Confronting the Challenges of a Participatory Culture (Part Five)

Today, I continue our serialization of the white paper written for the MacArthur Foundation. Today’s excerpt outlines three more of the social skills and cultural competencies we think young people need to develop if they are going to be able to fully participate in the new media landscape: Distributed Cognition, Collective Intelligence, and Judgment.

Distributed Cognition– the ability to interact meaningfully with tools that expand our mental capacities.

Challenging the traditional view that intelligence is an attribute of individuals, the distributed cognition perspective holds that intelligence is distributed across “brain, body, and world”, looping through an extended technological and sociocultural environment. Explaining this idea, Pea notes,

“When I say that intelligence is distributed, I mean that the resources that shape and enable activity are distributed in configurations across people, environments, and situations. In other words, intelligence is accomplished rather than possessed”

. Work in distributed cognition focuses on forms of reasoning that would not be possible without the presence of artifacts or information appliances and that expand and augment human’s cognitive capacities. These devices might be forms that externalize memory, such as a database, or they can be devices that externalize processes, such as the widely used spell checker. The more we rely on the capacities of technologies as a part of our work, the more it may seem that cognition is distributed.

Teachers have long encouraged students to bring scratch paper with them into math examinations, realizing that the ability to construct representations and record processes was vital in solving complex problems. If, as Clark notes, technologies are inextricably interwoven with thinking, it makes no sense to “factor out” what the human brain is doing as the “real” part of thinking, and to view what the technology is doing as a “cheat” or “crutch.” Rather, we can understand cognitive activity as shared among a number of people and artifacts, and cognitive acts as learning to think with other people and artifacts. Following this theory, students need to know how to think with and through their tools as much as they need to record information in their heads.

Gamers may be acquiring some of these distributed cognition skills through their participation in squadron-based video games. Gee suggests that in playing such games, one must form a mental map of what player and nonplayer characters are doing (nonplayer characters are characters controlled by the A.I of the game). To plan appropriately, players may not need to know what other participants know, but they do need to know what it is those participants are likely to do. Moreover, in playing the games, one may need to flip through a range of different representations of the state of the game world and of the actions that are occurring within it. Learning to play involves learning to navigate this information environment, understanding the value of each representational technology, knowing when to consult each and how to deploy this knowledge to reshape what is occurring. Instead of thinking as an autonomous problem-solver, the player becomes part of a social and technological system that is generating and deploying information at a rapid pace. Humans are able to play much more complex games (and to solve much more complex problems) in a world in which keeping track of key data and enacting well-understood computational processes can be trusted to the processing power of the computer, and they can thus focus more attention on strategic decision making.

Distributed cognition is not simply about technologies; it is also about tapping social institutions and practices or remote experts whose knowledge may be useful in solving a particular problem. According to this understanding, expertise comes in many shapes and sizes (both human and non-human). Experts can be expert practitioners, who can be consulted through such technologies as video conferencing, instant messaging, or email; some knowledge can emerge from technologies such as calculators, spread sheets, and expert systems; new insights can originate from the teacher or students or both. The key is having expertise somewhere within the distributed learning environment and making sure students understand how to access and deploy it.


Distributed Cognition– the ability to interact meaningfully with tools that expand our mental capacities.

Challenging the traditional view that intelligence is an attribute of individuals, the distributed cognition perspective holds that intelligence is distributed across “brain, body, and world”, looping through an extended technological and sociocultural environment. Explaining this idea, Pea notes,

“When I say that intelligence is distributed, I mean that the resources that shape and enable activity are distributed in configurations across people, environments, and situations. In other words, intelligence is accomplished rather than possessed”

. Work in distributed cognition focuses on forms of reasoning that would not be possible without the presence of artifacts or information appliances and that expand and augment human’s cognitive capacities. These devices might be forms that externalize memory, such as a database, or they can be devices that externalize processes, such as the widely used spell checker. The more we rely on the capacities of technologies as a part of our work, the more it may seem that cognition is distributed.

Teachers have long encouraged students to bring scratch paper with them into math examinations, realizing that the ability to construct representations and record processes was vital in solving complex problems. If, as Clark notes, technologies are inextricably interwoven with thinking, it makes no sense to “factor out” what the human brain is doing as the “real” part of thinking, and to view what the technology is doing as a “cheat” or “crutch.” Rather, we can understand cognitive activity as shared among a number of people and artifacts, and cognitive acts as learning to think with other people and artifacts. Following this theory, students need to know how to think with and through their tools as much as they need to record information in their heads.

