Revisiting Plagiarism

In an age when collaboration, teaming and consensus-based decisions become more important and emphasized in the work place, incorporating these practices into meaningful assessment continues to challenge higher education. How do we know that our students know what we need them to know?

Adding to the challenge, thoughtful instructors attempting to foster digital literacy and the use of technology in rich ways in the course experience find that the most effective tools also make it easier for learners to "collaborate" where not intended by the instructor.

One of the most challenging tools for instructors is the use of online testing. The affordances include the ability to offer more small tests with lower stakes because the burden of grading is lightened. But how do we know they're not cheating??

In "traditional", face-to-face courses, online tests also save valuable class time both in delivery and in eliminating paper return. And they include the value to the student of instant feedback on understanding. The consequences of this transfer of exams to the digital space means we hear more stories of extending study groups to the exam taking. Students gather, enter the exam, and compare responses. Many honestly are surprised when "caught" and informed this is not allowed.

Here, the burden has to lie with the instructor who assumes their notion of assessment and ethical behavior is the same for the students. Unless directly stated in the syllabus or in the directions for the test, collaborating on an assessment may not be wrong in the eyes of the students. If the instructor believes it is wrong, they need to state that. And, once stated, if the instructor realizes that their values and ideas on assessment is not the same as that of many students, the instructor has a number of options. Electronic options; not whining like the crazy fellow in Florida because students had access to a large pool of possible questions and studied them all.

Keeping up with practices seen, technology enables an instructor to prevent collaboration as surely as it enables the learners to compare answers. Especially if the LMS is Blackboard with its plethora of unused assessment options. Creating an exam using a) randomized questions, b) randomized answers, c) pools where each student gets a different set of questions, and d) multiple formats for questions makes it very, very hard for students to compare questions during a timed test. Ok, there's a bit of a tech challenge in setting up these options as each is done in a different place when creating the exam, but ASU has some very good documentation and how to do it, and if you run into trouble, "operators are standing by" to help! Here's a start:

• How to set up a pool
• How to display random order of questions in test creation settings
• How to display random order of answers in deployment settings

Digging deeper, Tom Angelo would ask if the assessment is being used to effectively improve student learning and would suggest we do much more with the technology. Used thoughtfully, electronic assessment enables students to learn more, learn deeply and to create a formative, lasting understanding of the course material. Instead of cursing the technology that creates a different kind of assessment, why not leverage online assessment to allow the student to try and try again to improve their understanding (and score) and to be better prepared for the next course, the next level, the next step in life?

Along with the randomized questions and unique question pools, Blackboard allows a) multiple attempts, b) accepting the highest attempt, and c) many, many formats of questions. Designing an assessment that allows students to examine, modify, and demonstrate what they have learned has never been easier. Leveraging technology in building assessments takes a bit of work up front but provides great return on investment. Tom Angelo would be proud.

Hot off the presses: Horizon Report 2011

Eagerly awaited each year, the New Media Consortium's Horizon Report is out! I don't always agree, as I'm more of an affordance and value fanatic than the techie types that work very hard to come to consensus here. Still, each year I eagerly await, digitally rip open, and comb their effort to "identify and describe emerging technologies likely to have considerable impact on teaching, learning, and creative expression within higher education."

Work hard they do, and always come up with some provoking, leading-edge, out-there technologies that will (they claim) influence how we incorporate technology into higher education initiatives. Check it out and see how some of us will be teaching 1, 2-3, 4-5 years up the road.

With eBooks, mobile devices, augmented reality, gaming, gesture-based computing and even incorporating learner analytics into the stew, there's a lot to consider in this release.

Note on the analytics bandwagon that so few understand but lots are tossing about:

We should start a drinking game for each time we see 'analytics' used to mean something else. Like assessment. Or data analysis. Or accountability. But the Horizon Report has good intention and some reason to suggest accountability and results will be demanded of HE up ahead. Kudos to them, even if the mentioned emerging technology is not about learning and/or analytics and/or emerging technology at all. Not at all. For more on my rant on this topic see recent article in EDUCAUSE Quarterly re Nudge Analytics)

So, could all these hot technologies wind up in the HE teaching and learning stew within next few years? It could happen. Will any of them be the disruptive innovation that changes the "industry" for the better? Not likely. I think that's eLearning, or the market-driven/customer culture of the new proprietary schools, but that's another post.

Read the Horizon Report!

Learning and eLearning

My expert opinion: learning is funky. No one seems to understand it. As Sly Stone says, "One child grows up to be somebody that just loves to learn/And another child grows up to be/ Somebody you'd just love to burn. "And when you're all grown up, learning and the willingness to change, grow, be wrong...becomes funkier.

For a very long time, I've made claims that technology and its "just in time" and personalized learning affordance has created a love of learning that we've never seen before, learning we understand even less. eLearning: obsessive, compulsive, all-the-time learning that creates passionate communities and keeps you up half the night clicking and commenting; changing, growing, adapting...learning. I've seen it in the work of my students and in my own life and work.

Elder faculty poo-poo it (technical term) and tell me that "it can't reproduce the magic of the classroom." I quietly mutter that there was seldom magic there for me (but oh you Google!) and attempt to show them the evidence.

