Dollar Photo for stock images. They are closing down as of April 15th. Does anyone use another vendor that comparable? We loved that fact that we could prepay for credits ($1 per image) rather than pay for a monthly subscription.
“As I create and modify my course syllabi, I want to make sure my students use APA 7th ed. when writing their formal assignments. For those of you who also use APA, what do you say in your syllabi? What matters to you with your students giving proper credit to sources, images, or videos? I’m trying to do better and expect better”
I never assume the they learned the format, and I build in an APA workshop. I use OWL Purdue and go over a sample paper first, then the APA PowerPoint. Then I give them a low stakes assignment (like a discussion post) to practice.
I talk about documentation more as a convention of their discourse community, not just citations. There is a certain structure and way of writing in APA, that along with citations, represent the values of a particular discourse community. Those are the things that matter to me. (I also get more buy in from students.)
I was happy to discover that APA now has decent examples online, free, at their website. So in my instructions to students, I linked to the main page and also 3 specific pages with commonly used items, such as newspaper articles online, and YouTube videos. So step 1 is providing tools. Step 2 is clearly expressed grade penalties.
I actually don’t say anything my syllabus. What I do is in my LMS: give them a template and links to the Purdue OWL and other relevant websites. I have also written a “Dr. Kaminski’s APA 7th Ed Guide”. It’s more of my pet peeves and what they should be focusing on that students often miss. I give a lot of grace on the first (low stakes) written assignment, with more focus on the APA portion than the actual content. After that, I’m expecting them to have it down.
I post resources to our LMS. Mostly the usual subjects (APA, Purdue OWL, etc). I often add a short video on the bias-free writing chapter because that’s often not covered in their intro to research writing courses. For citations, I’m more a stickler for complete information than semicolons and whatnot. I don’t feel good about deducting points for anything that students were taught with APA 6 that is different in 7 since we changed the rules on them.
I provide a free workshop at the beginning of the semester to explain the ‘why’ and provide practice. It carries a rather high weighting in our rubrics so…some understanding and ‘free points’ if they use it appropriately.
I have a different document I refer to in the syllabus titled “Writing Expectations”. I briefly explain the importance of using APA and the characteristics of academic writing (e.g. paraphrasing, avoiding over usage of direct quotes, and other things I see in student writing). The second page is an APA job aid that shows the basics for citations, reference lists, and leveled headings.
unless the images the person is using are so unique that there is nothing else like them and she’s using them in a critique or as an instructive example (for example, explaining an aspect of a Picasso painting) that’s not fair use.
Copyright for Teachers was a free webinar that Dr. Beth Holland and I hosted a few years ago. We addressed a slew of copyright questions and scenarios during presentation. You can watch the recording here.
It is really about how the world now works, and reflective of ideas that first gained ground in the 1980s and 90s. Back then, the French theorist Jean Baudrillard contended that the difference between actuality and mere simulation had long since broken down, a notion encapsulated in the postmodern concept of “hyperreality”.
The sociologist Zygmunt Bauman, in his book Intimations of Postmodernity, summarised Baudrillard’s portrayal of a culture in which “images represent nothing but themselves, information does not inform, [and] desires turn into their own objectives”.
“We live in a world where there is more and more information, and less and less meaning,” wrote Baudrillard in 1981.
IM 690 lab plan for March 3, MC 205: Oculus Go and Quest
Readings:
TAM:Technology Acceptances Model
Read Venkatesh, and Davis and sum up the importance of their model for instructional designers working with VR technologies and creating materials for users of VR technologies.
UTAUT: using the theory to learn well with VR and to design good acceptance model for endusers: https://blog.stcloudstate.edu/ims/2020/02/20/utaut/
Watch both parts of Victoria Bolotina presentation at the Global VR conference. How is she applying UTAUT for her research?
Read Bracq et al (2019); how do they apply UTAUT for their VR nursing training?
joining a space and collaborating and communicating with other users
Assignment: Group work
Find one F2F and one online peer to form a group.
Based on the questions/directions before you started watching the videos:
– Does this particular technology fit in the instructional design (ID) frames and theories covered
– how does this particular technology fit in the instructional design (ID) frames and theories covered so far?
– what models and ideas from the videos you will see seem possible to be replicated by you?
exchange thoughts with your peers and make a plan to create similar educational product
Post your writing in the following D2L Discussions thread
Augmented Reality with Hololens Watch videos at computer station)
Until now, technology that readily identifies everyone based on his or her face has been taboo because of its radical erosion of privacy. Tech companies capable of releasing such a tool have refrained from doing so; in 2011, Google’s chairman at the time said it was the one technology the company had held back because it could be used “in a very bad way.” Some large cities, including San Francisco, have barred police from using facial
But without public scrutiny, more than 600 law enforcement agencies have started using Clearview in the past year, according to the company, which declined to provide a list. recognition technology.
