Why He Said That: Working with Assumptions in a Respectful Workplace

A couple of weeks ago, angered by the unpleasant behavior of a stranger I encountered while traveling for work, I found myself once more caught up in a very common human tendency: I automatically blamed the behavior entirely on the individual's personality and character, without stopping to consider whether any other factors might have contributed to the situation.

Reflecting further after the incident, I was struck again by the prevalence of this tendency, which psychologists call the "fundamental attribution error", and the risks it poses for relationships -- especially in the workplace.

Because we have offices in different countries, and because we have work with clients around the world (in over 25 countries now!), my colleagues and I travel a lot internationally. Based as I am in our Sydney office, I enjoy it when my work-related travel keeps me closer to home. Luckily for me, we've been involved in some large-scale culture change projects in recent years with clients in New South Wales, Queensland and Victoria, and as a result, I've seen a lot of those 3 states over the last 24 months. I particularly love getting out and visiting locations like Broken Hill, Longreach and Cobden, and I typically post on Facebook photos of the different places I come across. I guess you could say that I often travel with two hats – the working hat and the tourist hat. And, to be completely honest, sometimes the tourist hat comes out a little too often when I’m driving in places I haven't been before.

Here is what happened when I pulled on my tourist hat a couple of weeks ago, when I was in Leeton, NSW, which is about mid-way between Sydney, to the north, and Melbourne, to the south.

I drove into town with a couple of goals in mind: first, to find the pharmacy; and, second, to get into the pharmacy before it closed at 5 p.m. When I say I had my tourist hat firmly on at the time, I refer to the fact that I was driving slowly, watching for streets and landmarks, trying to locate the Pharmacy, while keeping my eyes out for suitable parking spots, at the same time that I was taking in the local sights. Tourist that I was, I stopped in the middle of the main street as soon as I spotted the pharmacy, and made ready to back into the nearest open parking stall.

As I shifted into reverse, I heard a car horn; looking in my rear-view mirror, I realized there were 8 or more cars lined up at a stand-still on the road behind me. I saw that the driver of the nearest car was yelling out the window, though I could not hear what he was saying, and the target of his attention was not immediately apparent to me. In my tourist-minded state, I did not take the time to figure out what was going on. Instead, I simply continued reversing into the parking spot.

It did not help that I misjudged the angle somewhat on that first attempt, which necessitated my pulling forward again to re-position myself for another run at the parking job. This created more difficulty, as the driver in the car behind me had, in the meantime, started to edge his vehicle around mine instead of waiting for me to finish parking, so that I almost hit his car when I pulled forward again. He stopped abruptly and yelled abuse at me out the car window. I quickly put my hand up to apologize and defuse the situation, and off he sped.

I was that the incident had not escalated further, but could not stop the angry thoughts running through my head, all of which had to do with what a rude, impatient jerk the other driver was. (Actually, a number of other, much more colorful descriptors came to mind, which I won’t repeat here.) Did he think he was only one on the road?!

This was the fundamental attribution error, a term you have likely run across if you have taken any courses in leadership, conflict resolution, or basic psychology. It simply refers to the human tendency to identify "internal factors" such as personality and character as the cause for people's situations and behavior, and to ignore or minimize external factors that might have contributed to the situation.

It happens all the time.

And we fall into this trap regularly.

When a car cuts us off in traffic, when a family member makes a comment we don’t appreciate, when a co-worker looks at us in a certain way across the conference room in a meeting, we come up with stories to explain the behavior when we actually have no idea of the person's real motivation or what they were actually thinking at the time: "He's a jerk!"; "She's so totally self-absorbed"; "He just can't handle it when others disagree with him."

And we say it with such conviction!

Each of us is vulnerable to being victimized by the fundamental attribution error of others, too. Most of us can think of at least one time that we've heard of a family member, friend or co-worker explaining away specific situations with "explanations" based on our character or personality, without taking other important realities into account. It can be hard to hear that our concerns have been minimized with statements like, "she's always just trying to show she's in charge", or, "he's just like that, he can't stand up for himself in meetings."

3 critical assertions that seem to implicitly go along with the fundamental attribution error:

"I can slip up once in a while, and still be a good person. You, on the other hand, are a bad person, as your behavior on this occasion proves.""I excuse my own behavior based on my 'good intentions', but I'll judge your behavior based on the impact on me.""I'll ignore all the times I've messed up in the past, and just focus on this occasion on which you messed up."

The unfairness of each of these assertions is pretty apparent once stated aloud.

Curiosity and imagination can be useful in countering the effects of the fundamental attribution error. 

In my own case, it was only after I had cooled down that I was able to reflect on the situation more clearly; gradually I realized that in attributing the offending driver's behavior solely to his personality and character, I was simply guessing at why he had behaved so badly. There could in fact have been any number of explanations for his behavior at the time, aside from or in addition to his personality and character.

