TWO YEARS AGO, Alison Darcy built a robot to help out the depressed. As a clinical research psychologist at Stanford University, she knew that one powerful way to help people suffering from depression or anxiety is cognitive behavioral therapy, or C.B.T. It’s a form of treatment in which a therapist teaches patients simple techniques that help them break negative patterns of thinking.
In a study with 70 young adults, Darcy found that after two weeks of interacting with the bot, the test subjects had lower incidences of depression and anxiety. They were impressed, and even touched, by the software’s attentiveness.
Many tell Darcy that it’s easier to talk to a bot than a human; they don’t feel judged.
Darcy argues this is a glimpse of our rapidly arriving future, where talking software is increasingly able to help us manage our emotions. There will be A.I.s that detect our feelings, possibly better than we can. “I think you’ll see robots for weight loss, and robots for being more effective communicators,” she says. It may feel odd at first
RECENT HISTORY HAS seen a rapid change in at least one human attitude toward machines: We’ve grown accustomed to talking to them. Millions now tell Alexa or Siri or Google Assistant to play music, take memos, put something on their calendar or tell a terrible joke.
One reason botmakers are embracing artificiality is that the Turing Test turns out to be incredibly difficult to pass. Human conversation is full of idioms, metaphors and implied knowledge: Recognizing that the expression “It’s raining cats and dogs” isn’t actually about cats and dogs, for example, surpasses the reach of chatbots.
Conversational bots thus could bring on a new wave of unemployment — or “readjustment,” to use the bloodless term of economics. Service workers, sales agents, telemarketers — it’s not hard to imagine how millions of jobs that require social interaction, whether on the phone or online, could eventually be eliminated by code.
One person who bought a Jibo was Erin Partridge, an art therapist in Alameda, Calif., who works with the elderly. When she took Jibo on visits, her patients loved it.
For some technology critics, including Sherry Turkle, who does research on the psychology of tech at M.I.T., this raises ethical concerns. “People are hard-wired with sort of Darwinian vulnerabilities, Darwinian buttons,” she told me. “And these Darwinian buttons are pushed by this technology.” That is, programmers are manipulating our emotions when they create objects that inquire after our needs.
The precursor to today’s bots, Joseph Weizenbaum’s ELIZA, was created at M.I.T. in 1966. ELIZA was a pretty crude set of prompts, but by simply asking people about their feelings, it drew them into deep conversations.
AI is being used to monitor students and their work. The most prominent uses of AI in higher education are attached to applications designed to protect or preserve academic integrity through the use of plagiarism-detection software (60%) and proctoring applications (42%) (see figure 1).
The chatbots are coming! A sizable percentage (36%) of respondents reported that chatbots and digital assistants are in use at least somewhat on their campuses, with another 17% reporting that their institutions are in the planning, piloting, and initial stages of use (see figure 2). The use of chatbots in higher education by admissions, student affairs, career services, and other student success and support units is not entirely new, but the pandemic has likely contributed to an increase in their use as they help students get efficient, relevant, and correct answers to their questions without long waits.Footnote10 Chatbots may also liberate staff from repeatedly responding to the same questions and reduce errors by deploying updates immediately and universally.
AI is being used for student success tools such as identifying students who are at-risk academically (22%) and sending early academic warnings (16%); another 14% reported that their institutions are in the stage of planning, piloting, and initial usage of AI for these tasks.
Nearly three-quarters of respondents said that ineffective data management and integration (72%) and insufficient technical expertise (71%) present at least a moderate challenge to AI implementation. Financial concerns (67%) and immature data governance (66%) also pose challenges. Insufficient leadership support (56%) is a foundational challenge that is related to each of the previous listed challenges in this group.
Current use of AI
Chatbots for informational and technical support, HR benefits questions, parking questions, service desk questions, and student tutoring
Research applications, conducting systematic reviews and meta-analyses, and data science research (my italics)
Library services (my italics)
Recruitment of prospective students
Providing individual instructional material pathways, assessment feedback, and adaptive learning software
Proctoring and plagiarism detection
Student engagement support and nudging, monitoring well-being, and predicting likelihood of disengaging the institution
Bagchi, M. (2020). Conceptualising a Library Chatbot using Open Source Conversational AI. DESIDOC Journal of Library & Information Technology, 40, 329–333. https://doi.org/10.14429/djlit.40.6.1561
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.
Session 2: The Digital Age: The Impact and Future Possibilities Offered by Data and Technology
Thank you for registering to participate in the second Reimagining Minnesota State forum. The Forums have been designed to spark not only individual reflection but what we hope can serve as catalysts for discussions in a variety of venues. The Forum will be recorded and available for viewing on the Reimagining website.
