Diversity enriches us all

From “White Students on Why Schools Need More Teachers of Color“:

The societal advantages of more teachers of color become clearer when considering the racial socialization—or the processes by which people develop their ethnic identities—of white adults, including the parents who may stumble in communicating racial understanding to their children. A Public Religion Research Institute study on “American Values” circulated last summer, following the shooting in Ferguson, showed that 75 percent of white Americans have all-white social networks. This self-segregation could help explain the racial divide over Michael Brown’s death and why it was seemingly so hard for many whites to understand what transpired in Ferguson: Their worldview was restricted to mostly white friends and family. And in a 2014 study researchers found that “the messages that white teens received [from parents regarding race] were contradictory and incomplete,” concluding that schools are a crucial link in building “productive and genuine relationships” between whites and people of color.

Per Matthew Kay, the first black teacher for one Philadelphia high school student:

by interacting daily with people who come from different backgrounds, white students who harbor stereotypes and prejudgments may be able to chip away at those convictions. …

In his day-to-day dealings with students, Kay also fights the widespread, centuries-old narrative that black men are driven by anger and frustration. “I am affectionate and caring … I think it’s important that [the students] see we have the capacity to love.”

Underpinning it all, Kay said, are his close relationships with students and his ability to offer them a safe space to investigate and reflect on any racial privileges they enjoy without being made to feel morally deficient for having white skin.

However:

Thomas M. Philip, an education professor at UCLA whose work focuses on racial ideology and teachers… warned that putting the onus on teachers of color to carry the burden of discussions on larger historical and political issues carries significant risks, ranging from exceptionalism and tokenism to individualizing an institutional responsibility. …

Teacher diversity, Philip stressed, must be accompanied by systemic practices that support all educators in constructively navigating issues of race, racism, and racial justice. To do otherwise, he said, is to allow some to abdicate their role in engaging the same issues deeply and profoundly. “The unique strengths and perspectives of teachers of color are more likely to be beneficial for students if all educators, particularly white teachers and administrators, embrace the responsibility to work for racial equity and justice.”

The benefits and burdens belong to all of us.

When peers improve decision-making skill

In a study of 760+ fifth-graders described in “Group learning makes children better decision-makers, study finds”:

Children who had worked in collaborative groups… were better prepared to take on the role of decision-maker about [the moral dilemma in the story], the researchers found.

These children were more proficient at three key aspects of decision-making: recognizing more than one side of a dilemma, considering a range of reasons to support differing viewpoints, and weighing the costs and benefits associated with different decisions, according to the researchers.

These children appealed to a significantly greater number of moral principles and practical considerations when drawing conclusions about [recommended actions], the researchers found.

Students in the direct instruction condition performed no better than a control group of uninstructed students.

Don’t Just Acknowledge Bias, Demand Its Reduction

From Adam Grant and Sheryl Sandberg’s “When Talking About Bias Backfires“:

The assumption is that when people realize that biases are widespread, they will be more likely to overcome them. But new research suggests that if we’re not careful, making people aware of bias can backfire, leading them to discriminate more rather than less.

The key is to conclude the acknowledgment of the problem with clear disapproval of it, such as:

“Please don’t remove the petrified wood from the park.”

“A vast majority of people try to overcome their stereotypic preconceptions.”

“I don’t ever want to see this happen again.”

Social cues can be powerful; use them well.

Social-learning engineering

The social component of learning has long been overlooked from both a regulatory and a design perspective, with community formation often assumed to happen through the traditions of brick-and-mortar institutions. But as students spend less time at physical campuses, whether due to part-time status, family and work commitments, or online classes, deliberately planning how students will connect meaningfully with each other becomes necessary.

Coursera’s partnership to create “learning hubs” offers one example of how the education, business, and government worlds are exploring solutions to strengthen the tenuous social fabric that keeps students in class. Along with the basics of internet and technology access, these hubs also offer a more fundamental reason to return: social ties. Fellow classmates can offer instrumental support by sharing knowledge and experiences, but they also offer emotional support and validation when uncertainty strikes. While the time and effort required to build social ties may initially seem costly, the investment can pay off through higher enrollment and retention, as well as improved learning and satisfaction.

As these initiatives reveal, personalizing learning effectively goes beyond mere individualization to include genuine integration of the participants as people connected in a community.

