Diverse Faculty and Learner Lab
Diverse Faculty and Learner Lab
Welcome to CEITR research laboratory for cluster of projects related to exploring diverse faculty and learners’ issues, challenges, and teaching strategies.
We use secondary data to explore diverse faculty and learners issues related to teaching and learning. Using secondary data in research has some advantages. The data is public and using public data will simplify the need for lengthy IRB procedures. The secondary data may be difficult to get in any other venue. Quantitative analysis of secondary data has a long history. Recently, qualitative analysis of archived qualitative data is emerging in social science. Most commonly, content analysis, comparative and historical analysis are used in addition to statistical analysis.
Sub-topics/Teams 2019- 2020
Technological advances for advances for academic improvements with autistic student sin higher educations, Michelle Hill (leader), Troy Jeffers (students), Jennifer Calito (Alumni), Milinda Jaffe Bork (faculty), Laquisha Brown (alumni)
Opening new territories for the advantages of using music with diverse learners, Michelle Hill- faculty and team leader Shanel Harris (alumni) Fortune Taylor (Faculty) Shaquanna Robinson (alumni) Jacque Alexander (alumni) Laquisha Brown (alumni), Troy Jeffers (Student)
Exploring options for shaping immersive experiences access virtual reality curricula; Patricia Steele, Liston Bailey, Cheryl Burleigh, Margaret Kroposki [accepted for publication]
How do online curriculums incorporate the new multimedia possibilities that technology offers for learning? Andrew Lawlor: Team leader, Leonard Jackson (alumni) Taurus Jackson (alumni) Cass Smith (alumni) Sunni Lamppa
Collaborative team scoping lit review; Elizabeth Johnston, Cheryl Burleigh, Andrea Wilson
Online collaborative team narratives of publication success; Rita Hartman Christa Barton Patricia Akoje Danielle Sixsmith
Sub-topics/Teams 2017- 2018
- Discussion Forum
- PhD students' blogs
- Conversations among a group of mothers, who are earning a doctoral degree.
Articles that apply Content Analysis to specific problem
Creamer, E. G., & Ghoston, M. (2013). Using a mixed methods content analysis to analyze mission statements from colleges of engineering. Journal of Mixed Methods Research, 7(2), 110-120. doi:10.1177/1558689812458976
A mixed method design was used to conduct a content analysis of the mission statements of colleges of engineering to map inductively derived codes with the EC 2000 outcomes and to test if any of the codes were significantly associated with institutions with reasonably strong representation of women. Most institution’s (25 of 48) mission statement had two or fewer of the outcomes endorsed by the accrediting agency. The diversity code was significantly related to the representation of women, but is not one of the outcomes identified by the accrediting agency. The research demonstrates how mixed methods can be applied to content analysis.
Holman, D. K., & Banning, J. H. (2012). Honors dissertation abstracts: A bounded qualitative Meta-Study. Journal of the National Collegiate Honors Council, 13(1), 41-61.
A potential source of useful information about undergraduate honors education can be found in doctoral dissertation abstracts that focus on honors. Debra Holman and James Banning of Colorado State University sought to explore this resource by undertaking a bounded qualitative meta-study of such abstracts using document analysis. Three sub-questions focused their inquiry: (1) What are the general attributes of dissertations on honors education?; (2) What are the thematic subjects and topics associated with the dissertations?; and (3) Have these dissertation findings been published in higher education journals or books? This article provides an account of their research, including information on the meta-study framework they used, their selection of the dissertations for analysis, and their methods and procedures for analyzing the dissertations. Findings, a summary of publication-related trends for dissertations on honors education, and recommendations for future research are provided.
Stepchenkova, S., Kirilenko, A., Morrison, A. Facilitating Content Analysis in Tourism Research. SAGE Secondary Data Analysis. SAGE Publications Ltd. London: SAGE Publications Ltd.
This article proposes a methodological approach to analyzing multiple files of textual data typical in tourism studies in a transparent, replicable, and effective way. The approach proceeds with data preparation, identification of key variables, obtaining the word-frequency matrix, and subsequent dimensional reduction of word-frequency data. Obtaining a matrix of word frequencies from multiple units of qualitative data allows more sophisticated statistical analyses of data and, ultimately, hypothesis testing. The approach uses an efficient combination of two computer programs, CATPAC and WORDER; however, the methodology is not dependent on this particular software tandem. Other programs that perform the same functions can be used, and the choice, as always, is with the researcher. The objective of the article is to show that the proposed methodology is firmly grounded in the theory and practices of content analysis and is both simple and efficient enough to facilitate statistical data analysis in tourism studies.
Yalçın, S., ÇiğdemY., & Dibek, M. (2015). Content analysis of papers published in educational journals with high impact factors. Education & Science / Egitim ve Bilim, 40(182), 1-28. doi:10.15390/EB.2015.4868
The purpose of this study was to carry out a content analysis on the papers published in high-impact educational journals between 2009 and 2014 and to identify the trends over the selected years. The criteria for the analysis were; number of authors, time between the submission and publication of the papers, keywords, the field and rationale of the study, sample size, descriptions of participants, data collection tools and analysis, and software. The current study was designed as a descriptive content analysis study and utilized a purposive sampling technique. A total of 789 papers were selected from the "Journal of Educational Psychology", "Educational Psychologist", "Educational Researcher" and "American Education Research Journal". Content analysis was employed to analyze the collected data. The results of the analyses showed that the most commonly studied fields were educational psychology, linguistic properties and mathematics in the four journals. In terms of the content, the rationales for writing the papers were generally related to gaps in the literature and theoretical discussion. It was found that generally, studies involving research were conducted with elementary/high school students and data was collected from large samples (larger than 10000) using achievement tests and questionnaires. It was revealed that concerning the trends in data analysis methods, there was a similar pattern from 1970s to date, and generally, multilevel modelling was used when appropriate to the data sets. This situation indicates standard data analyses are essential for researchers. From the findings of the current study, it is recommended for researchers to work with heterogenous sample and various types of participants together (family, teacher, peer, etc.)
Articles related to methodology
Hsiu-Fang, H., & Shannon, S. (2005) Three approaches to qualitative content analysis. Qualitative Heath Research. 15:1277-1288, doi:10.1177/1049732305276687
Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
Guest, G. (2013). Describing mixed methods research: An alternative to typologies. Journal of Mixed Methods Research, 7(2), 141-151. doi:10.1177/1558689812461179
Scholars have created a variety of typologies to describe and simplify mixed methods research designs. In this article, I review the rationale for using these typologies and discuss some shortcomings of the existing methods of classification. I argue that current systems of classification, although useful for simple and less fluid types of mixed methods research, are not capable of capturing the complexity and iterative nature of larger, more intricate research projects. I suggest an alternative way of viewing and describing mixed methods research for studies that resist simple classification. This alternative perspective shifts the unit of reference to the point of interface—where QUAL and QUAN data are integrated—and reduces the number of descriptive dimensions to two—the timing and the purpose of data integration.
Mayring, P., (2000). Qualitative Content Analysis. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 1(2), Art. 20,http://nbn-resolving.de/urn:nbn:de:0114-fqs0002204.
This introduction criticizes the methodological dichotomization of qualitative and quantitative research, defines Qualitative Content Analysis as a mixed methods approach (containing qualitative and quantitative steps of analysis) and advocates common research criteria for qualitative and quantitative research. Finally, a step-by-step model of the (qualitative-quantitative) research process is presented. http://www.qualitative-research.net/index.php/fqs/article/view/1089/2385