Data Science and the Post-Liberal Arts University

Synergize Business With Artificial Intelligence Author: Dr. J. Nalatham, Principal, Government Arts and Science College, Avinashi-641654, Tirupur Dt. Tamil Nadu, India. DOI: https://doi.org/10.59646/synergizebusiness/044 ISBN: 978-81-965552-5-2 Date of Publication: September 19, 2023 About the Book: Artificial intelligence presents both the greatest potential and the greatest danger to small enterprises in the modern era. Now more than ever, artificial intelligence technologies are within reach of even the smallest of organisations. There is a significant influx of new low-cost AI apps reaching the market, and these tools may assist small businesses in swiftly expanding their earnings. These newly developed AI tools are simple to implement, do not call for specialised expertise such as that of software engineers or data scientists, and may be realised using no-code or low-code solutions. The author of this book breaks down the cognitive process into easy stages that the reader may instantly put into practise. You will find more deep methods to apply AI as you develop and expand, which will drive your new growth in a manner that has never been possible before.

Group work is a common practice in statistics and data science courses. However, students in introductory courses often have a wide range of previous experience with group work. In this study, we examine the perceptions of introductory statistics students around group formation at a medium-sized liberal arts university. Group experiences were implemented in two ways. First, students rotated through assigned group seating throughout the semester to work in new teams on in-class work. Second, students completed two group projects. For the first group project, students were randomly assigned a team, and on the second project, students could choose between picking a team of students or being randomized into a team. Pre- and post-semester surveys were used to gather student perceptions around group work formation and to better understand perceived benefits of each method. Students also completed post-project reflections about their project experiences. Surveys and reflections indicated that students preferred working with others that they knew best, but respondents still identified benefits such as getting to know other classmates when working in randomly assigned teams. Responses also indicated the importance of work ethic (e.g., trusting partners, fair distribution of workload) regarding potential teammates for both randomized and self-selected groups.

In 1997, the then-president of the University of Michigan, Lee Bollinger, was named as a defendant in two lawsuits brought in federal district court. The College of Literature, Science and Arts had denied admission to Jennifer Gratz and Patrick Hammacher, two White residents of Michigan. The applicants claimed that the University’s race-sensitive admissions policy had deprived them of their constitutional and statutory rights. Meanwhile, the University of Michigan Law School had denied admission to another White applicant, Barbara Grutter, and she too claimed reverse discrimination. How could the University defend itself? American jurisprudence is built around the concept of stare decisis: Precedent matters. It is helpful to an organization to be able to argue that its behaviors conform to and promote principles that the Court has explicitly endorsed in prior rulings. In American courts of law, as in the court of public opinion, a successful defense also requires that the defendant construct a cogent and coherent story about its behaviors and intentions. Increasingly, compelling stories must show that they are consistent not only with prevailing moral values but also with accepted social scientific data. Ever since the Supreme Court acknowledged in Brown v. Board of Education that social scientific studies have a legitimate role to play in its reasoning, lawyers have increasingly, and with varying degrees of success, called on social scientists to provide expert testimony. Social scientific data have made their way into public debates about policy and about law as well (Smith & Crosby, in press). Three questions thus faced the University of Michigan as it constructed a defense of race-sensitive admissions policies. First, could it articulate a coherent story to describe both its intentions and its actions? Second, could it link that story to established legal principles? Third, could it bring forward social scientific data to support its claims and could it refute social scientific data put forward by the other side? At least two different avenues lay open to the University as it set about to find answers and to construct a defense (Lehman, 2004; Stohr, 2004). It could decide to follow the road that led to the 1954 Brown victory for civil rights, emphasizing that, in view of the present consequences of historical discrimination,

Metal detection is a controversial topic within the contemporary cultural environment, due to its complex and sensitive implications within national legislations, cultural policies and participative involvement of cititzens in scientific data collection. However, this technology proved to have a huge potential for any research and investigations, especially for artistic research projects. The amount of data, archaeological context and artifacts is impressive and enables approach, development, progress and fair conclusions, at the scientific level, for artistic projects based on the study of modern history artifacts. The investigative project presented here is based on the last five years of research activity as Romanian artist practitioner of metal detecting, with comparative references to the main and trend setting Romanian artistic project of metal detecting R.A.P.I. – Romanian Archaeological Photography Index, developed by Michele Bressan and Bogdan Gоrbovan, both professional photographers and graduates of National University of Arts, Bucharest. Our approach is oriented towards the potential sculptural value of artifacts detected and unearthed within the world war 1 sites from the specific area of Prahova Valley, the place of fierce mountain battles at the end of 1916. As in the R.A.P.I. project, we used the wideranging photographic documentation of detected and dig-out military artifacts, but in more creative approach , rather than documentary, following the sculptural potential of free composition of objects and artifacts. Overdesigned and over-engineered, fabricated under high quality military standards or on the contrary, under industrial war effort ersatz regulations, these artifacts, wearing the centennial decay of underground and oblivion, express certain aestehtic qualities if composed in creative ways, as sculptural objects. The main objective of this study is the potential of metal detecting as a research tool to identify artifacts with sculptural readymade potential, composed and photographically investigated within creativity methods of contemporary sculpture. Used in the appropriate circumstances of legality, ethics, scientific rigor and also artistic creativity, metal detecting would acquire a major status within cultural enviroment through interdisciplinary artistic research projects combining art, archaeological survey, immersive history and participative citizen science.

Development of Education Curriculum in the Data Science Area for a Liberal Arts University

Analysis of International Students Knowledge Acquisition in Data Science Education at Private Liberal Arts University

Limited research has examined American collegiate coaches’ perceptions of collecting data for informing training practices. The purpose of this study was to examine collegiate coaches’ perspectives and needs for collecting data from their athletes using a qualitative approach. Four focus groups were conducted with NCAA Division I coaches ( N = 13) at a mid-sized liberal arts university. Coaches were asked how they could benefit from collecting data from their athletes, how they would use the data to answer questions about athletes’ performance, what data they would want to collect, and what concerns they had regarding data collection. Principles of thematic analysis were used to analyze the interviews. Most coaches (54%) felt that collecting data would provide evidence needed to support training methodologies, and they would benefit (i.e. make improvements to coaching and athlete training) from monitoring progress in their athletes (61%). Regarding performance questions, coaches were interested in utilizing a biomechanist to conduct movement analyses (23%) and assessing athletes’ mental and emotional states (23%). Coaches wanted to monitor athletes’ fatigue, recovery, mental health states, and health behaviors (i.e. sleep and diet; 15%). Coaches expressed concerns over finding an optimal time to test athletes (8%) and effective presentation of data to athletes (23%) while limiting body composition assessments due to athlete discomfort (15%). Findings from these focus groups suggest that coaches would like to collect data to learn more about athletes’ physical and mental states, but several logistical and practical concerns still exist regarding how to efficiently collect and utilize the data.