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digital humanities

7 Things You Should Know About Digital Humanities

Published:   Briefs, Case Studies, Papers, Reports  

https://library.educause.edu/resources/2017/11/7-things-you-should-know-about-digital-humanities

Lippincott, J., Spiro, L., Rugg, A., Sipher, J., & Well, C. (2017). Seven Things You Should Know About Digital Humanities (ELI 7 Things You Should Know). Retrieved from https://library.educause.edu/~/media/files/library/2017/11/eli7150.pdf

definition

The term “digital humanities” can refer to research and instruction that is about information technology or that uses IT. By applying technologies in new ways, the tools and methodologies of digital humanities open new avenues of inquiry and scholarly production. Digital humanities applies computational capabilities to humanistic questions, offering new pathways for scholars to conduct research and to create and publish scholarship. Digital humanities provides promising new channels for learners and will continue to influence the ways in which we think about and evolve technology toward better and more humanistic ends.

As defined by Johanna Drucker and colleagues at UCLA, the digital humanities is “work at the intersection of digital technology and humanities disciplines.” An EDUCAUSE/CNI working group framed the digital humanities as “the application and/or development of digital tools and resources to enable researchers to address questions and perform new types of analyses in the humanities disciplines,” and the NEH Office of Digital Humanities says digital humanities “explore how to harness new technology for thumanities research as well as those that study digital culture from a humanistic perspective.” Beyond blending the digital with the humanities, there is an intentionality about combining the two that defines it.

digital humanities can include

  • creating digital texts or data sets;
  • cleaning, organizing, and tagging those data sets;
  • applying computer-based methodologies to analyze them;
  • and making claims and creating visualizations that explain new findings from those analyses.

Scholars might reflect on

  • how the digital form of the data is organized,
  • how analysis is conducted/reproduced, and
  • how claims visualized in digital form may embody assumptions or biases.

Digital humanities can enrich pedagogy as well, such as when a student uses visualized data to study voter patterns or conducts data-driven analyses of works of literature.

Digital humanities usually involves work by teams in collaborative spaces or centers. Team members might include

  • researchers and faculty from multiple disciplines,
  • graduate students,
  • librarians,
  • instructional technologists,
  • data scientists and preservation experts,
  • technologists with expertise in critical computing and computing methods, and undergraduates

projects:

downsides

  • some disciplinary associations, including the Modern Language Association and the American Historical Association, have developed guidelines for evaluating digital proj- ects, many institutions have yet to define how work in digital humanities fits into considerations for tenure and promotion
  • Because large projects are often developed with external funding that is not readily replaced by institutional funds when the grant ends sustainability is a concern. Doing digital humanities well requires access to expertise in methodologies and tools such as GIS, mod- eling, programming, and data visualization that can be expensive for a single institution to obtain
  • Resistance to learning new tech- nologies can be another roadblock, as can the propensity of many humanists to resist working in teams. While some institutions have recognized the need for institutional infrastructure (computation and storage, equipment, software, and expertise), many have not yet incorporated such support into ongoing budgets.

Opportunities for undergraduate involvement in research, provid ing students with workplace skills such as data management, visualization, coding, and modeling. Digital humanities provides new insights into policy-making in areas such as social media, demo- graphics, and new means of engaging with popular culture and understanding past cultures. Evolution in this area will continue to build connections between the humanities and other disci- plines, cross-pollinating research and education in areas like med- icine and environmental studies. Insights about digital humanities itself will drive innovation in pedagogy and expand our conceptualization of classrooms and labs

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more on digital humanities in this IMS blog
http://blog.stcloudstate.edu/ims?s=digital+humanities

Cohort 8 research and write dissertation

When writing your dissertation…

Please have an FAQ-kind of list of the Google Group postings regarding resources and information on research and writing of Chapter 2

digital resource sets available through MnPALS Plus

http://blog.stcloudstate.edu/ims/2017/10/21/digital-resource-sets-available-through-mnpals-plus/ 

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[how to] write chapter 2

You were reminded to look at dissertations of your peers from previous cohorts and use their dissertations as a “template”: http://repository.stcloudstate.edu/do/discipline_browser/articles?discipline_key=1230

You also were reminded to use the documents in Google Drive: e.g. https://drive.google.com/open?id=0B7IvS0UYhpxFVTNyRUFtNl93blE

Please have also materials, which might help you organize our thoughts and expedite your Chapter 2 writing….

Do you agree with (did you use) the following observations:

The purpose of the review of the literature is to prove that no one has studied the gap in the knowledge outlined in Chapter 1. The subjects in the Review of Literature should have been introduced in the Background of the Problem in Chapter 1. Chapter 2 is not a textbook of subject matter loosely related to the subject of the study.  Every research study that is mentioned should in some way bear upon the gap in the knowledge, and each study that is mentioned should end with the comment that the study did not collect data about the specific gap in the knowledge of the study as outlined in Chapter 1.

The review should be laid out in major sections introduced by organizational generalizations. An organizational generalization can be a subheading so long as the last sentence of the previous section introduces the reader to what the next section will contain.  The purpose of this chapter is to cite major conclusions, findings, and methodological issues related to the gap in the knowledge from Chapter 1. It is written for knowledgeable peers from easily retrievable sources of the most recent issue possible.

Empirical literature published within the previous 5 years or less is reviewed to prove no mention of the specific gap in the knowledge that is the subject of the dissertation is in the body of knowledge. Common sense should prevail. Often, to provide a history of the research, it is necessary to cite studies older than 5 years. The object is to acquaint the reader with existing studies relative to the gap in the knowledge and describe who has done the work, when and where the research was completed, and what approaches were used for the methodology, instrumentation, statistical analyses, or all of these subjects.

If very little literature exists, the wise student will write, in effect, a several-paragraph book report by citing the purpose of the study, the methodology, the findings, and the conclusions.  If there is an abundance of studies, cite only the most recent studies.  Firmly establish the need for the study.  Defend the methods and procedures by pointing out other relevant studies that implemented similar methodologies. It should be frequently pointed out to the reader why a particular study did not match the exact purpose of the dissertation.

The Review of Literature ends with a Conclusion that clearly states that, based on the review of the literature, the gap in the knowledge that is the subject of the study has not been studied.  Remember that a “summary” is different from a “conclusion.”  A Summary, the final main section, introduces the next chapter.

from http://dissertationwriting.com/wp/writing-literature-review/

Here is the template from a different school (then SCSU)

http://semo.edu/education/images/EduLead_DissertGuide_2007.pdf 

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When conducting qualitative data, how many people should be interviewed? Is there a minimum or a max

Here is my take on it:

Simple question, not so simple answer.

It depends.

Generally, the number of respondents depends on the type of qualitative inquiry: case study methodology, phenomenological study, ethnographic study, or ethnomethodology. However, a rule of thumb is for scholars to achieve saturation point–that is the point in which no fresh information is uncovered in response to an issue that is of interest to the researcher.

If your qualitative method is designed to meet rigor and trustworthiness, thick, rich data is important. To achieve these principles you would need at least 12 interviews, ensuring your participants are the holders of knowledge in the area you intend to investigate. In grounded theory you could start with 12 and interview more if your data is not rich enough.

In IPA the norm tends to be 6 interviews.

You may check the sample size in peer reviewed qualitative publications in your field to find out about popular practice. In all depends on the research problem, choice of specific qualitative approach and theoretical framework, so the answer to your question will vary from few to few dozens.

How many interviews are needed in a qualitative research?

There are different views in literature and no one agreed to the exact number. Here I reviewed some mostly cited references. Based Creswell (2014), it is estimated that 16 participants will provide rich and detailed data. There are a couple of researchers agreed ‎on 10–15 in-depth interviews ‎are ‎sufficient ‎‎ (Guest, Bunce & Johnson 2006; Baker & ‎Edwards 2012).

your methodological choices need to reflect your ontological position and understanding of knowledge production, and that’s also where you can argue a strong case for smaller qualitative studies, as you say. This is not only a problem for certain subjects, I think it’s a problem in certain departments or journals across the board of social science research, as it’s a question of academic culture.

here more serious literature and research (in case you need to cite in Chapter 3)

Sample Size and Saturation in PhD Studies Using Qualitative Interviews

http://www.qualitative-research.net/index.php/fqs/article/view/1428/3027

https://researcholic.wordpress.com/2015/03/20/sample_size_interviews/

Gaskell, George (2000). Individual and Group Interviewing. In Martin W. Bauer & George Gaskell (Eds.), Qualitative Researching With Text, Image and Sound. A Practical Handbook (pp. 38-56). London: SAGE Publications.

Lieberson, Stanley 1991: “Small N’s and Big Conclusions.” Social Forces 70:307-20. (http://www.jstor.org/pss/2580241)

Savolainen, Jukka 1994: “The Rationality of Drawing Big Conclusions Based on Small Samples.” Social Forces 72:1217-24. (http://www.jstor.org/pss/2580299).

Small, M.(2009) ‘How many cases do I need ? On science and the logic of case selection in field-based research’ Ethnography 10(1) 5-38

Williams,M. (2000) ‘Interpretivism and generalisation ‘ Sociology 34(2) 209-224

http://james-ramsden.com/semi-structured-interviews-how-many-interviews-is-enough/

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how to start your writing process

If you are a Pinterest user, you are welcome to just sbuscribe to the board:

https://www.pinterest.com/aidedza/doctoral-cohort/

otherwise, I am mirroring the information also in the IMS blog:

http://blog.stcloudstate.edu/ims/2017/08/13/analytical-essay/ 

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APA citing of “unusual” resources

http://blog.stcloudstate.edu/ims/2017/08/06/apa-citation/

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statistical modeling: your guide to Chapter 3

working on your dissertation, namely Chapter 3, you probably are consulting with the materials in this shared folder:

https://drive.google.com/drive/folders/0B7IvS0UYhpxFVTNyRUFtNl93blE?usp=sharing

In it, there is a subfolder, called “stats related materials”
https://drive.google.com/open?id=0B7IvS0UYhpxFcVg3aWxCX0RVams

where you have several documents from the Graduate school and myself to start building your understanding and vocabulary regarding your quantitative, qualitative or mixed method research.

It has been agreed that before you go to the Statistical Center (Randy Kolb), it is wise to be prepared and understand the terminology as well as the basics of the research methods.

Please have an additional list of materials available through the SCSU library and the Internet. They can help you further with building a robust foundation to lead your research:

http://blog.stcloudstate.edu/ims/2017/07/10/intro-to-stat-modeling/

In this blog entry, I shared with you:

  1. Books on intro to stat modeling available at the library. I understand the major pain borrowing books from the SCSU library can constitute, but you can use the titles and the authors and see if you can borrow them from your local public library
  2. I also sought and shared with you “visual” explanations of the basics terms and concepts. Once you start looking at those, you should be able to further research (e.g. YouTube) and find suitable sources for your learning style.

I (and the future cohorts) will deeply appreciate if you remember to share those “suitable sources for your learning style” either by sharing in this Google Group thread and/or sharing in the comments section of the blog entry: http://blog.stcloudstate.edu/ims/2017/07/10/intro-to-stat-modeling.  Your Facebook group page is also a good place to discuss among ourselves best practices to learn and use research methods for your chapter 3.

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search for sources

Google just posted on their Facebook profile a nifty short video on Google Search
http://blog.stcloudstate.edu/ims/2017/06/26/google-search/

Watching the video, you may remember the same #BooleanSearch techniques from our BI (bibliography instruction) session of last semester.

Considering the fact of preponderance of information in 2017: your Chapter 2 is NOT ONLY about finding information regrading your topic.
Your Chapter 2 is about proving your extensive research of the existing literature.

