Integrating Data Science into a General Education Information Technology Course: An Approach to Developing Data Savvy Undergraduates

The National Academies recommend academic institutions foster a basic understanding of data science in all undergraduates. However, data science education is not currently a graduation requirement at most colleges and universities. As a result, many graduates lack even basic knowledge of data science. To address the shortfall, academic institutions should incorporate introductory data science into general education courses. A general education IT course provides a unique opportunity to integrate data science education. Modules covering databases, spreadsheets, and presentation software, already present in many survey IT courses, teach concepts and skills needed for data science. As a result, a survey IT course can provide comprehensive introductory data science education by adding a data science module focused on modeling and evaluation, two key steps in the data science process. The module should use data science software for application, avoiding the complexities of programming and advanced math, while enabling an emphasis on conceptual understanding. We implemented a course built around these ideas and found that the course helps develop data savvy in students

Experiential Statistics: A Case Study in Favor of Using Project-Based Learning to Advance Preliminary Statistics Content Knowledge in the Algebra I and Geometry Classroom

Preparing secondary students for college entrance requirements and the expectations of the job market, a market which is actively seeking the employees who are most qualified to take on jobs that require data analysis skills, is becoming increasingly important. Federal, state, and local education administrators and personnel must rewrite many of the general education curricula to incorporate data organization, collection, manipulation, application, and analysis in order to better prepare students for the expectations of college entrance and an ever-changing employment market. From a purely pedagogical standpoint, while traditional educational structure has been commonplace for decades in the United States, projects used as assessment tools are a more progressive way to gauge content understanding and course achievement, especially in mathematics. Algebra I and Geometry students at a lone high school were randomly assigned to participating teachers’ classes that were assigned to one of two main treatment groups, one that used projects, the other traditional instruments, as formative assessments, in order to gauge two main goals - the growth in achievement before and after a curricular unit involving statistics and the change in attitudes towards statistics before and after the statistics unit. Using several parametric (paired t testing and MANOVA) and an additional non-parametric statistical analyses on a variety of demographic and class variables and coupled with an interview of participating teachers, the results revealed that projects, from the perspective of both participating students and teachers, often are much more effective in increasing achievement and attitudes towards the science of statistics, especially in the secondary educational years. The results of this study would be useful in rewriting mathematics curriculum to incorporate more focused attention to the science of statistics

TLAD 2010 Proceedings:8th international workshop on teaching, learning and assesment of databases (TLAD)

This is the eighth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2010), which once again is held as a workshop of BNCOD 2010 - the 27th International Information Systems Conference. TLAD 2010 is held on the 28th June at the beautiful Dudhope Castle at the Abertay University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.This year, the workshop includes an invited talk given by Richard Cooper (of the University of Glasgow) who will present a discussion and some results from the Database Disciplinary Commons which was held in the UK over the academic year. Due to the healthy number of high quality submissions this year, the workshop will also present seven peer reviewed papers, and six refereed poster papers. Of the seven presented papers, three will be presented as full papers and four as short papers. These papers and posters cover a number of themes, including: approaches to teaching databases, e.g. group centered and problem based learning; use of novel case studies, e.g. forensics and XML data; techniques and approaches for improving teaching and student learning processes; assessment techniques, e.g. peer review; methods for improving students abilities to develop database queries and develop E-R diagrams; and e-learning platforms for supporting teaching and learning

TLAD 2010 Proceedings:8th international workshop on teaching, learning and assesment of databases (TLAD)

This is the eighth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2010), which once again is held as a workshop of BNCOD 2010 - the 27th International Information Systems Conference. TLAD 2010 is held on the 28th June at the beautiful Dudhope Castle at the Abertay University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.This year, the workshop includes an invited talk given by Richard Cooper (of the University of Glasgow) who will present a discussion and some results from the Database Disciplinary Commons which was held in the UK over the academic year. Due to the healthy number of high quality submissions this year, the workshop will also present seven peer reviewed papers, and six refereed poster papers. Of the seven presented papers, three will be presented as full papers and four as short papers. These papers and posters cover a number of themes, including: approaches to teaching databases, e.g. group centered and problem based learning; use of novel case studies, e.g. forensics and XML data; techniques and approaches for improving teaching and student learning processes; assessment techniques, e.g. peer review; methods for improving students abilities to develop database queries and develop E-R diagrams; and e-learning platforms for supporting teaching and learning

The Relationship Between Learning Mode and Student Performance in an Undergraduate Elementary Statistics Course in the United States

Faculty have conducted many studies on the relationship between learning mode and student performance but few researchers have evaluated final grades, grade distribution, and pass rates in a sophomore introductory statistics course with a non-traditional student population who self-selected the learning mode from among different course sections. Accordingly, we examined 307 end-of-course grades from four different modes of instruction: (a) online, (b) videosynchronous learning classroom, (c) videosynchronous learning home, and (d) traditional classroom in an introductory statistics course. All data on grades, which included pass rate and grade distribution, were collected from the nine-week January 2019 term. All learning modes used the same text, syllabus, assignments, quizzes, and tests. In this study, learning mode was not significantly related to end-of-course score, final grade distribution, or pass rate. Future researchers should explore the impacts of gender, instructor quality, different term lengths, and the standardized use of textbooks and syllabi on student performance when exploring the impact of learning mode on grades, grade distribution, and pass rates

Dreaming of Big Data: a method for evaluating the use of data in the undergraduate mathematics curriculum.

This report evaluates the current undergraduate curriculum at WPI in the face of advances in data storage and processing capability. Large quantities of data are now widely accessible in nearly every industry, and we predict that all students will require data analysis skills to succeed in their future careers. In this report, we investigate the educational needs of all students concerning data. We consider the relationship between data and mathematics to determine if th