When Content is Global : Digital Interpretation

At the core, museums offer the interpretation to offer people connections to collections. Lonnie Bunch, the museum’s director, says, “What we really want to do is humanize history.” The delivery method matters on one key level. Technology allows for vast off-site interpretation. But, even when visitors are not in the museum,  as Karen Franscona, Boston Museum of Fine Arts Director of Public Relations,  suggests interpretation still seeks “to explain things and expose our works of art to people who may have never come to our museum.”

Why use Technology-delivered Interpretation? 

People use technology. 88 percent of Americans used the Internet, and therefore a form of technology, in 2016.  Technology has allowed museums to become global as never before. Now your audience has grown from those who came onsite to those your find your presence (by choice or by surprise). Half of the visitors to the website are not planning a visit, for example. The museum’s largest audience sector might be those who don’t ever visit onsite.

Technology is a utility, not unlike electricity. Just as you use electricity to turn on the light in a classroom or to power your ticketing computers, technology fuels multiple functions of the museum–and multiple parts of our visitors’ lives.  They use it to buy plane tickets, read the news, and talk to friends. Technology is not for X, it’s for X,Y,Z.   Museums need to meet various needs equally well.

The content on technology has to be as good as anywhere else in the organization if not better. Your audience is particularly knowledgeable about bad content on technology. They use it all the time. Social media can’t be solely a sales channel. That would be the equivalent of a newspaper only being coupon circulars.  Interactives can’t just be bells and whistles.

So, start with the idea and the audience.Before we think a little about interpretation for technology, we might go back to the issues of writing labels. Museums create content for multiple audiences.  These audiences often have disparate needs.

 

Technology allows you to meet the differentiated needs of visitors better than ever.  You can produce content that combines visuals and text in a sophisticated manner.  Technology can be updated and more quickly relevant. You can meet respond to current events with incredible speed and specificity.

Each of these users can tap into multiple and differentiated engagements with your collection. Digital allows for better differentiation by format for the audience. Personalization is what people want. The visit to the site may be the reason that they are accessing technology-delivered interpretation or the impetus for using your off-site technology resources. They may never visit. Your technology, particularly social media, might reach those who otherwise would never even thinking about your museum.

In other words, technology interpretation can serve your existing audience better or draw new audiences. The numbers can be astonishing.  Art Institute of Chicago has about 1.5 million onsite visitors and 706000 on social media. LACMA 1.2 Million onsite and 2 million on social media platforms.

Technology-based interpretation writers, therefore, might have scores more consumers of their ideas than label writers. (Usually, these aren’t the same person). They are all likely using the same source information derived from the curator, say a catalog or curatorial write-up.

How should you use technology-delivered interpretation? 

  • Create purpose-built content for deployment. Just as you wouldn’t cut the catalog entry from the book to use as a label, don’t use the same text on the web as in social.  Remember people consume ideas differently when reading technology. Understand that people’s needs can be different even for the same technology tool. For example,  visitors to the website have many needs, so that are different than onsite visitors (such as planning your visit.)
  • Create connect that extends relationships.  Find ways that encourage people to check back. Show the installation process in phases. Be transparent about testing technology. Make the premature birth of an animal a national obsession. Let technology help your organization be honest with visitors.
  • Use each technology tool to its best ability. For example, social media is an engagement tool. Jonas Heide Smith shares in his Museums and the Web paper that social media can maximize reach but also add new levels of engagement within the institution and with new audiences. Think of your own experiences. Do you use your public Instagram to ask your mom to bring you dinner? (Also, don’t ask your mom to bring you dinner.)  And, then research numbers on what the general population is doing on different platforms.
  • Embrace content co-creation. People are already using technology to make and share content, mostly pictures. Allow them to do so, and then applaud them for it by amplifying their reach through shares on your channels. For example, social media, with “Take-overs” events allow museums to change the balance of power in content creation.
  • Don’t assume. Test! Much has been made about the youthful demographics on technology. But, don’t be the museum that assumes that ‘all the kids want X.’ Social media particularly allows you to try many different approaches fairly affordably. You might find that your funny meme is particularly popular with the older folks–they have smartphones too.
  • Be Game but Don’t Play Games:  Humor is incredibly challenging in print. Think of all those lame jokes that don’t come off in texts from your dad. Museums can certainly speak in the vernacular of the media but do it thoughtfully. Everyone knows when you are pandering. There are scores of examples of brands doing so, so wrong on social. Don’t be those brands.
  • Invest.  Right now, there are inherent time and money disparities in the field in general, but definitely in content creation. Curators spend years on catalogs and labels and social media needs to turn it around in minutes for pennies on the dollar. Without completely going into the issues with museum hierarchies, let’s focus on digital content. Make a plan that you can afford. Choose the platform that you can staff. And, then do that really well.