The techniques presented in the short video will arm you with methods to dig deeper and look further.

If you would like to do a decent job exploring all corners of the vast area called Internet, please consider other search engines similar to Google Scholar:

Microsoft Semantic Scholar (Semantic Scholar); Microsoft Academic Search; Academicindex.net; Proquest Dialog; Quetzal; arXiv;

https://www.google.com/; https://scholar.google.com/ (3 min); http://academic.research.microsoft.com/http://www.dialog.com/http://www.quetzal-search.infohttp://www.arXiv.orghttp://www.journalogy.com/
More about such search engines in the following blog entries:

http://blog.stcloudstate.edu/ims/2017/01/19/digital-literacy-for-glst-495/

and

http://blog.stcloudstate.edu/ims/2017/05/01/history-becker/

Let me know, if more info needed and/or you need help embarking on the “deep” search

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tips for writing and proofreading

please have several infographics to help you with your writing habits (organization) and proofreading, posted in the IMS blog:

https://blog.stcloudstate.edu/ims/2017/06/11/writing-first-draft/
https://blog.stcloudstate.edu/ims/2017/06/11/prewriting-strategies/ 

https://blog.stcloudstate.edu/ims/2017/06/11/essay-checklist/

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letter – request copyright permission

Here are several samples on mastering such letter:

https://registrar.stanford.edu/students/dissertation-and-thesis-submission/preparing-engineer-theses-paper-submission/sample-3

http://www.iup.edu/graduatestudies/resources-for-current-students/research/thesis-dissertation-information/before-starting-your-research/copyright-permission-instructions-and-sample-letter/

https://brocku.ca/webfm_send/25032

 

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IRDL proposal

Applications for the 2018 Institute will be accepted between December 1, 2017 and January 27, 2018. Scholars accepted to the program will be notified in early March 2018.

Title:

Learning to Harness Big Data in an Academic Library

Abstract (200)

Research on Big Data per se, as well as on the importance and organization of the process of Big Data collection and analysis, is well underway. The complexity of the process comprising “Big Data,” however, deprives organizations of ubiquitous “blue print.” The planning, structuring, administration and execution of the process of adopting Big Data in an organization, being that a corporate one or an educational one, remains an elusive one. No less elusive is the adoption of the Big Data practices among libraries themselves. Seeking the commonalities and differences in the adoption of Big Data practices among libraries may be a suitable start to help libraries transition to the adoption of Big Data and restructuring organizational and daily activities based on Big Data decisions.
Introduction to the problem. Limitations

The redefinition of humanities scholarship has received major attention in higher education. The advent of digital humanities challenges aspects of academic librarianship. Data literacy is a critical need for digital humanities in academia. The March 2016 Library Juice Academy Webinar led by John Russel exemplifies the efforts to help librarians become versed in obtaining programming skills, and respectively, handling data. Those are first steps on a rather long path of building a robust infrastructure to collect, analyze, and interpret data intelligently, so it can be utilized to restructure daily and strategic activities. Since the phenomenon of Big Data is young, there is a lack of blueprints on the organization of such infrastructure. A collection and sharing of best practices is an efficient approach to establishing a feasible plan for setting a library infrastructure for collection, analysis, and implementation of Big Data.
Limitations. This research can only organize the results from the responses of librarians and research into how libraries present themselves to the world in this arena. It may be able to make some rudimentary recommendations. However, based on each library’s specific goals and tasks, further research and work will be needed.

 

 

Research Literature

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”
– Dan Ariely, 2013  https://www.asist.org/publications/bulletin/aprilmay-2017/big-datas-impact-on-privacy-for-librarians-and-information-professionals/

Big Data is becoming an omnipresent term. It is widespread among different disciplines in academia (De Mauro, Greco, & Grimaldi, 2016). This leads to “inconsistency in meanings and necessity for formal definitions” (De Mauro et al, 2016, p. 122). Similarly, to De Mauro et al (2016), Hashem, Yaqoob, Anuar, Mokhtar, Gani and Ullah Khan (2015) seek standardization of definitions. The main connected “themes” of this phenomenon must be identified and the connections to Library Science must be sought. A prerequisite for a comprehensive definition is the identification of Big Data methods. Bughin, Chui, Manyika (2011), Chen et al. (2012) and De Mauro et al (2015) single out the methods to complete the process of building a comprehensive definition.

In conjunction with identifying the methods, volume, velocity, and variety, as defined by Laney (2001), are the three properties of Big Data accepted across the literature. Daniel (2015) defines three stages in big data: collection, analysis, and visualization. According to Daniel, (2015), Big Data in higher education “connotes the interpretation of a wide range of administrative and operational data” (p. 910) and according to Hilbert (2013), as cited in Daniel (2015), Big Data “delivers a cost-effective prospect to improve decision making” (p. 911).

The importance of understanding the process of Big Data analytics is well understood in academic libraries. An example of such “administrative and operational” use for cost-effective improvement of decision making are the Finch & Flenner (2016) and Eaton (2017) case studies of the use of data visualization to assess an academic library collection and restructure the acquisition process. Sugimoto, Ding & Thelwall (2012) call for the discussion of Big Data for libraries. According to the 2017 NMC Horizon Report “Big Data has become a major focus of academic and research libraries due to the rapid evolution of data mining technologies and the proliferation of data sources like mobile devices and social media” (Adams, Becker, et al., 2017, p. 38).

Power (2014) elaborates on the complexity of Big Data in regard to decision-making and offers ideas for organizations on building a system to deal with Big Data. As explained by Boyd and Crawford (2012) and cited in De Mauro et al (2016), there is a danger of a new digital divide among organizations with different access and ability to process data. Moreover, Big Data impacts current organizational entities in their ability to reconsider their structure and organization. The complexity of institutions’ performance under the impact of Big Data is further complicated by the change of human behavior, because, arguably, Big Data affects human behavior itself (Schroeder, 2014).

De Mauro et al (2015) touch on the impact of Dig Data on libraries. The reorganization of academic libraries considering Big Data and the handling of Big Data by libraries is in a close conjunction with the reorganization of the entire campus and the handling of Big Data by the educational institution. In additional to the disruption posed by the Big Data phenomenon, higher education is facing global changes of economic, technological, social, and educational character. Daniel (2015) uses a chart to illustrate the complexity of these global trends. Parallel to the Big Data developments in America and Asia, the European Union is offering access to an EU open data portal (https://data.europa.eu/euodp/home ). Moreover, the Association of European Research Libraries expects under the H2020 program to increase “the digitization of cultural heritage, digital preservation, research data sharing, open access policies and the interoperability of research infrastructures” (Reilly, 2013).

The challenges posed by Big Data to human and social behavior (Schroeder, 2014) are no less significant to the impact of Big Data on learning. Cohen, Dolan, Dunlap, Hellerstein, & Welton (2009) propose a road map for “more conservative organizations” (p. 1492) to overcome their reservations and/or inability to handle Big Data and adopt a practical approach to the complexity of Big Data. Two Chinese researchers assert deep learning as the “set of machine learning techniques that learn multiple levels of representation in deep architectures (Chen & Lin, 2014, p. 515). Deep learning requires “new ways of thinking and transformative solutions (Chen & Lin, 2014, p. 523). Another pair of researchers from China present a broad overview of the various societal, business and administrative applications of Big Data, including a detailed account and definitions of the processes and tools accompanying Big Data analytics.  The American counterparts of these Chinese researchers are of the same opinion when it comes to “think about the core principles and concepts that underline the techniques, and also the systematic thinking” (Provost and Fawcett, 2013, p. 58). De Mauro, Greco, and Grimaldi (2016), similarly to Provost and Fawcett (2013) draw attention to the urgent necessity to train new types of specialists to work with such data. As early as 2012, Davenport and Patil (2012), as cited in Mauro et al (2016), envisioned hybrid specialists able to manage both technological knowledge and academic research. Similarly, Provost and Fawcett (2013) mention the efforts of “academic institutions scrambling to put together programs to train data scientists” (p. 51). Further, Asomoah, Sharda, Zadeh & Kalgotra (2017) share a specific plan on the design and delivery of a big data analytics course. At the same time, librarians working with data acknowledge the shortcomings in the profession, since librarians “are practitioners first and generally do not view usability as a primary job responsibility, usually lack the depth of research skills needed to carry out a fully valid” data-based research (Emanuel, 2013, p. 207).

Borgman (2015) devotes an entire book to data and scholarly research and goes beyond the already well-established facts regarding the importance of Big Data, the implications of Big Data and the technical, societal, and educational impact and complications posed by Big Data. Borgman elucidates the importance of knowledge infrastructure and the necessity to understand the importance and complexity of building such infrastructure, in order to be able to take advantage of Big Data. In a similar fashion, a team of Chinese scholars draws attention to the complexity of data mining and Big Data and the necessity to approach the issue in an organized fashion (Wu, Xhu, Wu, Ding, 2014).

Bruns (2013) shifts the conversation from the “macro” architecture of Big Data, as focused by Borgman (2015) and Wu et al (2014) and ponders over the influx and unprecedented opportunities for humanities in academia with the advent of Big Data. Does the seemingly ubiquitous omnipresence of Big Data mean for humanities a “railroading” into “scientificity”? How will research and publishing change with the advent of Big Data across academic disciplines?

Reyes (2015) shares her “skinny” approach to Big Data in education. She presents a comprehensive structure for educational institutions to shift “traditional” analytics to “learner-centered” analytics (p. 75) and identifies the participants in the Big Data process in the organization. The model is applicable for library use.

Being a new and unchartered territory, Big Data and Big Data analytics can pose ethical issues. Willis (2013) focusses on Big Data application in education, namely the ethical questions for higher education administrators and the expectations of Big Data analytics to predict students’ success.  Daries, Reich, Waldo, Young, and Whittinghill (2014) discuss rather similar issues regarding the balance between data and student privacy regulations. The privacy issues accompanying data are also discussed by Tene and Polonetsky, (2013).

Privacy issues are habitually connected to security and surveillance issues. Andrejevic and Gates (2014) point out in a decision making “generated by data mining, the focus is not on particular individuals but on aggregate outcomes” (p. 195). Van Dijck (2014) goes into further details regarding the perils posed by metadata and data to the society, in particular to the privacy of citizens. Bail (2014) addresses the same issue regarding the impact of Big Data on societal issues, but underlines the leading roles of cultural sociologists and their theories for the correct application of Big Data.

Library organizations have been traditional proponents of core democratic values such as protection of privacy and elucidation of related ethical questions (Miltenoff & Hauptman, 2005). In recent books about Big Data and libraries, ethical issues are important part of the discussion (Weiss, 2018). Library blogs also discuss these issues (Harper & Oltmann, 2017). An academic library’s role is to educate its patrons about those values. Sugimoto et al (2012) reflect on the need for discussion about Big Data in Library and Information Science. They clearly draw attention to the library “tradition of organizing, managing, retrieving, collecting, describing, and preserving information” (p.1) as well as library and information science being “a historically interdisciplinary and collaborative field, absorbing the knowledge of multiple domains and bringing the tools, techniques, and theories” (p. 1). Sugimoto et al (2012) sought a wide discussion among the library profession regarding the implications of Big Data on the profession, no differently from the activities in other fields (e.g., Wixom, Ariyachandra, Douglas, Goul, Gupta, Iyer, Kulkami, Mooney, Phillips-Wren, Turetken, 2014). A current Andrew Mellon Foundation grant for Visualizing Digital Scholarship in Libraries seeks an opportunity to view “both macro and micro perspectives, multi-user collaboration and real-time data interaction, and a limitless number of visualization possibilities – critical capabilities for rapidly understanding today’s large data sets (Hwangbo, 2014).

