In the academic year of 2022, it is expected that 551,460 female and 331,530 male students will earn a Master’s degree in the United States. These figures are a significant increase from the academic year of 1950, when 16,980 female students and 41,220 male students earned a Master’s degree.

What is a Master’s degree?

A Master’s degree is an academic degree granted by universities after finishing a Bachelor’s degree. Master’s degrees focus in on a specific field and are more specialized than a Bachelor’s. A typical Master’s program is about two years long, with the final semester focusing on the thesis. Master’s degree programs are usually harder to get into than Bachelor’s degree programs, due to the rigor of the program. Because these programs are so competitive, those with a Master’s degree are typically paid more than those with a Bachelor’s degree.

Master’s degrees in the United States

The number of master’s degrees granted in the United States has steadily increased since the 1970s and is expected to continue to increase. In 2021, the Master’s degree program with the worst job prospects in the United States by mid-career median pay was counseling, while the program with the best job prospects was a physician's assistant.

In the academic year of 2020/21, about 202,334 Master's degrees were earned in business across the United States, making it the most common master's degree earned. In that same year, another 47,257 Master's degrees were earned in engineering.

Introduction This STEM advising outreach program was developed for undergraduate students who are contemplating future applications to PhD programs in the life sciences. The audience of ~20 students ranged in academic stage, and was composed mostly of life sciences undergraduates enrolled at Bowdoin College.

We have previously described two similar outreach events (ref. 1,2); this 90-minute combination of seminar and discussion built on that pilot program. This session at Bowdoin College was intended to complement the advising that students receive from their primary research mentors on campus. Although undergraduates at many excellent institutions have access to extensive pre-professional advising for careers in medicine, law and some other directions, the structure of advising for scientific research and the many career options that rely on PhD training is less consistent. Independent study or thesis research mentors are often a student’s primary source of advice. Career advisors have confirmed that reiteration and reinforcement of advising principles by professionals external to the school environment is helpful. Therefore, this outreach program’s content was developed with a goal of demystifying PhD programs and the benefits that they provide. The topics covered included (a) determining the key differences between programs, (b) understanding how PhD admissions works, (c) preparing an effective application, (d) proactive planning to strengthen one’s professional portfolio (internships, independent research, cultivating mentors), (e) key transferable skills that most students learn in graduate school, (f) what career streams are open to life science PhDs, and, (g) some national and institutional data on student career aspirations and outcomes (ref. 3). Methods The approach of bringing a faculty member and an administrative staff member who both have life science PhD training backgrounds was intentional. This allowed the program to portray different perspectives and experience to guide student career development, while offering credible witnesses to the types of experiences, skills and knowledge gained through PhD training. Central to the method of this outreach program is the willingness of graduate educators to meet the students on their own ground. The speakers guided students through a process of identifying national graduate programs that might best serve their individual interests and preferences. In addition to recruiting prospective applicants to Harvard Medical School (HMS) summer internships and PhD programs, the speakers made an explicit appeal to students to hone their professional portfolio proactively by discussing important skills that undergraduates need to be competitive in admissions and the career workplace including acquiring training in statistics and programming, soliciting diverse mentorship, acquiring authentic research experiences/internships, conducting thesis research, and obtaining fellowships). By reinforcing much of the anecdotal and formal advising content that is made available by faculty mentors and career counselors, our host saw the value of external experts to validate guidance.

This event built off our most recent event (ref. 2); we delivered a presentation covering the relevant topics and transitioned into an open discussion featuring a third visitor in our team. In contrast to the aforementioned previous event, the time constraint at lunch time prevented us from doing a formal panel. Our third speaker was a HMS Curriculum Fellow (ref. 4) whose career goals included teaching at a comparable institution (primarily undergraduate institution, PUI).

