Maximizing Human Potential

There is a disconnect between what is assessed in education and what is relevant throughout life. There are few resources, in or out of the classroom, for connecting assessments with feedback that can predict or improve life-outcomes. Our solution is to implement meta-learning through naturalistic educational interventions.

The Socos Philosophy

There exists an enormous amount of data on how students learn and workers perform. While there is an increasing awareness of the importance of skills like collaboration and creative problem solving, little is done to reinforce these traits. At Socos we take naturalistic data as the basis for our assessments. We close the educational loop by providing relevant feedback to educators on what they can do to improve life outcomes.

We are interested in fostering meta-learners, individuals who are activity in their own learning processes instead of just passively absorbing another’s teachings. These self-motivated students exhibit increases in metrics actually predictive of life outcomes like motivation, creativity, self-regulation, and metacognitive ability. Our research shows that anyone can be trained to become a meta-learner, through the combination of naturalistic assessments, just-in-time feedback, and a focus relevant life-outcomes.


Emotional Intelligence

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.

Socio-Economic Status

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.

Health Implications

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.

Meta-Learning

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.

Human Capital

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 which 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 that demonstrates that how students take notes over several weeks of a course is highly reflective of self-regulated learning aspects . Socos will be using the demonstrated importance of human participation in education to further the goal of life-long outcomes.

Naturalistic Interventions

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 current integration of 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.






"Vivienne Ming, PhD and Norma Ming, PhD at SXSW Edu 2014"

Keeping the Promise of Educational Technology

Services

One of the most fundamental challenges in teaching is peering inside students' heads and figuring out what they're thinking. While education is a field rich with data, obtaining high-quality data and processing them meaningfully and efficiently remains difficult. Whether in formal classes, individualized tutoring, or casual web queries, learners continually generate questions, comments, proposals, discussions and a multitude of other assessable work.

These constitute valuable assessment data for informing instructors’ professional judgment, but systematically analyzing them across multiple students and time-points demands attention and resources beyond what most teachers can spare. The quantity of possible data to track defies ambition. The vast majority is lost to any broader perspective for instructors, educational leaders, and decision-makers. Lessons go untried, assessments unvalidated, population trends undetected and teaching opportunities missed. Rather than constantly designing and administering new tests, education needs tools which can actually make intelligent use of existing data.


Kindersight

Assessing the Linguistic Environment of Kindergarteners

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 rightfully concerned about measuring children’s learning, their design and use 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.

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College Learners

Innovative Competency-Based Online College

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 are then given a pass or fail by an unbiased panel of assessors...

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Online Students

Online Student Discussion Predictive of Grades

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).

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Research

Since 2010 Socos has researched and developed technology capable of predicting outcomes based on naturalistic data. We are now focused on turning commonplace learning experiences directly into assessments which improve meta-learning.





Publications

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    Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., & Rumble, M.

    (2012)

    Defining twenty-first century skills. In Assessment and teaching of 21st century skills (pp. 17-66). Springer Netherlands.

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    Chen, E., & Miller, G. E.

    (2012)

    “Shift-and-Persist” Strategies Why Low Socioeconomic Status Isn’t Always Bad for Health. Perspectives on Psychological Science, 7(2), 135-158.

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    Cohen, G. L., & Sherman, D. K.

    (2014)

    The psychology of change: Self-affirmation and social psychological intervention. Annual review of psychology, 65, 333-371.

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    Ming & Ming

    (2012)

    Predicting Student Outcomes from Unstructured Data. UMAP2012.

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    Dweck, C.

    (2006)

    Mindset: The new psychology of success. Random House LLC.

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    Bumbacher & Ming

    (2012)

    Pitch-sensitive components emerge from hierarchical sparse coding natural sounds. ICPRAM2012

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    Geiser, S., & Studley, W. R.

    (2002)

    UC and the SAT: Predictive validity and differential impact of the SAT I and SAT II at the University of California. Educational Assessment, 8(1), 1-26.

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    Gertler, P., Heckman, J., Pinto, R., Zanolini, A., Vermeersch, C., Walker, S., ... & Grantham-McGregor, S.

    (2014)

    Labor market returns to an early childhood stimulation intervention in Jamaica. Science, 344(6187), 998-1001.

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    Ming, V.L. & Holt

    (2009)

    Evidence of efficient coding in human speech perception. JASA 129, Num. 3: 1312-1321.

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    Glogger, I., Schwonke, R., Holzäpfel, L., Nückles, M., & Renkl, A.

    (2012)

    Learning strategies assessed by journal writing: Prediction of learning outcomes by quantity, quality, and combinations of learning strategies. Journal of educational psychology, 104(2), 452.

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    Grant, A. M.

    (2008)

    Does intrinsic motivation fuel the prosocial fire? Motivational synergy in predicting persistence, performance, and productivity. Journal of applied psychology, 93(1), 48.

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    Karoly, L. A., Kilburn, M. R., & Cannon, J. S.

    (2006)

    Early childhood interventions: Proven results, future promise (Vol. 341). Rand Corporation.

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    Kidd, C., Palmeri, H., & Aslin, R. N.