Below are the directions whether you are attending in person or by live stream.
Catherine Haslag: Is there any research to show students retention in an online class vs a face-to-face course?
the challenge is not collecting, but integrating, using data.
silos = cylinder of excellence.
technology innovation around advising. iPASS resources.
adaptive learning systems – how students advance through the learning process.
games and simulations Bryan Mark Gill. voice recognition,
next 3 to 5 years AR. by 2023 40% with AR and VR
AI around the controversial. Chatbot and Voice assistants.
Unizin: 13 founding members to develop platform, Canvas, instructional services, data for predictive analytic, consistent data standard among institutions,
University innovation Alliance. Analytics as the linchpin for students’ success. graduation rates increase. racial gap graduation. Georgia State.
digital ethics. Mark Gill and Susana Nuccetelli. digital ethics: Susana Nuccetelli brought her students from the Philosophy Dept to Mark Gill’s SCSu Vizlab so we can discuss ethics and AI, last semester. jobrien@educause.edu
assistant vice president for student success and prevention Morgan State U
the importance of training in technology adoption
Dr. Peter Smith, Orkand Endowed Chair and Professor of Innovative Practices in Higher Education at University of Maryland University College
social disruption, national security issue,
Allan Taft Candadian researcher, 700 hours / year learning something. 14 h/w.
learners deserve recognition
free range learning.
how do we get a value on people from a different background? knowledge discrimination. we value it on where they learned it. then how you learned it and what you can do with it. talent and capacity not recognized.
we, the campus, don’t control the forces for a very first time. MIT undergrad curricula is free, what will happen. dynamics at work here. declining student numbers, legislation unhappy. technology had made college more expensive, not less. doing the right thing, leads to more disruption. local will be better, if done well. workplace can become a place for learning.
learning is a social activity. distance learning: being on the farthest raw of 300 Princeton lecture. there is a tool and there is people; has to have people at the heart.
what will work not only for MN, but for each of the campuses, the personalization.
staying still is death.
Panel discussion
what is the role of faculty in the vendor and discussions about technology. a heat map shows that IT people were testing the vendor web site most, faculty and student much less.
Way back in 1983, I identified A.I. as one of 20 exponential technologies that would increasingly drive economic growth for decades to come.
Artificial intelligence applies to computing systems designed to perform tasks usually reserved for human intelligence using logic, if-then rules, decision trees and machine learning to recognize patterns from vast amounts of data, provide insights, predict outcomes and make complex decisions. A.I. can be applied to pattern recognition, object classification, language translation, data translation, logistical modeling and predictive modeling, to name a few. It’s important to understand that all A.I. relies on vast amounts of quality data and advanced analytics technology. The quality of the data used will determine the reliability of the A.I. output.
Machine learning is a subset of A.I. that utilizes advanced statistical techniques to enable computing systems to improve at tasks with experience over time. Chatbots like Amazon’s Alexa, Apple’s Siri, or any of the others from companies like Google and Microsoft all get better every year thanks to all of the use we give them and the machine learning that takes place in the background.
Deep learning is a subset of machine learning that uses advanced algorithms to enable an A.I. system to train itself to perform tasks by exposing multi-layered neural networks to vast amounts of data, then using what has been learned to recognize new patterns contained in the data. Learning can be Human Supervised Learning, Unsupervised Learningand/or Reinforcement Learning like Google used with DeepMind to learn how to beat humans at the complex game Go. Reinforcement learning will drive some of the biggest breakthroughs.
Autonomous computing uses advanced A.I. tools such as deep learning to enable systems to be self-governing and capable of acting according to situational data without human command. A.I. autonomy includes perception, high-speed analytics, machine-to-machine communications and movement. For example, autonomous vehicles use all of these in real time to successfully pilot a vehicle without a human driver.
Augmented thinking: Over the next five years and beyond, A.I. will become increasingly embedded at the chip level into objects, processes, products and services, and humans will augment their personal problem-solving and decision-making abilities with the insights A.I. provides to get to a better answer faster.
Technology is not good or evil, it is how we as humans apply it. Since we can’t stop the increasing power of A.I., I want us to direct its future, putting it to the best possible use for humans.
Here’s how to evaluate the potential for mobile solutions
Before they set foot in their first class, incoming college students face a maze of requirements and resources that will be critical to their success. So-called “student supports” abound. Yet forty percent of first-year studentsdon’t return the following year, and a growing number report information overload as they navigate campus life amid newfound independence.
The nine in 10 undergraduates who own smartphones are probably familiar with the xkcd about it. College-aged Americans check their devices more than 150 times per day. So it should be no surprise that a growing body of research suggests that mobile solutions can play a critical role in enhancing the student experience.
