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Baylee A. Edwards; Jude Kolodisner; Jacob P. Youngblood; Katelyn M. Cooper; Sara E. Brownell – Advances in Physiology Education, 2024
The impersonal nature of high-enrollment science courses makes it difficult to build student-instructor relationships, which can negatively impact student learning and engagement, especially for members of marginalized groups. In this study, we explored whether an instructor collecting and sharing aggregated student demographics could positively…
Descriptors: Higher Education, Data Collection, Surveys, Demography
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Mark Adley; Hayley Alderson; Katherine Jackson; William McGovern; Liam Spencer; Michelle Addison; Amy O'Donnell – International Journal of Social Research Methodology, 2024
This paper considers the ethical and practical issues of recruiting for, and administering a quantitative survey with marginalised populations. These issues were identified through a focus group discussion, which consolidated and expanded upon informal conversations held previously by five researchers about their experiences of conducting a…
Descriptors: Foreign Countries, Researchers, Research, Research Design
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Matthew J. Mayhew; Christa E. Winkler – Journal of Postsecondary Student Success, 2024
Higher education professionals often are tasked with providing evidence to stakeholders that programs, services, and practices implemented on their campuses contribute to student success. Furthermore, in the absence of a solid base of evidence related to effective practices, higher education researchers and practitioners are left questioning what…
Descriptors: Higher Education, Educational Practices, Evidence Based Practice, Program Evaluation
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Burleson, James; Bott, Gregory J.; Carter, Michelle; Sarabadani, Jalal – Journal of Information Systems Education, 2023
To ensure validity in survey research, it is imperative that we properly educate doctoral students on best practices in data quality procedures. A 14-year analysis of 679 studies in the AIS "Basket of 8" journals noted undercommunication in the most pertinent procedures, consistent across journals and time. Given recent calls for…
Descriptors: Doctoral Programs, Curriculum Evaluation, Curriculum Development, Surveys
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Aiken, John M.; Lewandowski, H. J. – Physical Review Physics Education Research, 2021
We present a model for sharing quantitative data in the field of physics education research and use it to present a newly available dataset as an example. This model is in line with calls from across physics and science more generally to democratize data and results through open access. The model includes suggestions for data collection, creation…
Descriptors: Physics, Educational Research, Data, Shared Resources and Services
Kathleen Clarke; Adam R. Lalor – Association for Institutional Research, 2024
Traditional institutional research systems may limit who is counted and how they are counted because of limitations associated with disability classification, self-disclosure of disability status, and accessibility limitations inherent within some data-collection methods. As postsecondary institutions work toward improving access for disabled…
Descriptors: Inclusion, Students with Disabilities, Institutional Research, Ethics
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Magraw-Mickelson, Zoe; Wang, Harry H.; Gollwitzer, Mario – International Journal of Testing, 2022
Much psychological research depends on participants' diligence in filling out materials such as surveys. However, not all participants are motivated to respond attentively, which leads to unintended issues with data quality, known as careless responding. Our question is: how do different modes of data collection--paper/pencil, computer/web-based,…
Descriptors: Response Style (Tests), Surveys, Data Collection, Test Format
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Badia, Giovanna – New Review of Academic Librarianship, 2020
Multiple data collection or research methods exist for evaluating library spaces. Faced with numerous choices and limited time for gathering data, it becomes challenging for information professionals to determine the best way to proceed with evaluating their libraries' physical spaces. There is a gap in the literature on best practices for…
Descriptors: Academic Libraries, Data Collection, Evaluation Methods, Best Practices
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Friedman, Alon – Technology, Pedagogy and Education, 2018
Growing interest in Big Data is leading industries, academics and governments to accelerate Big Data research. However, how teachers should teach Big Data has not been fully examined. This article suggests criteria for redesigning Big Data syllabi in public and private degree-awarding higher education establishments. The author conducted a survey…
Descriptors: Data Collection, Data Analysis, Course Descriptions, Higher Education
Leysinger, Claudine; Hasgall, Alexander; Peneoasu, Ana-Maria – European University Association, 2020
In recent years, European universities and other stakeholders have taken interest in career tracking in doctoral education as one of the ways to better understand the potential professional future of doctoral candidates. This report reflects the outcomes of the work of the European University Association-Council for Doctoral Education (EUA-CDE)…
Descriptors: Career Development, Doctoral Degrees, Universities, International Organizations
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Knekta, Eva; Runyon, Christopher; Eddy, Sarah – CBE - Life Sciences Education, 2019
Across all sciences, the quality of measurements is important. Survey measurements are only appropriate for use when researchers have validity evidence within their particular context. Yet, this step is frequently skipped or is not reported in educational research. This article briefly reviews the aspects of validity that researchers should…
Descriptors: Factor Analysis, Surveys, Data Collection, Research Methodology
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Hustedt, Beth; Franklin, Jeff; Tate, Nicole – New Directions for Institutional Research, 2019
We discuss methods that can improve response rates in large-scale cross-sectional and longitudinal studies. Regardless of the specific study topic, sample member population, or method of contact, data collections should be designed with certain core principles in mind: legitimizing the study to prospective participants; presenting study…
Descriptors: Data Collection, Longitudinal Studies, Surveys, Response Rates (Questionnaires)
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Borden, Victor M. H.; Coates, Hamish – New Directions for Higher Education, 2017
Analytics derived from the student learning environment provide new insights into the collegiate experience; they can be used as a supplement to or, to some extent, in place of traditional surveys. To serve this purpose, however, greater attention must be paid to conceptual frameworks and to advancing institutional systems, activating new…
Descriptors: Educational Research, Data Collection, Data Analysis, College Students
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Stark, Emily; Kintz, Sedona; Pestorious, Chloey; Teriba, Akorede – Assessment & Evaluation in Higher Education, 2018
Departments and programmes in higher education are required to participate in an increasing number of programme, course and student assessments. These assessment requirements are also opportunities to develop student skills related to scientific literacy and research, if students are included in the process of developing, administering and…
Descriptors: Undergraduate Students, Information Literacy, Skill Development, Research Skills
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Fryer, Luke K.; Nakao, Kaori – Frontline Learning Research, 2020
Self-report is a fundamental research tool for the social sciences. Despite quantitative surveys being the workhorses of the self-report stable, few researchers question their format--often blindly using some form of Labelled Categorical Scale (Likert-type). This study presents a brief review of the current literature examining the efficacy of…
Descriptors: Measurement Techniques, Research Methodology, Surveys, Online Surveys
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