In the oft-cited marshmallow study, a child’s early-life ability to delay gratification has been shown to be predictive of life-long measures of success. However, such interventions, when poorly designed, can have contrary effects. In a lesser-known variant of the same study, prior to being given their first marshmallow the children were promised crayons or similar enticement by an adult who did not deliver on the promise. In each case of this reneging on a promise, children ate their first marshmallow right away. Children were trained to take what was available because they could not rely on a future promise, which has implications for the future success of those children.
It has been repeatedly demonstrated in scientific studies that small adjustments can create life-long changes. A famous example is a study of families of severely underprivileged toddlers in Kingston, Jamaica. Families were identified in a government program, and once each month for three years the parents were educated in simple nutrition, social and motivational skills. Twenty years later the children from those families were studied by a group of economists and found to be indistinguishable from more wealthy populations. Those simple interventions were able to effectively erase the fact that those children came from impoverished backgrounds.
Similar impacts from low-grade interventions were found in addressing health problems of children from families of low socioeconomic status in the United States. Eight years after the interventions, the youth who participated had significantly fewer health problems than controls. There is even more potential for impact when processes are triggered that are relevant for successful learning. In fact, the reason why these interventions are so effective is that they target personality characteristics such as persistence, motivation, and mindset, which prove to be key to development and life-outcomes.
Characteristics like the ability to delay gratification in the marshmallow study are important aspects of meta-learning. These learnable skills include creative problem solving, critical thinking, and collaboration, and are important to aspects of life. Students and professionals would benefit if these complex skills were studied in schools and taught in the workplace. Unfortunately, educational systems fail to teach to these goals, instead focusing on training domain-specific knowledge under the assumptions that these more complex skills will come about naturally. Specific knowledge is valuable, but in the modern era information is abundant and relevant knowledge changes very quickly. What actually matters most is the ability to learn whatever new information may be important, and to use it productively.
Education requires direct human participation. Parents, caregivers, colleagues, and teachers all play an important role in a learner’s development. This includes education in nurturant parenting, implicit education that fosters a growth mindset, and positive framing and affirmation. Socos is building on pre-existing research, but mainly in the realm of "hand analysis" of complex data. One study demonstrates that how students take notes over several weeks of a course is highly indicative of self-regulated learning skills. Socos will be using the demonstrated importance of human participation in education to further the goal of life-long outcomes.
Technology is sufficiently advanced that algorithms can accurately predict lifetime outcomes. When that information is provided recursively to the students and teachers it becomes actionable. However, the currently integrated technological assessments occur in tightly regulated environments. While they might provide flexibility in their assessment strategies, they can only do so by offloading standardization onto the environment. At Socos we take naturalistic student experiences and perform predictive assessment on lifelong outcomes.
Interest in improving early childhood learning across school and home settings is colliding with movements to increase standardized testing at ever younger ages. While testing proponents are rightly concerned about measuring children’s learning, tests carry many problems. Tests are valid only for the population and purpose for which they were designed, eliminating cultural bias from tests is extremely difficult, and tests are often designed as sequestered experiences stripped from authentic contexts.
Socos is in the early stages of a project with a new, competency-based online college, which Wired Magazine has named among the most innovative organizations in the world. This organization has taken an entirely new approach to self-directed learning. There are no grades or professors. Instead, progression through the curriculum is driven entirely by competency. Students work digitally with coaches who support students for the duration of their projects. Students’ work is then given a pass or fail by an unbiased panel of assessors...
Socos has conducted and published research based on online class discussion data at one of the world’s largest universities. Socos partnered with this university and subsequently published multiple journal articles describing how grades in a course could be successfully predicted. In academic studies, Socos has successfully predicted final grades by analyzing unstructured student text in online discussion forums, which also yielded preliminary topic maps that can be used in student thinking (Ming & Ming, 2012).
