Webinar: tools for collaborative research and early discovery
Librarians have been at the forefront in promoting open access publishing options and informing their researchers about the open access landscape. Open access is increasingly recognized as embedded within the larger framework of open science. Consequently, library and librarian roles are expanding into new areas such as open data, open educational resources and open infrastructure.
In this webinar, Elsevier product managers will present tools that enable more inclusive, collaborative and transparent research.
TOPICS:
•The library as publisher of OERs and OA journals with Digital Commons
•Open access content discovery in ScienceDirect and Scopus
•Open journal metrics: CiteScore, SNIP and SJR
•Publishing research outputs openly in Mendeley Data and SSRN
https://www.newyorker.com/magazine/2014/06/23/the-disruption-machine
Michael Porter, a professor at the Harvard Business School. The scholar who in some respects became his successor, Clayton M. Christensen, entered a doctoral program at the Harvard Business School in 1989 and joined the faculty in 1992. Christensen was interested in why companies fail. In his 1997 book, “The Innovator’s Dilemma,” he argued that, very often, it isn’t because their executives made bad decisions but because they made good good decisions, the same kind of good decisions that had made those companies successful for decades. (The “innovator’s dilemma” is that “doing the right thing is the wrong thing.”)
Christensen called “disruptive innovation”: the selling of a cheaper, poorer-quality product that initially reaches less profitable customers but eventually takes over and devours an entire industry.
Christensen has co-written books urging disruptive innovation in higher education (“The Innovative University”), public schools (“Disrupting Class”), and health care (“The Innovator’s Prescription”).
Startups are ruthless and leaderless and unrestrained, and they seem so tiny and powerless, until you realize, but only after it’s too late, that they’re devastatingly dangerous: Bang! Ka-boom! Think of it this way: the Times is a nation-state; BuzzFeed is stateless. Disruptive innovation is competitive strategy for an age seized by terror.
Replacing “progress” with “innovation” skirts the question of whether a novelty is an improvement: the world may not be getting better and better but our devices are getting newer and newer.
The word “innovate”—to make new—used to have chiefly negative connotations: it signified excessive novelty, without purpose or end.
Joseph Schumpeter, in his landmark study of business cycles, used the word to mean bringing new products to market, a usage that spread slowly, and only in the specialized literatures of economics and business.
Disruptive innovation can reliably be seen only after the fact.
Christensen has compared the theory of disruptive innovation to a theory of nature: the theory of evolution. But among the many differences between disruption and evolution is that the advocates of disruption have an affinity for circular arguments.
Like the bursting of the dot-com bubble, the meltdown didn’t dim the fervor for disruption; instead, it fuelled it, because these products of disruption contributed to the panic on which the theory of disruption thrives.
People aren’t disk drives. Public schools, colleges and universities, churches, museums, and many hospitals, all of which have been subjected to disruptive innovation, have revenues and expenses and infrastructures, but they aren’t industries in the same way that manufacturers of hard-disk drives or truck engines or drygoods are industries. Journalism isn’t an industry in that sense, either.
Historically, institutions like museums, hospitals, schools, and universities have been supported by patronage, donations made by individuals or funding from church or state. The press has generally supported itself by charging subscribers and selling advertising. (Underwriting by corporations and foundations is a funding source of more recent vintage.) Charging for admission, membership, subscriptions and, for some, earning profits are similarities these institutions have with businesses. Still, that doesn’t make them industries, which turn things into commodities and sell them for gain.
Christensen and Eyring’s recommendations for the disruption of the modern university include a “mix of face-to-face and online learning.” The publication of “The Innovative University,” in 2011, contributed to a frenzy for Massive Open Online Courses, or moocs, at colleges and universities across the country, including a collaboration between Harvard and M.I.T., which was announced in May of 2012. Shortly afterward, the University of Virginia’s panicked board of trustees attempted to fire the president, charging her with jeopardizing the institution’s future by failing to disruptively innovate with sufficient speed;
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more on Clayton Christensen in this IMS blog
https://blog.stcloudstate.edu/ims?s=clayton
Digital Media Has a Misinformation Problem—but It’s an Opportunity for Teaching.