I use scholarly evidence that eLearning is "just as good" (see No Significant Difference). It quiets them down, but never made enough sense to me. If researchers are finding no significant difference, they're measuring wrong. There IS a difference, and it's ownership, engagement, collaboration, being heard. I know that. I feel it. I see it in my students. I just don't know how to measure it.

But we see it all the time, and others are beginning to describe it. Chris Anderson of TED describes it in relation to internet-taught shifts and crowd accelerated innovation. New ideas are spreading and changing and transforming in rapidly adapted new memes via the Web. People are spreading ideas by finding like-minded explorers and exchanging links, creating content, inventing on top of what came before. Young people are learning new ways of being in the world by learning from each other via the Web. Young people are changing disciplinary practice by , tossing out what has been and demonstrating what could be.

The world of finance changed thanks to two young women who (separately) believed in microfinance and created Kiva.org (Jessica Jackley) and the Acumen Fund (Jacqueline Novagratz). Their new way of thinking CHANGED the lives of millions and changed my belief that there was little I could do.

The world of dance CHANGED due to young, untrained dancers learning moves from each other via YouTube videos. No one who's ever watched Lil Demon or the YouTube trained and promoted dancers of LXD doubts this regardless of measure. Crowd-accelerated access to evidence, crowd-supported desire to learn, the crowd shining light on your passion. Via the Internet.

Now, the dark and sad secret of my own passion: I am in a field that still rejects the open light that drives crowd accelerated innovation and love of deep learning. Education lags behind open source, open learning, open access. More and more young people love learning, hate school. But eLearning can change that. We can change that.

eLearning peeps: keep fighting that good fight. Let's keep posting the clips, showing the evidence. Let's find better ways to measure besides citing the numbers that are deserting the F2F experience for online programs. Let's continue to create and spread innovative practice. And let's keep posting great evidence like Chris Anderson's TED talk on crowd accelerated innovation.

Still working with scholarly types who like text better? Ask them to subscribe to Wired Magazine and read about these ideas. Or...tell them to read about crowd learning and innovation in Wired's story on the Web!

We're the teacher and the student and the crowd: plug in, teach, learn, transform the world. eLearning rocks!

Wicked Wicked Problem of Learning in the Digital Age

Finals week. Campus is already quieting down as learners and faculty head out for winter break. As we close up, I've decided that the theme of 2011 here at GridKnowledge will be wicked problems (see Rittel and Melvin 1972, and Conkel 2005 or heck, just go to Wikipedia).

Wicked: what we have in higher education as we drag ourselves into the digital age. We're a poster child of a wicked problem regarding our work infusing digital literacy into the HE experience.

Wicked: tough to understand let alone solve, dynamic/ shifting/ elusive, no stopping rules, lots of possible paths to solution. The second wicked of title comes in the resistance to change we're seeing in so many HE stakeholders who just want the world to stay the way it was just moments ago when we were kings of an industrial age and HE was revered through the land.

Maybe I should add a third wicked related to wicked #2: we have a new generation of learners (choose your pocket: X,Y,Z, D+, or iGen) that will NOT have the skills they need to face the next 15-20 jobs/distinct careers ahead of them when they leave the halls of the Academy. We like to pretend that our younger, wealthier learners (sorry you returning and less early-advantaged souls) already "get it," but as a technology researcher and an instructor, I can tell you that they don't.

Sure they FB and FourSquare and 18% of them now Twitter (welcome and what took you so long?). They check for updates and comments on their social plans, bored and disengaged, while we lecture in big, face-forward classrooms. They text and they upload pics taken with their cell phone. Many do so inappropriately and publicly. Many have no idea how to use these digital skills in academic or professional ways. When attempting to think about how they might leverage technology to learn, they experience information overload and frustration. Shirky claims overload is merely poor filters- but WHERE will these generations learn about filters, synthesis, skeptical reflection if not from their experience here?

I see most of my colleagues in HE abdicating any responsibility for the lack of preparation in basic educated digital literacy while we continue our hold-the-line protection of lecture, text, expert, listen to ME culture. ("Only people not like you are experts or should be cited. Wikipedia is not scholarly. Shared knowledge is suspect. The written text is our medium.") I see the business community losing faith in our intentions. I see a government that publicly states the need for a good HE system in the US, but lacks the will to demand or finance one. I see graduates returning to ask me what they should major in next so that they're actually prepared for what's out there. "I see dead practice everywhere," as M Night Shyamalan might say.

We've got wicked, wicked wicked problems to solve and if I thought about it, I'd probably add a few more wickeds. I'm thinking about it in 2011. My new year's resolution, affirmation and promise in the time I have left here. Happy holidays, see you next year!

ASU End of Semester: Posting Final Grades - With a Little Help

The wonderful thing about digital information is the just in timeliness of finding what you need when you need it. Still, much research suggests that we prefer to reach out to colleagues, friends, and trusted resources when looking for specific information rather than Google the hodge-podge of sometimes wrong-headed help files on the ASU Web site. Perhaps that's what Joe Cocker meant when he said "I get by with a little help from my friends."