Facial recognition technology has always been controversial. It makes people nervous about Big Brother. It has a tendency to deliver false matches for certain groups, like people of color. And some facial recognition products used by the police — including Clearview’s — haven’t been vetted by independent experts.
Clearview deployed current and former Republican officials to approach police forces, offering free trials and annual licenses for as little as $2,000. Mr. Schwartz tapped his political connections to help make government officials aware of the tool, according to Mr. Ton-That.
“We have no data to suggest this tool is accurate,” said Clare Garvie, a researcher at Georgetown University’s Center on Privacy and Technology, who has studied the government’s use of facial recognition. “The larger the database, the larger the risk of misidentification because of the doppelgänger effect. They’re talking about a massive database of random people they’ve found on the internet.”
Part of the problem stems from a lack of oversight. There has been no real public input into adoption of Clearview’s software, and the company’s ability to safeguard data hasn’t been tested in practice. Clearview itself remained highly secretive until late 2019.
The software also appears to explicitly violate policies at Facebook and elsewhere against collecting users’ images en masse.
while there’s underlying code that could theoretically be used for augmented reality glasses that could identify people on the street, Ton-That said there were no plans for such a design.
In May of last year, San Francisco banned facial recognition; the neighboring city of Oakland soon followed, as did Somerville and Brookline in Massachusetts (a statewide ban may follow). In December, San Diego suspended a facial recognition program in advance of a new statewide law, which declared it illegal, coming into effect. Forty major music festivals pledged not to use the technology, and activistsare calling for a nationwide ban. Many Democratic presidential candidates support at least a partial ban on the technology.
facial recognition bans are the wrong way to fight against modern surveillance. Focusing on one particular identification method misconstrues the nature of the surveillance society we’re in the process of building. Ubiquitous mass surveillance is increasingly the norm. In countries like China, a surveillance infrastructure is being built by the government for social control. In countries like the United States, it’s being built by corporations in order to influence our buying behavior, and is incidentally used by the government.
People can be identified at a distance by their heart beat or by their gait, using a laser-based system. Cameras are so good that they can read fingerprints and irispatterns from meters away. And even without any of these technologies, we can always be identified because our smartphones broadcast unique numbers called MAC addresses.
The data broker industry is almost entirely unregulated; there’s only one law — passed in Vermont in 2018 — that requires data brokers to register and explain in broad terms what kind of data they collect.
Until now, technology that readily identifies everyone based on his or her face has been taboo because of its radical erosion of privacy. Tech companies capable of releasing such a tool have refrained from doing so; in 2011, Google’s chairman at the time said it was the one technology the company had held back because it could be used “in a very bad way.” Some large cities, including San Francisco, have barred police from using facial recognition technology.
https://sched.co/JAqk
the type of data: wikipedia. the dangers of learning from wikipedia. how individuals can organize mitigate some of these dangers. wikidata, algorithms.
IBM Watson is using wikipedia by algorythms making sense, AI system
youtube videos debunked of conspiracy theories by using wikipedia.
semantic relatedness, Word2Vec
how does algorithms work: large body of unstructured text. picks specific words
lots of AI learns about the world from wikipedia. the neutral point of view policy. WIkipedia asks editors present as proportionally as possible. Wikipedia biases: 1. gender bias (only 20-30 % are women).
conceptnet. debias along different demographic dimensions.
citations analysis gives also an idea about biases. localness of sources cited in spatial articles. structural biases.
geolocation on Twitter by County. predicting the people living in urban areas. FB wants to push more local news.
danger (biases) #3. wikipedia search results vs wkipedia knowledge panel.
collective action against tech: Reddit, boycott for FB and Instagram.
data labor: what the primary resources this companies have. posts, images, reviews etc.
boycott, data strike (data not being available for algorithms in the future). GDPR in EU – all historical data is like the CA Consumer Privacy Act. One can do data strike without data boycott. general vs homogeneous (group with shared identity) boycott.
the wikipedia SPAM policy is obstructing new editors and that hit communities such as women.
how to access at different levels. methods and methodological concerns. ethical concerns, legal concerns,
tweetdeck for advanced Twitter searches. quoting, likes is relevant, but not enough, sometimes screenshot
engagement option
social listening platforms: crimson hexagon, parsely, sysomos – not yet academic platforms, tools to setup queries and visualization, but difficult to algorythm, the data samples etc. open sources tools (Urbana, Social Media microscope: SMILE (social media intelligence and learning environment) to collect data from twitter, reddit and within the platform they can query Twitter. create trend analysis, sentiment analysis, Voxgov (subscription service: analyzing political social media)
graduate level and faculty research: accessing SM large scale data web scraping & APIs Twitter APIs. Jason script, Python etc. Gnip Firehose API ($) ; Web SCraper Chrome plugin (easy tool, Pyhon and R created); Twint (Twitter scraper)
Facepager (open source) if not Python or R coder. structure and download the data sets.
