Date: Wednesday, April 3rd Time: 3:30 PM to 4:15 PM Conference Session: Concurrent Session 3 Streamed session Lead Presenter: Brian Kane (General Design LLC) Track: Research: Designs, Methods, and Findings Location: Juniper A Session Duration: 45min Brief Abstract:What happens when you apply design thinking to AI? AI presents a fundamental change in the way people interact with machines. By applying design thinking to the way AI is made and used, we can generate an unlimited amount of new ideas for products and experiences that people will love and use.https://onlinelearningconsortium.org/olc-innovate-2019-session-page/?session=6964&kwds=
Notes from the session:
design thinking: get out from old mental models. new narratives; get out of the sci fi movies.
narrative generators:
we need machines to make mistakes. Ai even more then traditional software.
Lessons learned: don’t replace people
Date: Thursday, April 4th Time: 8:45 AM to 9:30 AM Conference Session: Concurrent Session 4 Streamed session Lead Presenter: Matt Crosslin (University of Texas at Arlington LINK Research Lab) Track: Experiential and Life-Long Learning Location: Cottonwood 4-5 Session Duration: 45min Brief Abstract:How can teachers utilize chatbots and artificial intelligence in ways that won’t remove humans out of the education picture? Using tools like Twine and Recast.AI chatobts, this session will focus on how to build adaptive content that allows learners to create their own heutagogical educational pathways based on individual needs.++++++++++++++++
Date: Thursday, April 4th Time: 9:45 AM to 10:30 AM Conference Session: Concurrent Session 5 Streamed session Lead Presenter: Maikel Alendy (FIU Online) Co-presenter: Sky V. King (FIU Online – Florida International University) Track: Teaching and Learning Practice Location: Cottonwood 4-5 Session Duration: 45min Brief Abstract:“This is Us” demonstrates how leveraging storytelling in learning engages students to effectively communicate their authentic story, transitioning from consumerism to become creators and influencers. Addressing responsibility as a digital citizen, information and digital literacy, online privacy, and strategies with examples using several edtech tools, will be reviewed.++++++++++++++++++
Date: Thursday, April 4th Time: 11:15 AM to 12:00 PM Conference Session: Concurrent Session 6 Streamed session Lead Presenter: Kristin Bushong (Arizona State University ) Co-presenter: Heather Nebrich (Arizona State University) Track: Effective Tools, Toys and Technologies Location: Juniper C Session Duration: 45min Brief Abstract:Considering today’s overstimulated lifestyle, how do we engage busy learners to stay on task? Join this session to discover current efforts in implementing ubiquitous educational opportunities through customized interests and personalized learning aspirations e.g., adaptive math tools, AI support communities, and memory management systems.+++++++++++++
Date: Thursday, April 4th Time: 1:15 PM to 2:00 PM Conference Session: Concurrent Session 7 Streamed session Lead Presenter: Katie Linder (Oregon State University) Co-presenter: June Griffin (University of Nebraska-Lincoln) Track: Teaching and Learning Practice Location: Cottonwood 4-5 Session Duration: 45min Brief Abstract:The concept of High-impact Educational Practices (HIPs) is well-known, but the conversation about transitioning HIPs online is new. In this session, contributors from the edited collection High-Impact Practices in Online Education will share current HIP research, and offer ideas for participants to reflect on regarding implementing HIPs into online environments.https://www.aacu.org/leap/hipshttps://www.aacu.org/sites/default/files/files/LEAP/HIP_tables.pdf+++++++++++++++++++++++
Date: Thursday, April 4th Time: 3:45 PM to 5:00 PM Streamed session Lead Presenter: Manoush Zomorodi (Stable Genius Productions) Track: N/A Location: Adams Ballroom Session Duration: 1hr 15min Brief Abstract:How can we ensure that students and educators thrive in increasingly digital environments, where change is the only constant? In this keynote, author and journalist Manoush Zomorodi shares her pioneering approach to researching the effects of technology on our behavior. Her unique brand of journalism includes deep-dive investigations into such timely topics as personal privacy, information overload, and the Attention Economy. These interactive multi-media experiments with tens of thousands of podcast listeners will inspire you to think creatively about how we use technology to educate and grow communities.Friday
Date: Friday, April 5th Time: 8:30 AM to 9:30 AM Streamed session Lead Presenter: Michael Caulfield (Washington State University-Vancouver) Track: N/A Location: Adams Ballroom Position: 2 Session Duration: 60min Brief Abstract:Years ago, John Lyndon (then Johnny Rotten) sang that “anger is an energy.” And he was right, of course. Anger isn’t an emotion, like happiness or sadness. It’s a reaction, a swelling up of a confused urge. I’m a person profoundly uncomfortable with anger, but yet I’ve found in my professional career that often my most impactful work begins in a place of anger: anger against injustice, inequality, lies, or corruption. And often it is that anger that gives me the energy and endurance to make a difference, to move the mountains that need to be moved. In this talk I want to think through our uneasy relationship with anger; how it can be helpful, and how it can destroy us if we’re not careful.++++++++++++++++