As I worked up my curiosity and put my imagination into gear, I was easily able to generate several plausible alternative scenarios. These ranged from the driver having been in the middle of rushing to hospital to see his child in the emergency ward, to his having been in distress over hearing that day that his spouse was going to leave him. These imagined scenarios allowed me to contemplate the possibility that the yelling and swearing could have been less about the driver himself, and more about what was happening in his world.

I even ended up wondering whether the whole situation could have been more about me than anything else -- maybe I had inadvertently missed a traffic sign and actually caused the back-up of traffic by committing a driving infraction.

One way or the other, I was able to connect with the fact that I actually had no real idea what had been behind his behaviour.

None of that, of course, meant that I had to put up with being yelled or sworn at. But the incident did help me recognize once more how important dialogue and conversations are in making sense of any situation, and how important it is for me take personal responsibility in recognizing, acknowledging and checking out my own assumptions about the behavior of others.

Of course, the great thing about my own example in Leeton is that I never had to see the other driver again. All I had to do was manage my way out of my own frustrations and resentments, while carrying on with my journey.

It is typically more challenging when situations like this flare up in the workplace, as we often end up having to deal with the same person again and again over long periods of time. We become more vulnerable to the fundamental attribution error under these conditions.

My take is that all of us get a little short sighted when we become emotionally reactive over the behaviour of others, especially in the workplace. In the process we often fail to ask the right questions to understand and deal with the situation appropriately.

When we run with our assumptions about the behavior of colleagues, without first questioning those assumptions and checking them out, we can quickly find ourselves in a place of frustration and resentment. When this happens repeatedly with specific individuals, it places a real strain on our working relationships with them. In an effort to alleviate our own distress over the situation, we can be tempted to start talking badly about the individuals involved to our other colleagues, drawing them into the dynamic.

From the perspective of the workplace, it is important that people become competent both at self-managing in moments of frustration, and at engaging directly with people about those frustrations, rather than simply jumping to conclusions and working on assumptions about each other. At ProActive ReSolutions we teach a 6-step conversational model called Straight Talk as part of our Respectful Workplace Training Program for this purpose, and but whatever model or process you use, it is critical to find some way of keeping in check your own tendency to resort to the fundamental attribution error.

Next time you find yourself about to respond to someone's behavior by simply making unfavorable assumptions about their motivations or commenting negatively on their personality and character, take a pause. Work up some curiosity about what you don't know, and imagine some different scenarios that might (if true) make the behavior -- and the person -- seem more reasonable or understandable.

Then, from that place of curiosity and openness, try sitting down with the person for an informal conversation about what happened -- talk honestly and directly about the behaviors you observed, and the impact on you, including what you were left thinking and assuming. Express your genuine interest in understanding the other person's story about the incident. As part of the conversation, go ahead and ask for the person to do things differently next time, if that seems appropriate to you.

You might be surprised by what comes out of the conversation. At the least, you'll be doing the right thing for your workplace.

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Perspectives on Evidence-Based Research in Education--What Works? Issues in Synthesizing Educational Program Evaluations

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
Robert E. Slavin

Director of the Center for Research and Reform in Education at Johns Hopkins University, 200 W. Towsontown Boulevard, Baltimore, MD 21204; rslavin{at}jhu.edu. He is also director of the Institute for Effective Education at the University of York, in York, United Kingdom. His research focuses on comprehensive school reform, cooperative learning, research review, and evidence-based reform. Syntheses of research on educational programs have taken on increasing policy importance. Procedures for performing such syntheses must therefore produce reliable, unbiased, and meaningful information on the strength of evidence behind each program. Because evaluations of any given program are few in number, syntheses of program evaluations must focus on minimizing bias in reviews of each study. This article discusses key issues in the conduct of program evaluation syntheses: requirements for research design, sample size, adjustments for pretest differences, duration, and use of unbiased outcome measures. It also discusses the need to balance factors such as research designs, effect sizes, and numbers of studies in rating the overall strength of evidence supporting each program.

This article was written under funding from the Institute of Education Sciences, U.S. Department of Education (Grant No. R305A040082). However, any opinions expressed are those of the author and do not necessarily represent positions or policies of the institute. I would like to thank Harris Cooper, Carole Torgerson, Steven Ross, Bette Chambers, Alan Cheung, Philip Abrami, Marlene Darwin, Jon Baron, Mark Newman, and anonymous reviewers for comments on an earlier draft.

Received January 16, 2007. Revision received July 12, 2007. Revision received September 21, 2007. Accepted October 23, 2007.

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Zombie Apocalypse: New Threat to Workplaces?

Acknowledged internationally as a superb strategist, tactitian and martial arts instructor, who bridges the adjacent worlds of grappling, submission wrestling, MMA, jiu-jitsu, cage fighting and related disciplines, Kesting has outdone himself in his first forray into the new frontier of Zombie Defense.