Many people have written about this much better than I, so here is also a sampling:

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This is the fifth in a series of posts about considering Interpretation and Content to Meet Today’s Visitor’s Needs.

Previous Posts:

Are Museums Writing for Today’s Audience? Looking at the Changes in Literacy & Knowledge-Creation in Society

Labels in the World of Information Overload

Interpretation, Content, and the Use of Text in Museums

Visual Literacy and Importance of Imagery in Interpretation (Graphics/ Blog)

Engaging Interpretation

 

Are Museums Writing for Today’s Audience? Looking at the Changes in Literacy & Knowledge-Creation in Society

Evolution of Knowledge Acquisition

When our visitors walk into their museums, they will have already consumed a great deal of information and fast at a rate of, on average, 23 words per second.  Over the course of a day, people read an average 105,000 words.  They walk into your museum, only to use text to find the bathroom, learn about your collection, and find their way to the exit.  But, are museums textual practices keeping up with the literacy changes of our visitors?

Quick History of Knowledge Acquisition

  • Move from oral to print increases sphere of influence
  • Mass production is partnered with mass consumption of text
  • Technology exponentially increases not only production of but also access to text

When it comes to social change, there are usually two camps: it was better before and it is now wondrous. In terms of knowledge sharing, you might think that we are living in the moment before the mass extinction of books, just waiting for one more meteor from the tech sphere. You might instead think that we are finally in the great democratic (small d) age of knowledge. Either way, it might be useful to step down the historical path of literacy and knowledge sharing.

Knowledge in the early days was transmitted orally. Writing systems were implemented,  effectively separating the words from the speaker/ writing and thereby making ideas highly mobile. Early writing survives on pots and tablets.  And, while mobile, these writing documents were handmade and heavy. Pity the horse asked to transport a set of texts over a hill.

Scrolls helped with the weight of things. Even the most ornery, old mule could take one scroll to the next city-state. But, the codex, or spined-book, changed things. These stackable communication tools could be filled with dissertations and novelizations.  Books were then further improved in as mass media tools with the onset of printing.

Printing changed knowledge forever. Ideas whizzed out of machines in broadsheets, newspapers, pamphlets, posters, and books. Knowledge was now mass media, multi-format, and myriad. Finally, technology took up the charge from printing. Early website information was present in certain situations, like from desktop computers in homes, (remember that iconic buzz of the landline connection?) Smartphones, like the iPhone launched in 2007, meant that knowledge was in your pocket or hand all the time. The smartphone allowed you to get blogs, tweets, feeds, and all the other Web 2.0 tools continuously and continually.

Web 2.0 & Social Media: Faster, Shorter, and MORE

  • User-generated/ change in authority structure
  • High-volume text consumption
  • Writing and reading styles have changed

Web 2.0 with its social media tools made knowledge-work a global activity, hobby, or obsession, depending on where you stand. Everyone is writing all the time. This user-generated content has changed the power structures of knowledge. Users (i.e. readers) are making text to disseminate their ideas. Authority became dispersed being partially displaced from institutions to individuals. This dissemination of authority can be seen as a flowering of democratic knowledge-work or, alternately, an erosion of quality in knowledge-work. While this debate is beyond the topic at hand, those acquiring knowledge are basically reading on the front-line of this authority debate. Readers confront this question with every text that they read. For every like or retweet, they are endorsing the authority of the writer.

And, they are making these assessments in record time. Knowledge is being made faster than ever. An average 1.2 million words are added to Twitter every minute. This is 18 Billion words every day. Almost four TRILLION words every month. And, that is on a single platform. Add all the text your mom is writing about you on Facebook, the captions on Instagram, the food blogs, the comments on those food blogs about the problems with the recipes, the comments on FB posts… You get the point. You live the point. Text inundates readers daily. Rather than being overwhelmed, many are willingly accessing and responding to this text. People are reading more, even as they are reading fewer books. Longform literary texts, with 1000 pages to get to the denouement, has a smaller audience, but short bites are on the rise. In other words, rather than being on the decline, literacy is shifting.

