Social media as a learning tool: Five suggested sses for the classroom — from frontierinternet.com; with thanks to Laura Tscholl, Communications Specialist | The Gateway for this resource
On 11/06/2018,
in colleges, community colleges, cost of getting a degree, data related items, digital learning, higher education, IT in HE, leadership, liberal arts, platforms, student-related, universities,
by Daniel Christian
On 11/06/2018,
in 21st century, 24x7x365 access, accessibility / UDL, adjunct faculty, analytics, Artificial Intelligence/Agents/LLMs/and Related, assistive technologies, attention, blended learning, bots, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, Daniel S. Christian, digital learning, e-books, e-publishing related items (EPUB and more), e-readers, education, education technology, elearning, engagement / engaging students, face-to-face, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), hybrid learning, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interaction design, interactivity, interface design, internet, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning from the Living [Class] Room, learning preferences, library / librarians, memory, more voice more choice more control, neurodivergent/special needs, personalized/customized learning, platforms, productivity / tips and tricks, reading, society, student-related, teachers, teaching & learning, technology (general), tools, traditional / tradition, training / L&D, universities, user experience (UX), user interface design, using teams, vendors, vision/possibilities, visualizing information, writing, youth,
by Daniel Christian
From DSC:
I have often reflected on differentiation or what some call personalized learning and/or customized learning. How does a busy teacher, instructor, professor, or trainer achieve this, realistically?
It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all. That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!
- Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students
- Or learners that have different physical capabilities or restrictions
- Or learners that have different backgrounds and/or levels of prior knowledge
- Etc., etc., etc.
Educators and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc. On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?
Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.
Some of the ways that this could happen:
Use an HTML like language when writing a textbook, such as:
<MainPoint> The text for the main point here. </MainPoint>
<SubPoint1>The text for the subpoint 1 here.</SubPoint1>
<DetailsSubPoint1>More detailed information for subpoint 1 here.</DetailsSubPoint1>
<SubPoint2>The text for the subpoint 2 here.</SubPoint2>
<DetailsSubPoint2>More detailed information for subpoint 2 here.</DetailsSubPoint2>
<SubPoint3>The text for the subpoint 3 here.</SubPoint3>
<DetailsSubPoint3>More detailed information for subpoint 3 here.</DetailsSubPoint1>
<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>
<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>
<Conclusion> The text for the concluding comments here.</Conclusion>
<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.
Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples
of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>
On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:
- Show me just the main points
- Then add on the sub points
- Then fill in the details
OR - Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.
It’s like the layers of a Microsoft HoloLens app of the human anatomy:
Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:
This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.
Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience.
To recap:
- “Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.
- This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)
- Publishers create “overlays” or various layers that can be turned on or off by the learners
- Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.
- Can instantly collapse chapters to main ideas/outlines.
On 11/06/2018,
in active learning, attention, blended learning, Bring your own device (BYOD), change, collaboration, colleges, communications, community colleges, digital learning, education technology, engagement / engaging students, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, K-12 related, learning, learning ecosystem, learning hubs & pods & microschooling, learning spaces, library / librarians, maker movement, participation, platforms, project-based learning, second screen apps, smart classrooms, smart/connected TV, social learning / networks, student-related, teachers, teaching & learning, technologies for your home, technology (general), tools, trends, universities, user experience (UX), vendors, web-based collaboration, youth,
by Daniel Christian
Top Trends in Active and Collaborative Learning — from thesextantgroup.com by Joe Hammett
Excerpts:
My daughter is a maker. She spends hours tinkering with sewing machines and slime recipes, building salamander habitats and the like. She hangs out with her school friends inside apps that teach math and problem solving through multi-player games. All the while, they are learning to communicate and collaborate in ways that are completely foreign to their grandparent’s generation. She is 10 years old and represents a shift in human cognitive processing brought about by the mastery of technology from a very young age. Her generation and those that come after have never known a time without technology. Personal devices have changed the shared human experience and there is no turning back.
