Context for our vision
- "We want to learn; not to be taught"
- Gen Z is the first iGeneration (post 1995)
- Technology has become central to their learning experience and lives with good reason
- 17 different employers and 5 careers expected for the average Gen Z
Who is Generation Z
- Born between 1995 - 2012 (nearly 73 millinon individuals)
- Entered college between 2013-14 and today
- Adapting the Education Environment to Gen Z Students
- Digital is King
- Individualization is Critical
- Be relevant to the Real-World
- Be engaged, increase student engagement, launch students into successful careers (Stansbury, 2017)
"Kids today have grown up with technology. They're looking for experiences that use tech purposefully, not frivolously," Julie Evans, CEO of Project Tomorrow (emphasis added - https://blogs.edweek.org/edweek/DigitalEducation/2018/08/generation_z_prefers_learning_from_youtube.html)
How college is different -- Today and yesterday. (2018 Hoffowler, H.)
- More students are going to college
- 2000-2017 saw an increase of 5.1 million students - U.S. Dept of Ed
- College is more competitive
- acceptance rates at competitive colleges has decreased
- College is more expensive
- College tuition has more that doubled since 1985
- Textbooks cost much more
- Textbook costs are 812% higher than in 1985
- More technology is used in teaching and in learning
- Online learning is a huge factor
- 69% of millennials think they learn better with technology than from people - 50% of respondents older than 45 agreed
- Students are more diverse
- 1970 - 15% diversity - 2018 - 42% diversity among students
- 1970 less than half of student were female - 2018 more than 1/2 are female
- Fewer students identify with organized religion
- 2005 more than 25% of students identified with an organized religion
- 2014 less than 16% of students identified with an organized religion
- Students experience stress at higher levels today
- 70% to 80% of students have a job while attending school
- 40% of them work more than 30 hours a week
Advising and Student Success
Generation Z differs from Millennials
Generation Z (Phigital Generation)
- iGen by Jean Twenge
- Robot-proof Higher Education by Joseph Aoun
- University technology not meeting Gen Z needs
- Sync learning up for Gen Z
- Who will be your next learner?
- Unique characteristics of Gen Z
- 2016 State of Digital Media in Higher Education
- Barnes & Noble College Report: Getting to Know Gen Z
- UPCEA An Insider's Guide to Gen Z and Higher Education
- Education Must Adapt to Gen Z
- How to Teach Gen Z Students
- 4 Tactics to Engage Gen Z Students
- Digital Textbooks Lead to Degree Completion
Learning in Times of Accelerating Change of Industrial Revolution 4.0
The Future 4.0 University (Business World Education, 12/25/18)
“Education needs to be aligned with the fundamental changes in the nature of work and address the issue of employability”, excogitated Albert Einstein. The concept of what a University ought to be has changed over a period of last 50 decades. Well countries are moving towards the “Knowledge Economy” model of development and the Universities are bound to play a more constructive role and take up a leadership position in globalization and technological advancements. “Knowledge Economy” a term coined by Peter Drucker (1969) in his book,The Age of Discontinuity, discerns four major areas of discontinuity.
Moving from a "push" approach to a "pull" reality
- Previously higher education was a push field - we produced the donuts (degrees) and we chose in the way and time we chose
- Now, the economy and society has shifted - our donuts have become "day old" and "week old" - they just don't sell or satisfy the "customer" (both students and employers)
- It is the employer and the student (the payer) who now are choosing what they want; when and how they want it
- Increasingly, that is online, just-in-time to keep up with the changing technologies, while not ignoring the basic soft skills
- As Jim Fong says: "the revenue stream (in higher ed) is now the adult learner"
- Employers are increasingly tired of higher ed not providing what they need in entry level applicants and are dropping requirements for degrees or creating their own certificates (and soon degrees)
Employment Outcomes of Bachelor's Students (National Center for Educational Statistics)
New Technologies Changing Higher Education & Society - from degrees to degrees+ lifelong learning
Does Higher Education Still Prepare People for Jobs? (Harvard Business Review, 1/2019)
In short, we believe that market demands clearly call for a paradigm change. More and more students are spending more and more money on higher education, and their main goal is largely pragmatic: to boost their employability and be a valuable contributor to the economy. Even if the value attached to a university degree is beneficial to those who obtain it, companies can help change the narrative by putting less weight on “higher education” as a measure of intellectual competence and job potential, and instead, approach hiring with more open-mindedness.
The 60 Year Curriculum: Developing New Educational Models to Serve the Agile Labor Market (Chris Dede, Evolllution)
The average lifespan of the next generation is projected to be 80 to 90 years, and most people will need to work past the age of 65 to have enough savings to retire. Teenagers need to prepare for a future of multiple careers spanning six decades, plus retirement. Educators are faced with the challenge of preparing young people for unceasing reinvention to take on many roles in the workplace, as well as for careers that do not yet exist.
Upskilling in the 21st Century (Singh, Entrepreneur, 1/1/2019)
How do you upskill 400 million people where job markets change every 10 years? The internet. Online education will take over traditional learning in classrooms in the decade ahead. The largest schools in the world will be online and not a state-owned university. In the next decade, certifications will be replaced by skill reports and projects students have worked on. Degrees will become obsolete.
Tutoring and studying programs are becoming more advanced thanks to artificial intelligence, and soon they will be more available and able to respond to a range of learning styles. There are many more AI applications for education that are being developed including AI mentors for learners, further development of smart content and a new method of personal development for educators through virtual global conferences. Education might be a bit slower to the adoption of artificial intelligence and machine learning, but the changes are beginning and will continue.
Emerging Technologies: Just what is Artificial Intelligence?