Date: Friday, April 5th Time: 10:45 AM to 11:30 AM Conference Session: Concurrent Session 10 Streamed session Lead Presenter: Laurie Daily (Augustana University) Co-presenter: Sharon Gray (Augustana University) Track: Problems, Processes, and Practices Location: Juniper A Session Duration: 45min Brief Abstract:The purpose of this session is to explore the implementation of a Community of Practice to support professional development, enhance online course and program development efforts, and to foster community and engagement between and among full and part time faculty.+++++++++++++++
Date: Friday, April 5th Time: 11:45 AM to 12:30 PM Conference Session: Concurrent Session 11 Streamed session Lead Presenter: Katrina Rainer (Strayer University) Co-presenter: Jennifer M McVay-Dyche (Strayer University) Track: Teaching and Learning Practice Location: Cottonwood 2-3 Session Duration: 45min Brief Abstract:Learning is more effective and organic when we teach through the art of storytelling. At Strayer University, we are blending the principles story-driven learning with research-based instructional design practices to create engaging learning experiences. This session will provide you with strategies to strategically infuse stories into any lesson, course, or curriculum.
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.
+++++++++++++++++++++++++++
Warwick, C., Terras, M., & Nyhan, J. (2012). Digital humanities in practice . London: Facet Publishing in association with UCL Centre for Digital Humanities.
Colleges around the country have also started hiring staff members with titles like OER Coordinator and Affordable Content Librarian. Our series looked into how the movement is changing, and the research into the costsand benefits. You can even hear a podcast version here.
Flipped classrooms seem to be growing exponentially
Robert Talbert, a professor of mathematics at Grand Valley State University and author of the book Flipped Learning. Talbert recently tabulated how many scholarly articles are published each year about “flipping” instruction, meaning that traditional lecture-style material is delivered before class (often using videos) so that classroom time can be used for discussion and other more active learning.
More professors are looking to experts to help them teach. (Though some resist.)
By 2016, there were an estimated 13,000 instructional designers on U.S. campuses, according to a report by Intentional Futures. And that number seems to be growing.
There’s also a growing acceptance of the scholarly discipline known as “learning sciences,” a body of research across disciplines of cognitive science, computer science, psychology, anthropology and other fields trying to unlock secrets of how people learn and how to best teach.
Students are also finding their own new ways to learn online, by engaging in online activism. The era of a campus bubble seems over in the age of Twitter
Colleges are still struggling to find the best fit for online education
And what does it mean to teach an age of information overload and polarization?
Perhaps the toughest questions of all about teaching in the 21st century is what exactly is the professor’s role in the Internet age. Once upon a time the goal was to be the ‘sage on the stage,’ when lecturing was king. Today many people argue that the college instructor should be more of a ‘guide on the side.’ But as one popular teaching expert notes, even that may not quite fit.
And in an era of intense political polarization, colleges and professors are looking for best to train students to become digitally literate so they can play their roles as informed citizens. But just how to do that is up for debate, though some are looking for a nonpartisan solution.
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.
Eureka: machine learning tool, brainstorming engine. give it an initial idea and it returns similar ideas. Like Google: refine the idea, so the machine can understand it better. create a collection of ideas to translate into course design or others.
Netlix:
influencers and microinfluencers, pre- and doing the execution
a machine can construct a book with the help of a person. bionic book. machine and person working hand in hand. provide keywords and phrases from lecture notes, presentation materials. from there recommendations and suggestions based on own experience; then identify included and excluded content. then instructor can construct.
Design may be the least interesting part of the book for the faculty.
multiple choice quiz may be the least interesting part, and faculty might want to do much deeper assessment.
use these machine learning techniques to build assessment. how to more effectively. inquizitive is the machine learning
students engagements and similar prompts
presence in the classroom: pre-service teachers class. how to immerse them and practice classroom management skills
First class: marriage btw VR and use of AI – an environment headset: an algorithm reacts how teachers are interacting with the virtual kids. series of variables, oppty to interact with present behavior. classroom management skills. simulations and environments otherwise impossible to create. apps for these type of interactions
facilitation, reflection and research
AI for more human experience, allow more time for the faculty to be more human, more free time to contemplate.