The spaces in which this new human chooses to occupy must cater to their style of existence. They see every display as interactive and are growing up knowing that the entirety of human knowledge is available to them by simply asking Alexa. The 3D printer is a familiar concept and space travel for pleasure will be the norm when they have children of their own.
Current trends in active and collaborative learning are evolving alongside these young minds and when appropriately implemented, enable experiential learning and creative encounters that are changing the very nature of the learning process. Attention to the spaces that will support the educators is also paramount to this success. Lesson plans and teaching style must flip with the classroom. The learning space is just a room without the educator and their content.
…
8. Flexible and Reconfigurable
With floor space at a premium, classrooms need to be able to adapt to a multitude of uses and pedagogies. Flexible furniture will allow the individual instructor freedom to set up the space as needed for their intended activities without impacting the next person to use the room. Construction material choices are key to achieving an easily reconfigurable space. Raised floors and individually controllable lighting fixtures allow a room to go from lecture to group work with ease. Whiteboard paints and rail mounting systems make walls reconfigurable too!.
Active Learning, Flipped Classroom, SCALE-UP, TEAL Classroom, whatever label you choose to place before it, the classroom, learning spaces of all sorts, are changing. The occupants of these spaces demand that they are able to effectively, and comfortably, share ideas and collaborate on projects with their counterparts both in person and in the ether. A global shift is happening in the way humans share ideas. Disruptive technology, on a level not seen since the assembly line, is driving a change in the way humans interact with other humans. The future is collaborative.
On 10/31/2018,
in 21st century, A/V -- audio/visual, adjunct faculty, Amazon, Apple, Artificial Intelligence/Agents/LLMs/and Related, attention, blended learning, bots, Bring your own device (BYOD), cloud-based computing / apps / other cloud-related, collaboration, colleges, communities of practice, community colleges, Daniel S. Christian, design, digital learning, distance education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty, future, future of higher education, Google, higher education, human-computer interaction (HCI), hybrid learning, ideas, innovation, internet, IT in HE, law schools, learning, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, machine-to-machine communications, Microsoft, mobile technologies, multimedia, Natural Language Processing (NLP), Near Field Communication (NFC), personalized/customized learning, platforms, productivity / tips and tricks, second screen apps, smart classrooms, smart/connected TV, social learning / networks, student teaching/teacher education, student-related, tablets, teachers, teaching & learning, technology (general), tools, trends, United States, usability, user experience (UX), using teams, vendors, videoconferencing, Virtual Reality (VR) / worlds / learning, voice recognition / voice enabled interfaces, wearables, web-based collaboration, XR - extended reality,
by Daniel Christian
Are ‘smart’ classrooms the future? — from campustechnology.com by Julie Johnston
Indiana University explores that question by bringing together tech partners and university leaders to share ideas on how to design classrooms that make better use of faculty and student time.
Excerpt:
To achieve these goals, we are investigating smart solutions that will:
- Untether instructors from the room’s podium, allowing them control from anywhere in the room;
- Streamline the start of class, including biometric login to the room’s technology, behind-the-scenes routing of course content to room displays, control of lights and automatic attendance taking;
- Offer whiteboards that can be captured, routed to different displays in the room and saved for future viewing and editing;
- Provide small-group collaboration displays and the ability to easily route content to and from these displays; and
- Deliver these features through a simple, user-friendly and reliable room/technology interface.
…
Activities included collaborative brainstorming focusing on these questions:
- What else can we do to create the classroom of the future?
- What current technology exists to solve these problems?
- What could be developed that doesn’t yet exist?
- What’s next?
From DSC:
Though many peoples’ — including faculty members’ — eyes gloss over when we start talking about learning spaces and smart classrooms, it’s still an important topic. Personally, I’d rather be learning in an engaging, exciting learning environment that’s outfitted with a variety of tools (physically as well as digitally and virtually-based) that make sense for that community of learners. Also, faculty members have very limited time to get across campus and into the classroom and get things setup…the more things that can be automated in those setup situations the better!