Students were encouraged to have lunch during the session, as the program was held at midday to avoid conflicts with other academic or extracurricular events. ResultsAs the principal goal of the session was to encourage and engage students, not to evaluate them, and the students ranged widely in stage and long-term career objectives, there were no assessment surveys of learning gains. Informally, student engagement was excellent as judged by the frequency and thoughtful nature of questions asked during the discussion phase of the session. Ad hoc student feedback directly following the event was extremely positive, as was our host’s follow up by email after the event. The success of the program was also evident by an invitation for a repeat of the program or other forms of collaboration in the future, including the possibility of reciprocal visits to HMS.DiscussionThis advising session was a continued refinement of our prototype, and thus served to prepare us for a series of similar events across a larger network of colleges. Our decision to incorporate a HMS Curriculum Fellow served three purposes: (1) to engage speaker who pursued doctoral training at three different institutions (UCLA, Tufts University, Harvard University), (2) to broaden the range of career trajectories presented as outcomes from doctoral programs, and (3) to provide networking and career development opportunities for the Curriculum Fellow.

About this Dataset

Data & Sons recently completed our analysis of top tier economics journal publications from 2014 to 2017 and is pleased to announce the world’s top Economics PhD Programs based on alumni productivity.

Category

Social Sciences

Keywords

economics phd programs,best phd programs,best economics phd programs

Row Count

1491

Price

Free

Data on the top universities for Computer Science in 2025.

The purpose of this project is to improve the accuracy of statistical software by providing reference datasets with certified computational results that enable the objective evaluation of statistical software. Currently datasets and certified values are provided for assessing the accuracy of software for univariate statistics, linear regression, nonlinear regression, and analysis of variance. The collection includes both generated and 'real-world' data of varying levels of difficulty. Generated datasets are designed to challenge specific computations. These include the classic Wampler datasets for testing linear regression algorithms and the Simon & Lesage datasets for testing analysis of variance algorithms. Real-world data include challenging datasets such as the Longley data for linear regression, and more benign datasets such as the Daniel & Wood data for nonlinear regression. Certified values are 'best-available' solutions. The certification procedure is described in the web pages for each statistical method. Datasets are ordered by level of difficulty (lower, average, and higher). Strictly speaking the level of difficulty of a dataset depends on the algorithm. These levels are merely provided as rough guidance for the user. Producing correct results on all datasets of higher difficulty does not imply that your software will pass all datasets of average or even lower difficulty. Similarly, producing correct results for all datasets in this collection does not imply that your software will do the same for your particular dataset. It will, however, provide some degree of assurance, in the sense that your package provides correct results for datasets known to yield incorrect results for some software. The Statistical Reference Datasets is also supported by the Standard Reference Data Program.

Introduction This STEM advising outreach program was developed for undergraduate students who are contemplating future applications to PhD programs in the life sciences. The audience of ~15 students ranged in academic stage, and was composed of life sciences undergraduates enrolled at Colby College.

We have previously described similar outreach events (ref. 1-3); this 90-minute combination of seminar and discussion built on those pilot programs. This session at Colby College was intended to complement the advising that students receive from their primary research mentors on campus. Although undergraduates at many excellent institutions have access to extensive pre-professional advising for careers in medicine, law and some other directions, the structure of advising for scientific research and the many career options that rely on PhD training is less consistent, and often relies on individual mentors whose training backgrounds and career trajectories are quite diverse. Independent study or thesis research mentors are often a student’s primary source of advice. Career advisors have confirmed that reiteration and reinforcement of advising principles by professionals external to the school environment is helpful. Therefore, this outreach program’s content was developed with a goal of demystifying PhD programs and the benefits that they provide. The topics covered included (a) determining the key differences between programs, (b) understanding how PhD admissions works, (c) preparing an effective application, (d) proactive planning to strengthen one’s professional portfolio (including internships, independent research, and cultivating mentors), (e) key transferable skills that most students learn in graduate school, (f) what career streams are open to life science PhDs, and, (g) some national and institutional data on student career aspirations and outcomes (ref. 4). MethodsThe approach of bringing a faculty member and an administrative staff member who both have life science PhD training backgrounds and with program administrative experience was intentional. This allowed the speakers to portray different perspectives and experience to guide student career development, while offering credible reflections on the types of experiences, skills and knowledge gained through PhD training. Central to the method of this outreach program is the willingness of graduate educators to meet the students on their own ground. The speakers guided students through a process of identifying national graduate programs that might best serve their individual interests and preferences. In addition to recruiting prospective applicants to Harvard Medical School (HMS) summer internships and PhD programs, the speakers made an explicit appeal to students to hone their professional portfolio proactively. Students were encouraged to seek out opportunities to develop skills that undergraduates need to be competitive in admissions to graduate programs, that trainees need during graduate school, and that doctoral alumni apply in the careers and workplaces that come after. To that end, students were encouraged to pursue training in statistics and programming, develop a mentoring network, acquire authentic research experiences and pursue internships, conduct thesis research, and apply for fellowships. By reinforcing much of the anecdotal and formal advising content that is made available by faculty mentors and career counselors, our host saw the value of external experts to validate prior guidance offered on campus.

