AI Powered Human Performance Improvement
Machine Learning that automatically learns from your top human experts
What if you could model human performance at an individual level and then multiply that to scale across the organization?
We built the human-machine AI training technology so you can.
Now you can know how trainees are performing inside your simulations, scenarios and performance tasks. Automatically compare their performances to your selected performance criteria and experts. Build in realtime feedback to improve performance at scale.
We built the human-machine AI training technology so you can.
Now you can know how trainees are performing inside your simulations, scenarios and performance tasks. Automatically compare their performances to your selected performance criteria and experts. Build in realtime feedback to improve performance at scale.
The Award-Winning Metacog AI API Products
Who uses metacog’s APIs to power their next generation products?
To learn more about how to integrate metacog into your products, please visit our DEVELOPER SITE
Metacog is pleased to announce that it has been acquired by CompTIA, the Computing Technology Industry Association. Metacog as a Service is now supported by CompTIA. Please see PRESS RELEASE for further details.
Build powerful data model driven capabilities into your products that know how your users are critically thinking and that continuously evaluates what they can do to improve
real-world.
Problem Solving
Metacog is a learning analytics, human-computer interface and EDM rooted startup - uniquely leveraging streaming big-data technology to measure an individual’s ability to demonstrate in-demand skills.
Metacog evaluates HOW people think, and their DEMONSTRATED competencies - not just what they have memorized. Hard to assess skills such as complex problem solving, knowledge synthesis and collaboration are now measurable.
The key is unique instrumentation libraries to collect atomic level interaction data - not just clickstream and activity levels.
Metacog evaluates HOW people think, and their DEMONSTRATED competencies - not just what they have memorized. Hard to assess skills such as complex problem solving, knowledge synthesis and collaboration are now measurable.
The key is unique instrumentation libraries to collect atomic level interaction data - not just clickstream and activity levels.
observant.
Performance Capture
The Metacog API data platform supports delivery, analysis, and reporting of authentic, performance-based assessment.
Metacog’s trainable machine learning models and real-time data analytics observe the user (learner, candidate, employee) as they work through a digital task, capturing not just their final answers, but also their behavior, process, and problem-solving approaches. All in real-time.
Metacog goes far beyond assessing and auto-scoring simple written or selected responses that primarily assess ability to memorize, not to do the job.
Metacog’s trainable machine learning models and real-time data analytics observe the user (learner, candidate, employee) as they work through a digital task, capturing not just their final answers, but also their behavior, process, and problem-solving approaches. All in real-time.
Metacog goes far beyond assessing and auto-scoring simple written or selected responses that primarily assess ability to memorize, not to do the job.
intelligent.
Performance Improvement
Metacog brings AI performance scoring to real-world scenarios.
The rubric trainable scoring engine offers multi-dimensional insights into the knowledge, skills and abilities proven more credible predictors of an individual’s competence and future performance than conventional multiple choice assessments and traditional hiring methods.
Metacog is built on an IoT platform that harnesses unique streaming analytics, and real-time continuous feedback that can be individualized and automated for providing intelligence - at the point of performance.
The rubric trainable scoring engine offers multi-dimensional insights into the knowledge, skills and abilities proven more credible predictors of an individual’s competence and future performance than conventional multiple choice assessments and traditional hiring methods.
Metacog is built on an IoT platform that harnesses unique streaming analytics, and real-time continuous feedback that can be individualized and automated for providing intelligence - at the point of performance.
Get started NOW
Integrate the power of IoT Realtime process data streams, Machine Learning and Artificial Intelligence TODAY
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Step 1 Begin emitting process data from your new and existing products
Metacog Instrumentation API
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FeatureSemantic level instrumentation JavaScript Client Library enables realtime continuous streaming of all user’s interaction process data that has technology that automatically caches data for spotty networks (such as schools) to ensure data integrity.
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Use CasesSince this atomic level data is timestamped, it is granular enough to be fed to machine learning models to visualize behavior at scale, playback through data, and generate data science rooted inferences about activity that indicate both cognitive and non-cognitive path patterns (affect) that understand not only how a user is thinking and what their competencies are but also how they are feeling (boredom, frustration, confusion, etc.). Some uses for these capabilities include adoption, social-emotional learning, collaboration, and complex problem solving assessment.