The importance of the library with its traditional roles, as described by Sugimoto et al (2012) may continue, considering the Big Data platform proposed by Wu, Wu, Khabsa, Williams, Chen, Huang, Tuarob, Choudhury, Ororbia, Mitra, & Giles (2014). Such platforms will continue to emerge and be improved, with librarians as the ultimate drivers of such platforms and as the mediators between the patrons and the data generated by such platforms.

Every library needs to find its place in the large organization and in society in regard to this very new and very powerful phenomenon called Big Data. Libraries might not have the trained staff to become a leader in the process of organizing and building the complex mechanism of this new knowledge architecture, but librarians must educate and train themselves to be worthy participants in this new establishment.

 

Method

 

The study will be cleared by the SCSU IRB.
The survey will collect responses from library population and it readiness to use and use of Big Data.  Send survey URL to (academic?) libraries around the world.

Data will be processed through SPSS. Open ended results will be processed manually. The preliminary research design presupposes a mixed method approach.

The study will include the use of closed-ended survey response questions and open-ended questions.  The first part of the study (close ended, quantitative questions) will be completed online through online survey. Participants will be asked to complete the survey using a link they receive through e-mail.

Mixed methods research was defined by Johnson and Onwuegbuzie (2004) as “the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts, or language into a single study” (Johnson & Onwuegbuzie, 2004 , p. 17).  Quantitative and qualitative methods can be combined, if used to complement each other because the methods can measure different aspects of the research questions (Sale, Lohfeld, & Brazil, 2002).

 

Sampling design

 

  • Online survey of 10-15 question, with 3-5 demographic and the rest regarding the use of tools.
  • 1-2 open-ended questions at the end of the survey to probe for follow-up mixed method approach (an opportunity for qualitative study)
  • data analysis techniques: survey results will be exported to SPSS and analyzed accordingly. The final survey design will determine the appropriate statistical approach.

 

Project Schedule

 

Complete literature review and identify areas of interest – two months

Prepare and test instrument (survey) – month

IRB and other details – month

Generate a list of potential libraries to distribute survey – month

Contact libraries. Follow up and contact again, if necessary (low turnaround) – month

Collect, analyze data – two months

Write out data findings – month

Complete manuscript – month

Proofreading and other details – month

 

Significance of the work 

While it has been widely acknowledged that Big Data (and its handling) is changing higher education (http://blog.stcloudstate.edu/ims?s=big+data) as well as academic libraries (http://blog.stcloudstate.edu/ims/2016/03/29/analytics-in-education/), it remains nebulous how Big Data is handled in the academic library and, respectively, how it is related to the handling of Big Data on campus. Moreover, the visualization of Big Data between units on campus remains in progress, along with any policymaking based on the analysis of such data (hence the need for comprehensive visualization).

 

This research will aim to gain an understanding on: a. how librarians are handling Big Data; b. how are they relating their Big Data output to the campus output of Big Data and c. how librarians in particular and campus administration in general are tuning their practices based on the analysis.

Based on the survey returns (if there is a statistically significant return), this research might consider juxtaposing the practices from academic libraries, to practices from special libraries (especially corporate libraries), public and school libraries.

 

 

References:

 

Adams Becker, S., Cummins M, Davis, A., Freeman, A., Giesinger Hall, C., Ananthanarayanan, V., … Wolfson, N. (2017). NMC Horizon Report: 2017 Library Edition.

Andrejevic, M., & Gates, K. (2014). Big Data Surveillance: Introduction. Surveillance & Society, 12(2), 185–196.

Asamoah, D. A., Sharda, R., Hassan Zadeh, A., & Kalgotra, P. (2017). Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course. Decision Sciences Journal of Innovative Education, 15(2), 161–190. https://doi.org/10.1111/dsji.12125

Bail, C. A. (2014). The cultural environment: measuring culture with big data. Theory and Society, 43(3–4), 465–482. https://doi.org/10.1007/s11186-014-9216-5

Borgman, C. L. (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press.

Bruns, A. (2013). Faster than the speed of print: Reconciling ‘big data’ social media analysis and academic scholarship. First Monday, 18(10). Retrieved from http://firstmonday.org/ojs/index.php/fm/article/view/4879

Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. McKinsey Quarterly, 56(1), 75–86.

Chen, X. W., & Lin, X. (2014). Big Data Deep Learning: Challenges and Perspectives. IEEE Access, 2, 514–525. https://doi.org/10.1109/ACCESS.2014.2325029

Cohen, J., Dolan, B., Dunlap, M., Hellerstein, J. M., & Welton, C. (2009). MAD Skills: New Analysis Practices for Big Data. Proc. VLDB Endow., 2(2), 1481–1492. https://doi.org/10.14778/1687553.1687576

Daniel, B. (2015). Big Data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904–920. https://doi.org/10.1111/bjet.12230

Daries, J. P., Reich, J., Waldo, J., Young, E. M., Whittinghill, J., Ho, A. D., … Chuang, I. (2014). Privacy, Anonymity, and Big Data in the Social Sciences. Commun. ACM, 57(9), 56–63. https://doi.org/10.1145/2643132

De Mauro, A. D., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122–135. https://doi.org/10.1108/LR-06-2015-0061

De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. AIP Conference Proceedings, 1644(1), 97–104. https://doi.org/10.1063/1.4907823

Dumbill, E. (2012). Making Sense of Big Data. Big Data, 1(1), 1–2. https://doi.org/10.1089/big.2012.1503

Eaton, M. (2017). Seeing Library Data: A Prototype Data Visualization Application for Librarians. Publications and Research. Retrieved from http://academicworks.cuny.edu/kb_pubs/115

Emanuel, J. (2013). Usability testing in libraries: methods, limitations, and implications. OCLC Systems & Services: International Digital Library Perspectives, 29(4), 204–217. https://doi.org/10.1108/OCLC-02-2013-0009

Graham, M., & Shelton, T. (2013). Geography and the future of big data, big data and the future of geography. Dialogues in Human Geography, 3(3), 255–261. https://doi.org/10.1177/2043820613513121

Harper, L., & Oltmann, S. (2017, April 2). Big Data’s Impact on Privacy for Librarians and Information Professionals. Retrieved November 7, 2017, from https://www.asist.org/publications/bulletin/aprilmay-2017/big-datas-impact-on-privacy-for-librarians-and-information-professionals/

Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Ullah Khan, S. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47(Supplement C), 98–115. https://doi.org/10.1016/j.is.2014.07.006

Hwangbo, H. (2014, October 22). The future of collaboration: Large-scale visualization. Retrieved November 7, 2017, from http://usblogs.pwc.com/emerging-technology/the-future-of-collaboration-large-scale-visualization/

Laney, D. (2001, February 6). 3D Data Management: Controlling Data Volume, Velocity, and Variety.

Miltenoff, P., & Hauptman, R. (2005). Ethical dilemmas in libraries: an international perspective. The Electronic Library, 23(6), 664–670. https://doi.org/10.1108/02640470510635746

Philip Chen, C. L., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275(Supplement C), 314–347. https://doi.org/10.1016/j.ins.2014.01.015

Power, D. J. (2014). Using ‘Big Data’ for analytics and decision support. Journal of Decision Systems, 23(2), 222–228. https://doi.org/10.1080/12460125.2014.888848

Provost, F., & Fawcett, T. (2013). Data Science and its Relationship to Big Data and Data-Driven Decision Making. Big Data, 1(1), 51–59. https://doi.org/10.1089/big.2013.1508

Reilly, S. (2013, December 12). What does Horizon 2020 mean for research libraries? Retrieved November 7, 2017, from http://libereurope.eu/blog/2013/12/12/what-does-horizon-2020-mean-for-research-libraries/

Reyes, J. (2015). The skinny on big data in education: Learning analytics simplified. TechTrends: Linking Research & Practice to Improve Learning, 59(2), 75–80. https://doi.org/10.1007/s11528-015-0842-1

Schroeder, R. (2014). Big Data and the brave new world of social media research. Big Data & Society, 1(2), 2053951714563194. https://doi.org/10.1177/2053951714563194

Sugimoto, C. R., Ding, Y., & Thelwall, M. (2012). Library and information science in the big data era: Funding, projects, and future [a panel proposal]. Proceedings of the American Society for Information Science and Technology, 49(1), 1–3. https://doi.org/10.1002/meet.14504901187

Tene, O., & Polonetsky, J. (2012). Big Data for All: Privacy and User Control in the Age of Analytics. Northwestern Journal of Technology and Intellectual Property, 11, [xxvii]-274.

van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society; Newcastle upon Tyne, 12(2), 197–208.

Waller, M. A., & Fawcett, S. E. (2013). Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. Journal of Business Logistics, 34(2), 77–84. https://doi.org/10.1111/jbl.12010

Weiss, A. (2018). Big-Data-Shocks-An-Introduction-to-Big-Data-for-Librarians-and-Information-Professionals. Rowman & Littlefield Publishers. Retrieved from https://rowman.com/ISBN/9781538103227/Big-Data-Shocks-An-Introduction-to-Big-Data-for-Librarians-and-Information-Professionals

West, D. M. (2012). Big data for education: Data mining, data analytics, and web dashboards. Governance Studies at Brookings, 4, 1–0.

Willis, J. (2013). Ethics, Big Data, and Analytics: A Model for Application. Educause Review Online. Retrieved from https://docs.lib.purdue.edu/idcpubs/1

Wixom, B., Ariyachandra, T., Douglas, D. E., Goul, M., Gupta, B., Iyer, L. S., … Turetken, O. (2014). The current state of business intelligence in academia: The arrival of big data. CAIS, 34, 1.

Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering, 26(1), 97–107. https://doi.org/10.1109/TKDE.2013.109

Wu, Z., Wu, J., Khabsa, M., Williams, K., Chen, H. H., Huang, W., … Giles, C. L. (2014). Towards building a scholarly big data platform: Challenges, lessons and opportunities. In IEEE/ACM Joint Conference on Digital Libraries (pp. 117–126). https://doi.org/10.1109/JCDL.2014.6970157

 

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more on big data





Key Issues in Teaching and Learning Survey

The EDUCAUSE Learning Initiative has just launched its 2018 Key Issues in Teaching and Learning Survey, so vote today: http://www.tinyurl.com/ki2018.

Each year, the ELI surveys the teaching and learning community in order to discover the key issues and themes in teaching and learning. These top issues provide the thematic foundation or basis for all of our conversations, courses, and publications for the coming year. Longitudinally they also provide the way to track the evolving discourse in the teaching and learning space. More information about this annual survey can be found at https://www.educause.edu/eli/initiatives/key-issues-in-teaching-and-learning.

