An Overview of the New ACM/IEEE Information Technology Curricular Framework

ACM and IEEE have developed a curricular report titled, “Information Technology Curricula 2017: Curriculum Guidelines for Baccalaureate Degree Programs in Information Technology,” known also as IT2017. The development of this report has received worldwide content contributions from industry and academia through surveys as well as many international conferences and workshops. An open online publication of the report was made available in December 2017. This paper presents a digest of the content of the report, the IT curricular framework, and suggestions for its use in developing new information technology programs or enhancing existing ones. The heart of the IT curricular framework is a set of competencies identified through knowledge, skills, and dispositions, as supported by pedagogical research. The paper also describes ways in which institutions could use the curricular framework not only to develop information technology degree programs, but also to improve and enhance related computing programs

Essential competencies of exceptional professional software engineers

Department Head: Rodney R. Oldehoeft.1991 Fall.Includes bibliographical references (pages 141-144).This dissertation presents a differential study of exceptional and non-exceptional professional software engineers in the work environment. The first phase of the study reports an in-depth review of 20 engineers. The study reports biographical data, Myers-Briggs Type Indicator test results, and Critical Incident Interview data for 10 exceptional and 10 non-exceptional subjects. Phase 1 concludes with a description of 38 essential competencies of software engineers. Phase 2 of this study surveys 129 engineers. Phase 2 reports biographical data for the sample and concludes that the only simple demographic predictor of performance is years of experience in software. This variable is able to correctly classify 63% of the cases studied. Phase 2 also has the participants complete a Q-Sort of the 38 competencies identified in Phase 1. Nine of these competencies are differentially related to engineer performance. A10 variable Canonical Discriminant Function is derived which is capable of correctly classifying 81% of the cases studied. This function consists of three biographical variables and seven competencies. The competencies related to Personal Attributes and Interpersonal Skills are identified as the most significant factors contributing to performance differences

Computing Competencies for Undergraduate Data Science Curricula: ACM Data Science Task Force

At the August 2017 ACM Education Council meeting, a task force was formed to explore a process to add to the broad, interdisciplinary conversation on data science, with an articulation of the role of computing discipline-specific contributions to this emerging field. Specifically, the task force would seek to define what the computing/computational contributions are to this new field, and provide guidance on computing-specific competencies in data science for departments offering such programs of study at the undergraduate level. There are many stakeholders in the discussion of data science – these include colleges and universities that (hope to) offer data science programs, employers who hope to hire a workforce with knowledge and experience in data science, as well as individuals and professional societies representing the fields of computing, statistics, machine learning, computational biology, computational social sciences, digital humanities, and others. There is a shared desire to form a broad interdisciplinary definition of data science and to develop curriculum guidance for degree programs in data science. This volume builds upon the important work of other groups who have published guidelines for data science education. There is a need to acknowledge the definition and description of the individual contributions to this interdisciplinary field. For instance, those interested in the business context for these concepts generally use the term “analytics”; in some cases, the abbreviation DSA appears, meaning Data Science and Analytics. This volume is the third draft articulation of computing-focused competencies for data science. It recognizes the inherent interdisciplinarity of data science and situates computing-specific competencies within the broader interdisciplinary space

Relevance, benefits, and problems of software modelling and model driven techniques—A survey in the Italian industry

Context Claimed benefits of software modelling and model driven techniques are improvements in productivity, portability, maintainability and interoperability. However, little effort has been devoted at collecting evidence to evaluate their actual relevance, benefits and usage complications. Goal The main goals of this paper are: (1) assess the diffusion and relevance of software modelling and MD techniques in the Italian industry, (2) understand the expected and achieved benefits, and (3) identify which problems limit/prevent their diffusion. Method We conducted an exploratory personal opinion survey with a sample of 155 Italian software professionals by means of a Web-based questionnaire on-line from February to April 2011. Results Software modelling and MD techniques are very relevant in the Italian industry. The adoption of simple modelling brings common benefits (better design support, documentation improvement, better maintenance, and higher software quality), while MD techniques make it easier to achieve: improved standardization, higher productivity, and platform independence. We identified problems, some hindering adoption (too much effort required and limited usefulness) others preventing it (lack of competencies and supporting tools). Conclusions The relevance represents an important objective motivation for researchers in this area. The relationship between techniques and attainable benefits represents an instrument for practitioners planning the adoption of such techniques. In addition the findings may provide hints for companies and universitie

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research