Digital Literacy for St. Cloud State University
Gary Hunter ASA System Director for Policy, Procedure, and Intellectual Property
October 24, 2017 Koffee with Karen Webinar
Koffee with Karen (Copyright) 10.24.2017-1kjgygr
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more on copyright in this IMS blog:
https://blog.stcloudstate.edu/ims?s=copyright
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
https://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:
https://blog.stcloudstate.edu/ims/2017/08/13/analytical-essay/
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APA citing of “unusual” resources
https://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:
https://blog.stcloudstate.edu/ims/2017/07/10/intro-to-stat-modeling/
In this blog entry, I shared with you:
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: https://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
https://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.info; http://www.arXiv.org; http://www.journalogy.com/
More about such search engines in the following blog entries:
https://blog.stcloudstate.edu/ims/2017/01/19/digital-literacy-for-glst-495/
and
https://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://brocku.ca/webfm_send/25032
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More from Drakulic:
DRAKULIC, S. (2009). The Generation That Failed. Nation, 289(16), 16-17.
Slavenka describec what the East Germans called Die Quall der Wahl
When communism fell, Poland had Solidarity and Lech Walesa, Czechoslovakia had Václav Havel, Hungary had Fidesz, Bulgaria had Zhelyu Zhelev—and Yugoslavia had no democratic opposition at all. My note: Little she knew about the Bulgarian Opposition
A few years before the breakup of Yugoslavia, the political landscape was already filled with communists-turnednationalists (like Slobodan Milosevic and Franjo Tudjman). Nationalism became the only political “alter native” in Yugoslavia, leading us directly to wars in Croatia, Bosnia and Kosovo.
Yes, my generation lived too well, and obviously we mistook freedom and democracy for the freedom of shopping in the West. And as in a medieval morality play, we had to pay for that in the three wars to follow: our children fought those wars; they were killed, and their limbs were severed.
Drakulic, S. (2011). Serbia’s War Criminal. Nation, 292(25), 8. http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3daph%26AN%3d61138708%26site%3dehost-live%26scope%3dsite
Slavenka, D. (2008). Seduced by power and vanity. Toronto Star (Canada).
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more on history in this IMS blog
https://blog.stcloudstate.edu/ims?s=history
Chun, L. (2017). Discipline and power: knowledge of China in political science. Critical Asian Studies, 49(4), 501-522. doi:10.1080/14672715.2017.1362321
Lin Chun or ResearchGate: https://www.researchgate.net/profile/Chun_Lin18
p. 501 – is political science “softer” than the other soft social sciences?
thus… political science “may never live up to its lofty ambition of scientific explanation and prediction. Indeed, like other social sciences, it can be no more than a ‘ science in formation’ permanently seeking to surmount obstacles to objectivity.”
p. 502 disciplinary parochialism
the fetishes of pure observation, raw experience, unambiguous rationality, and one-way causality were formative influences in the genesis of the social sciences. the ‘unfortunate positivism” of such impulses, along with the illusion of a value-free science, converged to produce a behavioral revolution in the interwar period Behaviorism was then followed through an epistemological twist, by boldly optimistic leaps to an “end of ideology” and ultimately to a claimed “end of history” itself.
p. 503
early positivism was openly underpinned by an European condescension toward Asians’ “ignorance and prejudice.” Behind similar depictions lay a comprehensive Eurocentric social and political philosophy.
this is illustrated its view of China through the grand narrative of modernization.
p. 504
Robert McNamara famously reiterated that if World War I was a chemist’s war and Word War II a physicist’s, Vietnam “might well have to be considered the social scientists’ war.”
Although China nominally remains a communist state, it has doubtlessly changed color without a color revolution.
p. 505
In the fixed disciplinary eye, “China” is to specific to produce anything generalizable beyond descriptive and self-containing narratives. The area studies approach, in contrast to disciplinary approaches, is all about cultural, historical, and ethnographic specificities.
If first-hand information contradicts theoretical conclusions, redress is sought only at the former end (my note – ha ha ha, such an elegant but scathing criticism of [Western] academia).