ACADEMIC TRANSFORMATION (Holistic models supporting student success, leadership competencies for academic transformation, partnerships and collaborations across campus, IT transformation, academic transformation that is broad, strategic, and institutional in scope)

ACCESSIBILITY AND UNIVERSAL DESIGN FOR LEARNING (Supporting and educating the academic community in effective practice; intersections with instructional delivery modes; compliance issues)

ADAPTIVE TEACHING AND LEARNING (Digital courseware; adaptive technology; implications for course design and the instructor’s role; adaptive approaches that are not technology-based; integration with LMS; use of data to improve learner outcomes)

COMPETENCY-BASED EDUCATION AND NEW METHODS FOR THE ASSESSMENT OF STUDENT LEARNING (Developing collaborative cultures of assessment that bring together faculty, instructional designers, accreditation coordinators, and technical support personnel, real world experience credit)

DIGITAL AND INFORMATION LITERACIES (Student and faculty literacies; research skills; data discovery, management, and analysis skills; information visualization skills; partnerships for literacy programs; evaluation of student digital competencies; information evaluation)

EVALUATING TECHNOLOGY-BASED INSTRUCTIONAL INNOVATIONS (Tools and methods to gather data; data analysis techniques; qualitative vs. quantitative data; evaluation project design; using findings to change curricular practice; scholarship of teaching and learning; articulating results to stakeholders; just-in-time evaluation of innovations). here is my bibliographical overview on Big Data (scroll down to “Research literature”http://blog.stcloudstate.edu/ims/2017/11/07/irdl-proposal/ )

EVOLUTION OF THE TEACHING AND LEARNING SUPPORT PROFESSION (Professional skills for T&L support; increasing emphasis on instructional design; delineating the skills, knowledge, business acumen, and political savvy for success; role of inter-institutional communities of practices and consortia; career-oriented professional development planning)

FACULTY DEVELOPMENT (Incentivizing faculty innovation; new roles for faculty and those who support them; evidence of impact on student learning/engagement of faculty development programs; faculty development intersections with learning analytics; engagement with student success)

GAMIFICATION OF LEARNING (Gamification designs for course activities; adaptive approaches to gamification; alternate reality games; simulations; technological implementation options for faculty)

INSTRUCTIONAL DESIGN (Skills and competencies for designers; integration of technology into the profession; role of data in design; evolution of the design profession (here previous blog postings on this issue: http://blog.stcloudstate.edu/ims/2017/10/04/instructional-design-3/); effective leadership and collaboration with faculty)

INTEGRATED PLANNING AND ADVISING FOR STUDENT SUCCESS (Change management and campus leadership; collaboration across units; integration of technology systems and data; dashboard design; data visualization (here previous blog postings on this issue: http://blog.stcloudstate.edu/ims?s=data+visualization); counseling and coaching advising transformation; student success analytics)

LEARNING ANALYTICS (Leveraging open data standards; privacy and ethics; both faculty and student facing reports; implementing; learning analytics to transform other services; course design implications)

LEARNING SPACE DESIGNS (Makerspaces; funding; faculty development; learning designs across disciplines; supporting integrated campus planning; ROI; accessibility/UDL; rating of classroom designs)

MICRO-CREDENTIALING AND DIGITAL BADGING (Design of badging hierarchies; stackable credentials; certificates; role of open standards; ways to publish digital badges; approaches to meta-data; implications for the transcript; Personalized learning transcripts and blockchain technology (here previous blog postings on this issue: http://blog.stcloudstate.edu/ims?s=blockchain

MOBILE LEARNING (Curricular use of mobile devices (here previous blog postings on this issue:

http://blog.stcloudstate.edu/ims/2015/09/25/mc218-remodel/; innovative curricular apps; approaches to use in the classroom; technology integration into learning spaces; BYOD issues and opportunities)

MULTI-DIMENSIONAL TECHNOLOGIES (Virtual, augmented, mixed, and immersive reality; video walls; integration with learning spaces; scalability, affordability, and accessibility; use of mobile devices; multi-dimensional printing and artifact creation)

NEXT-GENERATION DIGITAL LEARNING ENVIRONMENTS AND LMS SERVICES (Open standards; learning environments architectures (here previous blog postings on this issue: http://blog.stcloudstate.edu/ims/2017/03/28/digital-learning/; social learning environments; customization and personalization; OER integration; intersections with learning modalities such as adaptive, online, etc.; LMS evaluation, integration and support)

ONLINE AND BLENDED TEACHING AND LEARNING (Flipped course models; leveraging MOOCs in online learning; course development models; intersections with analytics; humanization of online courses; student engagement)

OPEN EDUCATION (Resources, textbooks, content; quality and editorial issues; faculty development; intersections with student success/access; analytics; licensing; affordability; business models; accessibility and sustainability)

PRIVACY AND SECURITY (Formulation of policies on privacy and data protection; increased sharing of data via open standards for internal and external purposes; increased use of cloud-based and third party options; education of faculty, students, and administrators)

WORKING WITH EMERGING LEARNING TECHNOLOGY (Scalability and diffusion; effective piloting practices; investments; faculty development; funding; evaluation methods and rubrics; interoperability; data-driven decision-making)

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learning and teaching in this IMS blog
http://blog.stcloudstate.edu/ims?s=teaching+and+learning

scsu library position proposal

Please email completed forms to librarydeansoffice@stcloudstate.edu no later than noon on Thursday, October 5.

According to the email below, library faculty are asked to provide their feedback regarding the qualifications for a possible faculty line at the library.

  1. In the fall of 2013 during a faculty meeting attended by the back than library dean and during a discussion of an article provided by the dean, it was established that leading academic libraries in this country are seeking to break the mold of “library degree” and seek fresh ideas for the reinvention of the academic library by hiring faculty with more diverse (degree-wise) background.
  2. Is this still the case at the SCSU library? The “democratic” search for the answer of this question does not yield productive results, considering that the majority of the library faculty are “reference” and they “democratically” overturn votes, who see this library to be put on 21st century standards and rather seek more “reference” bodies for duties, which were recognized even by the same reference librarians as obsolete.
    It seems that the majority of the SCSU library are “purists” in the sense of seeking professionals with broader background (other than library, even “reference” skills).
    In addition, most of the current SCSU librarians are opposed to a second degree, as in acquiring more qualification, versus seeking just another diploma. There is a certain attitude of stagnation / intellectual incest, where new ideas are not generated and old ideas are prepped in “new attire” to look as innovative and/or 21st
    Last but not least, a consistent complain about workforce shortages (the attrition politics of the university’s reorganization contribute to the power of such complain) fuels the requests for reference librarians and, instead of looking for new ideas, new approaches and new work responsibilities, the library reorganization conversation deteriorates into squabbles for positions among different department.
    Most importantly, the narrow sightedness of being stuck in traditional work description impairs  most of the librarians to see potential allies and disruptors. E.g., the insistence on the supremacy of “information literacy” leads SCSU librarians to the erroneous conclusion of the exceptionality of information literacy and the disregard of multi[meta] literacies, thus depriving the entire campus of necessary 21st century skills such as visual literacy, media literacy, technology literacy, etc.
    Simultaneously, as mentioned above about potential allies and disruptors, the SCSU librarians insist on their “domain” and if they are not capable of leading meta-literacies instructions, they would also not allow and/or support others to do so.
    Considering the observations above, the following qualifications must be considered:
  3. According to the information in this blog post:
    http://blog.stcloudstate.edu/ims/2016/06/14/technology-requirements-samples/
    for the past year and ½, academic libraries are hiring specialists with the following qualifications and for the following positions (bolded and / or in red). Here are some highlights:
    Positions
    digital humanities
    Librarian and Instructional Technology Liaison

library Specialist: Data Visualization & Collections Analytics

Qualifications

Advanced degree required, preferably in education, educational technology, instructional design, or MLS with an emphasis in instruction and assessment.

Programming skills – Demonstrated experience with one or more metadata and scripting languages (e.g.Dublin Core, XSLT, Java, JavaScript, Python, or PHP)
Data visualization skills
multi [ meta] literacy skills

Data curation, helping students working with data
Experience with website creation and design in a CMS environment and accessibility and compliance issues
Demonstrated a high degree of facility with technologies and systems germane to the 21st century library, and be well versed in the issues surrounding scholarly communications and compliance issues (e.g. author identifiers, data sharing software, repositories, among others)

Bilingual

Provides and develops awareness and knowledge related to digital scholarship and research lifecycle for librarians and staff.

Experience developing for, and supporting, common open-source library applications such as Omeka, ArchiveSpace, Dspace,

 

Responsibilities
Establishing best practices for digital humanities labs, networks, and services

Assessing, evaluating, and peer reviewing DH projects and librarians
Actively promote TIGER or GRIC related activities through social networks and other platforms as needed.
Coordinates the transmission of online workshops through Google HangoutsScript metadata transformations and digital object processing using BASH, Python, and XSLT

liaison consults with faculty and students in a wide range of disciplines on best practices for teaching and using data/statistical software tools such as R, SPSS, Stata, and MatLab.

 

In response to the form attached to the Friday, September 29, email regarding St. Cloud State University Library Position Request Form:

 

  1. Title
    Digital Initiatives Librarian
  2. Responsibilities:
    TBD, but generally:
    – works with faculty across campus on promoting digital projects and other 21st century projects. Works with the English Department faculty on positioning the SCSU library as an equal participants in the digital humanities initiatives on campus
  • Works with the Visualization lab to establish the library as the leading unit on campus in interpretation of big data
  • Works with academic technology services on promoting library faculty as the leading force in the pedagogical use of academic technologies.
  1. Quantitative data justification
    this is a mute requirement for an innovative and useful library position. It can apply for a traditional request, such as another “reference” librarian. There cannot be a quantitative data justification for an innovative position, as explained to Keith Ewing in 2015. In order to accumulate such data, the position must be functioning at least for six months.
  2. Qualitative justification: Please provide qualitative explanation that supports need for this position.
    Numerous 21st century academic tendencies right now are scattered across campus and are a subject of political/power battles rather than a venue for campus collaboration and cooperation. Such position can seek the establishment of the library as the natural hub for “sandbox” activities across campus. It can seek a redirection of using digital initiatives on this campus for political gains by administrators and move the generation and accomplishment of such initiatives to the rightful owner and primary stakeholders: faculty and students.
    Currently, there are no additional facilities and resources required. Existing facilities and resources, such as the visualization lab, open source and free application can be used to generate the momentum of faculty working together toward a common goal, such as, e.g. digital humanities.

 

 

 

 

case study

Feagin, J. R., Orum, A. M., & Sjoberg, G. (1991). A Case for the case study. Chapel Hill: University of North Carolina Press.

https://books.google.com/books/about/A_Case_for_the_Case_Study.html?id=7A39B6ZLyJQC

or ILL MSU,M Memorial Library –General Collection HM48 .C37 1991

p. 2 case study is defined as an in-depth

Multi-faceted investigation, using qualitative research methods, of a single social phenomenon.
use of several data sources.

Some case studies have made use of both qualitative and quantitative methods.

Comparative framework.

The social phenomenon can vary: it can be an organization, it can be a role, or role-occupants.

p. 3Quantitative methods: standardized set of q/s

embedded librarian qualifications

qualifications of the embedded librarian: is there any known case for an academic library to employ as embedded librarian a specialist who has both MLIS and terminal degree in a discipline, where he works as embedded librarian.

