Cross-Institution & Cross-Sector Collaboration Long-Term Trend: Driving Ed Tech adoption in higher education for five or more years
Although a variety of collaborations between higher education and industry have emerged, more-explicit frameworks and guidelines are needed to define how these partnerships should proceed to have the greatest impact.
Proliferation of Open Educational Resources Mid-Term Trend: Driving Ed Tech adoption in higher education for the next three to five years
The United States lags on the policy front. In September 2017, the Affordable College Textbook Act was once again introduced in both the US House of Representatives and the Senate “to expand the use of open textbooks
It is unlikely that ACTA will pass, however, as it has been unsuccessfully introduced to two previous Congresses.
The Rise of New Forms of Interdisciplinary Studies
Faculty members, administrators, and instructional designers are creating innovative pathways to college completion through interdisciplinary experiences, nanodegrees, and other alternative credentials, such as digital badges. Researchers, along with academic technologists and developers, are breaking new ground with data structures, visualizations, geospatial applications, and innovative uses of opensource tools.
Growing Focus on Measuring Learning
As societal and economic factors redefine the skills needed in today’s workforce, colleges and universities must rethink how to define, measure, and demonstrate subject mastery and soft skills such as creativity and collaboration. The proliferation of data-mining software and developments in online education, mobile learning, and learning management systems are coalescing toward learning environments that leverage analytics and visualization software to portray learning data in a multidimensional and portable manner
Redesigning Learning Spaces
upgrading wireless bandwidth and installing large displays that allow for more natural collaboration on digital projects. Some are exploring how mixed-reality technologies can blend 3D holographic content into physical spaces for simulations, such as experiencing Mars by controlling rover vehicles, or how they can enable multifaceted interaction with objects, such as exploring the human body in anatomy labs through detailed visuals. As higher education continues to move away from traditional, lecture-based lessons toward more hands-on activities, classrooms are starting to resemble real-world work and social environments
Authentic Learning Experiences
An increasing number of institutions have begun bridging the gap between academic knowledge and concrete applications by establishing relationships with the broader community; through active partnerships with local organizations
Improving Digital Literacy Solvable Challenge: Those that we understand and know how to solve
Digital literacy transcends gaining discrete technological skills to generating a deeper understanding of the digital environment, enabling intuitive and discerning adaptation to new contexts and cocreation of content.107 Institutions are charged with developing students’ digital citizenship, promoting the responsible and appropriate use of technology, including online communication etiquette and digital rights and responsibilities in blended and online learning settings. This expanded concept of digital competence is influencing curriculum design, professional development, and student-facing services and resources. Due to the multitude of elements of digital literacy, higher education leaders must obtain institution-wide buy-in and provide support for all stakeholders in developing these competencies.
Despite its growing importance, it remains a complex topic that can be challenging to pin down. Vanderbilt University established an ad hoc group of faculty, administrators, and staff that created a working definition of digital literacy on campus and produced a white paper recommending how to implement digital literacy to advance the university’s mission: https://vanderbilt.edu/ed-tech/committees/digital-literacy-committee.php
Adapting Organizational Designs to the Future of Work
Technology, shifting information demands, and evolving faculty roles are forcing institutions to rethink the traditional functional hierarchy. Institutions must adopt more flexible, teambased, matrixed structures to remain innovative and responsive to campus and stakeholder needs.
Attempts to avoid bureaucracy also align with a streamlined workforce and cost elimination. Emphasis has been placed on designing better business models through a stronger focus on return on investment. This involves taking a strategic approach that connects financial practice (such as analyzing cost metrics and resource allocation) with institutional change models and goals.124
Faculty roles have been and continue to be impacted by organizational change, as well as by broader economic movements. Reflective of today’s “gig economy,” twothirds of faculty members are now non-tenure, with half working part-time, often in teaching roles at several institutions. This stands as a stark contrast to 1969, when almost 80 percent of faculty were tenured or tenuretrack; today’s figures are nearly inverted. Their wages are applying pressure to traditional organizational structures.Rethinking tenure programs represents another change to organizational designs that aligns with the future of work.