Gamers may be acquiring some of these distributed cognition skills through their participation in squadron-based video games. Gee suggests that in playing such games, one must form a mental map of what player and nonplayer characters are doing (nonplayer characters are characters controlled by the A.I of the game). To plan appropriately, players may not need to know what other participants know, but they do need to know what it is those participants are likely to do. Moreover, in playing the games, one may need to flip through a range of different representations of the state of the game world and of the actions that are occurring within it. Learning to play involves learning to navigate this information environment, understanding the value of each representational technology, knowing when to consult each and how to deploy this knowledge to reshape what is occurring. Instead of thinking as an autonomous problem-solver, the player becomes part of a social and technological system that is generating and deploying information at a rapid pace. Humans are able to play much more complex games (and to solve much more complex problems) in a world in which keeping track of key data and enacting well-understood computational processes can be trusted to the processing power of the computer, and they can thus focus more attention on strategic decision making.

Distributed cognition is not simply about technologies; it is also about tapping social institutions and practices or remote experts whose knowledge may be useful in solving a particular problem. According to this understanding, expertise comes in many shapes and sizes (both human and non-human). Experts can be expert practitioners, who can be consulted through such technologies as video conferencing, instant messaging, or email; some knowledge can emerge from technologies such as calculators, spread sheets, and expert systems; new insights can originate from the teacher or students or both. The key is having expertise somewhere within the distributed learning environment and making sure students understand how to access and deploy it.

Applications of the distributed cognition perspective to education suggest that students must learn the affordances of different tools and information technologies, and know which functions tools and technologies excel at and in what contexts they can be trusted. Students need to acquire patterns of thought that regularly cycle through available sources of information as they make sense of developments in the world around them. Distributed intelligence is not simply a technical skill, although it depends on knowing how to use tools effectively; it is also a cognitive skill, which involves thinking across “brain, body, and world.” The term “distributed intelligence” emphasizes the role that technologies play in this process, but it is closely related to the social production of knowledge that we are calling collective intelligence.

What Might Be Done

The theory of distributed cognition informs educational research and practice when it provides a perspective for envisioning new learning contexts, tools, curricula and pedagogy, participant structures, and goals for schooling.

• Augmented reality games represent one potential application of distributed intelligence to the learning process. Klopfer and Squire developed a range of games in which students use location-aware, GPS-enabled handheld computers to solve fictional problems in real spaces. For example, in Environmental Detectives, students determine the source of an imaginary chemical leak, which is causing environmental hazards on the MIT campus. Students can use their handhelds to drill imaginary wells and take readings on the soil conditions, but to do so, they must travel to the actual location. Data drawn from the computer is read against their actual physical surroundings–the distance between locations, the slope of the land, its proximity to the Charles River–and multiple players compare notes as they seek to resolve the game scenario.

• Students in the Comparative Media Studies Program have experimented with the use of handhelds to allow tourists to access old photographs of historic neighborhoods and compare them with what they are seeing on location . Elsewhere, students travel across the battlefield at Lexington conducting interviews with historical personage to better understand their perspective on what happened there in 1775 . In each case, direct perceptions of the real world and information drawn from information appliances are mutually reinforcing. The players combine multiple information sources in completing the tasks at hand.

• Byline is an Internet-based publishing and editing tool designed to focus attention on the organizational and structural features of journalism. By providing a space for the body of the story, the byline, and the lead, this “smart tool” scaffolds students’ processes of learning to write a journalistic story. By cueing students on what to write, where to write it, and even into such journalistic values as the need to catch the reader’s attention, this specially designed program helps students to learn the conventions and values of journalism.

• A classroom designed to foster distributed cognition encourages students to participate with a range of people, artifacts, and devices. The various forms of participation composing such cognitive activity might be understood more generally as the skill of knowing how to act within distributed knowledge systems. Interested in designing learning environments that would foster such a skill, Bell and Winn describe a classroom not only in which participation requires active collaborations with people and tools that are physically present, but also with people and tools that are virtually present through, for example, video conferencing with a science practitioner, using the web to connect to a database in Japan, and using Excel spreadsheets to simulate a mass spectrometer. In such classrooms, knowing how to act within the distributed knowledge system is more important than learning content. Because content is something that can be “held” by technologies such as databases, websites, wikis, and so forth, the curricular focus is on learning how to generate, evaluate, interpret, and deploy data.