This event built off our most recent event (ref. 3); we delivered a presentation covering the relevant topics and transitioned into an open discussion featuring a third visitor on our team. In contrast to the previous events (ref. 2), we did not use a panel format after the presentation. Our third speaker was a HMS Curriculum Fellow (ref. 5) whose career goals included teaching at a comparable institution (primarily undergraduate institution, PUI).

This event was held at the end of the day, and prior to dinner, to avoid conflicts with other academic or extracurricular events.ResultsAs the principal goal of the session was to encourage and engage students, not to evaluate them, and the students ranged widely in stage and long-term career objectives, there were no assessment surveys of learning gains. Informally, student engagement was excellent as judged by the frequency and thoughtful nature of questions asked during the discussion phase of the session. Ad hoc student feedback directly following the event was extremely positive. Our host’s participation and feedback was also encouraging; in particular, we learned that the portion of our presentation devoted to transferable skills gained from a PhD was well-received. The success of the program was also evident by an invitation for a repeat of the program or other forms of collaboration in the future, including the possibility of reciprocal visits to HMS.DiscussionThis advising session was a continued refinement of our prototype, which we continued to develop for an expanding network of colleges. Our decision to incorporate a HMS Curriculum Fellow served three purposes: (1) to engage another speaker so our team represented professionals who pursued doctoral training at three different institutions (UCLA, Tufts University, Harvard University), (2) to broaden the range of career trajectories presented as outcomes from doctoral programs, and (3) to provide networking and career development opportunities for the Curriculum Fellow.

In 2024, the average salary of a Washington University EMBA graduate three years after graduation was over ******* U.S. dollars. CEIBS graduates could expect the second-highest salary, reaching ******* U.S. dollars the same year. EMBAThe Executive MBA (EMBA) program is a graduate-level business degree program and is primarily designed for executives, managers, and similar business leaders. These programs are usually targeted towards working professionals, often in the middle stages of their career, and are often flexible to allow for part-time attendance while the student still works. An EMBA program allows a student to increase career options and update or add to their existing skill set. The best universities worldwide In the United States, Princeton University was considered one of the best colleges, with graduates earning a median of ******* U.S. dollars after 10 years. According to the Times Higher Education ranking of the best universities worldwide, the University of Oxford in the UK was considered the best.

The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.

The best master's degree for getting a job was considered to be Physicians Assistant with a mid-career median salary of ****** U.S. dollars in 2021. Salaries for nurse practitioner and computer science master's were also high.

The recent movement underscoring the importance of career taxonomies has helped usher in a new era of transparency in PhD career outcomes. The convergence of discipline-specific organizational movements, interdisciplinary collaborations, and federal initiatives has helped to increase PhD career outcomes tracking and reporting. Transparent and publicly available PhD career outcomes are being used by institutions to attract top applicants, as prospective graduate students are factoring in these outcomes when deciding on the program and institution in which to enroll for their PhD studies. Given the increasing trend to track PhD career outcomes, the number of institutional efforts and supporting offices for these studies have increased, as has the variety of methods being used to classify and report/visualize outcomes. This report comprehensively synthesizes existing PhD career taxonomy tools, resources, and visualization options to help catalyze and empower institutions to develop and publish their own PhD career outcomes. Similar fields between taxonomies were mapped to create a new crosswalk tool, thereby serving as an empirical review of the career outcome tracking systems available. Moreover, this work spotlights organizations, consortia, and funding agencies that are steering policy changes toward greater transparency in PhD career outcomes reporting. Such transparency not only attracts top talent to universities, but also propels research progress and technological innovation forward. Therefore, university administrators must be well-versed in government policies that may impact their PhD students. Engaging with government relations offices and establishing dialogues with policymakers are crucial steps toward staying informed about relevant legislation and advocating for more resources. For instance, much of the recent science legislation in the U.S. Congress, including the Creating Helpful Incentives to Produce Semiconductors (CHIPS) and Science Act, significantly impacts federal agency programs influencing universities. To ensure sustained development, it is imperative to support initiatives that enhance transparency, both in terms of legislation and resources. Increased funding for programs supporting transparency will aid legislatures and institutions in staying informed and responsive. Many efforts presented in this publication have received support from federal and state governments or philantrophic sources, underscoring the need for multifaceted support to initiate and perpetuate this level of systemic change.

