The Evolution of Data Science: A New Mode of Knowledge Production

Is data science a new field of study or simply an extension or specialization of a discipline that already exists, such as statistics, computer science, or mathematics? This article explores the evolution of data science as a potentially new academic discipline, which has evolved as a function of new problem sets that established disciplines have been ill-prepared to address. The authors find that this newly-evolved discipline can be viewed through the lens of a new mode of knowledge production and is characterized by transdisciplinarity collaboration with the private sector and increased accountability. Lessons from this evolution can inform knowledge production in other traditional academic disciplines as well as inform established knowledge management practices grappling with the emerging challenges of Big Data

Is science communication its own field?

The present comment examines to what extent science communication has attained the status of an academic discipline and a distinct research field, as opposed to the common view that science communication is merely a sub-discipline of media studies, sociology of science or history of science. Against this background, the authors of this comment chart the progress science communication has made as an emerging subject over the last 50 years in terms of a number of measures. Although discussions are still ongoing about the elements that must be present to constitute a legitimate disciplinary field, we show here that science communication meets four key elements that constitute an analytical framework to classify academic disciplines: the presence of a community; a history of inquiry; a mode of inquiry that defines how data is collected; and the existence of a communications network

Demonstration Classrooms: A Thematic Approach to Science/Mathematics Integration

A fundamental principle of ecology is that everything is interconnected. This observation holds true in the academic as well as the natural world; if we study an environmental issue in depth, we find that it cannot be resolved by means of any single discipline. Environmental studies transcend all disciplines so as to include the sciences, mathematics, technology, social studies, language arts and the practical and fine arts. The science component, ecology, is itself an integrating rather than a splintering science. It draws together the traditionally separate disciplines of biology, chemistry, physics and earth science. Mathematics provides a tool for quantifying and interpreting the data obtained through experimentation and observation

Ethical Reasoning in STEM Disciplines

In this study, it was aimed to determine ethical reasoning of lecturers in STEM disciplines in terms of several independent variables (gender, working another institution, age, academic title, academic discipline, service period). This study was designed as a survey research. Lecturers in STEM disciplines in Kahramanmaras Sutçuimam University were selected as participants of the study. ‘‘Ethical Reasoning Instrument (ERI)’ which was developed by Titus, Zoltowski, Huyck, and Oakes (2011) was used in order to collect data by adapting into Turkish. Data were analyzed by the help of independent sample t-test, one-way ANOVA and Kruskal-Wallis tests. The findings indicated that for all independent variables there were no statistically significant difference (p>.05) in ethical reasoning of lecturers. As an interesting result, it was determined that lecturers in engineering discipline have less ethical awareness than lecturers in medicine and science disciplines. Keywords: STEM, STEM Disciplines, Ethics, Ethical Reasoning

A Case Study on Elementary Teachers’ Experiences Teaching Computer Science

Computer science is an academic discipline that provides a new foundational skill for all students. The discipline helps students develop critical thinking skills and teaches students how to move beyond merely using technology to becoming creators. The importance of computer science has been recognized across the country as states are working to train staff, adopt standards, and create implementation plans. As the demand for computer science learning opportunities increase, elementary teachers need the necessary supports to help ensure equitable access for all students. The purpose of this qualitative case study was to gain an understanding elementary teachers’ experiences teaching computer science. Two research questions guided this study: What barriers do elementary teachers experience in teaching computer science to students? What strategies do elementary teachers develop in their experience teaching computer science to students? The data collection instruments were primary semistructured interviews, secondary semistructured interviews, and documents. The inductive analysis model was used to analyze the collected data from the semistructured interviews. The typological analysis model was used to analyze the documents. The key findings of this study revealed that elementary teachers experience internal and external barriers in teaching computer science. Participants understood the importance of teaching computer science to their students, prompting them to persevere and develop new strategies in their pedagogical approaches. Interviewees also developed strategies to limit the impact of the barriers they experienced teaching elementary computer science

The Mastery Rubric for Statistics and Data Science: promoting coherence and consistency in data science education and training

Consensus based publications of both competencies and undergraduate curriculum guidance documents targeting data science instruction for higher education have recently been published. Recommendations for curriculum features from diverse sources may not result in consistent training across programs. A Mastery Rubric was developed that prioritizes the promotion and documentation of formal growth as well as the development of independence needed for the 13 requisite knowledge, skills, and abilities for professional practice in statistics and data science, SDS. The Mastery Rubric, MR, driven curriculum can emphasize computation, statistics, or a third discipline in which the other would be deployed or, all three can be featured. The MR SDS supports each of these program structures while promoting consistency with international, consensus based, curricular recommendations for statistics and data science, and allows 'statistics', 'data science', and 'statistics and data science' curricula to consistently educate students with a focus on increasing learners independence. The Mastery Rubric construct integrates findings from the learning sciences, cognitive and educational psychology, to support teachers and students through the learning enterprise. The MR SDS will support higher education as well as the interests of business, government, and academic work force development, bringing a consistent framework to address challenges that exist for a domain that is claimed to be both an independent discipline and part of other disciplines, including computer science, engineering, and statistics. The MR-SDS can be used for development or revision of an evaluable curriculum that will reliably support the preparation of early e.g., undergraduate degree programs, middle e.g., upskilling and training programs, and late e.g., doctoral level training practitioners.Comment: 40 pages; 2 Tables; 4 Figures. Presented at the Symposium on Data Science & Statistics (SDSS) 202