Managing PartnerDr. Vivienne Ming, named one of 10 Women to Watch in Tech by Inc. Magazine, is a theoretical neuroscientist, technologist and entrepreneur. She is the co-founder and Managing Partner of Socos. Previously, Dr. Ming was Chief Scientist at Gild, an innovative startup that builds better companies by unleashing human potential in their workforce using machine learning. She is a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience pursuing her research in cognitive prosthetics. In her free time, Dr. Ming also explores augmented cognition using technology like Google Glass and has been developing predictive models of diabetes and bipolar disorder. She sits on the boards of StartOut and Our Family Coalition, and speaks on issues of LGBT inclusion and gender in technology. She lives in Berkeley with her wife and their two children. Her work and research has received extensive media attention including the New York Times, NPR, Nature, O Magazine, Forbes, and The Atlantic.
Director of Learning DesignDr. Norma Ming is a learning scientist and educational technology thought leader who works at the intersection of research and development, policy, and practice. A former high school and university educator, she is now Supervisor of Research in the San Francisco Unified School District’s Research, Planning, and Accountability department, where she coordinates results-oriented research to help the district implement its strategic plan. She merges a pragmatic understanding of the teaching enterprise with a long-term, systemic vision of how research can illuminate and policy can facilitate better learning. Previously, she taught as a lecturer in Education in Math, Science, and Technology at UC Berkeley’s Graduate School of Education. She earned an A.B. with honors in chemistry at Harvard University and a Ph.D. in cognitive psychology in the Program for Interdisciplinary Educational Research at Carnegie Mellon University.
Director of ResearchEngin is devoted to the development of the company’s core cognitive modeling and predictive analytics technology. He did his master’s thesis project at the Redwood Center for Theoretical Neuroscience at UC Berkeley under the supervision of Dr. Vivienne Ming, applying and further developing elaborate models of information processing to human speech and music. Mr. Bumbacher earned his master’s degree with honors in Neural Systems and Computation from the Swiss Federal Institute of Technology Zurich and the Institute of Neuroinformatics, both researching in the field of theoretical neuroscience and exploring models of collective intelligence through implementation of interactive flocking algorithms to control computer sound synthesis and 3D sound positioning. Prior to that, he finished his B.S. with honors in Physics at the same university.
Computer WhispererBrandon is a software engineer specializing in data systems. After earning a degree in Computational Mathematics (Minor Physics), he was professionally involved in digital cartography until joining Socos. In his free time he practices and teaches dance, runs a math club called SF Amateur Mathematicians, and organizes events.
App AdmiralWorking the interweb mines since 1999... bike riding, good coffee drinking, go playing coder who likes soldering things into existence.
Chief Operations OfficerKelsey is Socos' Chief Operations Officer and executive assistant to Vivienne Ming. Previously, she worked as an office administrator at LINES Dance Center. She is employed part-time as a professional ballet dancer in San Francisco and has worked with ballet companies in Princeton, NJ, and Los Angeles. Kelsey has also taught dance in the Bay Area and is always seeking new ways to unite technology and movement for greater ease in learning.
Coding CadetAfter working for a variety of SaaS start-ups in San Francisco, Jess is excited to be helping Socos to bring the best of childhood development research to every parent's fingertips. When Jess isn't coding, she's stretching her culinary muscles as an avid baker and general food enthusiast.
Machine Learning Intern 2016Sanjeev is a senior at UC Berkeley pursuing an EECS degree. He began programming in high school, because he wanted to be Tony Stark and build Jarvis. Now, he builds web apps and is finally dabbling in machine learning and artificial intelligence. In his spare time, he enjoys long-distance running, playing electric guitar, and cooking.
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Socos currently has two main areas of focus. Through our project Kindersight we are focused on assessing and improving the linguistic environment of kindergarteners. In our work with several different colleges and online universities we are implementing technology to predict outcomes and providing relevant feedback that can maximize learning potential. Download the Socos White Paper