Introduction: In an age of increasingly face-to-face, blended, and online Health Professions Education, students have more selections of where they will receive a degree. For an applicant, oftentimes, the first step is to learn more about a program through its website. Websites allow programs to convey their unique voice and to share their mission and values with others, such as applicants, researchers, and academics. Additionally, as the number of Health Professions Education programs rapidly grows, websites can share the priorities of these programs. Methods: In this study, we conducted a website review of 158 Health Professions Education websites to explore their geographical distributions, missions, educational concentrations, and various programmatic components. Results: We compiled this information and synthesized pertinent aspects, such as program similarities and differences, or highlighted the omission of critical data. Conclusion: Given that websites are often the first point of contact for prospective applicants, curious collaborators, and potential faculty, the digital image of HPE programs matters. We believe our findings demonstrate opportunities for growth within institutions and assist the field in identifying the priorities of HPE programs. As programs begin to shape their websites with more intentionality, they can reflect their relative divergence/convergence compared to other programs as they see fit and, therefore, attract individuals to best match this identity. Periodic reviews of the breadth of programs, such as those undergone here, are necessary to capture diversifying goals, and serve to help advance the field of Health Professions Education as a whole. Methods Our team deduced that most HPE programs would have a website, and that this would serve as a representation of how individuals within the program choose to view themselves and hope to be viewed by others. Further, our team determined that these websites would be an efficient means of collecting programmatic information for the purposes of learning more about program growth, diversity, and values. We conducted the website review from August 2021 to April 2022 using a list of worldwide Health Professions Education programs, which was acquired from the Foundation of Advancement of International Medical Education and Research’s (FAIMER’s) website. FAIMER was chosen as the origin source of programs studied due to its use in another published study evaluating HPE programs. Each master's degree in HPE offered by a university was counted separately, allowing us to note the differences in course and time requirements across all programs. Only HPE master's programs were selected for this study. Certificate and Ph.D. programs were excluded. Next, we developed a data extraction tool. Categories were jointly identified for data collection by three of our authors (JS, SW, and HM). JS, SW, and HW worked independently through a set of three HPE programs, obtaining the data for our selected categories. Afterward, we cross-checked each other's work for verification purposes. For example, if JS obtained the information, SW or HM, who were blinded to JS’s findings, would independently find the answers to the same questions/ topics. This was performed until an agreement between pre and post-review information was above 95%. There was no discovered information that was not agreed upon after discussion. Once 100% agreement was reached with this method, the total number of HPE programs analyzed was split between JS and SW, and the raw data was obtained for the same categories. This data then underwent a review by the other two researchers to ensure high accuracy. This review consisted of information verification on individual program websites where it was originally obtained. For example, if JS found the information about a program, SW and HM (now not blinded) would both have to independently find the same information. Any identified discrepancies were rectified through discussion, and three-way agreement was mandatory for the team to move on to the next program.