TAGS archiving google sheets, uses twitter API. anything older 7 days not avaialble, so harvest every week.
social feed manager (GWUniversity) – Justin Litman with Stanford. Install on server but allows much more.
legal concerns: copyright (public info, but not beyond copyrighted). fair use argument is strong, but cannot publish the data. can analyize under fair use. contracts supercede copyright (terms of service/use) licensed data through library.
methods: sampling concerns tufekci, 2014 questions for sm. SM data is a good set for SM, but other fields? not according to her. hashtag studies: self selection bias. twitter as a model organism: over-represnted data in academic studies.
methodological concerns: scope of access – lack of historical data. mechanics of platform and contenxt: retweets are not necessarily endorsements.
ethical concerns. public info – IRB no informed consent. the right to be forgotten. anonymized data is often still traceable.
table discussion: digital humanities, journalism interested, but too narrow. tools are still difficult to find an operate. context of the visuals. how to spread around variety of majors and classes. controversial events more likely to be deleted.
takedowns, lies and corrosion: what is a librarian to do: trolls, takedown,
development kit circulation. familiarity with the Oculus Rift resulted in lesser reservation. Downturn also.
An experience station. clean up free apps.
question: spherical video, video 360.
safety issues: policies? instructional perspective: curating,WI people: user testing. touch controllers more intuitive then xbox controller. Retail Oculus Rift
app Scatchfab. 3modelviewer. obj or sdl file. Medium, Tiltbrush.
College of Liberal Arts at the U has their VR, 3D print set up.
Penn State (Paul, librarian, kiniseology, anatomy programs), Information Science and Technology. immersive experiences lab for video 360.
CALIPHA part of it is xrlibraries. libraries equal education. content provider LifeLiqe STEM library of AR and VR objects. https://www.lifeliqe.com/
libraians, IT staff, IDs. help faculty with course design, primarily online, master courses. Concordia is GROWING, mostly because of online students.
solve issues (putting down fires, such as “gradebook” on BB). Librarians : research and resources experts. Librarians helping with LMS. Broadening definition of Library as support hub.
digital humanities is born f the encounter between traditional humanities and computational methods.
p. 5. From Humanism to Humanities
While the foundations of of humanistic inquiry and the liberal arts can be traced back in the west to the medieval trivium and quadrivium, the modern and human sciences are rooted in the Renaissance shift from a medieval, church dominated, theocratic world view to be human centered one period the gradual transformation of early humanism into the disciplines that make up the humanities today Was profoundly shaped by the editorial practices involved in the recovery of the corpus of works from classical antiquity
P. 6. The shift from humanism to the institution only sanctioned disciplinary practices and protocols that we associate with the humanities today is best described as a gradual process of subdivision and specialization.
P. 7. Text-based disciplines in studies (classics, literature, philosophy, the history of ideas) make up, from the very start, the core of both the humanities and the great books curricular instituted in the 1920s and 1930s.
P. 10. Transmedia modes of argumentation
In the 21st-century, we communicate in media significantly more varied, extensible, and multiplicative then linear text. From scalable databases to information visualizations, from video lectures to multi-user virtual platforms serious content and rigorous argumentation take shape across multiple platforms in media. The best digital humanities pedagogy and research projects train students both in “reading “and “writing “this emergent rhetoric and in understanding how the reshape and three model humanistic knowledge. This means developing critically informed literacy expensive enough to include graphic design visual narrative time based media, and the development of interfaces (Rather then the rote acceptance of them as off-the-shelf products).
P. 11. The visual becomes ever more fundamental to the digital humanities, in ways that compliment, enhance, and sometimes are in pension with the textual.
There is no either/or, no simple interchangeability between language and the visual, no strict sub ordination of the one to the other. Words are themselves visual but other kinds of visual constructs do different things. The question is how to use each to its best effect into device meaningful interpret wing links, to use Theodor Nelson’s ludic neologism.
P. 11. The suite of expressive forms now encompasses the use of sound, motion graphics, animation, screen capture, video, audio, and the appropriation and into remix sink of code it underlines game engines. This expanded range of communicative tools requires those who are engaged in digital humanities world to familiarize themselves with issues, discussions, and debates in design fields, especially communication and interaction design. Like their print predecessors, form at the convention center screen environments can become naturalized all too quickly, with the results that the thinking that informed they were designed goes unperceived.
p. 13.