Social media and Web 2.0 texts have changed readers. They expect short and sweet. That said, the long text doesn’t immediately turn them off. They are skimmers. You don’t think so? With the changes in readers, texts and writing are changing.  Look at this text. Its constructed for the skimmers amongst us. There are bold headings, like road signs, for the speeding readers. For the super-fast reader, there will be some quick bullets at the end.  So, why am I putting in all this text, then? b/c you are all looking for something different. In order word, long-form texts are being created to support the diversity of audiences and their differential interests. (Also, age-old norms are changing. Abbreviations are being the norm.)

Transformations in Knowledge-seeking

  • Knowledge seeking is easier than ever
  • Knowledge resources are wide, deep, diverse, broad, and ever-present
  • Knowledge seeking is often broad rather than deep

Along with literacy shifts, Web 2.0 tools have transformed knowledge-seeking. When was the last time you flipped through an encyclopedia to figure out the name for that line that separates two dates in a range? (En-dash, by the way). Now, as a museum/ knowledge worker, you are probably more predisposed to use physical/ analog texts to find answers, but even knowledge-workers Google things. This shift is important in the museum setting. Your viewers know how to look up textual facts. They can find out where Rembrandt was from if they care. They know how to figure out the definition of tempera, and where to watch a video of egg tempera being made. Facts are available to everyone. And, while you might see yourself as the purveyor of the real, verifiable facts, your visitors are also very good at finding answers (and they might have a different idea about what a verifiable fact is).  Your visitors, if motivated, can find any fact they need, but this increased ability to fact-find is not necessarily matched with a concomitant growth in critical reasoning.

The flip-side of this phenomena is that for every museum collection there is a web niche. So, there are knowledge-makers online creating the counterpart to everything. You have a collection of decorative objects, including Wedgewood salt shakers. Look up salt and pepper shakers. You will see an amazing world of savory dec arts. You are a natural history museum with skulls and bugs. Well, I assure you that you have scores of Instagram accounts that would pair nicely with your collection. In other words, you aren’t the only one out there. This phenomenon can be taken in two ways by museums, as an erosion of uniqueness or alternately, and more positively, as an expansion of their community.

What are the implications for Museums?

  • The short version: People are reading more, finding facts all the time, and being inundated with text. Museums need to understand these changes to make better text.

As a society, we are not the readers we were in 2007. This is not a value judgment. This is not about caring less about collection objects. This is about idea dissemination. People are getting info in a different way.

Before you attempt to bemoan the diminished state of knowledge today. Every generation has had some type of knowledge acquisition transition. And, those who are living through these changes are often completely unaware when cognition slowly changes accordingly.

You really only notice the giant jumps, like going back to a long-ago time period. Even the most scholarly of us might find listening to an oration of the Mahabharata for 12 hours or so a little overwhelming. You are not inherently dumber or smarter than the original audience that could sit through that Indian tale of duty. We are trained by society to acquire information. Information that is transmitted in the social vernacular will be more easily acquired. Said differently, people learn as society has trained them to; teach differently or they might not learn.

 

How do we give museum visitors what they want and need in terms of text? 

Begin by ensuring that the text is suitable for the delivery method. Social media often is entertaining, short, and timely whereas labels are site-specific, informative, and evergreen.

With our visitors becoming savvy information consumers, we need to spend more time and research money on evolving the all our textual information so that our knowledge-ecosystem works for our visitors. We need to be strategic about ideas and knowledge-dissemination. We need to work holistically on the text as a form of access and inclusion. It is imperative, as a field, that we spend time researching labels and think about innovating at that most basic element of our knowledge-ecosystem. If we don’t, our visitors, best case, will just Google it, or worse, stop coming.

Keep Clean Data

Data seems pretty cut and dried, but don’t be fooled. There are plenty of ways to fold in bias.  Here are some concrete steps to help you do your best to counteract the most common pitfalls.

Start with a clean tool/ protocol to collect data.