I also think that we need to be more welcoming to people who may not have come through a traditional education program (i.e., the M.L.S.) but who bring critical skills and new perspectives into the library.
The Changing Roles of Academic and Research Libraries – Higher Ed Careers – HigherEdJobs. (2013). Retrieved from https://www.higheredjobs.com/HigherEdCareers/interviews.cfm?ID=632

“Embedded librarian” is understood as librarians presence in traditional classroom environments and or through LMS.
Then opinions vary: According to Kvienlid (2012), http://www.cclibinstruction.org/wp-content/uploads/2012/02/CCLI2012proceedings_Kvenild.pdf

  1. “Their engagement can be over two or more class sessions, even co-teaching the class in some cases. This model provides in-depth knowledge of student research projects during the research and revision process.” This is for first-year experience students.
  2. Embedding with project teams in Business and STEM programs involves:  “in – depth participation in short – term projects, aiding the team in their searches, literature review, grant preparation, data curation, or other specialized information aspects of the project. This level of embedment requires a heavy time commitment during the length of the project, as well as subject expertise and established trust with the research team.”
  3. embedding in departments as a liaison. 
    “They are usually closely affiliated with the departme nt (maybe even more so than with the libraries) and might be paid out of departmental funds. These librarians learn the ways and needs of their patrons in their natural environment. They often work as finders of information, organizers of information, and taxonomy creators. Embedding within departments provides in – depth knowledge of the users of library services, along with potential isolation from other librarians. It involves a high degree of specialization, co – location and shared responsibility”

best practices, new opptunities (video, screencasts, social media. Adobe Connect) , Assessment

here is Kvenild 2016 article also

Kvenild, C., Tumbleson, B. E., Burke, J. J., & Calkins, K. (2016). Embedded librarianship: questions and answers from librarians in the trenches. Library Hi Tech34(2), 8-11.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dllf%26AN%3d124513010%26site%3dehost-live%26scope%3dsite

utilizing technology tools; and providing information literacy and assessment. Technology tools continue to evolve and change, and most librarians can anticipate using multiple learning management systems over time. There is an ongoing need for professional development in online library instruction and assessment

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Tumbleson, B. E., & Burke, J. (. J. (2013). Embedding librarianship in learning management systems: A how-to-do-it manual for librarians. Neal-Schuman, an imprint of the American Library Association.

http://blog.stcloudstate.edu/ims/2015/05/04/lms-and-embedded-librarianship/

read in red my emphasis on excerpts from that book

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Monroe-Gulick, A., O ’brien, M. S., & White, G. (2013). Librarians as Partners: Moving from Research Supporters to Research Partners. In Moving from Research Supporters to Research Partners. Indianapolis, IN. Retrieved from http://www.ala.org/acrl/sites/ala.org.acrl/files/content/conferences/confsandpreconfs/2013/papers/GulickOBrienWhite_Librarians.pdf

From Supporter to Partner

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Andrews, C. (2014). An Examination of Embedded Librarian Ideas and Practices: A Critical Bibliography.

http://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1000&context=bx_pubs

emphasis is on undergraduate. “a tremendous amount of literature published addressing library/faculty partnerships.”

“There will never be one golden rule when it comes to way in which a librarian networks with faculty on campus.”

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Bobish, G. (2011). Participation and Pedagogy: Connecting the Social Web to ACRL Learning Outcomes. Journal Of Academic Librarianship37(1), 54-63.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3daph%26AN%3d57844282%26site%3dehost-live%26scope%3dsite

https://www.researchgate.net/publication/232382226_Participation_and_Pedagogy_Connecting_the_Social_Web_to_ACRL_Learning_Outcomes

requested through researchgate

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Cahoy, E. S., & Schroeder, R. (2012). EMBEDDING AFFECTIVE LEARNING OUTCOMES IN LIBRARY INSTRUCTION. Communications In Information Literacy6(1), 73-90.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dllf%26AN%3d84110749%26site%3dehost-live%26scope%3dsite

attention must be paid to students’ affective, emotional needs throughout the research
process. My note: And this is exactly what comprise half of my service of. The relatively small amount of research into affective learning, as opposed to cognition, remains true to this day.

p. 78  As the 50-minute one-shot session is still the norm for library research sessions on the
majority of campuses, behavioral assessment can be problematic.

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Cha, T., & Hsieh, P. (2009). A Case Study of Faculty Attitudes toward Collaboration with Librarians to Integrate Information Literacy into the Curriculum. (Chinese). Journal Of Educational Media & Library Sciences46(4), 441-467.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dllf%26AN%3d502982677%26site%3dehost-live%26scope%3dsite

Meanwhile, different attitudes were revealed between teaching higher order thinking skills and lower order thinking skills. Librarian Domain Knowledge, Librarian Professionalism, Curriculum Strategies, and Student Learning were identified as factorial dimensions influencing faculty-librarian collaboration.

two major concerns of “Students Learning” and “Librarian Professionalism” from faculty provide insights that understanding pedagogy, enhancing instructional skills and continuing progress in librarian professionalism will contribute to consolidating partnerships when developing course-specific IL programs.

this proves how much right I am to develophttp://web.stcloudstate.edu/pmiltenoff/bi/

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COVONE, N., & LAMM, M. (2010). Just Be There: Campus, Department, Classroom…and Kitchen?. Public Services Quarterly6(2/3), 198-207. doi:10.1080/15228959.2010.498768

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p. 199 There is also the concept of the ‘‘blended librarian’’ as described by Bell and Shank (2004) to merge the assets and abilities of a librarian with those of one versed in technology. Academic librarians are obligated and privileged to merge several strengths to meet the needs of their user population. No longer is the traditional passive role acceptable. Bell and Shank (2004) implore academic librarians ‘‘to proactively advance their integration into the teaching and learning process’’ (p. 373).

p. 200 first year experience

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Dewey, B. I. (2004). The Embedded Librarian: Strategic Campus Collaborations. Resource Sharing & Information Networks17(1-2), 5-17.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3deric%26AN%3dEJ835947%26site%3dehost-live%26scope%3dsite

p. 6 the imperative for academic librarians to become embedded in the priorities of teaching, learning, and research in truly relevant ways. Embedding as an effective mode of collaboration will be explored through examples relating to the physical and virtual environment. An analysis of current approaches and next steps for the future will be addressed, with the goal of providing food for thought as librarians assess programs and activities in terms of positive collaboration and effectiveness

p. 9  new academic salon,
p. 10 the pervasive campus librarian
The fact that we are generalists and devoted to all disciplines and all sectors of the academic user community gives us a special insight on ways to advance the university and achieve its mission

this contradicts Shumaker and Talley, who assert that the embedded librarian is NOT a generalist, but specialist

p. 11 Central administrators, along with the chief academic officer, make critical funding and policy decisions affecting the library

p. 11 librarians and teaching.
In 2011, interim dean Ruth Zietlow “gave up” classes after the messy divorce with CIM. the library faculty poled itself to reveal that a significant number of the faculty does NOT want to teach.

p. 14 influencing campus virtual space
this library’s social media is imploded in its image.

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DREWES, K., & HOFFMAN, N. (2010). Academic Embedded Librarianship: An Introduction. Public Services Quarterly6(2/3), 75-82. doi:10.1080/15228959.2010.498773

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p. 75 Literature about embedded librarianship is so diverse that the definition of this term, as well as related goals and methods when embedding services and programs, can be difficult to define. What are some charateristics of an embedded program? Is embedding only achieved through an online classroom? How did embedded librarianship first begin in academic libraries?

p. 76 adopted as a term because it is a similar concept to embedded journalism.
Embedded librarian programs often locate librarians involved in the spaces of their users and colleagues, either physically or through technology, in order to become a part of their users’ culture. A librarian’s physical and metaphorical location is often what defines them as embedded.

David Shumaker and Mary Talley (see bottom of this blog entry)

Highly technical tasks, such as creating information architecture, using analytical software, and computer and network systems management were performed by less than 20% of the survey respondents. Shumaker and Talley also report embedded services are often found in tandem with specialized funding. This study also confirms embedded services are not new.

p. 77 history and evolution of the role

p. 79 methods of embedding

In North America, one would be hard-pressed to find a library that does not already electronically embed services into online reference chat, make use of Web 2.0 communication applications such as Twitter and blogs, and embed librarians and collaborators within online classrooms. These are all examples of the embedding process (Ramsay & Kinnie, 2006). The name embedded librarian in this context is a double entendre, as the insertion of widgets and multimedia files into HTML code when designing Web sites is usually called the embedding of the file.
My note: is this library actually is one that does not use Twitter and blogs in the hard-core meaning of library service

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Essinger, C. c., & Ke, I. i. (2013). Outreach: What Works?. Collaborative Librarianship5(1), 52-58.

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Recommendations:
The authors distributed their findings at a half day workshop attended by nearly all liaisons. They made the following recommendations:

  • • Personalize outreach.
  • • Spend more time marketing and reaching out to departments, even though it might mean having less time for other activities.
  • • Find an alternative advocate who can build your reputation through word-ofmouth if your relationship with your assigned department liaison is not fruitful.
  • • Seek opportunities to meet department staff in person.
  • • As much as possible, administrators should commit to keeping liaisons assignments static.

p. 57 that faculty outreach is similar to other types of relationship building: it requires time to establish trust, respect and appreciation on both sides. Even a liaison’s challenging first two years can, therefore, be viewed as productive because the relationship is developing in the background. This phenomenon also signals to library administrators the benefits of maintaining a stable workforce. Frequent changes in academic assignments and staff changes can lead to a less engaged user population, and also make the outreach assignment much more frustrating.

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Heider, K. L. (2010). Ten Tips for Implementing a Successful Embedded Librarian Program. Public Services Quarterly6(2-3), 110-121.

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embedded librarian program in the university’s College of Education and Educational Technology

p. 112 Make Sure You Have Buy-in from All Stakeholders

Include College=Department Faculty in the Interview Process

Look for the Following Qualities=Qualifications in an Embedded Librarian

Have a Physical Presence in the College=Department a Few Days Each Week

Serve as Bibliographer to College=Department

Offer Bibliographic Instruction Sessions and Guest Lectures at Main Campus, Branch Campuses, and Centers

Develop Collaborative Programs that Utilize the Library’s Resources for College=Department Improvement

#9 Offer to Teach Credit Courses for the College=Department When Department Faculty Are Not Available

#10: Publish Scholarly Works and Present at Professional Conferences with College=Department Faculty. again, Martin Lo, John Hoover,

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Hollister, C. V. (2008). Meeting Them where They Are: Library Instruction for Today’s Students in the World Civilizations Course. Public Services Quarterly4(1), 15-27.

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history and library. My note: can you break the silo in the history department? http://blog.stcloudstate.edu/ims/2017/05/01/history-becker/ 

world civilizations course

Faculty come to the world civilizations enterprise from a broad range of academic disciplines and world experiences, which has a significant impact on their interpretations of world history, their selections of course materials, their teaching styles, and their expectations for students. Moreover, faculty teach the course on a rotating basis. So, there is no single model of faculty-librarian collaboration that can be applied from section to section, or even from semester to semester. Faculty have widely differing views on the role of library instruction in their sections of the course, and the extent to which library research is required for coursework. They also differ in terms of their ability or willingness to collaborate with the libraries. As a result, student access to library instruction varies from section to section.

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Kesselman, M. A., & Watstein, S. B. (2009). Creating Opportunities: Embedded Librarians. Journal Of Library Administration49(3), 383-400.

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p. 384 embedded librarians in the blogosphere.
not even close to the local idea how blog must be used  for library use.

p. 387 definitions

p. 389 clinical librarianship – term from the 1970s.

p. 390 Special librarians and particularly those in corporate settings tend to be more integrated within the company they serve and are often instrumental in cost-related services such as competitive intelligence, scientific, and patent research.

p. 391 Librarians Collaborating With Faculty in Scholarly Communication Activities

My note: this is what I am doing with Martin Lo and used to do with John Hoover. Attempts with the sociology department, IS department

p. 392 Role of Librarians With Multidisciplinary Collaborations

my note : my work with Mark Gill and Mark Petzhold

p. 393 social media
again, this library cannot be farther from the true meaning of Web 2.0 collaboration.

p. 396 organizational structures

Three different types of organizational structures are generally recognized—hierarchical, matrix, and flat. We suggest that each of these conventional structures promotes, to some extent, its own brand of silos—silos that inherently pose obstacles to the assumption of new roles and responsibilities. For example, we question whether the hierarchical organization structures that define many of our libraries, with their emphasis on line, lateral staff and functional relationships and the relative ranks of parts and positions or jobs, are flexible enough to support new roles and responsibilities. In contrast, matrix management offers a different type of organizational management model in which people with similar skills are pooled for work assignments. We suggest that, in contrast to hierarchical structures, matrix management allows team members to share information more readily across task boundaries and allows for specialization that can increase depth of knowledge and allow professional development and career progression to be managed. The third organizational structure mentioned—flat or horizontal organizations, refers to an organizational structure with few or no levels of intervening management between staff and managers

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Kobzina, N. G. (2010). A Faculty—Librarian Partnership: A Unique Opportunity for Course Integration. Journal Of Library Administration50(4), 293-314.