Never one to rely on unhelpful generalizations, Kesting provides practical and effective techniques in this video for neutralizing zombies' primary offense, biting, while also distinguishing usefully between "eaters" (zombies who bite in order to devour) and "converters" (zombies who bite to contaminate and replicate).  While of limited assistance to interest-based negotiators and mediators seeking collaborative outcomes with zombies, there is little doubt that this analytical paradigm is of fundamental importance when escalation to physical confrontation proves unavoidable. 

Similarly, Kesting masterfully communicates the importance of early situational assessment, in order to distinguish between the "Slow Shufflers/Plodders" (think, Night of the Living Dead, Michael Jackson's Thriller, etc.) and "Speedy Zombies" (World War Z, etc.). Such situational assessment is, of course, critical in determining whether a neutralize and run strategy is even worth attempting during a zombie engagement.

If I have one substantive criticism of this video, it is Kesting's failure make any mention whatsoever of the importance of incorporating reference to zombie attacks into workplace violence policies, procedures and training, something that is, of course, critical to acheiving compliance with occupation health & safety regulations in many jurisdictions.

Others have objected to what they see as the exploitive use of under-aged zombies in this commercial production. I, personally, respectfully disagree with this position; I do not see any moral or legal basis for precluding the utilization of the undead in instructional videos, whether or not they are of the age of consent, in the sincere pursuit of reductions in rates of injury and even death amongst the living in workplaces.

I do, however, maintain my strong objection to animal testing in any form, whether or not the subjects are living, and I was relieved to receive confirmation from Kesting that no animal was involved in the making of this production.

HIGHLY RECOMMENDED: 4.5 out of 5.0 stars

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Curricular Coherence and the Common Core State Standards for Mathematics

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
In this work, we explored the relationship of the Common Core State Standards in Mathematics (CCSSM) to student achievement. Building on techniques developed for the Third International Mathematics and Science Study (TIMSS), we found a very high degree of similarity between CCSSM and the standards of the highest-achieving nations on the 1995 TIMSS. A similar analysis revealed wide variation in the proximity of state standards in effect in 2009 to the CCSSM. Finally, we used regression and analysis of covariance techniques to assess the relationship between the proximity of a state’s standards to the CCSSM and performance on the 2009 National Assessment of Educational Progress (NAEP). After adjusting for cut-points on state assessments and controlling for state demographics related to socioeconomic status and poverty, we found that states with standards more like the CCSSM, on average, had higher NAEP scores.

Received May 7, 2012. Revision received June 19, 2012. Accepted August 6, 2012.

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Design Experiments in Educational Research

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
Paul Cobb, Professor of Mathematics Education,

Vanderbilt University, Peabody College, Box 330, Nashville, TN 37203; paul.cobb{at}vanderbilt.edu. His research interests include classroom instructional design and analysis, the development of professional teaching communities, the institutional setting of teaching, and issues of diversity and equity as they play out in the mathematics classroom Jere Confrey, Professor,

University of Texas, Austin, Department of Curriculum and Instruction, SZB 518, Austin, TX 78712; jere{at}mail.utexas.edu. Her research interests include cognition and multiplicative relations, functions and trigonometry, technology design, and systemic reform Andrea diSessa, Chancellor’s Professor,

University of California, Berkeley, Graduate School of Education, 4647 Tolman Hall, Berkeley, CA 94720; disessa{at}soe.berkeley.edu. His research interests include conceptual and experiential knowledge in physics, and the design and use of flexible, comprehensible computer systems for learning Richard Lehrer, Professor and

Vanderbilt University, Department of Teaching and Learning, Peabody College, Box 330, 166 Wyatt Center, Nashville, TN 37203; rich.lehrer{at}vanderbilt.edu. His research interests include the design of learning environments for developing an understanding of mathematics and science Leona Schauble, Professor

Vanderbilt University, Department of Teaching and Learning, Peabody College, 1930 South Drive, Nashville, TN 37203; leona.schauble{at}vanderbilt.edu. Her research interests include cognitive development, especially the development of scientific thinking and model-based reasoning In this article, the authors first indicate the range of purposes and the variety of settings in which design experiments have been conducted and then delineate five crosscutting features that collectively differentiate design experiments from other methodologies. Design experiments have both a pragmatic bent—“engineering” particular forms of learning—and a theoretical orientation—developing domain-specific theories by systematically studying those forms of learning and the means of supporting them. The authors clarify what is involved in preparing for and carrying out a design experiment, and in conducting a retrospective analysis of the extensive, longitudinal data sets generated during an experiment. Logistical issues, issues of measure, the importance of working through the data systematically, and the need to be explicit about the criteria for making inferences are discussed.

Received August 23, 2002. Revision received November 6, 2002. Accepted November 7, 2002.

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How Companies Can Embrace Speed

by HBR IdeaCast  |   5:02 PM April 10, 2014

John Kotter, author of Accelerate, on how slow-footed organizations can get faster.

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TRANSCRIPT

A written transcript will be available by April 18.

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Learning, Teaching, and Scholarship in a Digital Age: Web 2.0 and Classroom Research: What Path Should We Take Now?