The catch [is] that Chinese otherness is in essence not a matter of cultural difference (hence limitations of criticizing Eurocentrism and Orientalism) and does not merely reproduce itself by inertia.
Given a long omitted self-critical rethinking of the discipline’s parochial base, calling for cross-fertilizing alone would be fruitless or even lead only to a one-way colonization of seemingly particularistic histories by an illusive universal science.
p. 506
political culture, once a key concept of political science’s hope for unified theorization, has turned out to be no answer
Long after its heyday, modernization theory – now with its new face of globalization – remains a primary signifier and legitimating benchmark. To those, who use it to gauge developments since 1945, private property and liberal democracy are permanent, unquestioned norms that are to be globally homogenized.
Moreover, since modernity is assumed to be a liberal capitalists condition, the revolutionary nationalism of an oppressed people remaking itself into a new historical subject noncompliant with capitalism cannot be modernizational.
p. 507
Political scientists and historical sociologists… saw the communist in power as formidable modernizers, but distinguished the Maoist model from the Stalinist in economic management and campaign politics.
Their analyses showed how organic connections between top-down mobilization and bottom-up participation cultivated in an active citizenry and high intensity politics. My note: I disagree here with the author, since such statement can be arbitrary from a historical point of view; indeed, for a short period of time, such “organic connection” can produce positive results, but once calcitrated (as it is in China for the past 6-7 decades), it turns stagnant.
p. 510
the state’s altered support base is essentially a matter of class power, involving both adaptive cultivation of new economic elites and iron-fist approaches to protest and dissent. By the same weight of historical logic, the party’s internal decay, loss of its founding ideological vision and commitment, and collusion with capital will do more than any outside force ever could do to destroy the regime.
That the Party stays in power is not primarily because the country’s economy continues to grow, but is more attributable to a residual social reliance on its credentials and organizational capacities accumulated in earlier revolutionary and socialist struggles. This historical promise has so far worked to the extent that cracks within the leadership are more or less held in check, resentment against local wrongs are insulated from central intentions, and social policies in one way or another respond to common outcries, consultative deliberations, and pressure groups.
p. 511
The word “madness” has indeed been freely employed to describe nations and societies judged inept at modern reason, as found in contemporary academic publications on epi- sodes of the PRC history.
My note: I agree with this – the deconstructionalists: (Jaques Derrida, Tzvetan Todorov) linguistically prove the inability of Western cultures to understand and explain other cultures. In this case, Lin Chun is right; just because western political scientist cannot comprehend foreign complex societal problems and/or juxtaposing them to their own “schemes,” prompts the same western researchers to announce them as “mad.”
p. 513aa
This is the best and worst of times for the globalization of knowledge. In one scenario, an eventual completion of the political science parameters can now seal both knowledge, sophisticatedly canalized, and ideology, universally uncontested – even if the two are never separable in the foundation of political science. In another scenario, causes and effects no longer rule out atypical polities, but the differences are presented as culturally incompatible. In either case, the trick remains to let anormalies make the norms validate preexist- ing disciplinary sanctions.
p. 514
Overcoming outmoded rigidities will nurture a robust scholarship committed to universally resonant theories.
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more on China in this IMS blog
https://blog.stcloudstate.edu/ims?s=china
the Wikipedia Adventure
https://en.wikipedia.org/wiki/Wikipedia:The_Wikipedia_Adventure
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more on wikipedia in this IMS blog
https://blog.stcloudstate.edu/ims?s=wikipedia
Two sets of open access, free digital resources that may be of interest to students and faculty have been added to SCSU’s online catalog (MnPALS Plus).
Open Textbook Library (a project of the University of Minnesota)
(appears in Collection drop-down menu as “Univ of Mn Open Textbook Library”)
“Open textbooks are textbooks that have been funded, published, and licensed to be freely used, adapted, and distributed. These books have been reviewed by faculty from a variety of colleges and universities to assess their quality. These books can be downloaded for no cost, or printed at low cost. All textbooks are either used at multiple higher education institutions; or affiliated with an institution, scholarly society, or professional organization.”