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my LIB 290 is such class. and I am the only one who is teaching it online by QM standards.
Can the administration encourage Global Studies to combine efforts with my LIB 290 and offer a campus-wide class?

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Lange, J. j., Canuel, R. r., & Fitzgibbons, M. m. (2011). Tailoring information literacy instruction and library services for continuing education. Journal Of Information Literacy5(2), 66-80.

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McGill. p. 77 The McGill University Library’s system-wide liaison model emphasises a disciplinary approach, placing the impetus for outreach and service on individual librarians responsible for particular departments and user groups.

 

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MCMILLEN, P., & FABBI, J. (2010). How to Be an E3 Librarian. Public Services Quarterly6(2/3), 174-186. doi:10.1080/15228959.2010.497454

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ILL

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Meyer, N. J., & Miller, I. R. (2008). The Library as Service-Learning Partner: A Win-Win Collaboration with Students and Faculty. College & Undergraduate Libraries15(4), 399-413.

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ILL

I did something similar with Keith Christensen in 2012: http://bit.ly/SCSUlibGame, yet again, blocked for further consideration

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Niles, P. (2011). Meeting the Needs of the 21st Century Student. Community & Junior College Libraries17(2), 47-51.

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about Millennials

millennials. p. 48 my note: the losing battle of telling the millennials the value of books

librarians need to emphasize that not all information
is found on the Web and that the information found there might not be
reliable, depending on its source

p. 49 The latest technology can be used for communication. Two examples of this modernization process are making podcasts of library lectures and using instant messaging to answer reference queries. Students need Reference Librarians to assist them in focusing their research, showing them appropriate sources and how to use those sources. The change is not how the librarians serve the students but how the service is delivered. Instead of coming to the reference desk Millennial students may choose to use e-mail, cell phones to send a text message or use a chat reference service to communicate with the librarian. Students want to have 24/7 access to library resources and librarians.

my note: and yet this library still uses 90ish communication – the facebook page is just an easy to edit web page and the concept of Web 2.0 has not arrived or shaped the current communication.

p. 50 Librarians should examine how they present library instruction and ensure that students know why it is important. Further, Lancaster and Stillman state that librarians need to “incorporate some computer-based instruction for Millennials as it allows them to go at their own speed and acknowledges their ability to manage information” (2003, 231).
and, once again, talking about inducing library instruction with technology: http://web.stcloudstate.edu/pmiltenoff/bi/

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Oakleaf, M., & VanScoy, A. (2010). Instructional Strategies for Digital Reference: Methods to Facilitate Student Learning. Reference & User Services Quarterly49(4), 380-390.

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constructivism, social constructivism, active learning

they have a graph about metagcognition. I wish, they had found place for metaliteracy also

p. 383. #5 Let them drive. this is EXACTLY what I am offering with:http://web.stcloudstate.edu/pmiltenoff/bi/
build their own construct

p. 386 my work with the doctoral cohorts:

In the current climate of educational accountability, reference librarians should embrace the opportunity to align reference service with the teaching and learning missions of their libraries and overarching institutions

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Rao, S., Cameron, A., & Gaskin-Noel, S. (2009). Embedding General Education Competencies into an Online Information Literacy Course. Journal Of Library Administration49(1/2), 59-73.

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online programs a 3-credit junior seminar course (JRSM 301) to assess general education competencies

p. 60 The 3-credit course titled LISC 260—Using Electronic Resources for Research has existed as a required course for this overseas cohort of students since the fall of 1999. The course was initially developed as a required course to introduce the Mercy College Libraries’ resources to this cohort of overseas students. Full-time librarians teach this course as an overload.

The course lasts for 8 weeks during fall and spring semesters and is divided into eight modules with five quizzes. Summer sessions are shorter; the summer version of the course runs for 6 weeks. There is no midterm exam, final exam, project, or term paper for this course. Sixty percent of the grade is based on the quizzes and assignments and 40% on discussion and class participation.

Each quiz addresses a specific competency. We identified the modules where the five competencies would fit best. A document containing the five general education competencies (critical thinking, information literacy, quantitative reasoning, critical reading, and writing) statements

Critical Thinking Competency This competency was placed in the second module covering the topic “Developing Search Strategies” in the second week of the course. In this module, students are required to select a topic and develop logical terminologies and search strings. This task requires a great deal of critical and analytical thinking and therefore lays the groundwork for the other competencies. The quizzes and assignments for this competency involve breaking or narrowing down the topic into subtopics, comparing two topics or ideas, and similar skills. It is hoped that students will be able to adopt Boolean and other search logic in clear and precise ways in their analyses and interpretations of their topic and use the search strategies they develop for continued assignments throughout the rest of the course.

p. 61. Information Literacy Competency The information literacy competency is introduced in the fourth module in the fourth week of the course. As part of the course, students are required to learn about the Mercy College Libraries’ indexes and databases, which this module addresses (“Information Literacy,” n.d.).

Quantitative Reasoning Competency

This seminar course is a library research course with no statistics or mathematics component. Many students enrolled in the course are not mathematics or statistics majors, hence some creativity was needed to evaluate their mathematical and computational skills. Students are given this competency in the fifth module during the fifth week of the course, which deals with subject-specific sources. It was decided that, to assess this competency, a quiz analyzing data obtained in a tabular format from one of the databases subscribed to by the library would fulfill the requirement. Students are given a choice of various countries and related data, and are asked to create some comparative demographic profiles. This approach has worked well because it gives students the opportunity to focus on countries and data that interest them.

 

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Abrizah, A., Inuwa, S., & Afiqah-Izzati, N. (2016). Systematic Literature Review Informing LIS Professionals on Embedding Librarianship Roles. Journal Of Academic Librarianship42(6), 636-643. doi:10.1016/j.acalib.2016.08.010

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requested through research gate

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Summey, T. P., & Kane, C. A. (2017). Going Where They Are: Intentionally Embedding Librarians in Courses and Measuring the Impact on Student Learning. Journal Of Library & Information Services In Distance Learning11(1/2), 158-174. doi:10.1080/1533290X.2016.1229429

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a pilot project utilizing a variety of methods.

p. 158 The concept of embedded librarians is not new, as it has antecedents in branch librarians of the seventies and academic departmental liaisons of the 1980s and 1990s. However, it is a way to proactively reach out to the campus community (Drewes & Hoffman, 2010).

There is not a one-size-fits-all definition for embedded librarianship. As a result, librarians in academic libraries may be embedded in their communities in a variety of ways and at varying levels from course integrated instruction to being fully embedded as a member of an academic department

p. 160 my note: the authors describe the standard use of LMS for embedded librarianship.

p. 163 they managed to fight out and ensure their efforts are “credited.” Assigning credits to embedded librarian activities can be a very tough process.

p. 165  assessment

the authors utilized a pre-module and post-module survey to assess the students’ performance using library resources. The survey also helped to determine the students’ perceived self-efficacy and confidence in using the library, its resources, and services. In addition, the researchers analyzed student responses to discussion questions, studied feedback at the end of the course in the course discussion forum, and conducted interviews with the faculty members teaching the courses (

In another study, researchers analyzed bibliographies of students in the course to identify what resources they cited in their research projects. More specifically, they analyzed the type and appropriateness of sources used by the students, their currency, and noting how deeply the students delved into their topics. They also looked at the number of references cited. The authors believed that examining the bibliographies provided an incomplete picture because it provided data on the sources selected by the students but not information on how they retrieved those sources.

p. 171 survey sample

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Wu, L., & Thornton, J. (2017). Experience, Challenges, and Opportunities of Being Fully Embedded in a User Group. Medical Reference Services Quarterly36(2), 138-149. doi:10.1080/02763869.2017.1293978

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this is somehow close to my role with the EDAD

Texas A&M University academic health sciences library integrating a librarian into the College of Pharmacy, approximately 250 miles away from the main library. preembedded and postembedded activities demonstrated the effectiveness and impact of

For this study, the fully embedded librarian is defined as one who is out of the traditional library and into an onsite setting to provide a full range of library services that enable collaboration with researchers or teaching faculty and support student learning. In this model, the embedded librarian is a team member of the RCOP rather than a service provider standing apart. The lines are not blurred as to the kind of services that should be embedded because the embedded librarian is 100% onsite. Very few reports in the literature describe fully embedded librarian models such as this. However, one similar model exists at the Arizona Health Sciences Library (AHSL), which is affiliated with the University of Arizona, where librarians relocated their permanent offices to the colleges of Nursing, Public Health, and Pharmacy. AHSL librarians spent close to 100% of their time in the colleges.

p. 144 The embedded librarian has gained recognition in the college and was appointed by the dean to serve on the Instructional Venues Ad Hoc Committee (IVC).

My note: This is what Tom Hergert and I have been advocating for years: the role of the librarian is not to find info and teach how to find info ONLY. The role of the librarian is to bring 21st century to School of Education: information literacy is only a fragment of metaliteracies. Information literacy is a 1990s priority. While it is still an important part of librarians goals, digital literacy, visual and media literacy, as well as technology literacy and pedagogical application of technology is imposed as integral part of the work of the mebedded librarian.

p. 145 Challenges and Opportunities

Another challenge involved the librarian’s decision-making and effective communications skills, especially when deciding to implement library services or programs. Other challenges included speaking the client group’s language and knowing the information needs of each group—faculty, students, staff, postdocs, research assistants, and research scientists—to deliver the right information at the point of need. The following strategies were practiced to overcome these challenges: .

  • A positive attitude can increase connectivity, networking, and collaboration beyond a limited space. Proactively seeking opportunities to participate and get involved in library events, instructional programs, training workshops, or committee work shortened the distance between the remote librarian and those in main campus. .
  • As video conferencing tools or programs (e.g., Adobe Connnect, Webex, Skype, Google Hangout, Zoom) were the primary means for the remote at 18:19 24 August 2017 librarian to attend library meetings and teach in library instructional programs, spending some time learning to use these tools and embracing them greatly increased the librarian’s capacity to overcome the feelings of disconnection.
  • The willingness to travel several times a year to the main campus to meet librarians face-to-face helped in understanding the system and in getting help that seemed complicated and difficult via remote resources (e.g., computer issues). .
  • Actively listening to the faculty and students during the conversations helped understand their information needs. This served as the basis to initiate any targeted library services and programs.

Despite the challenges, the embedded librarian was presented with numerous opportunities that a traditional librarian might think impossible or difficult to experience, for example, attending RCOP department meetings or RCOP executive committee meetings to present library resources and services, serving on RCOP committees, co-teaching with faculty in RCOP credit courses, creating and grading assignments counting toward total course credits, and being given access to all RCOP course syllabi in eCampus. (the last is in essence what I am doing right now)

p. 147 Marketing Embedded Library Services

The “What’s in It for Me” (WIIFM) principle1 was a powerful technique to promote embedded library services. The essentials of WIIFM are understanding patron needs and ensuring the marketing effort or communications addressing those needs15—in other words, always telling patrons what is in it for them when promoting library services and resources. Different venues were used to practice WIIFM: .