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
Christine GreenhowBeth RobeliaJoan E. Hughes

CHRISTINE GREENHOW is a postdoctoral associate in the College of Education and Human Development at the University of Minnesota, 125 Peik Hall, 159 Pillsbury Drive, Minneapolis, MN 55455; greenhow{at}umn.edu. Her research focuses on how people learn, teach, and collaborate using emerging social digital technologies (www.cgreenhow.org). She is currently leading a study of adolescent learners’ knowledge development, literacy, and community formation within and across two designed online social media spaces. She is the winner of the 2008 University of Minnesota Outstanding Postdoctoral Scholar award.

BETH ROBELIA is the executive director of Kitchen Table Learning, a research and evaluation company, 1496 Arona Street, Saint Paul, MN 55108; brobelia{at}kitchentablelearning.com. Her work on informal learning has spanned youth development, tutoring, teaching, and shipboard environmental education programs. Her work addresses how learning technologies can be used to bridge gender differences in science. She is currently investigating how construction toys and 3-D software develop students’ spatial reasoning abilities.

JOAN E. HUGHES is an associate professor of instructional technology in the College of Education at the University of Texas at Austin, 244M Sanchez Building, Austin, TX 78712; joanh{at}mail.utexas.edu. Her research examines preservice and in-service teachers’ development of knowledge and practice of technology integration in content areas. She is currently leading a longitudinal study with more than 7 years of data that examines the impact of 1:1 laptop computing in preservice teacher education. Since Windschitl first outlined a research agenda for the World Wide Web and classroom research, significant shifts have occurred in the nature of the Web and the conceptualization of classrooms. Such shifts have affected constructs of learning and instruction, and paths for future research. This article discusses the characteristics of Web 2.0 that differentiate it from the Web of the 1990s, describes the contextual conditions in which students use the Web today, and examines how Web 2.0’s unique capabilities and youth’s proclivities in using it influence learning and teaching. Two important themes, learner participation and creativity and online identity formation, emerged from this analysis and support a new wave of research questions. A stronger research focus on students’ everyday use of Web 2.0 technologies and their learning with Web 2.0 both in and outside of classrooms is needed. Finally, insights on how educational scholarship might be transformed with Web 2.0 in light of these themes are discussed.

Received November 2, 2008. Revision received March 11, 2009. Accepted March 24, 2009.

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To Tell Your Story, Take a Page from Kurt Vonnegut

by Andrea Ovans  |   11:10 AM April 15, 2014

In the 1989 movie Dead Poet’s Society, Robin Williams, playing the iconoclastic English teacher John Keating, dismisses the notion that you can judge the perfection of a poem mathematically by plotting how artfully it employs meter, rhyme, and metaphor against how important the subject is. Rather than have his students think they could graph the relative merits of, say, a Shakespeare sonnet against a poem by Alan Ginsberg, he has them rip up their textbooks. Data can’t tell us anything about stories, he’s saying, as pages of Understanding Poetry, by Dr. J. Evans Pritchard, Ph.D., fly all over the room.

Businesspeople are often advised to turn their data into stories to make them more persuasive. And that is certainly good advice. But they are given precious few tools to help them do that. It turns out though, John Keating notwithstanding, that graphs can be remarkably useful in demonstrating the mechanics underpinning an effective story. One person who’d given this a lot of thought was novelist Kurt Vonnegut, a real-life literary iconoclast if there ever was one.

Harvard’s Nieman Foundation for Journalism recently shed a spotlight on Vonnegut’s story graphs in its publication Nieman Storyboard (a wonderful resource on the art of storytelling in itself). Vonnegut devoted his master’s thesis at the University of Chicago to studying the shapes of stories. The thesis was rejected (apparently, Vonnegut’s advisors were of the John Keating school of literary criticism). But his ideas are thriving online in various storytelling tutorials.  Nieman offers up Vonnegut’s original presentation, now on YouTube, in which he graphs some of the most basic story structures and explains how they work.

“There’s no reason why the simple shapes of stories can’t be fed into computers,” Vonnegut begins. First up is one he calls Man in a Hole. “It needn’t be a man, and he needn’t fall into a hole,” he adds, for the metaphorically challenged among us. “That’s just an easy way to remember it.”

In the tradition of J. Evans Pritchard, he starts by drawing the vertical Good Fortune/Ill Fortune (or G-I) axis, with “sickness and poverty” at the bottom and “wealth and boisterous good health” at the top.  At the midpoint, he draws his x axis – B (for beginning) to E (for electricity). He’s joking of course, but he also wants to underscore the point that this is an exercise in relativity, since it’s the shape of the curve that matters, not the specific data points.

Then he places his chalk on the y axis a bit above the midpoint (“Why start with a depressing person?” he quips), draws a sine wave dropping down toward the bottom and rising up again: Somebody gets into trouble and gets out of it. “People love that story,” he says. “They never get sick of it!”  (This is doubly obvious is when you draw the business parallel by substituting a term like business, strategy, revenue, IT, HR, or whatever for the word somebody).

