- NSF-PAR ID:
- 10026726
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Polymer International
- Volume:
- 66
- Issue:
- 1
- ISSN:
- 0959-8103
- Page Range / eLocation ID:
- 7 to 12
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Abstract Objective This study aims at reviewing novel coronavirus disease (COVID-19) datasets extracted from PubMed Central articles, thus providing quantitative analysis to answer questions related to dataset contents, accessibility and citations. Methods We downloaded COVID-19-related full-text articles published until 31 May 2020 from PubMed Central. Dataset URL links mentioned in full-text articles were extracted, and each dataset was manually reviewed to provide information on 10 variables: (1) type of the dataset, (2) geographic region where the data were collected, (3) whether the dataset was immediately downloadable, (4) format of the dataset files, (5) where the dataset was hosted, (6) whether the dataset was updated regularly, (7) the type of license used, (8) whether the metadata were explicitly provided, (9) whether there was a PubMed Central paper describing the dataset and (10) the number of times the dataset was cited by PubMed Central articles. Descriptive statistics about these seven variables were reported for all extracted datasets. Results We found that 28.5% of 12 324 COVID-19 full-text articles in PubMed Central provided at least one dataset link. In total, 128 unique dataset links were mentioned in 12 324 COVID-19 full text articles in PubMed Central. Further analysis showed that epidemiological datasets accounted for the largest portion (53.9%) in the dataset collection, and most datasets (84.4%) were available for immediate download. GitHub was the most popular repository for hosting COVID-19 datasets. CSV, XLSX and JSON were the most popular data formats. Additionally, citation patterns of COVID-19 datasets varied depending on specific datasets. Conclusion PubMed Central articles are an important source of COVID-19 datasets, but there is significant heterogeneity in the way these datasets are mentioned, shared, updated and cited.more » « less
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This work in progress paper presents an example of conducting a systematic literature review (SLR) to understand students’ affective response to active learning practices, and it focuses on the development and testing of a coding form for analyzing the literature. Specifically, the full paper seeks to answer: (1) what affective responses do instructors measure, (2) what evidence is used to study those responses, and (3) how are course features connected with student response. We conducted database searches with carefully-defined search queries which resulted in 2,365 abstracts from 1990 to 2015. Each abstract was screened by two researchers based on meeting inclusion criteria, with an adjudication round in the case of disagreement. We used RefWorks, an online citation management program, to track abstracts during this process. We identified over 480 abstracts which satisfied our criteria. Following abstract screening, we developed and tested a manuscript coding guide to capture the salient characteristics of each paper. We created an initial coding form by determining what paper topics would address our research questions and reviewing the literature to determine the most frequent response categories. We then piloted and tested the reliability of the form over three rounds of independent pair-coding, with each round resulting in clarifications to the form and mutual agreement on terms’ meanings. This process of developing a manuscript coding guide demonstrates how to use free online tools, such as Google Forms and Google Sheets, to inexpensively manage a large SLR team with significant turnover. Currently, we are in the process of applying the coding guide to the full texts. When complete, the resulting data will be synthesized by creating and testing relationships between variables, using each primary source as a case study to support or refute the hypothesized relationship.more » « less
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Abstract Background This paper begins with the premise that ethics and diversity, equity, and inclusion (DEI) overlap in engineering. Yet, the topics of ethics and DEI often inhabit different scholarly spaces in engineering education, thus creating a divide between these topics in engineering education research, teaching, and practice.
Purpose We investigate the research question, “How are ethics and DEI explicitly connected in peer‐reviewed literature in engineering education and closely related fields?”
Design We used systematic review procedures to synthesize intersections between ethics and DEI in engineering education scholarly literature. We extracted literature from engineering and engineering education databases and used thematic analysis to identify ethics/DEI connections.
Results We identified three primary themes (each with three sub‐themes): (1) lenses that serve to connect ethics and DEI (social, justice‐oriented, professional), (2) roots that inform how ethics and DEI connect in engineering (individual demographics, disciplinary cultures, institutional cultures); and (3) engagement strategies for promoting ethics and DEI connections in engineering (affinity toward ethics/DEI content, understanding diverse stakeholders, working in diverse teams).
Conclusions There is a critical mass of engineering education scholars explicitly exploring connections between ethics and DEI in engineering. Based on this review, potential benefits of integrating ethics and DEI in engineering include cultivating a socially just world and shifting engineering culture to be more inclusive and equitable, thus accounting for the needs and values of students and faculty from diverse backgrounds.
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Abstract Understanding why animals (including humans) choose one thing over another is one of the key questions underlying the fields of behavioural ecology, behavioural economics and psychology. Most traditional studies of food choice in animals focus on simple, single‐attribute decision tasks. However, animals in the wild are often faced with multi‐attribute choice tasks where options in the choice set vary across multiple dimensions. Multi‐attribute decision‐making is particularly relevant for flower‐visiting insects faced with deciding between flowers that may differ in reward attributes such as sugar concentration, nectar volume and pollen composition as well as non‐rewarding attributes such as colour, symmetry and odour. How do flower‐visiting insects deal with complex multi‐attribute decision tasks?
Here we review and synthesise research on the decision strategies used by flower‐visiting insects when making multi‐attribute decisions. In particular, we review how different types of foraging frameworks (classic optimal foraging theory, nutritional ecology, heuristics) conceptualise multi‐attribute choice and we discuss how phenomena such as innate preferences, flower constancy and context dependence influence our understanding of flower choice.
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We conclude with a discussion of outstanding questions for future research. We also present a conceptual framework that incorporates the multiple dimensions of choice behaviour.