1. Keep data clean

There are plenty of ways to keep you tidy. First, have everyone use the same protocol. Ideally, keep your data collector pool down to a minimum. More people means potentially multiple interpretations. Train everyone the same. Take out the protocol and make sure everyone understands it. And, make sure everyone uses the same data collection tool. I used to work in a team of three data collectors. We had to agree to everything, and often huddled up to make sure we were on the same page. Be vigilant

2. Observe First, Interpret Later

Years ago, when I worked on hiring teachers for the public schools, I had to take a course on legal job interviews. The fear that the trainer burned into my soul always returns to me when I do interviews. Only write what people say–word for word. Do not interpret. This goes against your human nature. And, if you have a hard time writing, ask respondents if you can record them. Also, feel free to ask the people who provided the data whether your interpretations seem to be representative of their beliefs. Once all the data comes in, then you have the joy of interpretation. That said, once you get familiar with interpretation-free listening, you will also find joy in data collection.

3. Check out the competition.

After your initial interpretations, look to others to see how they are tackling this issue. What are their findings? What other issues might be occurring in the literature. This is sometimes called triangulation. If you can find other sources of data that support your interpretations, then you can have more confidence that what you’ve found is legitimate.

4. Check for alternative explanations.

False conclusions are absolutely the most likely place that bias comes into understanding data.  Jumping to conclusions can feel normal, like finishing someone’s sentence.  But, just was you can’t fill in the blanks for your respondents, don’t fill in the blanks for yourself too quickly.  Consider whether there are other reasons why you obtained your data. If you can rule out or account for alternative explanations, your interpretations will be stronger

5. Review findings with peers

Don’t be an island. Unless confidentiality prevents you, let others look at your data. You will only become better at your work with critical assessments. Additionally, when you allow peers to review your work, you might find commonalities. You might even be able to augment your argument.

For more about data bias, here is a long read sharing more issues like confirmation bias, ingroup bias, and knowledge bias. 

Bias in Data Analysis #musedata #musetech #data #bias

This is the second in a series of posts about confronting bias. These #longreads use narrative to help bring up bias in an accessible manner.

As Director of the Art Museum of New South Overthere, you are constantly being asked to make decisions based on data. Sure, you had your last math class in 10th grade, and then avoided math through your PhD. But, you are a specialist, I mean in lantern slides, but still, you got this, right?

Read these short scenarios and suss out where bias might come in.

Scenario 1

You are dying to know how much people like lantern slides. You write out a survey for your staff to deploy. You want to be direct with your visitors so that you don’t waste their time. So, you asked the people in the Joe Bright Memorial Lantern Slide Gallery (and broom closet).

  • “What do you like about lantern slides?”
  • “Is there anything that you don’t like about lantern slides?”
  • “What would you like to see with the lantern slide display?”

You were happy to find out that there is nothing that they don’t like about lantern slides. They also love your lantern display as it is. The only thing they want is more information, which is what you thought. They just wished they could know more about the slides! How wonderful to know what you do for a living is so relevant for people.

Explanation

In this case, you have several problems.  First, your survey questions are constructed with a particular slant towards lantern slides. This a situation of interview bias. It’s as they say in legal shows; you are leading the witness. When you construct survey questions you don’t want to tip the participants off to the “right” answer. People have an inherent need to please, and so they will answer in a way that seems correct.

Additionally, there is a selection bias at work here. You went to the gallery where you hope to make changes. On one hand, you are being proactive. However, you are skewing your data. You have a sampling error at play. A better study would interview not just current visitors to the lantern slide gallery but also those in the museum who are not currently going to the lantern slide gallery.  In other words, you want visitors and potential visitors to draw a complete picture of the situation.

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Scenario 2

Your first meeting this morning was with the board. This nice old lady, Sweetie Monroe, heiress to the great Marshmallow Mills fortune, was hoping you could explain why you don’t have any students in the galleries.  Now, you have never seen Sweetie upright before 1:00 pm in the morning. But, you also know that the school scheduling staff member, Peaches LaPew, is busy every morning. Last week, she tried to get you to do a Kindergarten tour, because you had more students than staff.

You’re not going to be able to show Ms. Monroe children in the flesh (you aren’t a miracle worker), so you ask your staff to do a little comparative analysis. Your head of Marketing/ Audience Research/ Programming & Security, Joe Exhaustino, has emailed you a super long report. Does he understand how busy you are? You don’t have time to go through this like you were in school. Luckily, it has a clear summary.  You have plenty of kids coming. Fabulous.

Explanation

In this case, I have bad news for me. You didn’t look too closely at your data. You used the data like a yes-man. This is an example of choice-supportive data. If you looked more closely at the data, you would notice that only 4 percent of visitors are 18 and under. Most of those are school groups. Now, I don’t know what your measure of success is, but 4 percent of total visitors seems extremely low.