Organizational structures are continuing to evolve on the administrative side as well. With an emphasis on supporting student success, many institutions are rethinking their student services, which include financial aid, academic advising, and work-study programs. Much of this change is happening within the context of digital transformation, an umbrella term that denotes the transformation of an organization’s core business to better meet customer needs by leveraging technology and data.
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added Nov 13, 2018
6 growing trends taking over academic libraries
BY MERIS STANSBURY
March 24th, 2017
Horizon Report details short-and long-term technologies, trends that will impact academic libraries worldwide in the next 5 years.
Research Data Management: The growing availability of research reports through online library databases is making it easier for students, faculty, and researchers to access and build upon existing ideas and work. “Archiving the observations that lead to new ideas has become a critical part of disseminating reports,” says the report.
Valuing the User Experience: Librarians are now favoring more user-centric approaches, leveraging data on patron touchpoints to identify needs and develop high-quality engaging experiences.
(Mid-Term, 3-5 years):
Patrons as Creators: Students, faculty, and researchers across disciplines are learning by making and creating rather than by simply consuming content. Creativity, as illustrated by the growth of user-generated videos, maker communities, and crowdfunded projects in the past few years, is increasingly the means for active, hands-on learning. People now look to libraries to assist them and provide tools for skill-building and making.
Rethinking Library Spaces: At a time when discovery can happen anywhere, students are relying less on libraries as the sole source for accessing information and more for finding a place to be productive. As a result, institutional leaders are starting to reflect on how the design of library spaces can better facilitate the face-to-face interactions.
(Long-Term, 5 or more years):
Cross-Institution Collaboration: Within the current climate of shrinking budgets and increased focus on digital collections, collaborations enable libraries to improve access to scholarly materials and engage in mission-driven cooperative projects.
Evolving Nature of the Scholarly Record: Once limited to print-based journals and monographic series, scholarly communications now reside in networked environments and can be accessed through an expansive array of publishing platforms. “As different kinds of scholarly communication are becoming more prevalent on the web, librarians are expected to discern the legitimacy of these innovative approaches and their impact in the greater research community through emerging altmetrics tools,” notes the report.
Improving digital literacy: According to the report, digital literacy transcends gaining isolated technological skills to “generate a deeper understanding of the digital environment, enabling intuitive adaptation to new contexts, co-creation of content with others, and an awareness of both the freedom and risks that digital interactions entail. Libraries are positioned to lead efforts to develop students’ digital citizenship, ensuring mastery of responsible and appropriate technology use, including online identity, communication etiquette, and rights and responsibilities.”
round table digital literacy. Jeff Plaman Dept of Education
SIG MN Literacy council
elearning strategies, embedding into faculty curriculum digital literacy.
microcredentials dissertation for professional development. how about grading
definition: where does it start and where does it end. what should people know and able to do. credibility of sources,
digital skills is the how, digital literacy is the what where
eshel alkalai read her
how do we assess disparities in digital literacy.
assessment digital literacy. diagnostic. google form: bit.ly/summit18dl
assignment banks. conceptual framework, where does it fit.
K12 technology mini-sessions. people are scared of acronyms. culture change. immediate win.
!*!*!*!*! — this article was pitched by Mark Vargas in the fall of 2013, back then dean of LRS and discussed at a faculty meeting at LRS in the same year—- !*!*!*!
New Roles for New Times: Transforming Liaison Roles in Research Libraries
(p. 4) Building strong relationships with faculty and other campus professionals, and establishing collaborative partnerships within and across institutions, are necessary building blocks to librarians’ success. In a traditional liaison model, librarians use their subject knowledge to select books and journals and teach guest lectures.
“Liaisons cannot be experts themselves in each new capability, but knowing when to call in a colleague, or how to describe appropriate expert capabilities to faculty, will be key to the new liaison role.
six trends in the development of new roles for library liaisons
user engagement is a driving factor
what users do (research, teaching, and learning) rather than on what librarians do (collections, reference, library instruction). In addition, an ALA-accredited master’s degree in library science is no longer strictly required.