Taking a Diversity, Equity, Inclusion & Accessibility Lens to Engineering Librarian Job Postings: Recommendations from an Analysis of Postings from 2018 and 2019

Objective: While diversity, equity, inclusion, and accessibility (DEIA) principles and practices have been incorporated into much of academic librarianship, there has been less focus on the job postings. Methods: In order to quantify ways in which DEIA is being integrated into job postings, we analyzed 48 job positions for engineering librarians posted in 2018 and 2019 via deductive thematic analysis, looking for trends in salary and qualifications related to education and academic or professional experience. Results: Of postings that listed a quantitative salary value, salary ranged from $45,000 to$81,606; the median was $60,750. However, only 33% (n = 16) of positions listed a quantitative salary value. For educational qualifications, we found that 98% of job postings (n = 47) listed a Master’s in Library and Information Science (MLIS) as a required qualification; however, 34% of these postings (n = 16) would accept an equivalent degree in lieu of the MLIS. Additionally, 73% (n = 35) of positions sought candidates with an MLIS and another degree; 91% of these positions (n = 32) wanted the additional degree to be in a science, technology, engineering, and mathematics discipline. For academic or professional experience, 56% of positions (n = 27) sought candidates with previous academic library experience. Conclusions: Using this data, we provide actionable recommendations on how to incorporate DEIA principles into any academic librarian job posting. Our study provides quantitative data and evidence-based recommendations that can be used to make DEIA an integral part of the job postings in academic librarianship

From art to science : a bibliometric analysis of architectural scholarly production from 1980 to 2015

According to recent literature on “architecture” as a discipline, practical knowledge relevant to its process of making has decreased in importance in favor of a more academic approach. Using data derived from Ulrich’s Periodical Directory and Clarivate Analytics’s Web of Science, this paper suggests providing empirical evidence supporting of such shift, as revealed by an overview of the dissemination practices in architecture scholarly production between 1980 and 2015. Our results support that architecture is becoming increasingly academic, as demonstrated by the growing proportion of articles and journals intended for scholars rather than for professionals. We also show that architecture is increasingly global, with decreased interest in local and/or national issues and the growing prevalence of English as a publication language. Finally, this academic focus is manifested in references cited by architectural papers with the gradual substitution of professional and artistic oriented knowledge, for scientific approaches tied to engineering and technology

Case studies: A security science research methodology

As a relatively new discipline Security Science is searching for academic acceptance very often combining established hard science approaches with those of Social Science and Humanities. Methodologies need to be developed to equip the discipline to conduct more varied research. One such method is the use of the case study approach, as it allows multiple inputs from a variety of sources to build up the research into a central review, allowing conclusions and recommendations to be drawn from the data. Though relatively common in the business world for conducting reports, this has not hitherto been the position in academia The objective of this speculative paper develops a process used for research and seeks to open a debate as to the importance of case studies in the security field; the paper argues that it is an underutilised research paradigm. The merits of using the case study structure will be discussed, including the debate over positivism and constructivism, which will then lead on to a potential analytical method called Interpretative Phenomological Analysis (IPA); used predominately in ethnographical studies. The importance of using a pilot study before proceeding to the full study is also suggested to avoid costly mistakes later in the research

Case studies: A security science research methodology

As a relatively new discipline Security Science is searching for academic acceptance very often combining established hard science approaches with those of Social Science and Humanities. Methodologies need to be developed to equip the discipline to conduct more varied research. One such method is the use of the case study approach, as it allows multiple inputs from a variety of sources to build up the research into a central review, allowing conclusions and recommendations to be drawn from the data. Though relatively common in the business world for conducting reports, this has not hitherto been the position in academia. The objective of this speculative paper develops a process used for research and seeks to open a debate as to the importance of case studies in the security field; the paper argues that it is an underutilised research paradigm. The merits of using the case study structure will be discussed, including the debate over positivism and constructivism, which will then lead on to a potential analytical method called Interpretative Phenomological Analysis (IPA); used predominately in ethnographical studies. The importance of using a pilot study before proceeding to the full study is also suggested to avoid costly mistakes later in the research