  • RCOP faculty email list was an effective way to reach out to all the faculty. An email message at the beginning of a semester to the faculty highlighted the embedded librarian’s services. During the semester, the librarian communicated with the faculty on specific resources and services addressing their needs, such as measuring their research impact at the time of their annual evaluation, sharing grant funding resources, and promoting MSL’s resources related to reuse of images. .
  • Library orientations to new students and new faculty allowed the librarian to focus on who to contact for questions and help, available resources, and ways to access them. . Being a guest speaker for the monthly RCOP departmental faculty meetings provided another opportunity for the librarian to promote services and resources.
  • Casual conversations with faculty, students, researchers, and postdocs in the hallway, at staff luncheons, and at RCOP events helped understand their information needs, which helped the librarian initiate MSL service projects and programs.
  • The Facebook private group, created by Instructional Technology & MSL Resources @ Rangel COP, was used to announce MSL resources and services. The group currently has 256 members. The librarian is one of the group administrators who answers student questions related to library and MSL resources. (social media is my forte)

p. 148 This model would not have been successful without the strong support from MSL leadership team and the RCOP administration.

the next step would be to conduct a systematic assessment to get feedback from RCOP administrators, faculty, students, staff, postdocs, and research assistants. The integration of the library instructional program into the RCOP curriculum should be included in RCOP final course evaluations. Another future direction might be to conduct a curriculum map to get a better idea about the learning objectives of each course and to identity information literacy instruction needs across the curriculum. The curriculum mapping might also help better structure library instruction delivery to RCOP. Teaching content might be structured more purposefully and logically sequenced across the curriculum to ensure that what students have learned in one course prepares them for the next ones.

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Blake, L., Ballance, D., Davies, K., Gaines, J. K., Mears, K., Shipman, P., & … Burchfield, V. (2016). Patron perception and utilization of an embedded librarian program. Journal Of The Medical Library Association104(3), 226-230. doi:10.3163/1536-5050.104.3.008

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The overall satisfaction with services was encouraging, but awareness of the embedded program was low, suggesting an overall need for marketing of services.

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Tumbleson, B. E. (2016). Collaborating in Research: Embedded Librarianship in the Learning Management System. Reference Librarian57(3), 224-234. doi:10.1080/02763877.2015.1134376

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O’Toole, E., Barham, R., & Monahan, J. (2016). The Impact of Physically Embedded Librarianship on Academic Departments. Portal: Libraries & The Academy16(3), 529-556.

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Agrawal, P. p., & Kumar, A. (2016). Embedded Librarianship and Academic Setup: Going beyond the library stockades. International Journal Of Information Dissemination & Technology6(3), 170-173.

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India. p. 173 as of today, most of the users are not able to differentiate the library professional who have a bachelor degree, Masters degree and who are doctorate of the subject. My note: not in my case and this is my great advantage.

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Madden, H., & Rasmussen, A. M. (2016). Embedded Librarianship: Einbindung von Wissenschafts- und Informationskompetenz in Schreibkurse / Ein US-amerikanisches Konzept. Bub: Forum Bibliothek Und Information68(4), 202-205.

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ILL

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Delaney, G., & Bates, J. (2015). Envisioning the Academic Library: A Reflection on Roles, Relevancy and Relationships. New Review Of Academic Librarianship21(1), 30-51. doi:10.1080/13614533.2014.911194

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overview of the literature on embedded librarianship

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Freiburger, G., Martin, J. R., & Nuñez, A. V. (2016). An Embedded Librarian Program: Eight Years On. Medical Reference Services Quarterly35(4), 388-396. doi:10.1080/02763869.2016.1220756

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close to my role with the doctoral cohorts

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Wilson, G. (2015). The Process of Becoming an Embedded Curriculum Librarian in Multiple Health Sciences Programs. Medical Reference Services Quarterly34(4), 490-497. doi:10.1080/02763869.2015.1082386

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ILL

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Milbourn, A. a. (2013). A Big Picture Approach: Using Embedded Librarianship to Proactively Address the Need for Visual Literacy Instruction in Higher Education. Art Documentation: Bulletin Of The Art Libraries Society Of North America32(2), 274-283.

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visual literacy – this is IMS area, which was de facto shot off by the omnipotence of “information literacy”

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Talley, M. (2007). Success and the Embedded Librarian. https://www.sla.org/wp-content/uploads/2013/05/Success_and_the_Embedded.pdf

Shumaker, D., Talley, M. Models of Embedded Librarianship: A Research Summary. https://www.sla.org/wp-content/uploads/2013/05/Models_of_Embedded.pdf

Shumaker, D., Talley, M. (2009). Models of Embedded Librarianship. Final Report.  Prepared under the Special Libraries Association Research Grant 2007. https://embeddedlibrarian.files.wordpress.com/2009/08/executivesummarymodels-of-embedded-librarianship.pdf

Shumaker, D. (2013). Embedded Librarianship: Digital World Future? http://www.infotoday.com/CIL2013/session.asp?ID=W30

Modelsof embeddedlibrarianship presentation_final_mt61509 from MaryTalley
slide 8: vision of embedded librarianship:
customer centric not library centric; located in their workplace not our workplace; focused on small groups not entire populations; composed of specialists, not generalists; dependent on domain knowledge not only library skills; aming an analysis and synthesis not simply delivery; in context, not out of context; built on trusted advice not service delivery
all of the above is embodied in my work with the doctoral cohorts
slide 9: why study? because traditional library service model is in decline
slide 11: broad analytical research on successful implementation is lacking
slide 20: large institutions more likely to offer specialized services
slide 21: domain knowledge through continuous learning, not always through formal degrees.
slide 39: what matters most
slide 40: strong leadership by library managers is critical (I will add here “by deans of other colleges)
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bibliography:

Abrizah, A., Inuwa, S., & Afiqah-Izzati, N. (2016). Systematic Literature Review Informing LIS Professionals on Embedding Librarianship Roles. Journal Of Academic Librarianship42(6), 636-643. doi:10.1016/j.acalib.2016.08.010

Agrawal, P. p., & Kumar, A. (2016). Embedded Librarianship and Academic Setup: Going beyond the library stockades. International Journal Of Information Dissemination & Technology6(3), 170-173.

Andrews, C. R. (2014). CUNY Academic Works An Examination of Embedded Librarian Ideas and Practices: A Critical Bibliography. An Examination of Embedded Librarian Ideas and Practices: A Critical Bibliography. Codex, 3(1), 2150–86. Retrieved from http://academicworks.cuny.edu/bx_pubs

Blake, L., Ballance, D., Davies, K., Gaines, J. K., Mears, K., Shipman, P., & … Burchfield, V. (2016). Patron perception and utilization of an embedded librarian program. Journal Of The Medical Library Association104(3), 226-230. doi:10.3163/1536-5050.104.3.008

Bobish, G. (2011). Participation and Pedagogy: Connecting the Social Web to ACRL Learning Outcomes. Journal Of Academic Librarianship37(1), 54-63.

Cahoy, E. S., & Schroeder, R. (2012). EMBEDDING AFFECTIVE LEARNING OUTCOMES IN LIBRARY INSTRUCTION. Communications In Information Literacy6(1), 73-90.

Cha, T., & Hsieh, P. (2009). A Case Study of Faculty Attitudes toward Collaboration with Librarians to Integrate Information Literacy into the Curriculum. (Chinese). Journal Of Educational Media & Library Sciences46(4), 441-467.

COVONE, N., & LAMM, M. (2010). Just Be There: Campus, Department, Classroom…and Kitchen?. Public Services Quarterly6(2/3), 198-207. doi:10.1080/15228959.2010.498768

Delaney, G., & Bates, J. (2015). Envisioning the Academic Library: A Reflection on Roles, Relevancy and Relationships. New Review Of Academic Librarianship21(1), 30-51. doi:10.1080/13614533.2014.911194

Dewey, B. I. (2004). The Embedded Librarian: Strategic Campus Collaborations. Resource Sharing & Information Networks17(1-2), 5-17.

DREWES, K., & HOFFMAN, N. (2010). Academic Embedded Librarianship: An Introduction. Public Services Quarterly6(2/3), 75-82. doi:10.1080/15228959.2010.498773

Essinger, C. c., & Ke, I. i. (2013). Outreach: What Works?. Collaborative Librarianship5(1), 52-58.

Freiburger, G., Martin, J. R., & Nuñez, A. V. (2016). An Embedded Librarian Program: Eight Years On. Medical Reference Services Quarterly35(4), 388-396. doi:10.1080/02763869.2016.1220756

Heider, K. L. (2010). Ten Tips for Implementing a Successful Embedded Librarian Program. Public Services Quarterly6(2-3), 110-121.

Hollister, C. V. (2008). Meeting Them where They Are: Library Instruction for Today’s Students in the World Civilizations Course. Public Services Quarterly4(1), 15-27.

Kesselman, M. A., & Watstein, S. B. (2009). Creating Opportunities: Embedded Librarians. Journal Of Library Administration49(3), 383-400.

Kobzina, N. G. (2010). A Faculty—Librarian Partnership: A Unique Opportunity for Course Integration. Journal Of Library Administration50(4), 293-314.

Kvenild, C. (n.d.). The Future of Embedded Librarianship: Best Practices and Opportunities. Retrieved from http://www.cclibinstruction.org/wp-content/uploads/2012/02/CCLI2012proceedings_Kvenild.pdf

Lange, J. j., Canuel, R. r., & Fitzgibbons, M. m. (2011). Tailoring information literacy instruction and library services for continuing education. Journal Of Information Literacy5(2), 66-80.

Madden, H., & Rasmussen, A. M. (2016). Embedded Librarianship: Einbindung von Wissenschafts- und Informationskompetenz in Schreibkurse / Ein US-amerikanisches Konzept. Bub: Forum Bibliothek Und Information68(4), 202-205.

MCMILLEN, P., & FABBI, J. (2010). How to Be an E3 Librarian. Public Services Quarterly6(2/3), 174-186. doi:10.1080/15228959.2010.497454

Meyer, N. J., & Miller, I. R. (2008). The Library as Service-Learning Partner: A Win-Win Collaboration with Students and Faculty. College & Undergraduate Libraries15(4), 399-413.

Milbourn, A. (2013). A Big Picture Approach: Using Embedded Librarianship to Proactively Address the Need for Visual Literacy Instruction in Higher Education. Art Documentation: Bulletin Of The Art Libraries Society Of North America32(2), 274-283.

The Changing Roles of Academic and Research Libraries – Higher Ed Careers – HigherEdJobs. (2013). Retrieved from https://www.higheredjobs.com/HigherEdCareers/interviews.cfm?ID=632

Niles, P. (2011). Meeting the Needs of the 21st Century Student. Community & Junior College Libraries17(2), 47-51.

Oakleaf, M., & VanScoy, A. (2010). Instructional Strategies for Digital Reference: Methods to Facilitate Student Learning. Reference & User Services Quarterly49(4), 380-390.

O’Toole, E., Barham, R., & Monahan, J. (2016). The Impact of Physically Embedded Librarianship on Academic Departments. Portal: Libraries & The Academy16(3), 529-556.

Rao, S., Cameron, A., & Gaskin-Noel, S. (2009). Embedding General Education Competencies into an Online Information Literacy Course. Journal Of Library Administration49(1/2), 59-73.