For digital humanists, design is a creative practice harnessing cultural, social, economic, and technological constraints in order to bring systems and objects into the world. Design in dialogue with research is simply a picnic, but when used to pose in frame questions about knowledge, design becomes an intellectual method. Digital humanities is a production based in Denver in which theoretical issues get tested in the design of implementations and implementations or loci after your radical reflection and elaboration.
Did you thaw humanists have much to learn from communication and media design about how to juxtapose and integrate words and images create hire he is of reading, Forge pathways of understanding, deployed grades in templates to best effect, and develop navigational schemata that guide in produce meaningful interactions.
P. 15. The field of digital digital humanities me see the emergence of polymaths who can “ do it all” : Who can research, write, shoot, edit, code, model, design, network, and dialogue with users. But there is also ample room for specialization and, particularly, for collaboration.
P. 16. Computational activities in digital humanities.
The foundational layer, computation, relies on principles that are, on the surface, at odds with humanistic methods.
P. 17. The second level involves processing in a way that conform to computational capacities, and this were explored in the first generation of digital scholarship and stylometrics, concordance development, and indexing.
P. 17.
Duration, analysis, editing, modeling.
Duration, analysis, editing, and modeling comprise fundamental activities at the core of digital humanities. Involving archives, collections, repositories, and other aggregations of materials, duration is the selection and organization of materials in an interpretive framework, argument, or exhibit.
P. 18. Analysis refers to the processing of text or data: statistical and quantitative methods of analysis have brought close readings of texts (stylometrics and genre analysis, correlation, comparisons of versions for alter attribution or usage patterns ) into dialogue with distant reading (The crunching cuff large quantities of information across the corpus of textual data or its metadata).
Edit think has been revived with the advent of digital media and the web and to continue to be an integral activity in textual as well as time based formats.
P. 18. Model link highlights the notion of content models- shapes of argument expressed in information structures in their design he digital project is always an expression of assumptions about knowledge: usually domain specific knowledge given an explicit form by the model in which it is designed.
P. 19. Each of these areas of activity- cure ration, analysis, editing, and modeling is supported by the basic building blocks of digital activity. But they also depend upon networks and infrastructure that are cultural and institutional as well as technical. Servers, software, and systems administration are key elements of any project design.
P. 30. Digital media are not more “evolved” have them print media nor are books obsolete; but the multiplicity of media in the very processes of mediation entry mediation in the formation of cultural knowledge and humanistic inquiry required close attention. Tug link between distant and clothes, macro and micro, and surface in depth becomes the norm. Here, we focus on the importance of visualization to the digital humanities before moving on to other, though often related, genre and methods such as Locative investigation, thick mapping, animated archives, database documentaries, platform studies, and emerging practices like cultural analytics, data mining and humanities gaming.
P. 35. Fluid texture out what he refers to the mutability of texts in the variants and versions Whether these are produced through Authorial changes, anything, transcription, translation, or print production
Cultural Analytics, aggregation, and data mining.
The field of cultural Analytics has emerged over the past few years, utilizing tools of high-end computational analysis and data visualization today sect large-scale coach data sets. Cultural Analytic does Not analyze cultural artifacts, but operates on the level of digital models of this materials in aggregate. Again, the point is not to pit “close” hermeneutic reading against “distant” data mapping, but rather to appreciate the synergistic possibilities and tensions that exist between a hyper localized, deep analysis and a microcosmic view
p. 42.
Data mining is a term that covers a host of picnics for analyzing digital material by “parameterizing” some feature of information and extract in it. This means that any element of a file or collection of files that can be given explicit specifications, or parameters, can be extracted from those files for analysis.
Understanding the rehtoric of graphics is another essential skill, therefore, in working at a skill where individual objects are lost in the mass of processed information and data. To date, much humanities data mining has merely involved counting. Much more sophisticated statistical methods and use of probability will be needed for humanists to absorb the lessons of the social sciences into their methods
P. 42. Visualization and data design
Currently, visualization in the humanities uses techniques drawn largely from the social sciences, Business applications, and the natural sciences, all of which require self-conscious criticality in their adoption. Such visual displays including graphs and charts, may present themselves is subjective or even unmediated views of reality, rather then is rhetorical constructs.
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Warwick, C., Terras, M., & Nyhan, J. (2012). Digital humanities in practice . London: Facet Publishing in association with UCL Centre for Digital Humanities.
Others have likened habitual Facebook use to a mental disorder, comparing it to drug addiction and even publishing magnetic-resonance images of what Facebook addiction “looks like in the brain.”
For abstainers, breaking up with Facebook freed up about an hour a day, on average, and more than twice that for the heaviest users.
research led by Ethan Kross, a professor of psychology at the University of Michigan, has found that high levels of passive browsing on social media predict lowered moods, compared to more active engagement.