Jason: Won’t the use of AI still reduce the amount of faculty needed?
Christina Dumeng: @Jason–I think it will most likely increase the amount of students per instructor.
Andrew Cole (UW-Whitewater): I wonder if instead of reducing faculty, these types of platforms (e.g., analytic capabilities) might require instructors to also become experts in the various technology platforms.
Dirk Morrison: Also wonder what the implications of AI for informal, self-directed learning?
Kate Borowske: The context that you’re presenting this in, as “your own jazz band,” is brilliant. These tools presented as a “partner” in the “band” seems as though it might be less threatening to faculty. Sort of gamifies parts of course design…?
Dirk Morrison: Move from teacher-centric to student-centric? Recommender systems, AI-based tutoring?
Andrew Cole (UW-Whitewater): The course with the bot TA must have been 100-level right? It would be interesting to see if those results replicate in 300, 400 level courses
This is a free event, thanks to our founding conference sponsor: School of Information at San José State University.
ATTENDING: We will send links for attending the conference a day or two before the event.
If you have friends or colleagues that wish to attend, this is a free event and we encourage you to share our information widely. However, please send them to the conference registration page (https://www.library20.com/instructionaldesign) rather than giving them the above link directly as it will allow us to track participation.
What is ID: ID create an environment conductive to students’ success. Thoughtful and applied design. Making faculty and instructors’ life easier. Allow faculty to do what they do best.
Lindsey: solving the instructional problem with the tools at hand.
go-to ed tech? What is the hot tech right now?
Lindsey: H5P (open source) CC – licensed, Moodle, WordPress, build online tutorials for free (Isolde), Norway, well based, VR tours. Will H5P become paid? Michael: cell phones Dana: Emory VoiceThread. From the chat: Articulate365 (pricy), Kahoot, Peardeck, Yellowdig, vidgrid, Adobe Spark, Adobe POst, padlet, Groupme instead of Canvas, Vyond, Coggle, wakelet, Phinx
Suggestions for librarians who want to build ID skills. Dana: connect with the regional community if no ID on campus. Community of practice. Using ID tools, speakers outside of campus. Lindsey: teaching myself what is most interesting to me. what technologies are important. Find a learning community. Michael: repeat the others
keep up to date on ID theory and practices: Dana – ELI, OLC (Online Learning Consortium). ELearning Heroes. Lindsay: corporate word. Michael: POD
the one-shot instruction: what is the approach (q/n from the chat); Dana – ID as a services. person dedicated following up with people requested either ID class or training, open the line of communication. summative evaluation type of activity since we are failing to evaluate how well students absorbed the information. LIndsey: one-shot for basics (e.g. freshman), build scaffold program, reserved the one shot for meeting with librarians, for hands-on. Michael: work with faculty member and rewrite a program, build assessment rather then only deliver
areas of impact: subject matter librarians, working with faculty to use of the library resources, new faculty drawn in info and if not follow up, Canvas support. Michael: librarians and ID working directly with faculty rewriting their curricula, measure it, demonstrating library need, 3000 students – correlation. document the lib contribution to student learning directly, the teaching-learning culture change. using info and data in more authentic ways. Lindsey: disconnect the way librarian teach vs faculty teach. Coordination scaffolding.
q/n from the chat. easily. how can non ID librarian can easily implement ID type:
Lindsey: new to ID? Google. Jargon and Acronyms. re framing how you see ed technology. technology as something to get the job done. no need to get fancy.
Dana: same as Lindsey. But also learning theories and learning outcomes. From ID perspective: what they will come out with by the end of the session. action words.
Michael: mindset. what students want to learn, before what I will teach. backward design – understanding by design. UDL. Grab a friend and talk through.
Tara
ed tech is not getting job done:
clickers for attendance is horrible idea.
I had a really interesting role in grad school where we lived in the land between tech support and pedagogical / design support.
From Rajesh Kumar Das to All panelists and other attendees: (02:38 PM)
Good to hear from mike about affective learning. In this case, could you please focus what kind of technique is approprite for what, i.e. Didactic instruction, a low-complexity teaching technique such as a “Quiz Bowl”, or Jigsaw Method as high-complexity strategy, or both.
From Hailey W. to All panelists and other attendees: (02:36 PM)
As an ID librarian and the campus LMS administrator I struggle with getting them to see that other side of my role. That I’m not just “tech support”. Anyone else? Een jsut not being tech support?
