Awareness as a Community Indicator

This post originally appeared in my blog Digital Amalgam, and was moved to this blog in July, 2007.

Inspiration this morning came from discovering Nancy White's liberal use of the Technorati tag 'community_indicators'. I enjoyed reading a blog entry she pointed to about "community of the path" (Debra Roby) and it got me to thinking about how I cross paths with so many at work, usually in meetings, and how we all get intertwined through a few overlapping responsibilities, and also how we choose to interact with one another at those crossover points.

I've been very aware lately of the ways in which I'm interacting with others, and sometimes not liking what I see in how I've chosen to interact. But as I've become more aware, I've started to notice something. Somehow, my interactions feel more "connected." I guess what I mean is that I don't feel as much (with some of the folks with whom I'm interacting) that I'm just crossing paths, but that I'm seeing more of where they're coming from and where they're going (what those other responsibilities are), and how that plays a role in how they choose to interact with me. I'm more aware, too, I've where I'm coming from and how that helps determine the choices I make in interaction.

Top Myths about Online Learning: Disembodiment

This post originally appeared in my blog Digital Amalgam, and was moved to this blog in July, 2007.

A few months ago, I was reading the book Stiff: The Curious Lives of Human Cadavers, by Mary Roach. It's a great book, and has nothing to do with educational technology, but the word "disembodied" appeared in it a lot. The use of that word was quite literal in this book, but it kept reminding me of the less literal use of the word as it's often bandied about in describing the experiences of online learners.

I did a quick Google search for +"disembodied" +"online learning" which at the time turned up 597 hits. Today it's turning up 677. Are there more skeptics out there? Or more people fighting the skeptics? Only digging through the search results will tell. It's worth looking at a few of the hits. One is a book review of book called On the Internet, which takes a negative stance on the Internet in general and on online learning in particular, which at one point draws on the same philosopher as the author does to refute the idea that engaging in the Internet is an act of disembodiment:

For Merleau-Ponty, there can be no experience outside the body and he would conclude that any warning about the dangers of disembodied experiences are pointless because such a thing is not possible.

The reviewer's overall point is that any new technology goes through this long period of misconception and myth. Can we please move beyond this period soon for online learning? It makes my job difficult when I discover that many of my colleagues have a mental model of online learning as I talk to them about how we might advance our goals related to it. As I'm talking with them about which courses and programs we might offer online, I often forget that in their mind this is a second-rate learning approach, and one that will end forever the close, personal relationships that students and faculty will have.

When I finally snap out of it and remember what they're thinking, I do my little song and dance reminding them that in online courses most students and instructors alike report that they're able to develop closer and mor meaningful relationships with more of their classmates/students. I try to explain that the asynchronous nature of onling learning does worlds to enhance interpersonal contact, plus reflection and critical thinking. I expound on the wonder of the tools in helping to better facilitate collaborative learning. And still, I know they're thinking that online learning is about disembodiment.

I think the best thing that can happen for these folks is that they take, and then teach, an online course themselves. But not all of them will, so I'll keep doing my song and dance.

Actually, more an more I can already begin to see a shift in thinking, and the myth of embodiment seems less present among my colleagues. However, I'm still mindful when I'm talking to someone who's never experienced online learning to deliver the "elevator pitch" part first--trying to make sure we have a shared picture of what I mean by online learning. Every time I do this, I confirm that the myth was alive and well because as I describe my view/experience of online learning I get a lot of "really?" and "oh, I didn't realize that."

So practice your anti-disembodiment elevator pitch. Let's see if we can kill off this myth in short order.

Blogs versus Discussion Boards, Continued

This post originally appeared in my blog Digital Amalgam, and was moved to this blog in July, 2007.

I've been enjoying a current thread on the EDUCAUSE Instructional Technology (INSTTECH) listserv about blogging versus discussion boards as tools for teaching and learning. The whole thread harkens back to posts (see posts on 9/8/2004, 9/12/2004, and 9/14/2004) here and elsewhere about this topic. I remain fascinated by the thinking going into the use of blogs as instructional tools, and also tools for development of communities.

(Maybe this interest will be enough to get me back to blogging regularly! I've been away from this for so long.)