There is so much discussion and confusion about AI nowadays. People talk about deeplearning and computerVision without context. In this short video, we see the context for thinking about AI.
You can think of deep learning, machine learning and artificial intelligence as a set of Russian dolls nested within each other, beginning with the smallest and working out. Deep learning is a subset of machine learning, and machine learning is a subset of AI, which is an umbrella term for any computer program that does something smart. In other words, all machine learning is AI, but not all AI is machine learning, and so forth.
Delivering Learning Opportunities at Scale - with the Help of AI
Can a 'Family of Bots' Reshape College Teaching? - (Young, EdSurge, 4/13/2018)
Here’s the scenario: Last year in an online course on artificial intelligence with 400 students, two chatbots joined 13 human TAs to answer student questions about the course and its content. Students were told that software robots were in the mix, and they were challenged to identify which of the voices they were interacting with were human and which were machine. The robot TAs were given the names Stacy Sisko and Ian Braun. One bot was designed to be a bit more personable than the other: if a student mentioned she was from Chicago, Stacy Sisko would make a comment about the city. Ian Braun was all business, and weighed in on fewer student questions (he was an older version of the software that the researchers keep refining). At the end of the semester about half of the students correctly guessed that Stacy was merely computer code. Only ten percent correctly identified Ian as a bot. And ten percent mistakenly thought that two of the human TAs were chatbots.
Artificial Intelligence and Cognitive Computing - context
It’s already happening in the fields of law, medicine, and banking. IBM Watson has been helping doctors diagnose medical conditions and analyze MRIs. Platforms like Symantec’s eDiscovery and Kroll Ontrack help attorneys to sort through thousands of documents in the blink of an eye. FutureAdvisor or Wealthfront help investors to make smarter decisions. In these specific cases, the fields have played to the strengths of AI in order to make more tedious tasks manageable within a smaller window of time. And if you ask any teacher what they’d love more of in order to be more effective in their field: it’s time.
The Promise of Personalized Learning, Enabled by AI (Schroeder, Inside Higher Ed)
A centuries-old challenge for teachers has been how to adapt learning materials and presentations to meet the varied backgrounds and abilities of students. Emerging technologies can help meet students where they are and customize learning for them.
An Alternative View - AI vs. IA
Obsessing Over AI Is the Wrong Way to Think About the Future (Anant Jhingran, Wired)
We’re actually nowhere near the self-sustaining robots Isaac Asimov imagined in I, Robot. What we have instead is intelligence amplification (IA), a field with exponentially more potential to change the world in the immediate future. The distinction between AI and IA is as simple as it is significant. AI makes machines autonomous and detached from humans; IA, in on the other hand, puts humans in control and leverages computing power to amplify our capabilities.... Doctors, for example, stand to benefit tremendously from IA in their interactions with patients. Say you have a doctor at the Mayo Clinic making a diagnosis. The patient is relying on the doctor’s expertise—but the publication of new medical research far outpaces the doctor’s ability to consume and analyze it. That’s where IA comes in. Rather than depending on his or her finite body of knowledge, the doctor can utilize supercomputers capable of surveying vast amounts of information quickly to present decisions the doctor might not have thought of or known about.
A Cautionary Note from the Late Stephen Hawkings
[specific reference to future of AI in last minute of video]
Stephen Hawking, Elon Musk, and Bill Gates Warn About Artificial Intelligence (Michael Sainato, Observer)
Mr. Hawking recently joined Elon Musk, Steve Wozniak, and hundreds of others in issuing a letter unveiled at the International Joint Conference last month in Buenos Aires, Argentina. The letter warns that artificial intelligence can potentially be more dangerous than nuclear weapons. The ethical dilemma of bestowing moral responsibilities on robots calls for rigorous safety and preventative measures that are fail-safe, or the threats are too significant to risk. Elon Musk called the prospect of artificial intelligence “our greatest existential threat” in a 2014 interview with MIT students at the AeroAstro Centennial Symposium. “I’m increasingly inclined to think that there should be some regulatory oversight, maybe at the national and international level, just to make sure that we don’t do something very foolish.” Microsoft co-founder Bill Gates has also expressed concerns about Artificial Intelligence. During a Q&A session on Reddit in January 2015, Mr. Gates said, “I am in the camp that is concerned about super intelligence. First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that though the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don’t understand why some people are not concerned.”
Quantum Computing driven by qubits
While a classical computer works with bits as information placeholders, a quantum computer works with quantum bits (qubits). While bits carry information in either a 0 or 1 state, qubits can be 0s and 1s at the same time thanks to quantum superposition. Meanwhile, entanglement allows particles to be manipulated despite the distance between them — anything that happens to one particle will instantly be reflected in the other. Information can, therefore, be sent across greater distances far more quickly than with classical computers.
A Video for those with an appetite for AI geek-speak
[2 "future" hints in the first 40 seconds]
2019 Bridging AI and Quantum Technologies
Throwaway the textbook and check out these YouTube channels if you are interested in building a career in artificial intelligence:
9 You Tube Channels That Will Teach You Everything You Need to Know About Artificial Intelligence (Taylor Donovan Barnett, Interesting Engineering, 1/24/19)
Questions for Reflection and Action:
- What are we doing to assure that what we are teaching - and how we are teaching - will be relevant to graduates in five years?
- Equally important with the technology, is our pedagogy advancing and adapting to self-directed learning?
- Are we sure that the career path that we are preparing will be there in five years, or will machine learning bots and other technologies overtake that role?
- How are we preparing our colleagues and students to keep up with the incredible rate of change?
- How are we preparing our students to transition throughout their careers to the changing workforce needs?
- Are we engaging business and industry in collaborating to develop curricula that is most relevant?
- Are we engaging students in the teaching and learning process?