In a networked world, local collections as ends in themselves make learning fragmentary and incomplete. (p. 5)
A multi-institutional approach is the only one that now makes sense.
Scholars already collaborate; libraries need to make it easier for them to do so.
but they also advise and collaborate on issues of copyright, scholarly communication, data management, knowledge management, and information literacy. The base level of knowledge that a liaison must possess is much broader than familiarity with a reference collection or facility with online searching; instead, they must constantly keep up with evolving pedagogies and research methods, rapidly developing tools, technologies, and ever-changing policies that facilitate and inform teaching, learning, and research in their assigned disciplines.
In many research libraries, programmatic efforts with information literacy have been too narrowly defined. It is not unusual for libraries to focus on freshman writing programs and a series of “one-shot” or invited guest lectures in individual courses. While many librarians have become excellent teachers, traditional one-shot, in-person instructional sessions can vary in quality depending on the training librarians have received in this arena; and they neither scale well nor do they necessarily address broader curricular goals. Librarians at many institutions are now focusing on collaborating with faculty to develop thoughtful assignments and provide online instructional materials that are built into key courses within a curriculum and provide scaffolding to help students develop library research skills over the course of their academic careers.
And many libraries stated that they lack instructional designers and/or educational technologists on their staff, limiting the development of interactive online learning modules and tutorials. (my note: or just ignore the desire by unites such as IMS to help).
(p. 7). This move away from supervision allows the librarians to focus on their liaison responsibilities rather than on the day-to-day operations of a library and its attendant personnel needs.
effectively support teaching, (1.) learning, and research; (2.) identify opportunities for further development of tools and services; (3.) and connect students, staff, and faculty to deeper expertise when needed.
At many institutions, therefore, the conversation has focused on how to supplement and support the liaison model with other staff.
At many institutions, therefore, the conversation has focused on how to supplement and support the liaison model with other staff.
the hybrid exists within the liaison structure, where liaisons also devote a portion of their time (e.g., 20% or more) to an additional area of expertise, for example digital humanities and scholarly communication, and may work with liaisons across all disciplinary areas. (my note: and at the SCSU library, the librarians firmly opposed the request for a second master’s degree)
functional specialists who do not have liaison assignments to specific academic departments but instead serve as “superliaisons” to other librarians and to the entire campus. Current specialist areas of expertise include copyright, geographic information systems (GIS), media production and integration, distributed education or e-learning, data management, emerging technologies, user experience, instructional design, and bioinformatics. (everything in italics is currently done by IMS faculty).
divided into five areas of functional specialization: information resources and collections management; information literacy, instruction, and curriculum development; discovery and access; archival and special collections; scholarly communication and the research enterprise.
E-Scholarship Collaborative, a Research Support Services Collaborative (p. 8).
p. 9. managing alerts and feeds, personal archiving, and using social networking for teaching and professional development
p. 10. new initiatives in humanistic research and teaching are changing the nature and frequency of partnerships between faculty and the Libraries. In particular, cross-disciplinary Humanities Laboratories (http://fhi.duke.edu/labs), supported by the John Hope Franklin Humanities Institute and the Andrew W. Mellon Foundation-funded Humanities Writ Large project, have allowed liaisons to partner with faculty to develop and curate new forms of scholarship.
consultations on a range of topics, such as how to use social media to effectively communicate academic research and how to mark up historical texts using the Text Encoding Initiative (TEI) guidelines
p. 11. Media literacy, and facilitating the integration of media into courses, is an area in which research libraries can play a lead role at their institutions. (my note: yet still suppressed or outright denied to IMS to conducts such efforts)
Purdue Academic Course Transformation, or IMPACT (http://www.lib.purdue.edu/infolit/impact). The program’s purpose is to make foundational courses at Purdue more student-centered and participatory. Librarians are key members of interdepartmental teams that “work with Purdue instructors to redesign courses by applying evidence-based educational practices” and offer “learning solutions” that help students engage with and critically evaluate information. (my note: as offered by Keith and myself to Miguel, the vice provost for undergrads, who left; then offered to First Year Experience faculty, but ignored by Christine Metzo; then offered again to Glenn Davis, who bounced it back to Christine Metzo).
