An extremely visible world demands new sensemaking
Information proliferation will continue, exacerbating the burden on families, learners, educators, and decision-makers to make sense of vast amounts of data. New tools for visualizing data will require new skills in discerning meaningful patterns. Social media and collaborative tools will leave “data trails” of people’s online interactions — including contributions to group activities, inquiries and searches, skills, digital resources, and preferences (such as playlists, buddy lists, and topics tracked) — and social networks. At the same time, sensors and global positioning systems in devices such as cell phones and car navigation systems will be able to capture location-based information along with health and environmental data. Together these tools will provide a robust, visible “data picture” of our lives as citizens, workers, and learners. Families, learners, educators, and decision-makers will need to become sophisticated at pattern recognition in order to create effective and differentiated learning experiences and environments. Furthermore, new skills in collective sensemaking will redefine forms of knowledge, knowing, and assessment.
- How do ubiquitous, visible data impact teaching, learning, and the assessment of learning experiences?
- How can we use data to enhance human decisions rather than automate them?
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New technologies for sensing, aggregating, and displaying information will demand new methods of sensemaking—interpreting and gaining meaning from abundant data. This deluge of data will take many forms:
- Biometric (such as health status data, fingerprints and retinal prints),
- Cognitive (such as collaboration histories in wikis or online games),
- Neurological (brain imaging data),
- Genetic (dna histories),
- Online personae (avatars and reputation profiles),
- Tagging (such as keywords on flickr or delicious),
- Taste trails (as documented in applications like Last fm).
The challenge is no longer finding information but making it meaningful. Several strategies for sensemaking will emerge:
- Mashups will blend multiple data sets to reveal discern underlying stories (for example, websites that use Google maps to display health status and poverty rates in a particular geography).
- Increasingly complex visualizations and simulations will help convey the meaning of abundant and diverse data through multi-sensory modes such as color, 3D spatial rendering, and even sound.
- Pattern recognition and play will merge as gaming expands far beyond the world of entertainment.
- Video games and collaborative alternative reality games (that leverage group knowledge and expertise) will become platforms for learning, especially for understanding dynamic systems when variables change and uncertainties are introduced into problem solving.
Reductionist metrics (such as an average score on a standardized test) will prove inadequate for accurate evaluation of performance—the standards are simply too static and often narrowly defined to encompass all the various forms and kinds of data being generated. Open-source assessment will prove much more powerful, incorporating multiple forms of capital and leveraging collective assessment platforms, such as reputation profiles and other forms of peer assessment and recognition of mastery.
All this will lead to a quantified self—the self represented and understood through various data trails. This quantified understanding will extend to schools and educational systems initially through the transparency afforded by social media applications. The quantified self opens the opportunity for differentiated learning, where the learner can forge a personal path through the morass of tools, information sets, and augmented experiences. What distinguishes a person won’t be their performance in a particular subject or through a particular method but rather their unique patterns across an unbounded range of subjects and methods.
Implications for Learning
Educators and learners will need to learn how to participate effectively in an abundant data world. New ways of seeing, knowing, and communicating will redefine learning environments, roles, and even forms of knowledge, knowing, and assessment.
- Perhaps most significantly, abundant data and the emerging opportunities for sensemaking create the opportunity for learners to become more self-reflective and aware of their learning.
- As it becomes easier to leave personal data trails (voluntary and automated self-documentation) about performance, preferences, and interactions, learners will have an ongoing reflection of themselves in the learning process.
- Educators and various learning agents will also have more transparency to reflect on their impact on and experience with learners.
Students and educators will need training to be able to participate in this world, to engage in various forms of sensemaking and help create new ones. Working with visualization tools, contributing to reputation economies, gaming, and moving through the metaverse (the fusion of the World Wide Web and the physical world) will be essential skills for life in the next decade and beyond.
Many students are worlds ahead of their educators in navigating these domains, but education must wrestle with questions about engaging in these practices in meaningful ways.