He goes on to graph Boy Meets Girl, starting right at the midpoint of the y axis – “an average person on an average day, not expecting anything.”  He draws a double sine wave rising up and then down and then up again. “Something wonderful happens, Oh hell. Got it back again” In business terms, the classic turnaround story (IBM comes to my mind here, and more than once).

The next one is more complicated, he warns. Despite what he’s just said, he starts at the bottom and stays there—a wretched person, a little girl, no less, has lost her mother and her father has married again to a horrible woman. The curve hovers at the bottom. A fairy godmother arrives, bestowing much-needed resources (shoes, a dress, mascara). With each gift, the line goes up incrementally, like a bar graph. The girl goes to a dance. The clock strikes 12:00. The resources dry up. The line drops almost straight down, but not all the way back (she has those memories, and maybe some IP or a valuable customer base). The prince finds her, the shoe fits. Facebook buys your start-up, the curve shoots up as you achieve off-scale happiness.

It so happens, he says, that this Cinderella story is “the most popular story in our Western civilization. Every time it’s retold somebody makes another million dollars. You’re welcome to do it.” Well, sure…

Here are all three stories, conveniently plotted on a single graph:

But watch the video (it’s less than five minutes long), and two things become apparent. The first is certainly that so many successful business stories follow patterns embedded in Western civilization’s most primal literary conventions. It’s easy to see why marshalling data to tell one of these kinds of stories – rags turning into riches, mistakes rectified, challenges overcome, the right resources and the right contacts saving the day — would be so compelling. And there’s probably an argument here for reading more fiction, to give John Keating his due.

The second is that Vonnegut’s delivery matters as much as his ideas. His timing is perfect.  His language is concrete and unexpected. He’s showing you the simplicity that underlies apparent complexity – that’s what data are so good at doing. But he’s just as concerned with making sure you’re paying attention — since no one is persuaded by something they don’t remember.

Persuading with Data
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Living Contradictions and Working for Change: Toward a Theory of Social Class-Sensitive Pedagogy

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
This essay describes a vision of social class–sensitive pedagogy aimed at disrupting endemic classism in schools. We argue persistent upward mobility discourses construct classist hierarchies in schools and classroom practice and are founded on misunderstandings of work, lived experiences of social class, and the broader social and economic context of the United States and the world. Educators may unwittingly alienate the very students they hope to inspire, cause for serious inquiry into what a social class–sensitive pedagogy might entail. The manuscript highlights five interrelated principles that provide insights to what research tells us and how it can be used in K–12 and teacher education.

Received September 27, 2011. Revision received April 24, 2012. Revision received July 27, 2012. Revision received September 7, 2012. Accepted February 10, 2013.

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Early Reading Skills and Academic Achievement Trajectories of Students Facing Poverty, Homelessness, and High Residential Mobility

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
This investigation tested the importance of early academic achievement for later achievement trajectories among 18,011 students grouped by level of socioeconomic risk. Students considered to be at highest risk were those who experienced homelessness or high residential mobility (HHM). HHM students were compared with students eligible for free meals, students eligible for reduced price meals, and students who were neither HHM nor low income. Socioeconomic risk and oral reading ability in first grade predicted growth of reading and math achievement in Grades 3 through 8. Risk status predicted achievement beyond the effects of early reading scores and also moderated the prediction of later growth in reading achievement from early oral reading. Results underscore the early emergence and persistence of achievement gaps related to poverty, the high and accumulating risk for HHM students, and the significance of oral reading in first grade as both an early indicator of risk and a potential protective factor.

This research was supported in part by predoctoral fellowships awarded to J. J. Cutuli from the Center for Neurobehavioral Development (CNBD) at the University of Minnesota and from the National Institute of Mental Health (NIMH; No. 5T323MH015755) and by grants to Ann S. Masten from the Center for Urban and Regional Affairs (CURA) at the University of Minnesota and the National Science Foundation (NSF; No. 0745643). We would like to thank the administration, staff, and families of the Minneapolis Public Schools (MPS), and particularly Margo Hurrle for her special efforts on behalf of homeless and highly mobile students in the MPS. The views and conclusions in this article represent the opinions of the authors and do not necessarily reflect the views of the CNBD, NIMH, CURA, NSF, or the MPS.

Received November 3, 2011. Revision received March 12, 2012. Accepted March 17, 2012.

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Investigating School Leadership Practice: A Distributed Perspective

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Design-Based Research: A Decade of Progress in Education Research?

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
Terry Anderson1Julie Shattuck2

1Athabasca University, Centre for Distance Education, Edmonton, Alberta, Canada

2Frederick Community College, Centre for Distributed Learning, Frederick, MD Design-based research (DBR) evolved near the beginning of the 21st century and was heralded as a practical research methodology that could effectively bridge the chasm between research and practice in formal education. In this article, the authors review the characteristics of DBR and analyze the five most cited DBR articles from each year of this past decade. They illustrate the context, publications, and most popular interventions utilized. They conclude that interest in DBR is increasing and that results provide limited evidence for guarded optimism that the methodology is meeting its promised benefits.