For more information, see https://open.umn.edu/opentextbooks/
Ebooks Minnesota
“Ebooks Minnesota is an online ebook collection for all Minnesotans. The collection covers a wide variety of subjects for readers of all ages, and features content from our state’s independent publishers, including some of our best literature and nonfiction.”
For more information, see https://mndigital.org/projects/ebooks-minnesota
These resources are included in any search done in the online catalog. To view or search one of these collections specifically, go the the Advanced Search in MnPALS Plus and select the desired collection from the Collection dropdown. Users can add search terms, or just click “Find” without entering any search terms to see the entire collection.
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https://blog.stcloudstate.edu/ims?s=information+literacy
Instructor, Michael Pickle. September 26, 4-5:30PM for SPED 204
short link to this blog entry: http://bit.ly/scsusped204
My name is Plamen Miltenoff and I will be leading your digital literacy instruction today: Here is more about me: http://web.stcloudstate.edu/pmiltenoff/faculty/ and more about the issues we will be discussing today: https://blog.stcloudstate.edu/ims/
As well as my email address for further contacts: pmiltenoff@stcloudstate.edu
https://www.semanticscholar.org/
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https://www.stcloudstate.edu/library/
here is the link to SPED:
https://stcloud.lib.minnstate.edu/subjects/guide.php?subject=SPED
50 min : http://web.stcloudstate.edu/pmiltenoff/bi/
5 min to introduce and make a connection
Plan 1. Introduction to the library (for library novices: Virtual Reality library orientation and gamified library instruction )
15 min for a Virtual Reality tours of the Library + quiz on how well they learned the library:
http://bit.ly/VRlib
and 360 degree video on BYOD:
Play a scavenger hunt IN THE LIBRARY: http://bit.ly/learnlib
The adoption of college and career-ready standards has included an addition of argumentative writing at all grade levels. Interpreting expectations among the types of argument (e.g., opinion, persuasive, argument, etc.) can be difficult. Begin first by outlining the subtle, but significant differences among them. Download a chart that defines each and their purposes, techniques, components, etc
Bibliographic Indexing Leader
Register for the September 28th webinar
https://www.brighttalk.com/webcast/13703/275301
metadata: counts of papers by yer, researcher, institution, province, region and country. scientific fields subfields
metadata in one-credit course as a topic:
publisher – suppliers =- Elsevier processes – Scopus Data
h-index: The h-index is an author-level metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. The index is based on the set of the scientist’s most cited papers and the number of citations that they have received in other publications.
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https://www.brighttalk.com/webcast/9995/275813
Librarians and APIs 101: overview and use cases
Christina Harlow, Library Data Specialist;Jonathan Hartmann, Georgetown Univ Medical Center; Robert Phillips, Univ of Florida
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Christian Lauersen, University of Copenhagen; Sarah Wright, Cornell University; Anita de Waard, Elsevier
https://www.brighttalk.com/webcast/9995/226043
Data Literacy: access, assess, manipulate, summarize and present data
Statistical Literacy: think critically about basic stats in everyday media
Information Literacy: think critically about concepts; read, interpret, evaluate information
data information literacy: the ability to use, understand and manage data. the skills needed through the whole data life cycle.
Shield, Milo. “Information literacy, statistical literacy and data literacy.” I ASSIST Quarterly 28. 2/3 (2004): 6-11.
Carlson, J., Fosmire, M., Miller, C. C., & Nelson, M. S. (2011). Determining data information literacy needs: A study of students and research faculty. Portal: Libraries & the Academy, 11(2), 629-657.
embedded librarianship,
Courses developed: NTRESS 6600 research data management seminar. six sessions, one-credit mini course
http://guides.library.cornell.edu/ntres6600
BIOG 3020: Seminar in Research skills for biologists; one-credit semester long for undergrads. data management organization http://guides.library.cornell.edu/BIOG3020
lessons learned:
http://www.thepress.purdue.edu/titles/format/9781612493527
ideas behind data information literacy, such as the twelve data competencies.