Jennifer Sparrow Dec 13, 2018
https://www.edsurge.com/news/2018-12-13-digital-media-has-a-misinformation-problem-but-it-s-an-opportunity-for-teaching
https://www.edsurge.com/news/2018-12-13-digital-media-has-a-misinformation-problem-but-it-s-an-opportunity-for-teaching
Research has shown that 50 percent of college students spend a minimum of five hours each week on social media. These social channels feed information from news outlets, private bloggers, friends and family, and myriad other sources that are often curated based on the user’s interests. But what really makes social media a tricky resource for students and educators alike is that most companies don’t view themselves as content publishers. This position essentially absolves social media platforms of the responsibility to monitor what their users share, and that can allow false even harmful information to circulate.
“How do we help students become better consumers of information, data, and communication?” Fluency in each of these areas is integral to 21st century-citizenry, for which we must prepare students.
In English 202C, a technical writing course, students use our Invention Studio and littleBits to practice inventing their own electronic devices, write instructions for how to construct the device, and have classmates reproduce the invention.
The proliferation of mobile devices and high-speed Wi-Fi have made videos a common outlet for information-sharing. To keep up with the changing means of communication, Penn State campuses are equipped with One Button Studio, where students can learn to produce professional-quality video. With this, students must learn how to take information and translate it into a visual medium in a way that will best benefit the intended audience. They can also use the studios to hone their presentation or interview skills by recording practice sessions and then reviewing the footage.
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more on digital media in this IMS blog
https://blog.stcloudstate.edu/ims?s=digital+media
Data-Driven Design Is Killing Our Instincts
Valuing data over design instinct puts metrics over users
Benek Lisefski August 13, 2019
https://modus.medium.com/data-driven-design-is-killing-our-instincts-d448d141653d
Overreliance on data to drive design decisions can be just as harmful as ignoring it. Data only tells one kind of story. But your project goals are often more complex than that. Goals can’t always be objectively measured.
Data-driven design is about using information gleaned from both quantitative and qualitative sources to inform how you make decisions for a set of users. Some common tools used to collect data include user surveys, A/B testing, site usage and analytics, consumer research, support logs, and discovery calls.
Designers justified their value through their innate talent for creative ideas and artistic execution. Those whose instincts reliably produced success became rock stars.
In today’s data-driven world, that instinct is less necessary and holds less power. But make no mistake, there’s still a place for it.
Data is good at measuring things that are easy to measure. Some goals are less tangible, but that doesn’t make them less important.
Data has become an authoritarian who has fired the other advisors who may have tempered his ill will. A designer’s instinct would ask, “Do people actually enjoy using this?” or “How do these tactics reflect on our reputation and brand?”
Digital interface design is going through a bland period of sameness.
Data is only as good as the questions you ask
When to use data vs. when to use instinct
Deciding between two or three options? This is where data shines. Nothing is more decisive than an A/B test to compare potential solutions and see which one actually performs better. Make sure you’re measuring long-term value metrics and not just views and clicks.
Sweating product quality and aesthetics? Turn to your instinct. The overall feeling of quality is a collection of hundreds of micro-decisions, maintained consistency, and execution with accuracy. Each one of those decisions isn’t worth validating on its own. Your users aren’t design experts, so their feedback will be too subjective and variable. Trust your design senses when finessing the details.
Unsure about user behavior? Use data rather than asking for opinions. When asked what they’ll do, customers will do what they think you want them to. Instead, trust what they actually do when they think nobody’s looking.
Building brand and reputation? Data can’t easily measure this. But we all know trustworthiness is as important as clicks (and sometimes they’re opposing goals). When building long-term reputation, trust your instinct to guide you to what’s appealing, even if it sometimes contradicts short-term data trends. You have to play the long game here.
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more on big data in this IMS blog
https://blog.stcloudstate.edu/ims?s=big+data