• With new technologies, new cognitive possibilities arise. Educators need to create new activities when new technologies are introduced into the classroom. If the calculator is used to add 2+2, it is the capacities of the calculator that are solving the problem; when calculation is “off loaded” onto the calculator, the student is free to solve more complex problems. The proliferation of digital technologies requires a concerted effort to envision activities that enable students to engage in more complex problem domains. For example, as a vehicle for assessing the various ways ecommerce affects the environment, students could be given the problem of comparing the environmental impact of shipping 250,000 copies of Harry Potter and the Goblet of Fire directly to individual customers rather than to bookstores. Reflecting on the intended outcome for such a comparison, Yagelski notes, “The click of the computer mouse to order a copy of Harry Potter from Amazon.com can seem a simple and almost natural act, yet it represents participation in this bewilderingly complex web of material connections that is anything but simple. And that participation contributes to the condition of our planet.” See http://english.ttu.edu/kairos/6.2/features/yagelski/crisis.htm.

Collective Intelligence– the ability to pool knowledge and compare notes with others towards a common goal

As users learn to exploit the potential of networked communication, they participate in a process that Levy calls “collective intelligence.” Like-minded individuals gather online to embrace common enterprises, which often involve access and processing information. In such a world, Levy argues, everyone knows something, nobody knows everything, and what any one person knows can be tapped by the group as a whole. We are still experimenting with how to work within these knowledge cultures and what they can accomplish when we pool knowledge. Levy argues that as a society, we are currently at an apprenticeship phase, during which we try out and refine skills and institutions that will sustain the social production of knowledge. Levy sees collective intelligence as an alternative source of power, one that allows grassroots communities to respond effectively to government institutions that emerge from the nation state or to corporate interests that sustain multinational commerce. Already, we are seeing governments and industries seek ways to “harness collective intelligence,” which has become the driving force behind what people are calling Web 2.0.

Currently, children and adults are acquiring the skills to operate within knowledge communities be interacting with popular culture. As has often been the case, we learn through play that we later apply to more serious tasks. So, for example, the young Pokémon fans, who each know some crucial detail about the various species, constitute a collective intelligence whose knowledge is extended each time two youth on the playground share something about the franchise.

Such knowledge sharing can assume more sophisticated functions as it moves online. For example, Matrix fans have created elaborate guides which help them track information about the fictional Zion resistance movement featured in the film. Young people are playing with collective intelligence as they participate in the vast knowledge communities that emerged from the online game I Love Bees. Some estimate that as many as 3 million players participated in history’s most challenging scavenger hunt. After working through puzzles so complicated they mandated the effective collaboration of massive numbers of people with expertise across a variety of domains and geographic locations, players gathered clues by answering more than 40,000 payphone calls across all 50 U.S. states and eight countries. They then fed those clues back into online tools designed to support large-scale collaboration for all players to deconstruct and analyze. If players were unfamiliar with how to participate in the community, other players would train them in the necessary skills. In another example, fans of the television show Survivor have used the Internet to track down information and identify the names of contestants before they are announced by the network. They have also used satellite photographs to identify the location of the Survivor base camp despite the producer’s “no fly over” agreements with local governments. These knowledge communities change the very nature of media consumption–a shift from the personalized media that was central to the idea of the digital revolution toward socialized or communalized media that is central to the culture of media convergence.

As players learn to work and play in such knowledge cultures, they come to think of problem-solving as an exercise in teamwork. Consider the following postings made by members of The Cloudmakers, a team formed in a game similar to I Love Bees:

The solutions do not lie in the puzzles we are presented with, they lie in the connections we make, between the ideas and between one another. These are what will last. I look down at myself and see that I, too, have been incorporated into the whole, connections flowing to me and from me, ideas flowing freely as we work together, as individuals and as a group, to solve the challenges we are presented with. The solution, however, does not lie in the story. We are the solution.

* * *

The 7500+ people in this group … we are all one. We have made manifest the idea of an unbelievably intricate intelligence. We are one mind, one voice … made of 7500+ neurons… We are not one person secluded from the rest of the world… We have become a part of something greater than ourselves.