From Vickie Kline to All panelists and other attendees: (02:44 PM)
As a librarian not formally trained in ID, I think a good entry point for exploring is Universal Design for Learning. We also need to pay attention to creating accessibility materials…
From Heather Quintero to All panelists and other attendees: (02:45 PM)
I always start with ADDIE… I am formally trained in ID and am an IT trainer for librarians. ADDIE is a framework for every class I make for both live and online classes. Don’t disregard ADDIE.
From Allison Rand to All panelists and other attendees: (02:47 PM)
The Wiggins and McTighe is a great book!
From Roberta (Robin) Sullivan to All panelists and other attendees: (02:53 PM)
@Rachel, Peggy, Shane – an open source course is available. Check out the SUNY’s Quality by Design (QbD): Strategies for Effective Teaching and Quality Course Design at: http://suny.edu/qbd This course is available as a facilitated version at least once each semester and as a self-paced non-facilitated version in Blackboard’s CourseSites. After completing the course requirements you can earn a Digital Badge to show your accomplishment.
From Naomi Toftness to All panelists and other attendees: (02:55 PM)
Just heard the terms “deliberate innovation” vs. “desperate innovation” that totally speaks to my situation with wanting to adopt the new cool tech
++++++++++++++++++++++ SESSION LINK – https://sas.elluminate.com/d.jnlp?sid=2008350&password=LIB2019IDPart7 — If the session link doesn’t work for you, please copy and paste into your browser.
Session Title: Gamifying Instruction: Breakouts and Badges!
Your Name and Title: Dr. Brenda Boyer, Librarian & Instructor
Your Library, School, or Organization Name: Kutztown Sr. High School, Rutgers University
Your Twitter Handle (@name): @bsboyer
Name(s) of Co-Presenter(s): Brenda Boyer
Area of the World from Which You Will Present: Kutztown, PA
Language in Which You Will Present: English
Target Audience: Instructional Design Librarians
Short Session Description: Build engagement for your online library instruction using LMS features, Breakout boxes, and digital badges.
Session Strand (use the “tag”): {Session Strand (use the “tag”):}
Full Session Description: It’s time to amp up your library instruction! Gamifying instruction in research skills such as database usage, advanced searching, & more can increase engagement and drive independent learning for students of all ages. This session will describe how learning management system (LMS) features can be combined with digital microcredentials (i.e. badges) and breakout boxes to gamify instruction that can be otherwise deemed boring (for both the learners and the librarian!).
Link to Conference Site Session Proposal (full URL with http://):https://www.library20.com/forum/topics/gamifying-instruction-breakouts-and-badges
Other Websites / URLs Associated with Your Session:
Your Bio: Dr. Brenda Boyer is a librarian and instructional designer. She has developed online instruction for secondary learners in the Kutztown (PA) School District, as well as for graduate and professional development learners at Wilson College and Rutgers University. She designed and instructs the Rutgers graduate course, Learning Theory, Inquiry, & Instructional Design, and is a frequent presenter at AASL, Internet@Schools. She has published articles in School Library Journal, Teacher Librarian, and School Library Connection.
are we getting the job done, is our instruction sticking, what evidence we do have?
differentiate: who is ready to do what” at what skill level? how to bring everybody up to speed?
3 elements of Digital Gamification: leverage LMS (set game levels); how digital badges are paired 3. using digital breakout boxes to push challenge, skills
each chat as prerequisite for the next. prerequisite in LMS. Each game level is module. completed with a quizz. if they pass the quiz, opens challenge.1. what is page (facts about a tool to learn about[ what the tool does, feature, etc.) 2. suppe rshort video tour (3 min max), talk about something unique 3. quick quiz (max 5 q/s from the intro page and video). pass the quiz (100 %) to unlock the challenge level. 4. challenge level. digital breakout box embedded in the LMS. breakout using Google Forms. various locks (words, letter, numbers)
Badges why?
Badgr, Credly, iDoceo
Breakout Boxes
++++++++++++++++++++++
SESSION LINK – https://sas.elluminate.com/d.jnlp?sid=2008350&password=LIB2019IDPart8 — If the session link doesn’t work for you, please copy and paste into your browser. Session Title: Improving Library Tutorials: The Multimedia Design Principles
Your Name and Title: Darlene Aguilar, Instructional Design Librarian
Your Library, School, or Organization Name: Loyola Marymount University
Your Twitter Handle (@name): @DarleneA_ID
Name(s) of Co-Presenter(s):
Area of the World from Which You Will Present: Los Angeles, CA
Short Session Description: This session will review Mayer’s (2001) Multimedia Design Principles to help improve instructional modules, tutorials, and videos.