A colleague of mine had a great insight about this thread, when I sent her a link to it. She pointed out that there might be something missing with regard to the "blog culture" when folks are comparing them to discussion boards. She points out that blogs can't be looked at just as a tool. She has an interesting point here, I think--that we have to consider the weight of the "cultural shift" that might be necessary to use blogs effectively.

But then, can't the same be said for using discussion boards effectively? More exploration of this to come...

Origins, Part V: Exploring Institutional Research

This post originally appeared in my short-lived blog Truth and Beauty, and was moved to this blog in June, 2007.

The kinds of challenges I came up against while thinking through the issues I describe in Origins posts III (quality in distance learning) and IV (inputs versus outputs) have led me over the last year to an interest in the world of Institutional Research (click to read Wikipedia entry on I.R.).

I recently applied to the graduate certificate program in I.R. at Penn State University. I hope to complete the program online as a way of further exploring the field and finding out if it's what will hold my interest for the rest of my career in Higher Education. I'm delaying my plans for a doctoral program right now, hoping that the certificate program would give me a chance to hone in on some ideas for my dissertation, assuming I end up doing something related to I.R...

Perhaps the best thing for this post would be to simply include here the personal statement I wrote for my application to Penn State. This is the long form--I discovered after I wrote it that I had to limit it to one page, so the version I submitted is a bit shorter. In any case, this provides some good background related to why I'm interested in I.R. (and repeats some of what I've said in earlier "orgins" posts):

I never would have predicted that I’d become interested in data. In my positions of increasing responsibility related to technology in education, though, I have faced continued pressure to justify the use of technological tools for teaching and learning. I’ve been asked to demonstrate the effectiveness of these tools in achieving intended outcomes, and have often struggled to put together the data to provide such illustrations. My search for the right information, and enough of it, has gradually led me to a fascination with data and its implications for educational decision-making.

This search also raised for me a lot of questions about data and effectiveness. As I began to undertake the job of illustrating technology’s value, I discovered that data alone didn’t tell the whole story. In fact, I often found data meaningless in the absence of other important information: What are the goals and intended outcomes? What are the specific strategies and applications we’ve deployed toward reaching these outcomes? How do we know which inputs are supporting, or creating barriers to, our success? What about information and data from other institutions—can this tell us something about ourselves? These questions have often been harder to answer than I thought they would be, but I learned that the real value of the data was not only in what it could tell you, but also in what it made you question.

One example of learning the value of data—specifically its relationship to goals and outcomes—comes from Marlboro College in Vermont, where I led curriculum development for a graduate program focused on technology in education. Marlboro College was at the time a school decidedly non-technological and more than a bit resistant to technology, but I feel that we succeeded in communicating the value of technology in education. We did this by asking what the core institutional values and goals were. A student-centered curriculum is a fundamental part of the college’s mission, and we were able to show how technology increases the institution’s and instructors’ ability to be student-centered. Since many of our students in this program were teachers themselves, we also focused the curriculum on developing goal setting and problem solving skills. Students were asked to develop technology-based solutions to real educational problems and eschew using technology for its own sake. I had learned that data must be viewed within a context of institutional goals, and applied this insight to my work.

As director of distance education at Southern New Hampshire University, I continued to work on tying my efforts to institutional objectives. I also began to find that data could be tremendously useful in plotting strategies for working toward objectives. Enrollment, student satisfaction, and student success (drop/withdrawal/failure rates and grade distributions) all became important indicators to me, but their utility went beyond providing evidence for a match with the strategic plan. What these data started to do was to tell me stories of the experiences that our students and faculty were having. I was able to use the stories that the data were telling to look at our inputs—the technology we were deploying, the marketing strategies, student support services, and faculty development. I learned that the data could give us hints about how to design the right combination of inputs to grow the programs.

At North Shore Community College, I am on the senior staff of the college’s Academic Affairs component. I continue to employ the lessons I’ve learned about data and asking the right questions. My job is largely about setting the strategic direction for educational technology at the institution, and connecting that strategy to other areas in Academic Affairs, Student and Enrollment Services, Administrative Affairs, and Institutional Advancement. I’m a little closer to a 33,000-foot view of the planning process now, and I’ve discovered that information about goals and inputs, while valuable, is not all that’s needed to make decisions. Also necessary is the ability to see that although these things drive the institution’s planning efforts, strategy requires more than a simple laundry list of goals, inputs, and outcomes. A process must be applied for all this data to be turned into strategy.