Balancing human-human and human-computer interaction

A fundamental challenge in implementing personalized learning is in determining just how much it should be personal—or interpersonal, to be more specific. Carlo Rotella highlights the tension between the customization afforded by technology and the machine interface needed to collect the data supporting that customization. He narrows in on the crux of the problem thus:

For data to work its magic, a student has to generate the necessary information by doing everything on the tablet.

That invites worries about overuse of technology interfering with attention management, sleep cycles, creativity, and social relationships.

One simple solution is to treat the technology as a tool that is secondary to the humans interacting around it, with expert human facilitators knowing when and how to turn the screens off and refocus attention on the people in the room. As with any tool, recognizing when it is hindering rather than helping will always remain a critical skill in using it effectively.

Yet navigating the human-to-data translation remains a tricky concern. In some cases, student data or expert observations can be coded and entered into the database manually, if worthwhile. Wearable technologies (e.g., Google Glass, Mio, e-textiles) seek to shorten the translation distance by integrating sensory input and feedback more seamlessly in the environment. Electronic paper, whiteboards, and digital pens provide alternate data capture methods through familiar writing tools. While these tools bring the technology closer to the human experience, they require more analysis to convert the raw data into manipulable form and further beg the question of whether the answer to too much technology is still more technology. Instructional designers will always need to evaluate the cost-benefit equation of when intuitive human observation and reflection is superior, and when technology-enhanced aggregation and analysis is superior.

On the realistic use of teaching machines

From the perspective that all publicity is good publicity, the continued hype-and-backlash cycle in media representations of educational technology is helping to fuel interest in its potential use.  However, misleading representations, even artistic or satirical, can skew the discourse away from realistic discussions of the true capacity and constraints of the technology and its appropriate use. We need honest appraisals of strengths and weaknesses to inform our judgment of what to do, and what not to do, when incorporating teaching machines into learning environments.

Adam Bessie and Arthur King’s cartoon depiction of the Automated Teaching Machine convey dire warnings about the evils of technology based on several common misconceptions regarding its use. One presents a false dichotomy between machine and teacher, portraying the goal of technology as replacing teachers through automation. While certain low-level tasks like marking multiple-choice questions can be automated, other aspects of teaching cannot. Even while advocating for greater use of automated assessment, I note that it is best used in conjunction with human judgment and interaction. Technology should augment what teachers can do, not replace it.

A second misconception is that educational programs are just Skinner machines that reinforce stimulus-response links. The very premise of cognitive science, and thus the foundation of modern cognitive tutors, is the need to go beyond observable behaviors to draw inferences about internal mental representations and processes. Adaptations to student performance are based on judgments about internal states, including not just knowledge but also motivation and affect.

A third misconception is that human presence corresponds to the quality of teaching and learning taking place. What matters is the quality of the interaction, between student and teacher, between student and peer, and between student and content. Human presence is a necessary precondition for human interaction, but it is neither a guarantee nor a perfect correlate of productive human interaction for learning.

Educational technology definitely needs critique, especially in the face of its possible widespread adoption. But those critiques should be based on the realities of its actual use and potential. How should the boundaries between human-human and human-computer interaction be navigated so that the activities mutually support each other? What kinds of representations and recommendations help teachers make effective use of assessment data? These are the kinds of questions we need to tackle in service of improving education.

MOOCs plus big data

In The Coming Big Data Education Revolution, Doug Guthrie argues that “big data”, rather than MOOCs, represent the true revolution in education:

MOOCs are not a transformative innovation that will forever remake academia. That honor belongs to a more disruptive and far-reaching innovation – “big data.” A catchall phrase that refers to the vast numbers of data sets that are collected daily, big data promises to revolutionize online learning and, in doing so, higher education.

I agree that there are exciting new discoveries and innovations still yet to be made through the advent of big data in education, and I also agree that MOOCs’ current reliance on scaling up delivery of existing content isn’t particularly revolutionary. Yet I see the two movements as overlapping and complementary, rather than as competing forces.

While MOOCs may not (yet) have revolutionized instruction, they have revolutionized access for many learners. Part of their appeal for those interested in their growth is their potential for enabling large-scale analysis due to the high enrollments as well as the availability of online data. The opportunity to study such large numbers of students across such disparate contexts is rare in traditional academic settings, and it permits discoveries of learning trajectories and error patterns that might otherwise get missed as noise amidst smaller samples.