Shumaker, D., Talley, M. Models of Embedded Librarianship: A Research Summary. https://www.sla.org/wp-content/uploads/2013/05/Models_of_Embedded.pdf

Shumaker, D., Talley, M. (2009). Models of Embedded Librarianship. Final Report.  Prepared under the Special Libraries Association Research Grant 2007. https://embeddedlibrarian.files.wordpress.com/2009/08/executivesummarymodels-of-embedded-librarianship.pdf

Shumaker, D. (2013). Embedded Librarianship: Digital World Future? http://www.infotoday.com/CIL2013/session.asp?ID=W30

Summey, T. P., & Kane, C. A. (2017). Going Where They Are: Intentionally Embedding Librarians in Courses and Measuring the Impact on Student Learning. Journal Of Library & Information Services In Distance Learning11(1/2), 158-174. doi:10.1080/1533290X.2016.1229429

Talley, M. (2007). Success and the Embedded Librarian. https://www.sla.org/wp-content/uploads/2013/05/Success_and_the_Embedded.pdf

Tumbleson, B. E., & Burke, J. (John J. . (2013). Embedding librarianship in learning management systems : a how-to-do-it manual for librarians. Retrieved from http://www.worldcat.org/title/embedding-librarianship-in-learning-management-systems-a-how-to-do-it-manual-for-librarians/oclc/836261183

Tumbleson, B. E. (2016). Collaborating in Research: Embedded Librarianship in the Learning Management System. Reference Librarian57(3), 224-234. doi:10.1080/02763877.2015.1134376

Wilson, G. (2015). The Process of Becoming an Embedded Curriculum Librarian in Multiple Health Sciences Programs. Medical Reference Services Quarterly34(4), 490-497. doi:10.1080/02763869.2015.1082386

Wu, L., & Thornton, J. (2017). Experience, Challenges, and Opportunities of Being Fully Embedded in a User Group. Medical Reference Services Quarterly36(2), 138-149. doi:10.1080/02763869.2017.1293978

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more about embedded librarian in this IMS blog
http://blog.stcloudstate.edu/ims?s=embedded+librarian

intro to stat modeling

Introduction to Statistical Modelling (bibliography)

These are the books available at the SCSU library with their call #s:

Graybill, F. A. (1961). An introduction to linear statistical models. New York: McGraw-Hill. HA29 .G75

Dobson, A. J. (1983). Introduction to statistical modelling. London ; New York: Chapman and Hall. QA276 .D59 1983

Janke, S. J., & Tinsley, F. (2005). Introduction to linear models and statistical inference. Hoboken, NJ: Wiley. QA279 .J36 2005

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resources from the Internet:

visuals (quick reference to terms and issues)

consider this short video:
http://blog.stcloudstate.edu/ims/2017/07/06/misleading-graphs/

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more on quantitative and qualitative research in this IMS blog
http://blog.stcloudstate.edu/ims?s=quantitative
http://blog.stcloudstate.edu/ims?s=qualitative+research

digital assessment literacy

Eyal, L. (2012). Digital Assessment Literacy — the Core Role of the Teacher in a Digital Environment. Journal Of Educational Technology & Society, 15(2), 37-49.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3daph%26AN%3d76559253%26site%3dehost-live%26scope%3dsite

Common to all is a view of the level of literacy as a measure of the quality of human capital of a society or a particular area. Literacy develops in interaction with the environment (Vygotsky, 1987).

digital assessment literacy refers to the role of the teacher as an assessor in a technology-rich environment.

Learning Management Systems (LMS) benefits and limitations

Measurement allows quantitative description of a particular characterization of an individual, expressed in numbers.

the combination of assessment and measurement provides a thorough and accurate picture, based upon which practical conclusions can be drawn (Wagner, 1997). A test is a systematic process in which an aspect of student behavior is quantitatively evaluated (Suen & Parkes, 2002).

For several decades this system of assessment has been criticized for a variety of reasons, including the separation between the teaching-learning process and the evaluation process, the relatively low level of thinking required, and the quantitative reporting of results, which does not contribute to students’ progress. In the last decade, the central argument against the tests system is that their predictability is limited to the field and context in which the students are tested, and that they do not predict student problem solving ability, teamwork, good work habits and honesty.

teachers mistakenly believe that repeating lessons will improve students’ achievements.

To evaluate how well the goals were achieved, objective measurement methods are employed (Black, et al., 2004).

Eshet- Alkalai (2004) offered a detailed conceptual framework for the term ‘digital literacy’ that includes: photo-visual thinking; reproduction thinking; branching thinking; information thinking; and socio-emotional thinking.

Eshet-Alkalai, Y. (2004). Digital literacy: A conceptual framework for survival skills in the digital era. Journal of Educational Multimedia and Hypermedia, 13(1), 93–106.

Eshet-Alkalai, Y., & Chajut, E. (2009). Changes Over Time in Digital Literacy. Cyberpsychology & Behavior, 12(6), 713-715. doi:10.1089/cpb.2008.0264

two major patterns of change over time: (a) closing the gap between younger and older participants in the tasks that emphasize profi- ciency and technical control and (b) widening the gap between younger and older participants in tasks that emphasize creativity and critical thinking. Based on the comparison with the matched control groups, we suggest that experience with technology, and not age, accounts for the observed lifelong changes in digital literacy skills

Eshet-Alkalai, Y., & Soffer, O. (2012). Guest Editorial – Navigating in the Digital Era: Digital Literacy: Socio-Cultural and Educational Aspects. Journal Of Educational Technology & Society, 15(2), 1.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3daph%26AN%3d76559228%26site%3dehost-live%26scope%3dsite

a wide range of technological, cognitive and social competences—collectively termed “Digital Literacy.” Users thus must become “digitally literate” in order to cope effectively with the complex sociological, cognitive and pedagogical challenges these technologies pose. These skills include, for example, the ability to operate computers and navigate the net effectively, to cope with large volumes of information, to evaluate the reliability of information, and to critically assess what seem to be natural (and not ideologically biased) technological tools. In a different way from the spirit of modern print, learners construct and consume knowledge in non-linear environments. They need to learn, collaborate and solve problems effectively in virtual (non face-to-face) learning environments, and to communicate effectively in technology-mediated social participation environments.

It is important to note: digital literacy, then, is not limited simply to computer and Internet operation and orientation. It also relates to a variety of epistemological and ethical issues arise due to the unique characteristics of digital technologies and that are often overlapped with trends related to the post-modern and post-structural era. These include questions regarding the authority of knowledge, intellectual property and ownership, copyright, authenticity and plagiarism. Furthermore, issues such as self-representation, virtual group dynamics, and on-line addiction also arise.

 

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more on digital literacy in this IMS blog
http://blog.stcloudstate.edu/ims?s=digital+assessment+literacy

document analysis methodology

document analysis – literature on the methodology

  • Bowen, G. A. (n.d.). Document Analysis as a Qualitative Research Method. Qualitative Research Journal, 9, 27–40.
    https://www.academia.edu/8434566/Document_Analysis_as_a_Qualitative_Research_Method
    Document analysis is a systematic procedure for reviewing or evaluating documents—both printed and electronic (computer-based and Internet-transmitted) material. Like other analytical methods in qualitative research, document analysis requires that data be examined and interpreted in order to elicit meaning, gain understanding, and develop empirical knowledge(Corbin&Strauss,2008;seealsoRapley,2007).
    Document analysis is often used in combination with other qualitative research methods as a means of triangulation—‘the combination of methodologies in the study of the same phenomenon’ (Denzin, 1970, p. 291)
    The qualitative researcher is expected to draw upon multiple (at least two) sources of evidence; that is, to seek convergence and corroboration through the use of different data sources and methods. Apart from documents, such sources include interviews, participant or non-participant observation, and physical artifacts (Yin,1994).By triangulating data, the researcher attempts to provide ‘a confluence of evidence that breeds credibility’ (Eisner, 1991, p. 110). By examining information collected through different methods, the researcher can corroborate findings across data sets and thus reduce the impact of potential biases that can exist in a single study. According to Patton (1990), triangulation helps the researcher guard against the accusation that a study’s findings are simply an artifact of a single method, a single source, or a single investigator’s bias. Mixed-method studies (which combine quantitative and qualitative research techniques)sometimes include document analysis. Here is an example: In their large-scale, three-year evaluation of regional educational service agencies (RESAs), Rossman and Wilson (1985) combined quantitative and qualitative methods—surveys (to collect quantitative data) and open ended, semi structured interviews with reviews of documents (as the primary sources of qualitative data). The document reviews were designed to identify the agencies that played a role in supporting school improvement programs.
  • Glenn A. Bowen, (2009) “Document Analysis as a Qualitative Research Method”, Qualitative Research Journal, Vol. 9 Issue: 2, pp.27-40, doi: 10.3316/QRJ0902027
    http://www.emeraldinsight.com/action/showCitFormats?doi=10.3316%2FQRJ0902027
  • Document Review and Analysis
    https://www.bcps.org/offices/lis/researchcourse/develop_docreview.html

Qualitative

  • Semiotics (studies the life of signs in society; seeks to understand the underlining messages in visual texts; forms basis for interpretive analysis)
  • Discourse Analysis (concerned with production of meaning through talk and texts; how people use language)
  • Interpretative Analysis (captures hidden meaning and ambiguity; looks at how messages are encoded or hidden; acutely aware of who the audience is)
  • Conversation Analysis (concerned with structures of talk in interaction and achievement of interaction)
  • Grounded Theory (inductive and interpretative; developing novel theoretical ideas based on the data)

Document Analysis
Document analysis is a form of qualitative research in which documents are interpreted by the researcher to give voice and meaning around an assessment topic. Analyzing documents incorporates coding content into themes similar to how focus group or interview transcripts are analyzed. A rubric can also be used to grade or score a document. There are three primary types of documents:

• Public Records: The official, ongoing records of an organization’s activities. Examples include student transcripts, mission statements, annual reports, policy manuals, student handbooks, strategic plans, and syllabi.

• Personal Documents: First-person accounts of an individual’s actions, experiences, and beliefs. Examples include calendars, e-mails, scrapbooks, blogs, Facebook posts, duty logs, incident reports, reflections/journals, and newspapers.

• Physical Evidence: Physical objects found within the study setting (often called artifacts). Examples include flyers, posters, agendas, handbooks, and training materials.

As with all research, how you collect and analyse the data should depend on what you want to find out. Since you haven’t told us that, it is difficult to give you any precise advice. However, one really important matter in using documents as sources, whatever the overall aim of your research, is that data from documents are very different from data from speech events such as interviews, or overheard conversations.So the first analytic question you need to ask with regard to documents is ‘how are these data shaped by documentary production ?’  Something which differentiates nearly all data from documents from speech data is that those who compose documents know what comes at the end while still able to alter the beginning; which gives far more opportunity for consideration of how the recepient of the utterances will view the provider; ie for more artful self-presentation. Apart from this however, analysing the way documentary practice shapes your data will depend on what these documents are: for example your question might turn out to be ‘How are news stories produced ?’ – if you are using news reports, or ‘What does this bureaucracy consider relevant information (and what not relevant and what unmentionable) ? if you are using completed proformas or internal reports from some organisation.

An analyse technique is just like a hardware tool. It depends where and with what you are working to choose the right one. For a nail you should use a hammer, nad there are lots of types of hammers to choose, depending on the type of nail.

So, in order to tell you the bettet technique, it is important to know the objectives you intend to reach and the theoretical framework you are using. Perhaps, after that, We could tell you if you should use content analysis, discourse or grounded theory (which type of it as, like the hammer, there are several types of GTs).

written after Bowen (2009), but well chewed and digested.

1. Introduction: Qualitative vs. Quantitative Research?

excellent guide to the structure of a qualitative research

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more on qualitative research in this IMS blog
http://blog.stcloudstate.edu/ims?s=qualitative+research

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