I’ve long posted items re: machine-to-machine communications, voice recognition/voice-enabled interfaces, artificial intelligence, bots, algorithms, a variety of vendors and their products including Amazon’s Alexa / Apple’s Siri / Microsoft’s Cortana / and Google’s Home or Google Assistant, learning spaces, and smart classrooms, as I do think those things are components of our future learning ecosystems.
On 10/27/2018,
in colleges, community colleges, digital audio, digital learning, digital video, education technology, engagement / engaging students, higher education, human-computer interaction (HCI), research, society, student-related, teaching & learning, technologies for your home, tools, universities,
by Daniel Christian
2018 Students and Technology Research Study — from library.educause.edu
Topics Covered
- Device access, use, and importance to academic success
- Campus Wi-Fi experiences
- Learning management system use and satisfaction
- Student learning environment preferences
- Experiences with instructors and technology
- Commuter students and internet access
- Student online activities
- Institutional awareness of student disability and accessibility
- Student use and assessment of success tools
On 10/24/2018,
in adjunct faculty, assessment, attention, blended learning, colleges, communities of practice, community colleges, Daniel S. Christian, digital learning, digital storytelling, education, education technology, elearning, engagement / engaging students, face-to-face, faculty, hybrid learning, ideas, instructional design, interactivity, K-12 related, law schools, learning, learning theories, memory, motivation, multimedia, online learning, pedagogy, presentations, psychology, story, storytelling, student-related, teachers, teaching & learning, teaching online, tools, universities, user experience (UX),
by Daniel Christian
From DSC:
Ever notice how effective Ted Talks begin? They seek to instantly grab your attention with a zinger question, a somewhat shocking statement, an interesting story, a joke, an important problem or an issue, a personal anecdote or experience, a powerful image/photo/graphic, a brief demonstration, and the like.
Grabbing someone’s attention is a key first step in getting a piece of information into someone’s short-term memory — what I call getting through “the gate.” If we can’t get through the gate into someone’s short-term memory, we have zero (0) chance of having them actually process that information and to think about and engage with that piece of content. If we can’t make it into someone’s short-term memory, we can’t get that piece of information into their long-term memory for later retrieval/recall. There won’t be any return on investment (ROI) in that case.
So why not try starting up one of your classes this week with a zinger question, a powerful image/photo/video, or a story from your own work experience? I’ll bet you’ll grab your students’ attentions instantly! Then you can move on into the material for a greater ROI. From there, offering frequent, low-stakes quizzes will hopefully help your students slow down their forgetting curves and help them practice recalling/retrieving that information. By the way, that’s why stories are quite powerful. We often remember them better. So if you can weave an illustrative story into your next class, your students might really benefit from it come final test time!
Also relevant/see:
Ready, set, speak: 5 strong ways to start your next presentation — from abovethelaw.com by Olga Mack, with thanks to Mr. Otto Stockmeyer for this resource
No matter which of these five ways you decide to launch your presentation, ensure that you make it count, and make it memorable.
Excerpts:
- Tell a captivating story
- Ask thought-provoking questions to the audience
- State a shocking headline or statistic
- Use a powerful quote
- Use silence
When delivering a speech, a pause of about three or even as many as 10 seconds will allow your audience to sit and quiet down. Because most people always expect the speaker to start immediately, this silence will thus catch the attention of the audience. They will be instinctively more interested in what you had to say, and why you took your time to say it. This time will also help you gather your nerves and prepare to speak.