TERRY ANDERSON is a professor at Athabasca University, Centre for Distance Education, 10011 109th Street, Edmonton, Alberta T5J 3S8, Canada; terrya{at}athabascau.ca. His research focuses on social networking in distance education courses.

JULIE SHATTUCK is an instructional designer and assistant professor at Frederick Community College, Centre for Distributed Learning, 7932 Opossumtown Pike, Frederick, MD 21702; jshattuck{at}frederick.edu. She is a doctoral student at Athabasca University, and her research focuses on adjunct faculty training for online teaching.

Received July 7, 2011. Revision received September 20, 2011. Accepted September 26, 2011. © 2012 American Educational Research Association

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An Educational Psychology Success Story: Social Interdependence Theory and Cooperative Learning

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
David W. JohnsonRoger T. Johnson

DAVID W. JOHNSON is a professor in the Department of Educational Psychology, University of Minnesota, 60 Peik Hall, 159 Pillsbury Drive SE, Minneapolis, MN 55455; johns010{at}umn.edu. His research focuses on cooperation and competition, conflict resolution, and diversity.

ROGER T. JOHNSON is a professor in the Department of Curriculum and Instruction, University of Minnesota, 60 Peik Hall, 159 Pillsbury Drive SE, Minneapolis, MN 55455; johns009{at}umn.edu. His research focuses on inquiry learning, cooperation and competition, and conflict resolution. The widespread and increasing use of cooperative learning is one of the great success stories of social and educational psychology. Its success largely rests on the relationships among theory, research, and practice. Social interdependence theory provides a foundation on which cooperative learning is built. More than 1,200 research studies have been conducted in the past 11 decades on cooperative, competitive, and individualistic efforts. Findings from these studies have validated, modified, refined, and extended the theory. From the theory, procedures for the teacher’s role in using formal and informal cooperative learning and cooperative base groups have been operationalized. Those procedures are widely used by educators throughout the world. The applications have resulted in revisions of the theory and the generation of new research.

This article is based on the Distinguished Contributions to Educational Research Award Lecture presented at the 2009 AERA annual meeting.

Received May 4, 2009. Revision received May 8, 2009. Accepted May 8, 2009.

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No Research Left Behind

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Why Consumer Tech Is So Irritatingly Incremental

by Juan Pablo Vazquez Sampere  |   8:00 AM April 11, 2014

In the late 1960s, Michelin introduced the radial tire into the U.S. market. This was no surprise to the top five U.S.-based bias-ply tire manufacturers (Goodyear, Firestone, Uniroyal, B.F. Goodrich, and General Tire). After all, it was hardly a new technology; the first radial tire patents had been filed more than 40 years before. And they’d all seen radial tires take over the European market.

But even though radial tires were far superior to bias tires in terms of durability, cost per mile, and safety – and could be sold for an attractively higher price — they presented a challenge to U.S. incumbents. The process used to manufacture them was completely different from the one they used to make bias-ply tires. To produce radials, the U.S. giants basically needed to start their companies all over again — practically nothing of what they knew about producing bias-ply tires could be reused. Almost none of their patents would be useful (the tire business was the second most research-intensive industry in the U.S after chemicals). And so, even with the price premium, Michelin was the only company that had figured out how to produce radial tires profitably at scale.

Long story short, Michelin took over 50% of the entire tire U.S. market in the first 18 months after their introduction. And the Akron Ohio-based bias-ply tire manufacturing industry, which by 1920 had produced more millionaires than Silicon Valley has produced until just recently, essentially vanished. This is the transformational and dramatic effect of a superior technology entering an industry.

Again and again this story repeated itself in the 19th and 20th centuries. Gas lamps gave way to incandescent lamps. Refrigerators replaced ice boxes. Propeller planes yielded to jet engines. Joseph Schumpeter documented this pattern in Capitalism, Socialism, and Democracy, coining the term entrepreneur, which he described as the person who, when successful, revolutionizes an industry through the process of “creative destruction” (creative for the superior technologies, destructive for all the established firms that would go out of business).

Tesla, Nespresso, and Geox are current successful examples of such high-end disruptions. But how common is this phenomenon today? How often have you seen a firm revolutionize an industry by creating a superior product using a new business model? Not nearly so often.

Superior technologies do not take over industries as frequently as they once did because consumers today are different from those of a few decades ago. In much of the 20th century, technological innovation produced products that had plenty of room for improvement, opening up opportunities for high-end disruption. This went on in most industries until about the 1980s. Before that, most cars, for instance, were notoriously unreliable, prone to rust, and unlikely to last past 100,000 miles. Television picture quality remained unsatisfactory as the technology evolved from vacuum tubes to solid state to digital to HD. As a result consumers learned to compensate. They learned to repair their cars or to recognize which brand of a particular product was currently best.

