As we enter the Fourth Industrial Revolution (4IR), we must be vigilant to keep our classes relevant to the rapidly changing workplace and the emerging digital aspects of life in the 2020s.
deployment of 5G delivery to mobile computing
Certainly, 5G provides a huge upgrade in bandwidth, enabling better streaming of video and gaming. However, it is the low latency of 5G that enables the most powerful potential for distance learning. VR, AR and XR could not smoothly function in the 4G environment because of the lag in images and responses caused by a latency rate of 50 milliseconds (ms). The new 5G technologies drop that latency rate to 5 ms or less, which produces responses and images that our brains perceive as seamlessly instant.
The larger discussions, from what constitutes a nutritious diet to what actions will best further U.S. interests, require conversations between ordinary citizens and experts. But increasingly, citizens don’t want to have those conversations. Rather, they want to weigh in and have their opinions treated with deep respect and their preferences honored not on the strength of their arguments or on the evidence they present but based on their feelings, emotions, and whatever stray information they may have picked up here or there along the way.
Hofstadter argued that this overwhelming complexity produced feelings of helplessness and anger among a citizenry that knew itself to be increasingly at the mercy of more sophisticated elites. “
Credentialism can run amok, and guilds can use it cynically to generate revenue or protect their fiefdoms with unnecessary barriers to entry. But it can also reflect actual learning and professional competence, helping separate real experts from amateurs or charlatans.
Experts are often wrong, and the good ones among them are the first to admit it…. Yet these days, members of the public search for expert errors and revel in finding them—<b>not to improve understanding but rather to give themselves license to disregard all expert advice they don’t like.<b>
The convenience of the Internet is a tremendous boon, but mostly for people already trained in research and who have some idea what they’re looking for. It does little good, unfortunately, for a student or an untrained layperson who has never been taught how to judge the provenance of information or the reputability of a writer.
Libraries, or at least their reference and academic sections, once served as a kind of first cut through the noise of the marketplace. The Internet, however, is less a library than a giant repository where anyone can dump anything. In practice, this means that a search for information will rely on algorithms usually developed by for-profit companies using opaque criteria. Actual research is hard and often boring. It requires the ability to find authentic information, sort through it, analyze it, and apply it.
Government and expertise rely on each other, especially in a democracy. The technological and economic progress that ensures the well-being of a population requires a division of labor, which in turn leads to the creation of professions. Professionalism encourages experts to do their best to serve their clients, respect their own knowledge boundaries, and demand that their boundaries be respected by others, as part of an overall service to the ultimate client: society itself.
Dictatorships, too, demand this same service of experts, but they extract it by threat and direct its use by command. This is why dictatorships are actually less efficient and less productive than democracies (despite some popular stereotypes to the contrary). In a democracy, the expert’s service to the public is part of the social contract.
Too few citizens today understand democracy to mean a condition of political equality in which all get the franchise and are equal in the eyes of the law. Rather, they think of it as a state of actual equality, in which every opinion is as good as any other, regardless of the logic or evidentiary base behind it.
#DunningKrugerEffect #metacognition #democracy #science #academy #fakenews #conspiracytheories #politics #idiocracy #InformationTechnology #Internet
Abrizah, A., Inuwa, S., & Afiqah-Izzati, N. (2016). Systematic Literature Review Informing LIS Professionals on Embedding Librarianship Roles. Journal of Academic Librarianship, 42(6), 636–643. https://doi.org/10.1016/j.acalib.2016.08.010
identifies and documents embedding librarianship roles as reported in the Library and Information Science (LIS) literature.
Findings The roles of embedded librarians were identified, especially in the context of service delivery, all of which reported to be applied to academic libraries. Information literacy instruction, research and other scholarly activities, distance and online learning as well as embedding in classrooms, were described as ways of ensuring successful embedding librarianship. Implications The roles reported in the literature should inform practicing librarians contemplating embedding practices, guide formal embedded librarianship programs, and encourage other librarians to consider new skills in support of embedding roles.
p. 637 The idea behind EL model is to demonstrate librarians’ expertise asinformation specialists and to apply this expertise in ways that willhave a direct and deep impact on the research, teaching or otherworks being done (Carlson & Kneale, 2011).Carlson and Kneale(2011)pointed out that as librarians seek to redefine themselves, themodel of EL is generating interest as an effectual way of applying theknowledge and skills of librarians towards the information challengesof the digital age.