Session Strand (use the “tag”): {Session Strand (use the “tag”):}
Full Session Description: Librarians are creating more online modules, videos, and tutorials to teach information literacy skills. Whether designing instruction online or in-person, research-based instructional methods are required and learning Mayer’s Multimedia Design Principles is the best place to start. In this session, I will review essential prior-knowledge on image types and working memory. I will then show learners how to minimize cognitive overload using these 12 principles: multimedia, spatial contiguity, temporal contiguity, coherence, modality, redundancy, individual differences, signaling, pacing, concepts first, personalization, and human voice.
Link to Conference Site Session Proposal (full URL with http://):https://www.library20.com/forum/topics/improving-library-tutorials-the-multimedia-design-principles
Other Websites / URLs Associated with Your Session:https://linkedin.com/in/darlene-aguilar/
Your Bio: Darlene Aguilar is an Instructional Design Librarian at Loyola Marymount University where she designs and develops video tutorials and online modules on information literacy and library related topics. Additionally, she provides “best practices” training in instructional design to other LMU librarians. She graduated from the University of Southern California with a Master’s in Education for Learning Design and Technology and previously worked at LAUSD for 7 years. She strives to remove learning barriers that are embedded in instruction and curriculum and make learning accessible to all learners.
Open Textbook Webinar — a 90-minute online meeting to learn about open textbooks.
Peer review of open textbooks is a critical component of assessing quality and supporting faculty looking for resources to use in their own classes. After the workshop, you’ll be eligible to earn a $200 stipend if you provide a short review of an open textbook from the OpenTextbook Library. Reviews are due 6-8 weeks following the workshop.
To prepare for the webinar, please take a few minutes and visit the Open Textbook Library (http://open.umn.edu/opentextbooks/). Glance through the Open Textbook Library and look for textbooks in your discipline that may be appropriate for you to review. In order to receive the $200 stipend, you must 1) participate in the webinar and 2) complete a textbook review. (Please note: There may not be texts available for review in your areas of expertise.)
When:Wednesday, November 14, 2018; 2:30 pm – 4:00 pm
Note that additional Open Textbook Webinars are scheduled throughout the academic year. Please contact Karen Pikula, OER Faculty Development Coordinator, at Karen.Pikula@minnstate.edu if you cannot attend the meeting on Monday.
Sejnowski, T. J. (2018). The Deep Learning Revolution. Cambridge, MA: The MIT Press.
How deep learning―from Google Translate to driverless cars to personal cognitive assistants―is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Buzzwords like “deep learning” and “neural networks” are everywhere, but so much of the popular understanding is misguided, says Terrence Sejnowski, a computational neuroscientist at the Salk Institute for Biological Studies.
Sejnowski, a pioneer in the study of learning algorithms, is the author of The Deep Learning Revolution(out next week from MIT Press). He argues that the hype about killer AI or robots making us obsolete ignores exciting possibilities happening in the fields of computer science and neuroscience, and what can happen when artificial intelligence meets human intelligence.
Machine learning is a very large field and goes way back. Originally, people were calling it “pattern recognition,” but the algorithms became much broader and much more sophisticated mathematically. Within machine learning are neural networks inspired by the brain, and then deep learning. Deep learning algorithms have a particular architecture with many layers that flow through the network. So basically, deep learning is one part of machine learning and machine learning is one part of AI.
December 2012 at the NIPS meeting, which is the biggest AI conference. There, [computer scientist] Geoff Hinton and two of his graduate students showed you could take a very large dataset called ImageNet, with 10,000 categories and 10 million images, and reduce the classification error by 20 percent using deep learning.Traditionally on that dataset, error decreases by less than 1 percent in one year. In one year, 20 years of research was bypassed. That really opened the floodgates.
The inspiration for deep learning really comes from neuroscience.
AlphaGo, the program that beat the Go champion included not just a model of the cortex, but also a model of a part of the brain called the basal ganglia, which is important for making a sequence of decisions to meet a goal. There’s an algorithm there called temporal differences, developed back in the ‘80s by Richard Sutton, that, when coupled with deep learning, is capable of very sophisticated plays that no human has ever seen before.
there’s a convergence occurring between AI and human intelligence. As we learn more and more about how the brain works, that’s going to reflect back in AI. But at the same time, they’re actually creating a whole theory of learning that can be applied to understanding the brain and allowing us to analyze the thousands of neurons and how their activities are coming out. So there’s this feedback loop between neuroscience and AI