Indeed, these groups have been drawn from playing games to confronting real-world social problems, such as tracking campaign finances or trying to solve local crimes, as they develop a new sense of self-confidence in their ability to tackle challenges collectively, challenges that, as individuals, they would be unable to face.

This focus on teamwork and collaboration is also, not coincidentally, how the modern workplace is structured–around ad-hoc configurations of employees, brought together because their diverse skills and knowledge are needed to confront a specific challenge, then dispersed into different clusters of workers when new needs arise. Doctorow has called such systems “ad-hocracies,” suggesting that they contrast in every possible way with prior hierarchies and bureaucracies. Our schools do an excellent job, consciously or unconsciously, teaching youth how to function within bureaucracies. They do almost nothing to help youth learn how to operate within an ad-hocracy.

Collective intelligence is increasingly shaping how we respond to real-world problems. On August 29, 2005, Hurricane Katrina tore apart the levee that protected New Orleans from Lake Pontchartrain and the Mississippi River. Not only was the ability of ordinary citizens to share self-produced media and information pivotal in shaping the view of the situation for the outside world (thereby bringing in more relief funds), but it allowed for those affected by the disaster to effectively assist one another. After Jonathan Mendez’s parents evacuated from Louisiana to his home in Austin, Texas, he was eager to find out if the floods had destroyed their home in Louisiana. Unfortunately for him, media coverage of the event was focused exclusively on the most devastated parts of New Orleans, with little information about the neighborhood where his parents lived. With some help from his coworker, they were able, within a matter of hours, to modify the popular “Google maps” web service to allow users to overlay any information they had about the devastation directly onto a satellite map of New Orleans. Shortly after making their modification public, more than 14,000 submissions covered their map. This allowed victims scattered throughout the United States to find information about any specific location–including verifying that the Mendez’s house was still intact.

Unfortunately, most contemporary education focuses on training autonomous problem solvers and is not well suited to equip students with these skills. Whereas a collective intelligence community encourages ownership of work as a group, schools grade individuals. Whereas Jonathan Mendez was admired for having appropriated Google’s mapping web service , students in school are often asked to swear that what they turn is their “own work.”

Leadership within a knowledge community requires the ability to identify specific functions for each member of the team based on his or her expertise and to interact with the team members in an appropriate fashion. Teamwork involves a high degree of interdiscipline–the ability to reconfigure knowledge across traditional categories of expertise. In early February 2004, Eric Klopfer, an MIT professor of urban studies and planning, along with a team of researchers from the Education Arcade, conducted “a Hi-Tech Who Done It” for middle-school youth and their parents inside the Boston Museum of Science. Teams of three adult-child pairs were given handhelds to search for clues of the whereabouts and identity of the notorious Pink Flamingo Gang, who had stolen an artifact and substituted a fake in its place. Thanks to museum’s newly installed wi-fi network and the players’ location-aware handhelds, each gallery offered the opportunity to interview cyber-suspects, download objects, examine them with virtual equipment, and trade their findings. Each parent-child unit was assigned a different role– biologists, detectives, or technologists–enabling them to use different tools on the evidence they gathered. This is simply one of many recent cooperative games that assigned distinct roles to each player, giving each access to a different set of information, and thus creating strong incentives for them to pool resources.

Schools, on the other hand, often seek to develop generalists rather than allowing students to assume different roles based on their emerging expertise. The ideal of the Renaissance man was someone who knew everything or at least knew a great deal about a range of different topics. The ideal of a collective intelligence is a community that knows everything and individuals who know how to tap the community to acquire knowledge on a just-in-time basis. Minimally, schools should be teaching students to thrive in both worlds: having a broad background on a range of topics, but also knowing when they should turn to a larger community for relevant expertise. They must know how to solve problems on their own but also how to expand their intellectual capacity by working on a problem within a social community. To be a meaningful participant in such a knowledge culture, students must acquire greater skills at assessing the reliability of information, which may come from multiple sources, some of which are governed by traditional gatekeepers, others of which must be crosschecked and vetted within a collective intelligence.

What Might Be Done

Schools can deploy aspects of collective intelligence when students pool observations and work through interpretations with others studying the same problems at scattered locations. Such knowledge communities can confront problems of greater scale and complexity than any given student might be able to handle.