Introduction: Publications arguing against the null hypothesis significance testing (NHST) procedure and in favor of good statistical practices have increased. The most frequently mentioned alternatives to NHST are effect size statistics (ES), confidence intervals (CIs), and meta-analyses. A recent survey conducted in Spain found that academic psychologists have poor knowledge about effect size statistics, confidence intervals, and graphic displays for meta-analyses, which might lead to a misinterpretation of the results. In addition, it also found that, although the use of ES is becoming generalized, the same thing is not true for CIs. Finally, academics with greater knowledge about ES statistics presented a profile closer to good statistical practice and research design. Our main purpose was to analyze the extension of these results to a different geographical area through a replication study.Methods: For this purpose, we elaborated an on-line survey that included the same items as the original research, and we asked academic psychologists to indicate their level of knowledge about ES, their CIs, and meta-analyses, and how they use them. The sample consisted of 159 Italian academic psychologists (54.09% women, mean age of 47.65 years). The mean number of years in the position of professor was 12.90 (SD = 10.21).Results: As in the original research, the results showed that, although the use of effect size estimates is becoming generalized, an under-reporting of CIs for ES persists. The most frequent ES statistics mentioned were Cohen's d and R2/η2, which can have outliers or show non-normality or violate statistical assumptions. In addition, academics showed poor knowledge about meta-analytic displays (e.g., forest plot and funnel plot) and quality checklists for studies. Finally, academics with higher-level knowledge about ES statistics seem to have a profile closer to good statistical practices.Conclusions: Changing statistical practice is not easy.This change requires statistical training programs for academics, both graduate and undergraduate.

The number of graduates by institution type, program type, credential type, gender and Classification of Instructional Programs, Primary groupings (CIP_PG).

This book is written for statisticians, data analysts, programmers, researchers, teachers, students, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using the R programming language. R is an open-source software and object-oriented programming language with a development environment (IDE) called RStudio for computing statistics and graphical displays through data manipulation, modelling, and calculation. R packages and supported libraries provides a wide range of functions for programming and analyzing of data. Unlike many of the existing statistical softwares, R has the added benefit of allowing the users to write more efficient codes by using command-line scripting and vectors. It has several built-in functions and libraries that are extensible and allows the users to define their own (customized) functions on how they expect the program to behave while handling the data, which can also be stored in the simple object system.For all intents and purposes, this book serves as both textbook and manual for R statistics particularly in academic research, data analytics, and computer programming targeted to help inform and guide the work of the R users or statisticians. It provides information about different types of statistical data analysis and methods, and the best scenarios for use of each case in R. It gives a hands-on step-by-step practical guide on how to identify and conduct the different parametric and non-parametric procedures. This includes a description of the different conditions or assumptions that are necessary for performing the various statistical methods or tests, and how to understand the results of the methods. The book also covers the different data formats and sources, and how to test for reliability and validity of the available datasets. Different research experiments, case scenarios and examples are explained in this book. It is the first book to provide a comprehensive description and step-by-step practical hands-on guide to carrying out the different types of statistical analysis in R particularly for research purposes with examples. Ranging from how to import and store datasets in R as Objects, how to code and call the methods or functions for manipulating the datasets or objects, factorization, and vectorization, to better reasoning, interpretation, and storage of the results for future use, and graphical visualizations and representations. Thus, congruence of Statistics and Computer programming for Research.

Objective: Describe the current situation of the area Medicine III of CAPES and detect challenges for the next four years of evaluation. Methods: The area's documents and reports of meetings were read from 2004 to 2013 Medicine III Capes as well as reports and evaluation form of each Postgraduate Program (PPG) of the area and the sub-page of the area from the Capes website. The data relating to the evaluation process, the assessment form and faculty, student and scientific production data of all of Post-Graduate Programs of Medicine III were computed and analyzed. From these data were detected the challenges of the area for the next four years (2013-2016). Results: Among the 3,806 PPG, Medicine III had 41 PPG during last triennial evaluation and progressed from 18% to 43% of PPG very good or more concept (triennium 2001-2003 and 2010-2012). Most PPG were located in the South-East region (32), three in the South and two in the North-East. There was no PPG in North or Central-West regions. In 2013 and 2014 there were four approved Professional Master Degree Programs and one Master (M) and Doctorate (PhD). The average of permanent professors was 558 teachers with about three students/professor. The number of PhD graduates has increased as well as the reason PhD/MD. The proportion of in high impact periodicals (A1, A2, B1 and B2) jumped from 30% to 50% demonstrating positive community response to the policy area. The challenges identified were: decrease regional asymmetry, increase the number of masters and doctors of excellence, reassessment of Brazilian journals, stimulate and set internationalization indicators, including post-doctors and definition of its indicators, the PPG nucleation analysis, PPG 3x3, include primary and secondary education, professional master and indicators of technological scientific production and solidarity. Conclusion: Medicine III has been scientifically consolidated and their scientific researchers demonstrated maturity reaching a high level and matched to areas of greatest tradition and history. For the maintenance and advancement of the area some challenges and goals were established to be developed in the period from 2013 to 2016.

