students and has kept it as a core element in computer science education (ACM, 2008). For purposes of this paper, we will focus on the teaching of engineering within the computer science discipline. Unlike other topics in the computer science major, the techniques and principles taught in engineering are often first developed and refined in industry before arriving in the classroom. As commercial development techniques and tools evolve, so pedagogical methodologies change. Computer science educators have taken different approaches to teaching engineering over the years, both as a result of changing methodologies as well as individual beliefs about what teaching methods work best in a particular academic environment. This paper is a case study in applying current productivity tools (specifically Redmine) in a engineering course at our institution. The objectives of the study are to investigate how to integrate the tools into the existing structure and evaluate their impact. We describe our experience in recently changing our approach to teaching engineering to be more aligned with current tools and how to effectively use them in an academic environment. The paper begins with an overview of engineering teaching methods, then describes our traditional approach and motivation for changing, how the new approach was integrated into the course, our experience with the change, and, finally, our plans for the future Software Engineering Education Background Software Engineering is defined as the application of a systematic, disciplined, quantifiable approach to the development, operation and maintenance of software (Petkovic, Thompson, & Todtenhoefer, 2006, p. 294). The need to teach engineering in colleges has been identified for decades. Stiller & LeBlanc (2002) point out as far back as the early 1990's, ACM Computing Curricula suggested that the at least one engineering course should be required in accredited computer science programs. They point out that the number of large projects in industry demand this and suggest that the proof of the success of these accredited computer science programs should be seen in the reduction of failure in the design and operation of large computer programs. Software engineering programs can be thought of as a replacement for the old apprenticeship programs which taught the trades to workman (Stroulia, Bauer, Craig, Reid, & Wilson, 2011). The issue, however, is how to bring this effect into the classroom. Many educators feel that current practices of teaching engineering are not adequately preparing students for the real world of development. Nurkkala & Brandle (2011) summarize the problems with current teaching approaches: * No product--students are creating projects, not commercial grade products * Short duration--single semester, or two-semester, courses impose an artificial time constraint * High turnover--new students each semester means the talent pool remains shallow and student skills are not developing based on previous experience * Low complexity--by necessity given time constraints and skill sets * No maintenance--as a result of short duration, students do not experience a key aspect of development, the maintenance phase * No customer--most engineering projects do not interface with a real customer To address these shortcomings, different approaches to teaching engineering have emerged and been proposed in the literature. …

The Scholars of Excellence in Engineering and Computer Science (SEECS) program initiated its first cohort of 20 students in fall 2009. Funded for two, five-year awards through a National Science Foundation (NSF) S-STEM grant, the interdisciplinary, multi-year, mixed academic-level program offers scholarships to students based on academic merit and financial need. The goals of the scholarship program are (1) to increase the number of academically talented, but financially disadvantaged students in the stated majors, (2) to assist students to be successful in their undergraduate education, and (3) to foster professional development for careers or graduate education.

This report summarizes recent and projected enrollment and staffing growth in undergraduate computer science (CS) programs for a selected group of colleges. It originates from a concern that liberal arts colleges, like other colleges and universities, will soon face a new crisis in undergraduate computer science education, one in which teaching and laboratory resources are severely strained by a rapid surge in enrollments in both the introductory courses and the CS major itself. If this is true, liberal arts colleges and universities that value their computer science programs must begin to aggressively expand their CS faculty ranks and laboratory support in the near term.