skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


This content will become publicly available on April 23, 2026

Title: Interdisciplinary Methods Exchange: A Joint-Class Guest Speaker Workshop
This workshop brings scholars in the social sciences together for a 10-week “Interdisciplinary Research Methods Exchange.” Scholars speak to a group of social science undergraduate majors about their current and prior research, highlighting their background, education, methodological challenges, and successes. A series of short writing assignments and optional methods assignment for thesis or capstone classes asks students to reflect on their experiences with the speakers, and a pre- and post-survey helps instructors assess whether learning objectives were met. This workshop functions as an integrated part of the course schedule and aims to expose students to the diversity of research topics, approaches, and methods in the social sciences and to increase interest in and knowledge about social science research careers.  more » « less
Award ID(s):
2222427
PAR ID:
10597662
Author(s) / Creator(s):
;
Publisher / Repository:
TRAILS: Teaching Resources and Innovations Library for Sociology
Date Published:
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. The Department of Biological Sciences at Minnesota State University, Mankato, a primarily undergraduate institution, is developing and implementing the “Research Immersive Scholastic Experience in Biology” (RISEbio) program. RISEbio is a National Science Foundation-funded scholarship and support program that is targeting incoming Biological Sciences freshmen with demonstrated financial need and academic potential. The overall goal of RISEbio is to increase student academic success through: (1) Increasing student social integration and support, (2) developing student technical and professional skills, and (3) implementing a freshman immersive research program. To form a social support network, scholars will be part of a RISEbio learning community. A unique, core component of RISEbio is to provide scholars with an authentic real-world research experience by modifying freshman research initiatives utilized by research-intensive universities to fit within the available infrastructure at Minnesota State University, Mankato. During a scholar’s first year, they exchange their Introductory Biology 1 lab for an applied course, Foundational Methods in Biology. In their second semester, scholars join a research stream in exchange for their Introductory Biology 2 lab. The stream research continues on to their third semester. One of two initial research streams is focused on neuroscience and is titled “Brain and Behavior.” Students in this stream examine the neural control of reproductive behavior by examining gene expression in the brain of the seasonally breeding green anole lizard (Anolis carolinensis). Students will extract RNA from the hypothalamus of breeding and non-breeding lizard brains, then design primers and use quantitative PCR in conjunction with bioinformatic analysis to identify genes that are differentially expressed in the brain between seasons. If differentially expressed genes are found, students will learn how to design and perform in situ hybridizations to examine the localization of these genes within the brain. Following the third semester, scholars enter the “next steps” stage which offers support to identify additional opportunities on and off campus, including mentoring the next group of RISEbio Scholars or joining research labs to continue conducting undergraduate research. RISEbio will also provide a platform to test how this program translates to student persistence and academic success. To our knowledge, this is the first freshman research initiative developed at a regional comprehensive university. 
    more » « less
  2. Scholars and public figures have called for improved ethics and social responsibility education in computer science degree programs in order to better address consequential technological issues in society. Indeed, rising public concern about computing technologies arguably represents an existential threat to the credibility of the computing profession itself. Despite these increasing calls, relatively little is known about the ethical development and beliefs of computer science students, especially compared to other science and engineering students. Gaps in scholarly research make it difficult to effectively design and evaluate ethics education interventions in computer science. Therefore, there is a pressing need for additional empirical study regarding the development of ethical attitudes in computer science students. Influenced by the Professional Social Responsibility Development Model, this study explores personal and professional social responsibility attitudes among undergraduate computing students. Using survey results from a sample of 982 students (including 184 computing majors) who graduated from a large engineering institution between 2017 and 2021, we compare social responsibility attitudes cross-sectionally among computer science students, engineering students, other STEM students, and non-STEM students. Study findings indicate computer science students have statistically significantly lower social responsibility attitudes than their peers in other science and engineering disciplines. In light of growing ethical concerns about the computing profession, this study provides evidence about extant challenges in computing education and buttresses calls for more effective development of social responsibility in computing students. We discuss implications for undergraduate computing programs, ethics education, and opportunities for future research. 
    more » « less
  3. This report presents the findings of a workshop on social innovation funded by the National Science Foundation under Grant No. SMA-1240596. The workshop took place August 27-28, 2013 at Rutgers Business School in Newark, New Jersey. The workshop that explored the intersection of the social, behavioral, and economic sciences and social policy and entrepreneurship. The goal was to develop a research agenda in social innovation and establish collaborative arrangements to build bridges between knowledge creators and practitioners. A research agenda is presented and recommendations are made for future work in social innovation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation 
    more » « less
  4. The project mission was to organize a workshop aimed to explore how the US data science community can cooperate with and benefit from collaborations with partners in Serbia and the West Balkan region. The scope included fundamental data science methods and high-impact applications related to big data processing, security and privacy in critical infrastructures, biomedical informatics, and computational archeology. The proposed workshop facilitated closing the gap between data science research in the US and Serbia and the region and brought together data scientists with researchers from disciplines that until recently had little exposure to data science methods, potentially enabling collaborative breakthroughs in those scientific fields. A large fraction of participants from both sides were early career researchers including advanced level graduate students, postdoctoral research associates, and assistant/associate professors within 10 years of obtaining their Ph.D. The participants included a large fraction of female and minority scientists. The workshop objective was achieved by including the following inter-related objectives: (1) Establishing new multidisciplinary international collaborations between data science, mathematics, and sciences that generate big data and require advanced methods; (2) Reinforcing collaboration mechanisms between the NSF and Serbia’s Ministry of Education, Science and Technological Development and organize joint research projects; and (3) Widening the impact of the workshop, by involving researchers and stakeholders from the West Balkan region. The workshop consisted of four tracks, each co-chaired by 3 investigators from the US, Serbia and another West Balkan country. Tangible outcomes from the workshop include a report describing workshop activities for each of four tracks and a proposal recommending research collaboration areas of interest for all parties and determining collaboration mechanisms and programs to facilitate collaboration. 
    more » « less
  5. Hacisalihoglu, Gokhan (Ed.)
    In many areas of science, the ability to use computers to process, analyze, and visualize large data sets has become essential. The mismatch between the ability to generate large data sets and the computing skill to analyze them is arguably the most striking within the life sciences. The Digital Image and Vision Applications in Science (DIVAS) project describes a scaffolded series of interventions implemented over the span of a year to build the coding and computing skill of undergraduate students majoring primarily in the natural sciences. The program is designed as a community of practice, providing support within a network of learners. The program focus, images as data, provides a compelling ‘hook’ for participating scholars. Scholars begin the program with a one-credit spring semester seminar where they are exposed to image analysis. The program continues in the summer with a one-week, intensive Python and image processing workshop. From there, scholars tackle image analysis problems using a pair programming approach and can finish the summer with independent research. Finally, scholars participate in a follow-up seminar the subsequent spring and help onramp the next cohort of incoming scholars. We observed promising growth in participant self-efficacy in computing that was maintained throughout the project as well as significant growth in key computational skills. DIVAS program funding was able to support seventeen DIVAS over three years, with 76% of DIVAS scholars identifying as women and 14% of scholars identifying as members of an underrepresented minority group. Most scholars (82%) entered the program as first year students, with 94% of DIVAS scholars retained for the duration of the program and 100% of scholars remaining a STEM major one year after completing the program. The outcomes of the DIVAS project support the efficacy of building computational skill through repeated exposure of scholars to relevant applications over an extended period within a community of practice. 
    more » « less