But as established firms’ efforts to improve their products (what we call “sustaining innovations” in disruptive innovation theory), together with some occasional high-end disruptions, made products and services cumulatively better year after year, so many became so good that consumers either could not appreciate the product improvements or were simply unwilling to pay for them. And so we find that even though tire manufacturers today can produce much better tires than radials, consumers find that radials work just fine and aren’t willing to pay more for these superior technologies. As a result most of these designs end up being discontinued; a good example is the Michelin PAX tire.

When an industry reaches this point, opportunities at the high end dwindle, and there’s far more scope for low-end disruptions – offerings that combine a technology with an new, incompatible business model to produce an offering that’s not better than the incumbent’s offer (since they don’t really need to be) but are instead radically simpler, far more convenient, or very much more affordable (the classical definition of disruptive innovation introduced by Clayton Christensen). Crest Whitestrips, for example, are radically more affordable and convenient than going to the dentist to whiten your teeth. Digital photography is far more convenient than developing film.

So many industries have in fact reached this point that, as things stand in the 21st century, we know very little about when a high-end disruption will succeed. Recent research suggests that they would work in industries where the following criteria are met:

The majority of consumers are highly dissatisfied with the current products or services. This occurs today most commonly in highly regulated industries that are hampered in some way from improving their offerings (as was the case, for example, when AT&T held a monopoly over telephony in the U.S.)The industry is fragmented, which means that even the leading firms are limited in their ability to retaliate against upstarts.The new company is fully integrated from the beginning, which means that it does not outsource critical functional departments to keep its cost structure low. Rather, it has developed an entirely new business model to profitably exploit a new, superior technology.The new entrant uses a different distribution channel from the incumbents. This is perhaps the most important criterion, since it’s relatively easy for incumbents to use their market power to bar start-ups from established distribution systems.

The odds of meeting all of these criteria is relatively small. And so the odds of success of a new high-end disruption are correspondingly small. In fact, the rarity of a successful high-end disruption is the reason so many new and superior technologies that could do so much to help industries evolve and benefit customers never gain a market foothold.

Most entrepreneurs still think that just because their technology is superior it will inevitably be widely adopted in the marketplace. But consumers don’t work like that. Next time you come across an engineer aiming to commercialize a superior new technology, ask if his industry meets the criteria described above. If not, he’d do much better to focus on low-end disruption by encapsulating the technology in a product that is in some way simpler, more convenient – and seriously more affordable— than anything currently on the market. After all, technologies don’t dictate how they must be commercialized, managers do.

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At The Gathering!

Here we are at The Gathering. Overall a great idea for an event and well executed.

Sorry, I could not read the content fromt this page.

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Icebreaker: You Can Only Ask One Question

Exercise Similarity Analysis helps you to find the training activities you are looking for quicker than ever before by letting you follow clusters of similar exercises. Our Similarity Algorithm can accurately spot exercises in the collection which are similar to the one you are currently reading. These are shown in order of similarity at the end of each training activity. Following clusters of exercises can inspire you to find better exercises suitable for your specific training needs.

We are constantly looking for ways to make it easier for you to find what you want. Please let us know about your views on this or other features.

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Those Who Understand: Knowledge Growth in Teaching

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Upping the Ante of Text Complexity in the Common Core State Standards: Examining Its Potential Impact on Young Readers

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
The Common Core Standards for the English Language Arts (CCSS) provide explicit guidelines matching grade-level bands (e.g., 2–3, 4–5) with targeted text complexity levels. The CCSS staircase accelerates text expectations for students across Grades 2–12 in order to close a gap in the complexity of texts typically used in high school and those of college and career. The first step of the band at second and third grades is examined because it marks the entry into the staircase and a critical developmental juncture. In this article, we examine the theoretical and empirical support for three assumptions that underlie the acceleration of text complexity in Grades 2–3. Then we identify patterns in American reading achievement and instruction to illustrate the potential and far-reaching consequences of an increase in the first step of the CCSS staircase.

Received November 22, 2011. Revision received April 5, 2012. Accepted June 29, 2012.

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Infusing Neuroscience Into Teacher Professional Development

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
Bruer advocated connecting neuroscience and education indirectly through the intermediate discipline of psychology. We argue for a parallel route: The neurobiology of learning, and in particular the core concept of plasticity, have the potential to directly transform teacher preparation and professional development, and ultimately to affect how students think about their own learning. We present a case study of how the core concepts of neuroscience can be brought to in-service teachers—the BrainU workshops. We then discuss how neuroscience can be meaningfully integrated into pre-service teacher preparation, focusing on institutional and cultural barriers.

Received June 21, 2012. Revision received November 15, 2012. Revision received June 3, 2013. Accepted July 1, 2013.

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What Gets in the Way of Listening

by Amy Jen Su and Muriel Maignan Wilkins  |   8:00 AM April 14, 2014

As your role grows in scale and influence, so too must your ability to listen. But listening is one of the toughest skills to master — and requires uncovering deeper barriers within oneself.