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Scenario 3

Before you can get to your chance at regaling Ms. Monroe about your fabulous student tours, you find yourself stunned by numbers. You are sitting at a breakfast meeting with the directors of all the local organizations. The head of the Community Development Corporation is sharing a graphic. Apparently, the average percentage of family visitors at museums is 10 percentage. Eek. You get nervous. So, you turn to the guy next to you, the Director of Coffee Cups & Porcupine baskets. He smiles and then says, “Oh, yes, that’s just average. We are at 18%.” You leave the meeting despondent, and shoot off a quick email to your grant office/ gardener to get money right now for school tours.

Explanation

In this case, the data was combined inappropriately, though you wouldn’t necessarily know it. You didn’t have all the information when you sat in that meeting and looked the graph.  The number crunches decided more numbers were better. But, in doing so, they didn’t use like categories. In this case, the number cruncher didn’t separate out school groups. Only two of the four museums do school tour. This means that in those museums children are coming in though out the week without adults. They will have higher numbers of children than those who don’t do school tours. The lesson is that you need to thoughtful in combining data. There are other challenges with combining data. If you aren’t careful, when you aggregate data, you can accidentally contradict what the original data said. This is called the Simpson Paradox.

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Scenario 4

You are hoping to buy more media adds. You call on Joe Exhaustino again, but this time with your demographic numbers. He gives you the classic bell chart with mostly mid-aged people attending the new exhibition. No surprises. So, you will just use digital adds to get more young people. Finally, an easy decision. After the ads go out, you take a turn in your Lantern Slide gallery. Something odd is up. The gallery is full of really old men. You go back to Joe and ask him if his numbers are right.  He shows you his numbers. He had used a good-sized sample. He crunched the numbers and he ended up with a graph that didn’t look right. So, Joe removed the outliers, the old people.

Explanation

Joe has been doing numbers for years. And, he assumed that the attendance numbers should conform to a bell curve. This is called the Non-Normality bias. But, another bias was in play here.  Instead of investigating the outliers, they disregarded those numbers. Joe did better on his second crack at it. Along with the quantitative data, he looked at surveys. Turns out the lantern slide gallery had become a mecca for the over 95 set. Practically, everyone in the state in that age demographic comes to the museum to check out those sweet slides, particularly on “free coffee Friday”.

The Near-Future of Museum Education for K-12 Audiences

FutureEducationInfographic

 

This afternoon I had the privilege of participating in the North Carolina Museum of Art’s project, #NCMAAsk (search twitter for more), which is focused on museums, technology, and the future.  There were a number of issues that came up, but, many of them centered around hearing, listening, and flexibility.

Museums in their partnership with schools have can serve as advocates for students and teachers, but only if they are creating programming, experiences, resources, and spaces that respond to their needs.  In terms of advocating for teachers, it includes helping them out, it includes offering teachers the language that they can use to communicate the importance of the arts to their higher ups. It terms of advocating for students, it is about creating and implementing curriculum that is student centered.

Museums have the lucky position of being outside of the school’s systems.  They don’t have the same rules and museum experiences don’t end in grades.  We don’t know who is the smart student, the weird kid, or the screw up.  A good museum educator takes all of the kids where they come, and brings them all into the experience.  On an even footing, but in a totally different learning experience, a totally different kid might find themselves as the smart kid.  In museums, K-12 classrooms get the chance to visit an alternate learning universe, if it is even for one hour.

I was asked to me an oracle of the future of education.  I think there are some big issues, such as competency-based education and the complete restructuring of the grade-level system.  I think museums, with their high-quality digital tools, apps, and powerful search engines, will be poised to be right there at the horizon of education.  But, I am more focused on the closer targets.  In the short term, I am focused on how to deepen engagement through multi-visit experiences, as well as the ways that after school education can be impacted by museums. Also, I am interested to think about the ways that museums can use technology to augment K-12, such as through distance learning, online learning, and simulations.

Finally, individualized learning is already happening every where.  Phones are tools for learning and creativity.  Museums can employ them in gallery spaces with students. But, this requires the staff being comfortable with these tools and finding authentic ways to use them.  Taking the students lead, so allowing them to search on their phones when they are researching something in the galleries, is a great way to use mobile as a tool.