1. Is the mobile app native?
We’ve all had the frustrating experience of using a smartphone to navigate a page that was designed for a computer. But when designing native mobile apps, developers start with the small screen, which leads to simpler, cleaner platforms that get rid of the clutter of the desktop browsing experience.
As smartphones overtake laptops and desktops as the most popular way for young people to get online, native design is critical for universities to embrace.
2. Is there a simple content management system?
It’s also critical to explore whether mobile apps integrate with an institution’s existing LMS, CMS, and academic platforms. The most effective apps will allow you to draw upon and translate existing content and resources directly into the mobile experience. My note: this is why it is worth experimenting with alternatives to LMS, such as Facebook Groups: they allow ready-to-use SIMPLE mobile interface.
3. Does it allow you to take targeted action?
At-risk or disengaged students often require more targeted communication and engagement which, if used effectively, can prevent them falling into those categories in the first place.
Unlike web-based tools, mobile apps should not only communicate information, but also generate insights and reports, highlighting key information into how students use the platform.
4. Does it offer communication and social networking opportunities?
Teenagers who grew up with chatbots and Snapchat expect instant communication to be part of any online interaction. Instead of making students toggle between the student affairs office and conversations with advisors, mobile platforms that offer in-app messaging can streamline the experience and keep users engaged.
new forms of human-computer interaction (HCI) such as augmented reality (AR),virtual reality (VR) and mixed reality (MR).
p. 21
combining AR/VR/MR with cognitive computing and artificial intelligence (AI) technologies (such as machine learning, deep learning, natural language processing and chatbots).
Some thought-provoking questions include:
Will remote workers be able to be seen and interacted with via their holograms (i.e., attending their meetings virtually)? What would this mean for remote learners?
Will our smartphones increasingly allow us to see information overlaid on the real world? (Think Pokémon Go, but putting that sort of technology into a vast array of different applications, many of which could be educational in nature)
How do/will these new forms of HCI impact how we design our learning spaces?
Will students be able to pick their preferred learning setting (i.e., studying by a brook or stream or in a virtual Starbucks-like atmosphere)?
Will more devices/platforms be developed that combine the power of AI with VR/AR/MR-related experiences? For example, will students be able to issue a verbal question or command to be able to see and experience walking around ancient Rome?
Will there be many new types of learning experiences,like what Microsoft was able to achieve in its collaboration with Case Western Reserve University [OH]? Its HoloLens product transforms the way human anatomy can be taught.
p. 22 Extensive costs for VR design and development drive the need for collaborative efforts.
Case Western Reserve University, demonstrates a collaboration with the Cleveland Clinic and Microsoft to create active multi-dimensional learning using holography.
the development of more affordable high-quality virtual reality solutions.
AR game developed by the Salzburg University of Applied Sciences [Austria] (http://www.fh-salzburg.ac.at/en/) that teaches about sustainability, the environment and living green.
Whether using AR for a gamified course or to acclimate new students to campus, the trend will continue into 2017.
Google Expeditions This virtual reality field trip tool works in conjunction with Google Cardboard and has just been officially released. The app allows teachers to guide students through an exploration of 200 (and growing) historical sites and natural resources in an immersive, three-dimensional experience. The app only works on Android devices and is free.
Flippity This app works in conjunction with Google Sheets and allows teachers to easily make a Jeopardy-style game.
Google Science Journal This Android app allows users to do science experiments with mobile phones. Students can use sensors in the phone or connect external sensors to collect data, but can also take notes on observations, analyze and annotate within the app.
Google Cast This simple app solves issues of disparate devices in the classroom. When students download the app, they can project from their devices onto the screen at the front of the room easily. “You don’t have to have specific hardware, you just have to have Wi-Fi,”
Constitute This site hosts a database of constitutions from around the world. Anything digitally available has been aggregated here. It is searchable by topic and will pull out specific excerpts related to search terms like “freedom of speech.”
YouTube a database of YouTube Channels by subject to help educators with discoverability (hint subjects are by tab along the bottom of the document).
Zygote Body This freemium tool has a lot of functionality in the free version, allowing students to view different parts of human anatomy and dig into how various body systems work.
Pixlr This app has less power than Photoshop, but is free and fairly sophisticated. It works directly with Google accounts, so students can store files there.
uild With Chrome This extension to the Chrome browser lets kids play with digital blocks like Legos. Based on the computer’s IP address, the software assigns users a plot of land on which to build nearby. There’s a Build Academy to learn how to use the various tools within the program, but then students can make whatever they want.
Google CS First Built on Scratch’s programming language, this easy tool gives step-by-step instructions to get started and is great for the hesitant teacher who is just beginning to dip a toe into coding.