Another potential innovation which traditional MOOCs (xMOOCs) have not yet explored is new models of building cohorts and communities from amidst a large pool of learners, a goal at the heart of “connectivist MOOCs” (cMOOCs) that highlights peer-learning pedagogy. Combine xMOOCs and cMOOCs, and you can improve educational access even further by enabling courses to spring up whenever and wherever enough people, interest, and resources converge. Add in the analytical power of big data, and then you have the capacity to truly personalize learning, by providing both the experiences that best support students’ learning and the human interactions that will enrich those experiences.

Letting children choose promotes prosocial behavior

As described in “Giving Preschoolers Choice Increases Sharing Behavior“:

[S]haring when given a difficult choice leads children to see themselves in a new, more beneficent light. Perceiving themselves as people who like to share makes them more likely to act in a prosocial manner in the future.

Previous research has shown that this idea — as described by the over-justification effect — explains why rewarding children for sharing can backfire. Children come to perceive themselves as people who don’t like to share since they had to be rewarded for doing so. Because they don’t view themselves as “sharers” they are less likely to share in the future.

Developmental psychologists Nadia Chernyak and Tamar Kushnir found that compared to children who were given a non-costly choice or who were required to share, preschoolers given a costly choice were more likely to share again at a subsequent opportunity.

My thoughts:

  1. I would be interested in an analysis comparing the effect of the conditions on the children who did not share– that is, collecting baseline data on children’s initial propensity to share, and then comparing how the interventions affected them across the range of initial tendencies.
  2. I wonder how well this would apply to long-term planning and diligence (e.g., completing homework, practicing a difficult skill, doing chores).

The results do suggest that choice can be a powerful mechanism for promoting positive habits and attitudes, something which I think parents and schools could harness more productively. That choice can potentially foster empathy and perspective-taking is very encouraging.


Full reference: N. Chernyak, T. Kushnir. Giving Preschoolers Choice Increases Sharing Behavior. Psychological Science, 2013; DOI: 10.1177/0956797613482335

Empathizing with actions above appearance

In two previous posts, I emphasized the importance of encouraging children in general and girls in particular to value actions above appearance, noting that I would especially want to promote perspective-taking, self-regulation, and cognitive flexibility rather than looks. “Fit and Feminist” blogger Caitlin echoes this sentiment:

[W]hat your body looks like is not as important as what it can do.

She objects to the disconnect between achievement and the appearance of achievement, with regard to how we judge physical fitness:

When a person has a lean body, it serves as visual shorthand of sorts, indicating that the person most likely trains hard and who [sic] has excellent nutrition… You can’t see a person’s 1RM or their 5K PR, but you can see their visible abs, you know?

Imagery carries an immediacy that surpasses words and numbers, even when crafted into a compelling narrative. We process images much more quickly and viscerally than we process stories, and we have less experience critiquing pictures than we do analyzing and arguing using language.

Images themselves strip away context, removing the periphery and exaggerating the impact of anything contained within the frame. Still images also remove temporal context, inviting us to fill in but allowing us to forget what might have happened before and after the photo. In today’s highly connected and media-saturated world, we archive and recirculate images capturing unusual moments, someone’s “best of” achievement rather than the ordinary everyday which we mentally discard. Instead we create unrealistic expectations based on this visual vocabulary in which only the rare and easily perceived is worth remembering and emulating:

[W]hen we hold up ultra-leanness as The Fitness Goal for recreational athletes like myself as well as people who are just trying to keep themselves healthy, we are basically saying that everyone should be held to the same standards as elite athletes. This is insane! In what other area of our lives are we expected to emulate the best of the best? Are we all expected to write Pulitzer Prize winning novels? Must we all be capable of singing like the angelic offspring of Mariah Carey and Whitney Houston? Should we all be able to engineer the tools necessary to identify the Higgs-Boson particle? No! So why does this idea persist that says we must all have the bodies of Olympic athletes before we can be considered fit and healthy?

Even trickier is our tendency to try to identify with the subject of a photo, mapping ourselves onto the person we see (or imagine). As Paul Bloom notes, people are influenced by appearance and perceived similarity to themselves when judging competence, culpability, and worth:

People are understandably empathetic toward the victims of crime, particularly when they are young and vulnerable, when they are attractive, and when they share our race or ethnicity.

[W]hen the victim of a crime is attractive, the defendant tends to get a longer prison sentence; if the defendant is attractive, he or she gets a lighter sentence.