This paper investigates the dynamics of discrimination in Political Science PhD programs with a survey of current political science graduate students in the top 50 departments. We focus on mentorship, funding, sexual harassment, racism, homophobia, and labor exploitation: 20% of respondents report labor exploitation, 19% experienced racial discrimination, 9% report sexual harassment and 6% experienced homophobia. Discrimination is uneven across individuals: Some groups of graduate students experience widespread discrimination, especially racial discrimination, while other groups are largely unaware of these issues. We ran a survey experiment to gauge the impact of misconduct on formal reporting mechanisms and find that hearing about racial discrimination has a chilling effect on reporting. Importantly, we find that experiencing discrimination harms how satisfied students are in their programs. We find that factors linked to student vulnerability, like international status and funding, are significantly associated with harassment, and that reporting discrimination predicts more discrimination.

In an impressive increase from years past, 39 percent of women in the United States had completed four years or more of college in 2022. This figure is up from 3.8 percent of women in 1940. A significant increase can also be seen in males, with 36.2 percent of the U.S. male population having completed four years or more of college in 2022, up from 5.5 percent in 1940.

4- and 2-year colleges

In the United States, college students are able to choose between attending a 2-year postsecondary program and a 4-year postsecondary program. Generally, attending a 2-year program results in an Associate’s Degree, and 4-year programs result in a Bachelor’s Degree.

Many 2-year programs are designed so that attendees can transfer to a college or university offering a 4-year program upon completing their Associate’s. Completion of a 4-year program is the generally accepted standard for entry-level positions when looking for a job.

Earnings after college

Factors such as gender, degree achieved, and the level of postsecondary education can have an impact on employment and earnings later in life. Some Bachelor’s degrees continue to attract more male students than female, particularly in STEM fields, while liberal arts degrees such as education, languages and literatures, and communication tend to see higher female attendance.

All of these factors have an impact on earnings after college, and despite nearly the same rate of attendance within the American population between males and females, men with a Bachelor’s Degree continue to have higher weekly earnings on average than their female counterparts.

A great advantage of our rigorous doctoral training is that as PhD economists we speak a common language that allows for efficient vetting and quick dissemination of ideas and insights. But what good is sophisticated grammar and a powerful vocabulary if the contents of our narratives are lacking? Our top three criteria for admissions to PhD programs are prior coursework in math, the quantitative GRE score, and prior coursework in economics. To attract top talent and prevent becoming a stagnant discipline that loses the influence we have in society and academia, students' creativity, originality, and drive should receive more weight.

The interview data was gathered for a project that investigated the practices of instructors who use quantitative data to teach undergraduate courses within the Social Sciences. The study was undertaken by employees of the University of California, Santa Barbara (UCSB) Library, who participated in this research project with 19 other colleges and universities across the U.S. under the direction of Ithaka S+R. Ithaka S+R is a New York-based research organization, which, among other goals, seeks to develop strategies, services, and products to meet evolving academic trends to support faculty and students.

The field of Social Sciences has been notoriously known for valuing the contextual component of data and increasingly entertaining more quantitative and computational approaches to research in response to the prevalence of data literacy skills needed to navigate both personal and professional contexts. Thus, this study becomes particularly timely to identify current instructors’ practi..., The project followed a qualitative and exploratory approach to understand current practices of faculty teaching with data. The study was IRB approved and was exempt by the UCSB’s Office of Research in July 2020 (Protocol 1-20-0491).Â

The identification and recruitment of potential participants took into account the selection criteria pre-established by Ithaka S+R: a) instructors of courses within the Social Sciences, considering the field as broadly defined, and making the best judgment in cases the discipline intersects with other fields; b) instructors who teach undergraduate courses or courses where most of the students are at the undergraduate level; c) instructors of any rank, including adjuncts and graduate students; as long as they were listed as instructors of record of the selected courses; d) instructors who teach courses were students engage with quantitative/computational data.Â

The sampling process followed a combination of strategies to more easily identify instructo..., The data folder contains 10Â pdf files with de-identified transcriptions of the interviews and the pdf files with the recruitment email and the interview guide.Â