Faculty collaboration with the embedded librarian is the core of em-bedded information literacy instruction. Faculty-librarian relationshipbuilding is of great significance because the two must work closely to-gether over an extended period of time, it is essential that librarianschoose their partnership carefully. Several librarians stress the need towork only in partnerships where there is trust and mutual respect(Carncross, 2013). Librarians build these relationships in differentways, while collaborative relationship can be built in numerous ways,it is essential that bothparties have common goals and know the impor-tance of developing information literacy skills in their students. The most significant collaboration are from campuses in which librarian and university administrators have made information literacy a priority on campus, and have provided librarians and faculty with the time re-quired to make the collaboration successful (Cramer, 2013).
The embedded librarian is focused on course goals and learning objectives outside of the library and across the curriculum
The review designates that EL in courses, classrooms and depart-ments see librarians conducting the following specific tasks: teach stu-dents how to be savvy searchers using computer and laptops (Boyer,2015); collaborate where librarian and faculty member teach eachother, exchanging favors, and the librarian selecting useful resourcesfor the faculty (Ivey, 2003); take part in meetings to promote librarian’spresence and establish communication with the students, researchersand faculty (Jacobs, 2010); provide access to course-related library re-sources, in-class instruction sessions, library instructional handouts, in-formation on referencing style, library Webinar information as well asteach note-taking (Bezet, 2013).
The review shows that academic libraries that engage their distancelearning communities through an embedded librarian as online co-instructors to deliver technological applications such as instant messag-ing, e-mail, and wikis. This EL model facilitates direct interaction be-tween students and librarians regardless of physical proximity.Edwards and Black (2012)andEdwards et al. (2010)evaluated the pro-gram of embedded librarians in an online graduate educational technol-ogy course and found that students were helped with their onlineassignments.
Got a new open access article out on the ways AI is embedding in education research. Well-funded precision education experts and learning engineers aim to collect psychodata, brain data and biodata as evidence of the embodied substrates of learning. https://t.co/CbdHReXUiz
This article presents an examination of how education research is being remade as an experimental data-intensive science. AI is combining with learning science in new ‘digital laboratories’ where ownership over data, and power and authority over educational knowledge production, are being redistributed to research assemblages of computational machines and scientific expertise.
Research across the sciences, humanities and social sciences is increasingly conducted through digital knowledge machines that are reconfiguring the ways knowledge is generated, circulated and used (Meyer and Schroeder, 2015).
Knowledge infrastructures, such as those of statistical institutes or research-intensive universities, have undergone significant digital transformation with the arrival of data-intensive technologies, with knowledge production now enacted in myriad settings, from academic laboratories and research institutes to commercial research and development studios, think tanks and consultancies. Datafied knowledge infrastructures have become hubs of command and control over the creation, analysis and exchange of data (Bigo et al., 2019).
The combination of AI and learning science into an AILSci research assemblage consists of particular forms of scientific expertise embodied by knowledge actors – individuals and organizations – identified by categories including science of learning, AIED, precision education and learning engineering.
Precision education overtly uses psychological, neurological and genomic data to tailor or personalize learning around the unique needs of the individual (Williamson, 2019). Precision education approaches include cognitive tracking, behavioural monitoring, brain imaging and DNA analysis.
Expert power is therefore claimed by those who can perform big data analyses, especially those able to translate and narrate the data for various audiences. Likewise, expert power in education is now claimed by those who can enact data-intensive science of learning, precision education and learning engineering research and development, and translate AILSci findings into knowledge for application in policy and practitioner settings.
the thinking of a thinking infrastructure is not merely a conscious human cognitive process, but relationally performed across humans and socio-material strata, wherein interconnected technical devices and other forms ‘organize thinking and thought and direct action’.
As an infrastructure for AILSci analyses, these technologies at least partly structure how experts think: they generate new understandings and knowledge about processes of education and learning that are only thinkable and knowable due to the computational machinery of the research enterprise.
Big data-based molecular genetics studies are part of a bioinformatics-led transformation of biomedical sciences based on analysing exceptional volumes of data (Parry and Greenhough, 2018), which has transformed the biological sciences to focus on structured and computable data rather than embodied evidence itself.