Thus, instructors (many teaching larger enrollment courses in past semesters) are now wandering into the halls here at ASU asking "Does anyone remember how to submit Roster Grades from Blackboard??" The information is out there, but not easy to find, and not completely helpful, so after walking numerous colleagues through the process in preparation for the crunch, I'm posting a summary here.

To automatically send your final grades from Blackboard to Roster Grades, you'll need to:

- create a letter grade total column in Blackboard. Instructions here, at the BB help site, for creating a total column. Remember to choose "primary display = letter"

Then follow the ASU Roster Grades Instructions page embedded deep in BB help files:

- designate your created column as the external grade column to export (#1 on ASU Instructions page)

- verify that the Blackboard default letter grade conversion scale is same as your scale (#2 on ASU Instructions page)

- export your BB grades (#4 on Instructions page)

- verify and post grades in Roster grades (#5 on Instructions page)

Note: Ignore step #3 in ASU Instructions. It assumes you're giving up your BB total-pts column after converting the column to a letter grade. You do NOT have to sacrifice this column (an important record) to post grades.

Yes, there are a few steps to muddle through, but much much faster than posting each grade by hand. Congratulations on making it through another semester. Hopefully, you were able to do it with a little help from your friends.

Flip that Lecture

Yeay, Karl Fisch! You go where few have gone before. Karl says STOP LECTURING YOUR STUDENTS and let them learn. Flip the Lecture notion: let your students watch lecture videos at home before the class.

In class: help them, work with them, engage them. Here's the whole story, as told by Daniel Pink (you know, A Whole New Mind, Drive...).

Now, of course I loved the story because I am a strong advocate for killing the lecture. It's not how most of us learn, despite how much teachers love to do it. When a rare teacher embraces the anti-lecture with videos (especially if the videos are then done in short, topical bites like the beloved Sal Khan - yes, beloved by me and many learning designers and funding agencies), then we have a thing of beauty.

The real fun, and added extra in the story, includes the fact that Pink isn't a learning designer, he's a societal scanner so his approach is Flip Thinking everywhere. Yeay to that too. Go Dan!

Nudge Analytics: Knowing and Doing

Things often take time to brew. Awhile back, an economist colleague of mine, Dr. Phil Mizzi, turned me on to Nudge, the work of Thaler and Sunstein (2008) on how a nudge in the right direction can subtly influence people to make good decisions. Their idea was to define a framework for choice architecture that takes into consideration the humanness of people, and how easy it is to not make decisions. When given free will, people often choose not by not choosing. Not to save, not to take care of their health, not to do simple personal, tiny things to protect the common good. In Nudge, the authors look at the economic benefits of nudging people to do the right thing.

A few years later, Phil and I can't help noting how machines have advanced in not just gathering data, but searching for patterns and noting significance. Decision architecture suddenly becomes much easier by eliminating the human-intensive intervention described in Nudge, but also becomes more reliable regarding the architecture piece of the choice architecture puzzle. In the authors' examples, someone is deciding the value and parameters of the nudge, rather than allowing analytics to gather, sort, compare, contrast and determine the objectivity of the nudge toward good. In one example, the authors describe a Save More Tomorrow plan that a number of corporations have implemented to help their employees save money through voluntarily auto-deduction. The authors state that thousands of corporations now use this nudge model, with triple the savings seen previously. But even economists can't tell a company what percent of salary best balances nudge vs. return. Why not let a machine do that? Across an institution or a multi-institutional study, machines could pattern-match and adjust recommended percent that would encourage participation at best savings rate. Nudge analytics: No guessing; no assumptions; no bias.

Close to home, the implications and affordances are deep when we think about the wasted information available in current university systems. The machine knows how many times students log into ALL the sections of ENG 101 in Blackboard. The machine knows the final grade of each of these students. The machine knows what percentage of students that login twice a week receive an A. Not many is our guess, but the machine doesn't have to guess. The machine could send out a note to the student's portal page or email on a weekly basis, letting the student know the likelihood that they'll receive an A based on their performance, matched against historical data. The machine could nudge the student to log in more often and raise their likelihood.

And that's just one idea from our own backyard. Starting to obsess on the idea, I'm beginning to see nudge analytics pop up in the most interesting places. Recently, with days to spare before the early voting sign up closes for the November election, I received an email from Organizing for America (President Obama's initiative to encourage citizens to vote) that is a perfect example of nudge analytics. The letter reminded me of the importance of my vote, and just let me know that AZ has a site online that takes moments to sign up to be on the Permanent Early Voter List.

I was nudged. My decision, my choice, just a nudge to be a better citizen. I gave that example to one of the intrepid reporters at InsideAZPolitics.com, and they put up the story and the link to AZ PEVL.

Consider their story, and this blog ending, a simple nudge. If you're as lazy, harried, stressed or forgetful as most of us, consider voting early. Sign up at the PEVL site before Monday to early vote by mail-in ballot in November. If you miss the deadline, sign up in time for the next local election.

Nudge analytics on the part of the machines at Organizing for America; just a simple, Thaler and Sunstein type nudge from me and InsideAZPolitics.com. Sign up. Know, then do. It'll be a decision that's good for the common good.