p. 15. The NCSU Libraries Fellows Program offers new librarians a two-year appointment during which they develop expertise in a functional area and contribute to an innovative initiative of strategic importance. NCSU Libraries typically have four to six fellows at a time, bringing in people with needed skills and working to find ongoing positions when they have a particularly good match. Purdue Libraries have experimented with offering two-year visiting assistant professor positions. And the University of Minnesota has hired a second CLIR fellow for a two-year digital humanities project; the first CLIR fellow now holds an ongoing position as a curator in Archives and Special Collections. The CLIR Fellowship is a postdoctoral program that hires recent PhD graduates (non-librarians), allowing them to explore alternative careers and allowing the libraries to benefit from their discipline-specific expertise.
Guess what … I searched for Brenda Perea (in hopes of maybe getting some information on how they set up their system) … One of her current positions is with Credly … Do we still want to reach out to her?
94%: Institutions offering alternative credentials
1 in 5: Colleges and universities that issue badges
Nearly 2/3: Institutions that cited alternative credentials as an important strategy for the future.
-Source: “Demographic Shifts in Educational Demand and the Rise of Alternative Credentials,” University Professional and Continuing Education Association and Pearson, 2016
Defining Online Education
The term “online education” has been used as a blanket phrase for a number of fundamentally different educational models. Phrases like distance education, e-Learning, massively open online courses (MOOCs), hybrid/blended learning, immersive learning, personalized and/or adaptive learning, master courses, computer based instruction/tutorials, digital literacy and even competency based learning have all colored the definitions the public uses to define “online education.”
online education” as having the following characteristics:
Students who enroll in online courses or programs may reside near or far from the campus(es) providing the course(s) or program.
A student’s course load may include offering where attendance is required in person or where an instructor/students are not required to be in the same geographic location.
Students may enroll in one or more individual online course offerings provided by one or more institutions to that may or may not satisfy degree/program requirements.
Student may pursue a certificate, program, or degree where a substantial number of courses, perhaps all, are taken without being in the same geographic location as others.
Organizational Effectiveness Research Group (OERG),
As the workgroup considered strategies that could advance online education, they were asked to use the primary and secondary sources listed above to support the fifteen (15) strategies that were developed
define a goal as a broad aspirational outcome that we strive to attain. Four goal areas guide this document. These goal areas include access, quality, affordability and collaboration. Below is a description of each goal area and the assumptions made for Minnesota State.
Access
Over twenty percent of existing Minnesota State students enroll in online courses as a way to satisfy course requirements. For some students, online education is a convenient option; for others, online is the only option available
Quality
The Higher Learning Commission (HLC) accreditation guidelines review the standards and processes institutions have in place to ensure quality in all of educational offerings, including online.
There are a number of ways in which institutions have demonstrated quality in individual courses and programs including the evaluation of course design, evaluation of instruction and assessment of student
Affordability
a differential tuition rate to courses that are offered online. If we intend to have online education continue to be an affordable solution for students, Minnesota State and its institutions must be good stewards of these funds and ensure these funds support online education.
Online education requires different or additional services that need to be funded
transparency is important in tuition setting
Collaboration
Distance Minnesota is comprised of four institutions Alexandria Technical & Community College, Bemidji State University, Northland Community & Technical College, and Northwest Technical College) which collaborate to offer student support services, outreach, e-advising, faculty support, and administrative assistance for online education offerings.
Strategies
strategies are defined as the overall plan used to identify how we can achieve each goal area.
Action Steps
Strategy 1: Ensure all student have online access to high quality support services
students enrolled in online education experiences should have access to “three areas of support including academic (such as tutoring, advising, and library); administrative (such as financial aid, and disability support); and technical (such as hardware reliability and uptime, and help desk).”