On 10/19/2018,
in 21st century, 24x7x365 access, A/V -- audio/visual, Amazon, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, colleges, communities of practice, community colleges, competency-based learning/education, computer science, content development, aggregation, repositories, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, data related items, digital learning, disruption, distance education, e-books, e-publishing related items (EPUB and more), e-readers, education, education reform, education technology, educational games / serious games, elearning, emerging technologies, engagement / engaging students, entrepreneurship, experimentation, future, future of higher education, game-changing environment, generational differences, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interactivity, internet, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, library / librarians, lifelong learning, microlearning, mobile learning, MOOCs -- Massive Open Online Courses, more voice more choice more control, multimedia, Natural Language Processing (NLP), New "Amazon.com" of Higher Education, new business models, online learning, online media, online tutoring, personalized/customized learning, platforms, reinvent, second screen apps, social learning / networks, society, staying relevant, streams of content, student-related, surviving, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vision/possibilities, voice recognition / voice enabled interfaces, workplace,
by Daniel Christian
Inside Amazon’s artificial intelligence flywheel — from wired.com by Steven Levy
How deep learning came to power Alexa, Amazon Web Services, and nearly every other division of the company.
Excerpt (emphasis DSC):
Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.
It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in a recommendations system that now runs on a totally new machine-learning infrastructure. Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.
“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”
Maybe the force.
From DSC:
When will we begin to see more mainstream recommendation engines for learning-based materials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!
- Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.
- AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.
- Voice-driven interfaces.
- Matching employees to employers.
- Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.
- From cradle to grave. Lifelong learning.
- Multimedia-based, interactive content.
- Asynchronously and synchronously connecting with others learning about the same content.
- Online-based tutoring/assistance; remote assistance.
- Reinvent. Staying relevant. Surviving.
- Competency-based learning.
![The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV](http://danielschristian.com/learning-ecosystems/wp-content/uploads/2012/07/The-Living-Class-Room-Daniel-S-Christian-July-2012.jpg)
We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”
Also relevant/see:
Online education’s expansion continues in higher ed with a focus on tech skills — from educationdive.com by James Paterson
Dive Brief:
- Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.
- Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.
- Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.
On 10/18/2018,
in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, change, changing business models, colleges, community colleges, competency-based learning/education, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, future, future of higher education, game-changing environment, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, K-12 related, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, New "Amazon.com" of Higher Education, personalized/customized learning, platforms, programming, society, staying relevant, student-related, technologies for your home, technology (general), tools, training / L&D, trends, United States, universities, vendors, vision/possibilities,
by Daniel Christian
In the 2030 and beyond world, employers will no longer be a separate entity from the education establishment. Pressures from both the supply and demand side are so large that employers and learners will end up, by default, co-designing new learning experiences, where all learning counts.
OBJECTIVES FOR CONVENINGS
- Identify the skills everyone will need to navigate the changing relationship between machine intelligence and people over the next 10-12 years.
- Develop implications for work, workers, students, working learners, employers, and policymakers.
- Identify a preliminary set of actions that need to be taken now to best prepare for the changing work + learn ecosystem.
Three key questions guided the discussions:
- What are the LEAST and MOST essential skills needed for the future?
- Where and how will tomorrow’s workers and learners acquire the skills they really need?
- Who is accountable for making sure individuals can thrive in this new economy?
This report summarizes the experts’ views on what skills will likely be needed to navigate the work + learn ecosystem over the next 10–15 years—and their suggested steps for better serving the nation’s future needs.
In a new world of work, driven especially by AI, institutionally-sanctioned curricula could give way to AI-personalized learning. This would drastically change the nature of existing social contracts between employers and employees, teachers and students, and governments and citizens. Traditional social contracts would need to be renegotiated or revamped entirely. In the process, institutional assessment and evaluation could well shift from top-down to new bottom-up tools and processes for developing capacities, valuing skills, and managing performance through new kinds of reputation or accomplishment scores.