Take, for example, our client, Janet, a successful principal in a management consulting firm.  She recently received 360-degree feedback from colleagues that she needed to improve her listening skills.  This confused her — she had always thought of herself as an active listener.  When we asked her colleagues why, they described how she wouldn’t exactly answer questions in meetings — and how she often had different takeaways from the rest of the team.  Janet wanted to explore what was happening.  It seemed simple enough, and yet why was she having trouble? The key, ironically, is to focus on yourself.

Ignore your inner critic. Janet realized that she wasn’t tracking to the dialogue because she was nervous about her own performance.  Her mind was attuned to a different voice — that of her own inner critic — monitoring how she was doing in the meeting.  This was especially true during presentations. Janet’s performance anxiety overshadowed her ability to hear the concerns underlying each question and kept her from noticing the audience’s cues to move along. Shift your focus from “getting a good grade” to the presentation’s greater purpose. What excites you about the topic or audience?

Expand how you see your role. To fully listen, you must first believe it is a critical part of your job.  To quote from Boris Groysberg and Michael Slind’s article, Leadership Is a Conversation, “Leaders who take organizational conversation seriously know when to stop talking and start listening.”  As Janet continued to explore why she wasn’t listening, she realized she’d boxed herself in.  As a management consultant, she described her role as, “providing efficient solutions to clients.”  We discussed how she might update her view from problem solver to trusted advisor — one that not only provided counsel but listened deeply to clients’ issues and concerns.  Consider if you’ve boxed yourself in by role definition.  Do you believe your primary job is to provide direction only?

Put aside your fear and anticipation. Listening demands being fully present and ready to respond to what might get thrown your way. But our listening shuts down when we’re anticipating what might happen next.  Janet found that while another person was talking, her mind was already thinking about what she might say next or anticipating what might be said.  This was especially true during difficult conversations, when she anticipated confrontation. She’d rush through what she wanted to say without listening as a way to avoid her fears of conflict. But listening is an especially important skill in navigating difficult conversations, where multiple interests and agendas must be aligned.  Our full attention is demanded to understand what the hot-button issues are or what the potential misunderstandings might be. Notice if your listening shuts down when you’re emotionally uncomfortable.  Are you aware of your triggers? 

Be open to having your mind changed. Janet also realized that she was working hard to appear confident and to make sure she was offering her point of view in meetings.  In trying to be more assertive, she came off as having prematurely made up her mind.  One of Janet’s partners shared this tip, “I do have a viewpoint going in but I don’t assume or try to show I’m the smartest person in the room.  In fact, I go in with the assumption that my colleagues are smart too and therefore might have good reason for having a different position.  I’m willing to hear them out for the sake of getting to the best answer, not just my answer.”  Listening, then, is actually a sign of incredible self-confidence. Are you trying too hard to convey confidence and missing others’ perspectives in the process?

While tactically there are many ways to strengthen your listening skills, you must focus on the deeper, internal issues at stake to really improve. Listening is a skill that enables you to align people, decisions, and agendas. You cannot have leadership presence without hearing what others have to say.

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Inequities in Educational and Psychological Outcomes Between LGBTQ and Straight Students in Middle and High School

Impact Factor:2.779 | Ranking:6/219 in Education & Educational ResearchSource:2012 Journal Citation Reports® (Thomson Reuters, 2013)
This study finds that, compared with straight-identified youth, youth who identify as lesbian, gay, bisexual, transgender, or questioning (LGBTQ) are at greater risk of suicidal thoughts, suicide attempts, victimization by peers, and elevated levels of unexcused absences from school. Results disaggregated by LGBTQ subgroups reveal heterogeneity within the broad LGBTQ group, with bisexual youth appearing to be particularly at risk. Also, although the risk gaps in school belongingness and unexcused absences are significant in high school, we find that these gaps are significantly greater in middle school, suggesting heightened early risk for LGBTQ-identified students. By raising awareness of educational inequities related to LGBTQ identification, this study lays the descriptive groundwork for interventions aimed at improving psychological and educational outcomes for these students.

JOSEPH P. ROBINSON is an assistant professor of quantitative and evaluative research methodologies at the University of Illinois, Urbana- Champaign, Department of Educational Psychology, 210F Education Building, 1310 S. Sixth Street, Champaign, IL 61820; jpr{at}illinois.edu. His research focuses on causal inference and quasi-experimental designs, policy analysis and program evaluation, and issues related to educational equity and access.

DOROTHY L. ESPELAGE is a professor of educational psychology at the University of Illinois, Urbana-Champaign, Department of Educational Psychology, 226A Education Building, 1310 S. Sixth Street, Champaign, IL 61820; espelage{at}illinois.edu. Her research focuses on bullying and peer victimization, homophobic teasing, and sexual harassment among adolescents.

Received October 27, 2010. Revision received April 7, 2011. Revision received August 7, 2011. Accepted August 8, 2011. © 2011 American Educational Research Association

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