• Scientists in fields requiring simple, yet extensive, data analysis tasks could partner with junior high teachers to have students help collect or analyze real data. Eelgrass is both the most abundant seagrass in Massachusetts and one of the most ecologically valuable marine and estuarine habitats in North American coastal waters. The MIT Sea Grant College Program developed a project where students in different schools learn to cultivate eelgrass and collaboratively share data regarding the levels of nitrates, oxygen, and so forth in affected habitats through the project website: http://seagrantdev.mit.edu/eelgrass/

• Sites such as ning.com offers nonprogrammers tools for rapidly creating social web applications that allow users to interact with and share information with one another. For example, a Mandarin teacher could easily create an online travel guide in which students (potentially nationwide) would each contribute write-ups of interesting sites in their local areas that would be of interest to visitors from China.

• Students taking civic classes might be encouraged to map their local governments using a Wikipedia-like program, bringing together names of government officials, reports on government meetings, and key policy debates. The information would be accessible to others in their own communities. They might also compare notes with students living in other parts of the country to identify policy alternatives that might address problems or concerns in their communities.

Judgment– the ability to evaluate the reliability and credibility of different information sources

Although it is exciting to see players harness collective intelligence to successfully solve problems of unprecedented complexity, this process also involves a large number of errors. Misinformation emerges, is worked over, refined or dismissed before a new consensus emerges. We are taught to think of knowledge as a product, but within a collective intelligence, knowledge is also always in process. As such, one must understand where one is in the vetting process to know how much trust to place in any given piece of information. In a game such as I Love Bees, these mistakes are generally of little consequence and often serve as a source of amusement than anything else. As these same technologies are employed in understanding world events, we must better understand the strengths and limitations of these new practices of knowledge production.

For example, one key technology in online collective intelligence communities is a wiki. Although it may be possible for a small group of individuals to contribute erroneous information, wiki enthusiasts argue that giving all members of a larger community the ability to correct any mistakes will ultimately lead to more accurate information. In many cases, this concept has proved surprisingly effective. In one study, Nature magazine compared the accuracy of articles in Wikipedia, an enormous online encyclopedia constructed entirely through the efforts of volunteers using wiki technologies, with equivalent articles in Encyclopedia Britannica. They concluded the accuracy levels of the two to be roughly the same. (This wasn’t because Wikipedia was flawless, but rather because even sources such as Encyclopedia Britannica are flawed). Students must be taught to read both sources from a critical perspective.

The Nature article also identifies that wikis perform best when a large number of participants are actively using the technology to correct mistakes. Whereas the Wikipedia article on global warming enjoys more than 10,000 authors, each passionately committed to ensuring the accuracy of its content, the biographical article on John Seigenthaler cited him as having a possible involvement in the assassinations of Robert F. Kennedy and John F. Kennedy for a period of 132 days before someone corrected it. Given the disparity in the accuracy of different articles, students need to develop an intuitive understanding of how the contents of a wiki are produced by participating in their construction, and then actively reflecting on the different possibilities for inaccuracies.

In truth, schools should always teach students critical thinking skills for “sussing out” the quality of information, yet historically schools have had a tendency to fall back on the gatekeeping functions of professional editors and journalists, not to mention of textbook selection committee and librarians, to ensure that the information is generally reliable. Once students enter cyberspace, where anyone can post anything, they need skills in evaluating the quality of different sources, how perspectives and interests can color representations, and the likely mechanisms by which misinformation is perpetuated or corrected. We need to balance a trust of traditional gatekeeping organizations (Public Television, Smithsonian, National Geographic, for example) with the self-correcting potential of grassroots knowledge communities. Traditional logic would suggest, for example, that 60 Minutes, a long-standing network news show, would be more accurate than a partisan blog, but in fall 2004, bloggers working together recognized flaws in the evidence that had been vetted by the established news agency. As Gillmore notes, we are entering a world in which citizen journalists often challenge and sometimes correct the work of established journalists, even as journalists debunk the urban folklore circulated in the blogging community.

Misinformation abounds online, but so do mechanisms for self-correction. In such a world, we can only trust established institutions so far. We all must learn how to read one source of information against another; to understand the contexts within which information is produced and circulated; to identify the mechanisms that ensure the accuracy of information as well as realizing under which circumstances those mechanisms work best. Confronted with a world in which information is unreliable, many of us fall back on cynicism, distrusting everything we read. Rather, we should foster a climate of healthy skepticism, in which all truth claims are weighed carefully, but there is an ethical commitment to identifying and reporting the truth.