[B]aby-faced individuals also tend to get lighter punishments, perhaps because they inspire parental warmth.

[J]udging someone based on the geometry of his features is, from a moral and legal standpoint, no better than judging him based on the color of his skin. Actually, both biases reflect the parochial and irrational nature of empathy.

Bloom also highlights our tendency to selectively empathize with people on one side of a conflict while disregarding the other, and with identifiable individuals rather than anonymous numbers:

Typically, political disputes involve a disagreement over whom we should empathize with.

Too often, our concern for specific individuals today means neglecting crises that will harm countless people in the future.

Appearances are seductive, readily merging with our imagined selves and crowding out invisible others.

What we ought to do instead is maintain a healthy separation between ourselves and the targets of our empathy. Parenting expert Janet Lansbury continually highlights the value of empathizing with young children, as distinct from simply identifying with them. It requires acknowledging others’ feelings while also remaining separate from them.

The more you are willing to agree with your child’s feelings while calmly holding on to the boundary, the easier it will be for her to release her resistance and move on.

They need to be able to complain, resist, stomp their feet, cry, express their darker feelings with the assurance that they have our acceptance and acknowledgment. They need to know that they have a leader who will help them to comply with rules and boundaries in the face of their No’s, and not be intimidated by their displeasure and disagreement.

Is my attitude toward my baby’s fussing or crying one of curiosity rather than impatience and assumption?

Am I soothing my baby by understanding and meeting her needs, or shushing, jiggling and stifling her because I want the crying to stop?

Am I following my impulse to calm my child by saying, for example, “You’re okay”? Or am I staying connected and centered by acknowledging her feelings: “You bumped into the table. Ouch, that hurt you!”

Am I hurrying the feelings along, or waiting patiently for them to be fully released?

Our capacity for empathy needs to go beyond thinking of others as replicas or extensions of ourselves, to recognizing that they are distinct from ourselves. We can acknowledge the reality and legitimacy of others’ feelings without assuming responsibility for changing those feelings or giving in to their demands. Instead of rushing to shelter or console innocent and adorable babies—focusing on their obvious appearance of vulnerability and cuteness—we observe their actions to better understand their particular goals and needs, which may not be the same as ours. Empathy is not ownership.

By maintaining this difference in perspective, both between appearance and action and between ourselves and others, we marry empathy to reason and allow space for incorporating multiple angles and unknowns in our empathy calculus.

Alternate models for structuring learning interactions

Timothy Chester ponders the power of many-to-many peer networks in facilitating learning:

If there is to be a peer-based, many-to-many collaborative structure ensuring rigor and the mastery of learning outcomes, it must also be deemed authoritative and persuasive by participants. Some ways to ensure authority and persuasiveness might include the following:

  1. The teacher must drive the collaboration. While teachers engaged in many-to-many relationships with students are not the authoritative center of the collaboration, they are responsible for structuring the student experience and stewarding the learning processes that occur.
  2. The collaboration has to be bounded by a mutually agreed upon scope and charter. Compared to traditional one-to-many collaborations, many-to-many forms can appear chaotic or disorganized. In order to drive effective learning, many-to-many collaborations must operate within a set of boundaries – those things we might define as learning objectives, outcomes, standards, or rubrics. As steward of the learning process, the teacher must take responsibility for structuring the learning collaboration within a set of consistent and firm boundaries that include these structures.
  3. There must be incentives for full student participation. Critics of peer grading systems in MOOCs note that such interactions by students many times lack significant investment of time and focus – resulting in peer feedback that is spurious. Both the quality and the quantity of peer feedback within a many-to-many system have to be statistically significant in order to avoid such spuriousness.

There are many models of such networks in both formal and informal learning settings: peer review systems (e.g., Calibrated Peer Review, SWoRD peer review, Expertiza), tutoring and peer learning communities (e.g., Grockit, P2PU, Khan Academy, OpenStudy), Q&A / discussion boards (e.g., StackOverflow), online communities (e.g., DIY, Ravelry), and wikis. The challenge for formal learning environments is to foster and nurture the kind of authentic, meaningful social interactions that emerge from sustained interaction within informal communities, in the context of the top-down and often short-lived peer experiences typically associated with school classes. Yet for personalized learning to succeed on a large scale, it needs to solve this problem effectively, so that learners are not isolated but can benefit from each other’s presence, support, errors, and wisdom.