    (2013)

    Rational snacking: Young children’s decision-making on the marshmallow task is moderated by beliefs about environmental reliability. Cognition, 126(1), 109-114.

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    Luhmann, M., Hofmann, W., Eid, M., & Lucas, R. E.

    (2012)

    Subjective well-being and adaptation to life events: a meta-analysis. Journal of personality and social psychology, 102(3), 592.

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    Ming, N. C., & Ming, V.

    (2012 September)

    Automated predictive assessment from unstructured student writing. In DATA ANALYTICS 2012, The First International Conference on Data Analytics (pp. 57-60).

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    Mischel, W., Ayduk, O., Berman, M. G., Casey, B. J., Gotlib, I. H., Jonides, J., ... & Shoda, Y.

    (2010)

    ‘Willpower’over the life span: decomposing self-regulation. Social Cognitive and Affective Neuroscience.

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    Pellegrino, J. W., & Hilton, M. L. (Eds.).

    (2013)

    Education for life and work: Developing transferable knowledge and skills in the 21st century. National Academies Press

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    Roberts, B. W., Kuncel, N. R., Shiner, R., Caspi, A., & Goldberg, L. R.

    (2007)

    The power of personality: The comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes. Perspectives on Psychological Science, 2(4), 313-345.

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    Rothstein, J. M.

    (2004)

    College performance predictions and the SAT. Journal of Econometrics, 121(1), 297-317.

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    Wiliam, D.

    (2011)

    What is assessment for learning?. Studies in Educational Evaluation, 37(1), 3-14.

The three co-founders of Socos have combined their expertise

in Cognition, Education and Machine Learning.

About Us

The Socos team all have a very personal relationship all aspects of education. From peer-reviewed research, teaching, and algorithmic predictions of student success, each member brings expertise to the problem of closing the education gap and improving real-world outcomes.

Vivien Ming
Vivienne Ming, PhD

Executive Director

Dr. Vivienne Ming, named one of 10 Women to Watch in Tech in 2013 by Inc. Magazine, is a theoretical neuroscientist, technologist and entrepreneur. She served as chief scientist at Gild, an innovative startup that applies machine learning to predict optimal candidates for technology jobs, and to bring meritocracy to job markets. She joined Gild in 2012 to oversee R&D and IP development, solving problems in data mining, text analysis, cognitive modeling and algorithm development. Dr. Ming also co-founded her own cutting-edge edtech startup, Socos, with her wife, Norma. She is a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience pursuing her research in neuroprosthetics. In her free time, Dr. Ming also explores augmented cognition using technology like Google Glass and has been developing a predictive model of diabetes to better manage blood glucose levels.

Ming
Norma Ming, PhD

Director of Learning Design

Dr. 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 Didstrict’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.

Engin Bumbacher
Engin Bumbacher

Director of Research

Engin 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. Engin 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.







Vivien Ming
Brandon Istenes

Software Engineer

Brandon is a computer whisperer based out of beautiful San Francisco. He commands the computers to do Socos’ bidding, and they seem to listen to him. After earning a degree in Computational Mathematics (Minor Physics), he began making maps for A Very Big Corporation, which he left just before joining Socos. In the meantime he started a math meetup called SF Amateur Mathematicians and has been working on a business to help fund reforestation. In his free time he practices and teaches dance and co-organizes a big dance event.

Ming
Robin Peter Zander

Project Management & Behavior Design

Robin has spent his professional life studying cognition, development, and learning. In private practice he has worked hands-on with special needs children around the world to expedite the learning process. Prior to joining Socos, he advised start-ups on strategic development and consulted to improve organizational functioning for HP, Intel, Xerox, and other Fortune 500s. Robin works closely with the Stanford Persuasive Technology Lab studying tools to maximize lifelong health outcomes. Robin is author of several books on the learning process. He obtained his B.A. from Reed College in Behavioral Psychology.

Engin Bumbacher
David Ortiz

Front End Web Developer Intern

David works with Balsamiq, HTML 5, CSS3, Parallax, Twitter-Bootstrap, WordPress, PhP, JavaScript, JQuery, MySQL, Google Cloud Platform & Git/GitHub. David loves to learn, and to stay current with the new economy, he has completed a Web Development boot camp at Coding Dojo. David received a B.A. from Cal State San Marcos (CSUSM) in Visual and Performing Arts and Technology. While at CSUSM, David studied Japanese language and then immersed himself in Japanese culture, specifically Sumi-e painting and Japanese cinema (1949-1987) at Kansai Gaidai University in Hirakata City, Japan.

"At Socos we are developing

and implementing technology which turns learning experiences
directly into predictive analytics focused on developing autodidactic
centurylearning focused on 21st skills".

CONTACT US

Learn more about Consulting services for educational datamining Developing a Cognitive Analytics plug-in for your course or LMS Designing adaptive learning systems

Recent Talks

* Lawrence Berkeley Labs
* LinkedIn
* SXSWEdu2014 keynote
* Pearson Foundation's "Be the Source" interviews
* EdLab Groundbreakers vialogue

Current Projects

* Bridging the Word Gap (US Prez.)
* KinderSight
* College Learners
* UT Austin
* Washington College

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.