In an effort to advance my strategic efforts, I’m looking outward. I want to know what the data are “out there.” What have other institutions set as their objectives? What are their inputs? How well are they doing in reaching their outcomes? As an advisory board member of the National University Telecommunications Network (NUTN), I’ve been contributing my ideas to a distance learning benchmarking initiative. The initiative seeks to scaffold individual institutional strategies by providing results data, in the aggregate, from a wide variety of participating schools. Through my participation in the effort, I’m trying to remind the developers that results can’t be “unbundled” from the best practices. Both the outcomes data and the inputs must be a part of the planned benchmarking tool because either one of these alone loses meaning.

All too often, I’ve witnessed institutional leaders, policy makers and legislators confuse data with real outcomes. The statistics provide an important part of the story, but they are only a representation, and the real story includes so much more. While in graduate school, I took a course at MIT in system dynamics. After we spent a semester building complex models and simulating the behavior of economic systems over time, our instructor included a lecture on “Truth and Beauty.” The simulations, he warned us, may have been beautiful, and they may even have told us a powerful story. However, they shouldn’t be confused with reality—which is far more complex than we’d ever be able to model.

I worry that this kind of confusion is sometimes at the heart of educational decision-making. In numerous recent speaking engagements, United States Department of Education Secretary Margaret Spellings has said “In Texas we like to joke ‘In God we trust. All others, bring data.’” As it turns out, that phrase can be attributed to the late W. Edwards Deming, father of Total Quality Management (TQM) and continuous improvement—a pioneer in scientific management. W. Edwards Deming has also been reported to say, “Data will provide you with three percent of what you really need to know.”

My experience confirms that, in an age of accountability in education, it’s worth trying to find and record the data. The ability to search for the other 97% “…of what you really need to know,” however, must be part of the academy’s institutional research and effectiveness capacity. I hope to be able to explore these ideas, and translate them into practice, as part of Penn State’s graduate certificate program in Institutional Research.

Origins, Part IV: Inputs versus Outputs, versus Process

This post originally appeared in my short-lived blog Truth and Beauty, and was moved to this blog in June, 2007.

As I've learned the ways that the academy is viewed, it seems that a lot if boils down to inputs and outputs--inputs being the "stuff" that makes up a college, from buildings to curriculum to faculty and support staff; outputs being student success rates, research, etc.

It appears to me that in this age of accountabilty in education that there is some confusion about which of these things we ought to be paying most attention to. What really matters about a college? If you look at what the accreditors have looked at for many years, you'd probably say that what matters are the inputs. Accreditors have traditionally looked primarily at things like how well the curriculum is structured, how governance works, how many volumes there are in the library, how much faculty and administrators are paid, and other things related to the composition of the institution.

More and more, however, we're starting to see a trend toward looking more closely at the outputs. Especially for public institutions, there is an increasing pressure to track and report student success and other outcome measures. Public and private institutions alike are finding that both regional and national/professional accreditors are putting more and more outcomes assessment into their accreditation standards.

I think that both of these views on what makes for a good institution come up short. For me, it feels that we need to understand that the sustainable success of an institution lies neither in its inputs or its outcomes. Instead, it is the capacity of the institution to really understand the connection between its inputs and outputs that matters, in my view. An institution that's doing poorly on outcomes needs to be able to assess why it's doing poorly--which of its strategies or tactics (inputs) are acting as barriers to success? An institution that's doing well needs to know how to sustain success by understanding which inputs are bolstering it.

In either situation, an institution has to have the capacity to understand that over time there are likely to be shifts in what sustains or blocks success, and they need good planning capacity to lay out evolving strategies and tactics.

Maybe this capacity--the ability to assess and to plan--is itself an input. But I think that we should look at the institutional research and assessment capacity as the third leg of a tripod that includes inputs, outcomes and this process of analyzing and planning.