…
In October 2017, Chris Wanstrath, CEO of Github, the foremost code-sharing and social networking resource for programmers today, made a bold statement: “The future of coding is no coding at all.” He believes that the writing of code will be automated in the near future, leaving humans to focus on “higher-level strategy and design of software.” Many of the experts at the convenings agreed. Even creating the AI systems of tomorrow, they asserted, will likely require less human coding than is needed today, with graphic interfaces turning AI programming into a drag-and-drop operation.
Digital fluency does not mean knowing coding languages. Experts at both convenings contended that effectively “befriending the machine” will be less about teaching people to code and more about being able to empathize with AIs and machines, understanding how they “see the world” and “think” and “make decisions.” Machines will create languages to talk to one another.
…
Here’s a list of many skills the experts do not expect to see much of—if at all—in the future:
- Coding. Systems will be self-programming.
- Building AI systems. Graphic interfaces will turn AI programming into drag-and-drop operations.
- Calendaring, scheduling, and organizing. There won’t be need for email triage.
- Planning and even decision-making. AI assistants will pick this up.
- Creating more personalized curricula. Learners may design more of their own personalized learning adventure.
- Writing and reviewing resumes. Digital portfolios, personal branding, and performance reputation will replace resumes.
- Language translation and localization. This will happen in real time using translator apps.
- Legal research and writing. Many of our legal systems will be automated.
- Validation skills. Machines will check people’s work to validate their skills.
- Driving. Driverless vehicles will replace the need to learn how to drive.
Here’s a list of the most essential skills needed for the future:
- Quantitative and algorithmic thinking.
- Managing reputation.
- Storytelling and interpretive skills.
- First principles thinking.
- Communicating with machines as machines.
- Augmenting high-skilled physical tasks with AI.
- Optimization and debugging frame of mind.
- Creativity and growth mindset.
- Adaptability.
- Emotional intelligence.
- Truth seeking.
- Cybersecurity.
The rise of machine intelligence is just one of the many powerful social, technological, economic, environmental, and political forces that are rapidly and disruptively changing the way everyone will work and learn in the future. Because this largely tech-driven force is so interconnected with other drivers of change, it is nearly impossible to understand the impact of intelligent agents on how we will work and learn without also imagining the ways in which these new tools will reshape how we live.
On 10/17/2018,
in 21st century, A/V -- audio/visual, active learning, career development, colleges, community colleges, digital learning, education, education technology, higher education, teaching & learning, tools, trends, United States, universities,
by Daniel Christian
Benchmarking Higher Ed AV Staffing Levels — Revisited — from campustechnology.com by Mike Tomei
As AV-equipped classrooms on campus increase in both numbers and complexity, have AV departments staffed up accordingly? A recent survey sheds some light on how AV is managed in higher education.
Excerpt:
I think we can all agree that new AV system installs have a much higher degree of complexity compared to AV systems five or 10 years ago. The obvious culprits are active learning classrooms that employ multiple displays and matrix switching backends, and conferencing systems of varying complexity being installed in big and small rooms all over campus. But even if today’s standard basic classrooms are offering the same presentation functionality as they were five years ago, the backend AV technology running those systems has still increased in complexity. We’re trying to push very high resolution video signals around the room; copyright-protected digital content is coming into play; there are myriad BYOD devices and connectors that need to be supported; and we’re making a strong push to connect our AV devices to the enterprise network for monitoring and troubleshooting. This increase in AV system complexity just adds to the system design, installation and support burdens placed upon an AV department. Without an increase in FTE staff beyond what we’re seeing, there’s just no way that AV support can truly flourish on campuses.
Today we’re reopening the survey to continue to gather data about AV staffing levels, and we’ll periodically tabulate and publish the results for those that participate. Visit www.AV-Survey.com to take the survey. If you would like to request the full 2018 AV staffing survey results, including average AV department budgets, staffing levels by position, breakouts by public/private/community colleges and small/medium/large schools, please send an e-mail to me (mike@tomeiav.com) and to Craig Park from The Sextant Group (cpark@thesextantgroup.com).