As a system, students have access to a handful of statewide services, include tutoring services through Smarthinking and test proctoring sites.
Strategy 2: Establish and maintain measures to assess and support student readiness for online education
A persistent issue for campuses has been to ensure that students who enroll in online course are aware of the expectations required to participate actively in an online course.
In addition to adhering to course expectations, students must have the technical competencies needed to perform the tasks required for online courses
Strategy 3: Ensure students have access to online and blended learning experiences in course and program offerings.
Strategy 4: These experiences should support and recognize diverse learning needs by applying a universal design for learning framework.
The OERG report included several references to efforts made by campuses related to the providing support and resources for universal design for learning, the workgroup did not offer any action steps.
Strategy 5: Expand access to professional development resources and services for faculty members
As online course are developed and while faculty members teach online courses, it is critical that faculty members have on-demand access to resources like technical support and course assistance.
5A. Statewide Faculty Support Services – Minnesota State provide its institutions and their faculty members with access to a centralized support center during extended hours with staff that can assist faculty members synchronously via phone, chat, text/SMS, or web conference
5C. Instructional Design and Technology Services – Establish a unit that will provide course design and instructional technology services to selected programs and courses from Minnesota State institutions.
Quality
Strategy 1: Establish and maintain a statewide approach for professional development for online education.
1B. Faculty Mentoring – Provide and sustain faculty mentoring programs that promote effective online pedagogy.
1C. Professional development for support staff – including instructional designers, D2L Brightspace site administrators and campus trainers, etc.)
2018 Special Focus: Education in a Time of Austerity and Social Turbulence 21–23 June 2018 University of Athens, Athens, Greece http://thelearner.com/2018-conference
Theme 8: Technologies in Learning
Technology and human values: learning through and about technology
Crossing the digital divide: access to learning in, and about, the digital world
New tools for learning: online digitally mediated learning
Virtual worlds, virtual classrooms: interactive, self-paced and autonomous learning
Ubiquitous learning: using the affordances of the new mediaDistance learning: reducing the distance
Theme 9: Literacies Learning
Defining new literacies
Languages of power: literacy’s role in social access
Instructional responses to individual differences in literacy learning
The visual and the verbal: Multiliteracies and multimodal communications
Literacy in learning: language in learning across the subject areas
The changing role of libraries in literacies learning
Languages education and second language learning
Multilingual learning for a multicultural world
The arts and design in multimodal learning
The computer, internet, and digital media: educational challenges and responses
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PROPOSAL: Paper presentation in a Themed Session
Title
Virtual Reality and Gamification in the Educational Process: The Experience from an Academic Library
short description
VR, AR and Mixed Reality, as well as gaming and gamification are proposed as sandbox opportunity to transition from a lecture-type instruction to constructivist-based methods.
long description
The NMC New Horizon Report 2017 predicts a rapid application of Video360 in K12. Millennials are leaving college, Gen Z students are our next patrons. Higher Education needs to meet its new students on “their playground.” A collaboration by a librarian and VR specialist is testing the opportunities to apply 360 degree movies and VR in academic library orientation. The team seeks to bank on the inheriting interest of young patrons toward these technologies and their inextricable part of a rapidly becoming traditional gaming environment. A “low-end,” inexpensive and more mobile Google Cardboard solution was preferred to HTC Vive, Microsoft HoloLens or comparable hi-end VR, AR and mixed reality products.
The team relies on the constructivist theory of assisting students in building their knowledge in their own pace and on their own terms, rather than being lectured and/or being guided by a librarian during a traditional library orientation tour. Using inexpensive Google Cardboard goggles, students can explore a realistic set up of the actual library and familiarize themselves with its services. Students were polled on the effectiveness of such approach as well as on their inclination to entertain more comprehensive version of library orientation. Based on the lessons from this experiment, the team intends to pursue also a standardized approach to introducing VR to other campus services, thus bringing down further the cost of VR projects on campus. The project is considered a sandbox for academic instruction across campus. The same concept can be applied for [e.g., Chemistry, Physics, Biology) lab tours; for classes, which anticipate preliminary orientation process.