http://blogs.lib.purdue.edu/dil/the-twelve-dil-competencies/
http://blogs.lib.purdue.edu/dil/what-is-data-information-literacy/
Johnston, L., & Carlson, J. (2015). Data Information Literacy : Librarians, Data and the Education of a New Generation of Researchers. Ashland: Purdue University Press. http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dnlebk%26AN%3d987172%26site%3dehost-live%26scope%3dsite
NEW ROLESFOR LIbRARIANS: DATAMANAgEMENTAND CURATION
the capacity to manage and curate research data has not kept pace with the ability to produce them (Hey & Hey, 2006). In recognition of this gap, the NSF and other funding agencies are now mandating that every grant proposal must include a DMP (NSF, 2010). These mandates highlight the benefits of producing well-described data that can be shared, understood, and reused by oth-ers, but they generally offer little in the way of guidance or instruction on how to address the inherent issues and challenges researchers face in complying. Even with increasing expecta-tions from funding agencies and research com-munities, such as the announcement by the White House for all federal funding agencies to better share research data (Holdren, 2013), the lack of data curation services tailored for the “small sciences,” the single investigators or small labs that typically comprise science prac-tice at universities, has been identified as a bar-rier in making research data more widely avail-able (Cragin, Palmer, Carlson, & Witt, 2010).Academic libraries, which support the re-search and teaching activities of their home institutions, are recognizing the need to de-velop services and resources in support of the evolving demands of the information age. The curation of research data is an area that librar-ians are well suited to address, and a num-ber of academic libraries are taking action to build capacity in this area (Soehner, Steeves, & Ward, 2010)
REIMAgININg AN ExISTINg ROLEOF LIbRARIANS: TEAChINg INFORMATION LITERACY SkILLS
By combining the use-based standards of information literacy with skill development across the whole data life cycle, we sought to support the practices of science by develop-ing a DIL curriculum and providing training for higher education students and research-ers. We increased ca-pacity and enabled comparative work by involving several insti-tutions in developing instruction in DIL. Finally, we grounded the instruction in the real-world needs as articu-lated by active researchers and their students from a variety of fields
Chapter 1 The development of the 12 DIL competencies is explained, and a brief compari-son is performed between DIL and information literacy, as defined by the 2000 ACRL standards.
chapter 2 thinking and approaches toward engaging researchers and students with the 12 competencies, a re-view of the literature on a variety of educational approaches to teaching data management and curation to students, and an articulation of our key assumptions in forming the DIL project.
Chapter 3 Journal of Digital Curation. http://www.ijdc.net/
http://www.dcc.ac.uk/digital-curation
https://blog.stcloudstate.edu/ims/2017/10/19/digital-curation-2/
https://blog.stcloudstate.edu/ims/2016/12/06/digital-curation/
chapter 4 because these lon-gitudinal data cannot be reproduced, acquiring the skills necessary to work with databases and to handle data entry was described as essential. Interventions took place in a classroom set-ting through a spring 2013 semester one-credit course entitled Managing Data to Facilitate Your Research taught by this DIL team.
chapter 5 embedded librar-ian approach of working with the teaching as-sistants (TAs) to develop tools and resources to teach undergraduate students data management skills as a part of their EPICS experience.
Lack of organization and documentation presents a bar-rier to (a) successfully transferring code to new students who will continue its development, (b) delivering code and other project outputs to the community client, and (c) the center ad-ministration’s ability to understand and evalu-ate the impact on student learning.
skill sessions to deliver instruction to team lead-ers, crafted a rubric for measuring the quality of documenting code and other data, served as critics in student design reviews, and attended student lab sessions to observe and consult on student work
chapter 6 Although the faculty researcher had created formal policies on data management practices for his lab, this case study demonstrated that students’ adherence to these guidelines was limited at best. Similar patterns arose in discus-sions concerning the quality of metadata. This case study addressed a situation in which stu-dents are at least somewhat aware of the need to manage their data;
chapter 7 University of Minnesota team to design and implement a hybrid course to teach DIL com-petencies to graduate students in civil engi-neering.
stu-dents’ abilities to understand and track issues affecting the quality of the data, the transfer of data from their custody to the custody of the lab upon graduation, and the steps neces-sary to maintain the value and utility of the data over time.
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more on Scopus in this IMS blog
https://blog.stcloudstate.edu/ims?s=scopus