Isin and Ruppert (2019) have recently conceptualized an emergent form of power that they characterize as sensory power. Building on Foucault, they note how sovereign power gradually metamorphosed into disciplinary power and biopolitical forms of statistical regulation over bodies and populations. Sensory power marks a shift to practices of data-intensive sensing, and to the quantified tracking, recording and representing of living pulses, movements and sentiments through devices such as wearable fitness monitors, online natural-language processing and behaviour-tracking apps. Davies (2019: 515–20) designates these as ‘techno-somatic real-time sensing’ technologies that capture the ‘rhythms’ and ‘metronomic vitality’ of human bodies, and bring about ‘new cyborg-type assemblages of bodies, codes, screens and machines’ in a ‘constant cybernetic loop of action, feedback and adaptation’.
Techno-somatic modes of neural sensing, using neurotechnologies for brain imaging and neural analysis, are the next frontier in AILSci. Real-time brainwave sensing is being developed and trialled in multiple expert settings.
News and Media Literacy (and the lack of) is not very different from Information Literacy
An “information literate” student is able to “locate, evaluate, and effectively use information from diverse sources.” See more About Information Literacy
Developing Your Research Topic/Question
Research always starts with a question. But the success of your research also depends on how you formulate that question. If your topic is too broad or too narrow, you may have trouble finding information when you search. When developing your question/topic, consider the following:
Is my question one that is likely to have been researched and for which data have been published? Believe it or not, not every topic has been researched and/or published in the literature.
Be flexible. Consider broadening or narrowing the topic if you are getting a limited number or an overwhelming number of results when you search. In nursing it can be helpful to narrow by thinking about a specific population (gender, age, disease or condition, etc.), intervention, or outcome.
Discuss your topic with your professor and be willing to alter your topic according to the guidance you receive.
Getting Ready for Research
Library Resources vs. the Internet
How (where from) do you receive information about your professional interests?
Advantages/disadvantages of using Web Resources
Evaluating Web Resources
Google or similar; Yahoo, Bing
Reddit, Digg, Quora
Become a member of professional organizations and use their online information
Use the SCSU library page to online databases
Building Your List of Keywords
Why Keyword Searching?
Why not just type in a phrase or sentence like you do in Google or Yahoo!?
Because most electronic databases store and retrieve information differently than Internet search engines.
A databases searches fields within a collection of records. These fields include the information commonly found in a citation plus an abstract (if available) and subject headings. Search engines search web content which is typically the full text of sources.
The bottom line: you get better results in a database by using effective keyword search strategies.
To develop an effective search strategy, you need to:
determine the key concepts in your topic and
develop a good list of keyword synonyms.
Why use synonyms?
Because there is more than one way to express a concept or idea. You don’t know if the article you’re looking for uses the same expression for a key concept that you are using.
Consider: Will an author use:
Hypertension or High Blood Pressure?
Teach or Instruct?
Therapy or Treatment?
Don’t get “keyword lock!” Be willing to try a different term as a keyword. If you are having trouble thinking of synonyms, check a thesaurus, dictionary, or reference book for ideas.
How to find the SCSU Library Website
SCSU online databases
SCSU Library Web page
Test your knowledge:
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Basic Research Skills
Identifying a Scholarly Source
How do you evaluate a source of information to determine if it is appropriate for academic/scholarly use. There is no set “checklist” to complete but below are some criteria to consider when you are evaluating a source.
Does the author cite reliable sources?
How does the information compare with that in other works on the topic?
Can you determine if the information has gone through peer-review?
Are there factual, spelling, typographical, or grammatical errors?
Who do you think the authors are trying to reach?
Is the language, vocabulary, style and tone appropriate for intended audience?
What are the audience demographics? (age, educational level, etc.)
Are the authors targeting a particular group or segment of society?
Who wrote the information found in the article or on the site?
What are the author’s credentials/qualifications for this particular topic?
Is the author affiliated with a particular organization or institution?
What does that affiliation suggest about the author?
Is the content current?
Does the date of the information directly affect the accuracy or usefulness of the information?
What is the author’s or website’s point of view?
Is the point of view subtle or explicit?
Is the information presented as fact or opinion?
If opinion, is the opinion supported by credible data or informed argument?
Is the information one-sided?
Are alternate views represented?
Does the point of view affect how you view the information?
What is the author’s purpose or objective, to explain, provide new information or news, entertain, persuade or sell?
Does the purpose affect how you view the information presented?
Exporting bibliography records
Zotero. Zotero AddOn for Chrome and Firefox. Zotero for Microsoft Word. Zotero AddOn for Edublog.
through the Zotero AddOn for browsers
through “export RIS” file
Copyright and Fair Use
Author Rights and Publishing & Finding Author Instructions for Publishing in Scholarly Journals