Following the VR orientation, the traditional students’ library instruction, usually conducted in a room, is replaced by a dynamic gamified library instruction. Students are split in groups of three and conduct a “scavenger hunt”; students use a jQuery-generated Web site on their mobile devices to advance through “hoops” of standard information literacy test. E.g., they need to walk to the Reference Desk, collect specific information and log their findings in the Web site. The idea follows the strong interest in the educational world toward gaming and gamification of the educational process. This library orientation approach applies the three principles for gamification: empowers learners; teaches problem solving and increases understanding.
Similarly to the experience with VR for library orientation, this library instruction process is used as a sandbox and has been successfully replicated by other instructors in their classes.
Media literacy. Differentiated instruction. Media literacy guide.
Fake news as part of media literacy. Visual literacy as part of media literacy. Media literacy as part of digital citizenship.
Web design / web development
the roles of HTML5, CSS, Java Script, PHP, Bootstrap, JQuery, React and other scripting languages and libraries. Heat maps and other usability issues; website content strategy. THE MODEL-VIEW-CONTROLLER (MVC) design pattern
Social media for institutional use. Digital Curation. Social Media algorithms. Etiquette Ethics. Mastodon
I hosted a LITA webinar in the fall of 2016 (four weeks); I can accommodate any information from that webinar for the use of the IM students
OER and instructional designer’s assistance to book creators.
I can cover both the “library part” (“free” OER, copyright issues etc) and the support / creative part of an OER book / textbook
“Big Data.” Data visualization. Large scale visualization. Text encoding. Analytics, Data mining. Unizin. Python, R in academia.
I can introduce the students to the large idea of Big Data and its importance in lieu of the upcoming IoT, but also departmentalize its importance for academia, business, etc. From infographics to heavy duty visualization (Primo X-Services API. JSON, Flask).
NetNeutrality, Digital Darwinism, Internet economy and the role of your professional in such environment
I can introduce students to the issues, if not familiar and / or lead a discussion on a rather controversial topic
Digital assessment. Digital Assessment literacy.
I can introduce students to tools, how to evaluate and select tools and their pedagogical implications
Wikipedia
a hands-on exercise on working with Wikipedia. After the session, students will be able to create Wikipedia entries thus knowing intimately the process of Wikipedia and its information.
Effective presentations. Tools, methods, concepts and theories (cognitive load). Presentations in the era of VR, AR and mixed reality. Unity.
I can facilitate a discussion among experts (your students) on selection of tools and their didactically sound use to convey information. I can supplement the discussion with my own findings and conclusions.
eConferencing. Tools and methods
I can facilitate a discussion among your students on selection of tools and comparison. Discussion about the their future and their place in an increasing online learning environment
Digital Storytelling. Immersive Storytelling. The Moth. Twine. Transmedia Storytelling
I am teaching a LIB 490/590 Digital Storytelling class. I can adapt any information from that class to the use of IM students
VR, AR, Mixed Reality.
besides Mark Gill, I can facilitate a discussion, which goes beyond hardware and brands, but expand on the implications for academia and corporate education / world
Instructional design. ID2ID
I can facilitate a discussion based on the Educause suggestions about the profession’s development
Microcredentialing in academia and corporate world. Blockchain
IT in K12. How to evaluate; prioritize; select. obsolete trends in 21 century schools. K12 mobile learning
Podcasting: past, present, future. Beautiful Audio Editor.
a definition of podcasting and delineation of similar activities; advantages and disadvantages.
Gender, race and age in education. Digital divide. Xennials, Millennials and Gen Z. generational approach to teaching and learning. Young vs old Millennials. Millennial employees.
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.
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
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.
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
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:
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
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: 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.
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:
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.
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 (https://blog.stcloudstate.edu/ims?s=big+data) as well as academic libraries (https://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.
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