Students are theoretically taught in school how to critically assess the pros and cons of an argument. In an increasingly pervasive media environment, they also must be able to recognize when arguments are not explicitly identified as such. The new mediated landscape of mainstream news sources, collaborative blog projects, unsourced news sites, and increasingly sophisticated marketing techniques aimed at ever-younger consumers demand that students be taught how to distinguish fact from fiction, argument from documentation, real from fake, and marketing from enlightenment.

“To be a functioning adult in a mediated society, one needs to be able to distinguish between different media forms and know how to ask basic questions about everything we watch, read, or hear,” says Thoman and Jolls.

“Although most adults learned through English classes to distinguish a poem from an essay, it is amazing how many people do not understand the difference between a daily newspaper and a supermarket tabloid, what makes one website legitimate and another one a hoax, or how advertisers package products to entice us to buy”

.

Even when media content has been determined credible, it is vital for students to also identify and analyze the perspective of the producer: who is presenting what to whom, and why. Existing media literacy materials excel in examining the forces behind controversial media properties, particularly provocative visuals, its intentions, and effects.

As Buckingham notes, children may lack some of the core life experiences and basic knowledge that might help them to discriminate between accurate and inaccurate accounts:

[T]here is as yet relatively little research about how children make judgements about the reliability of information on the Internet, or how they learn to deal with unwelcome or potentially upsetting content. Children may have more experience of these media than many adults, but they mostly lack the real-world experience with which media representations can be compared; and this may make it harder for them to detect inaccuracy and bias”

Reviewing the literature on how children make sense of online resources, Buckingham finds that students lack both knowledge and interest in assessing how information was produced for and within digital environments: “

Digital content was ‘often seen as originating not from people, organisations, and businesses with particular cultural inclinations or objectives, but as a universal repository that simply existed ‘out there'”

. Other studies find that children remain unaware of the motives behind the creation of websites, have difficulty separating commercial from noncommercial sites, and lack the background to identify the sources of authority behind claims made by website authors.

As this discussion has suggested, judgment might be seen as part of our existing conception of literacy–a core research skill of the kind that has long been fundamental to the school curriculum. Yet, this discussion also underscores that judgment operates differently in an era of distributed cognition and collective intelligence. Judgment requires not simply logic, but also an understanding of how different media institutions and cultural communities operate. Judgment works not simply on knowledge as the product of traditional expertise, but also on the process by which grassroots communities work together to generate and authenticate new information.

What Might Be Done

Judgment has long been the focus of media literacy education in the United States and around the world as students are encouraged to ask critical questions about the information they are consuming.

• The Boston-based Youth Voice Collaborative has developed an exercise that gives students a range of news stories and asks them to rank the stories according to traditional news standards. The process is designed to encourage students to understand what criteria journalists use to determine the “news value” of different events and to encourage students to express their own priorities about what information matters to them and why.

• http://news.google.com aggregates articles from thousands of news sources worldwide. This allows users to compare and contrast the framing of a single issue from different media sources. Students are encouraged to read several articles closely, underlining words they believe might shape how readers understand and feel about what they are reading.

• The New Medial Literacies project at MIT has developed a set of activities to involve students in understanding how representations of “truth” and “fiction” vary in different media forms and, therefore, how different techniques must be learned, and choices must be made, when seeking to manipulate meanings by altering representations. For example, in an image manipulation activity, students search for an image of an event (such as the March on Washington, the Kennedy assassination) and are taught how to change the picture in a way that changes the meaning. By manipulating images, students become familiar with the ways images may be altered to persuade and influence. In developing this manipulation skill, students are encouraged to think about why image, sound, and textual representations are altered and what that means to them as consumers, voters, and citizens.

• A growing number of teachers are using the Talk Pages for contested Wikipedia entries as illustrations of the types of questions one might want to ask about any information and the processes and criteria by which disputes about knowledge might be resolved.

• Tools such as lijit.com allow readers of a website to alert friends who subsequently read the same website that its content may be suspect. Students might also be encouraged to take advantage of sites such as snopes.com, which regularly report on frauds and misinformation circulating online and provide good illustrations of the ways that one could test the credibility of information

Comments

  1. sudarshan goala says:

    i m an NGO ACTIVIEST AT thr same time state resource person of Right to information Act.2005.(INDIA). My activicty is maingly confine with providing training. so i will be delight if u provide some relevent information for me on participatory learining.