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Documentationhttps://developer.metacog.com/logger/overview
https://developer.metacog.com/logger/instrumentationguide
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Step 2 Store & Retrieve Process Data
Metacog Data Storage API
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FeatureDataRequest API allows users to retrieve the original event streams as they were logged by the widget for a set of filtered sessions.The validated events are stored in the main database, without any restrictions on the amount or age of the records. Once all the data is stored in the main database, it can be retrieved from, and processed by different services: from raw data extraction to complex Educational Data Mining processes and visualizations tools, to API's, metacog offers you a wide range of options for extracting meaningful information from your data.
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Use CasesThe retrieval-data API is a JSON-based REST API that allows users of the metacog platform to request data originated in learning objects instrumented using the instrumentation input API.
Given the large amount of data logged by each learning object, the results of a query are not returned immediately. Instead, a data-request object is created in the server to keep track of the current request, based on the filter parameters defined by the client, while the real processing is executed as a background process.
The API allows polling the data-request object in order to know the status of the background process. The client may also wait for an automatic e-mail notification to a prevalidated e-mail address, indicating that the process is finished, and the data can then be downloaded. -
Documentation
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Step 3 Visualize Your Process Data
Metacog Data Visualization API
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FeatureThis tutorial presents the VisualizationRequest API as one of the ways to retrieve information stored in the Metacog Platform by instrumented widgets, and how the Client Side Library offer helper methods to interact with the API to build aggregated reports via Javascript.
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Use CasesThe intended audience are both the Domain Experts who want to understand what kind of aggregated datasets are available out-of-the-box and the Front End Developers who need to build visually-appealing reports based on those datasets.
Once you have an instrumented widget and your learners start to use it, an amazingly huge amount of rich data will begin to being stored in the Metacog Backend.
Currently, the Metacog Platform offers two ways to retrieve information, with more services being under active development. The VisualizationRequest API allows you to retrieve aggregated datasets with different views of your data. They are useful for general data-exploration without the need to download and process the original event streams. -
Documentation
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Step 4 Record, Playback and Score models via your rubrics
Metacog Authentic Scoring Service API
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FeatureMetacog Training Toolbar is used to record and playback Training Sessions, on an already instrumented widget, and in the context of a particular Learning Task. This service provides the ability to score open ended performances via rubrics.
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Use CasesTarget Audience is learning experts who want to create Training Sessions for Learning Tasks, in order to train the system with the goal of producing automated real-time scores from Learner Sessions. A Score is an object that represents an association between a Rubric and a Training Session, and holds specific values for each dimension in the Rubric.
In scoring mode, the goal of the learning expert is to visually check the event stream of a Training Session and based on what he sees, make decisions about the values for each dimension. Also, he/she can mark the event stream with special markers (indicators) to enrich the scoring information. -
Documentation
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Step 5 Send your recommendation engine preprocessed scores for individualization
Score and Forward API
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FeatureSending scoring results in a format available by recommendation engines such as Knewton, etc.
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Use CasesSince recommendation engines are built to probabilistically adapt to where the user is in their learning progression for a given subject matter (a directed acyclic knowledge graph) then feed content or questions to their zone of proximal development, they have been limited in the past to multiple choice questions due to complexity. Metacog enables more authentic and real-world measures of competency being assessed in digital environments to be utilized to add a much deeper and wider range of learning objects capable of providing individualized responses. This allows product differentiation through enabling much more engaging content to be utilized to improve adoption and churn rates, as well as simultaneously testing complex skills.
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Documentation
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Step 6 Non-cognitive skills assessment (such as affect, persistence, collaboration and creativity)
Diagnostics API
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FeatureThe ability to markup user sessions to train a machine learning model to automatically detect behavior patterns such as boredom, frustration, WTF and engagement.
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Use CasesSince this atomic level data is timestamped, it is granular enough to be fed to machine learning models to visualize behavior at scale, playback through data, and generate data science rooted inferences about activity that indicate both cognitive and non-cognitive path patterns (affect) that understand not only how a user is thinking and what their competencies are but also how they are feeling. Some use cases for these capabilities include improving adoption, social-emotional learning, collaboration, and complex problem solving assessment.
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Documentationhttps://developer.metacog.com/logger/overview
https://developer.metacog.com/logger/instrumentationguide
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Step 7 Playback user behavior through data for audit purposes
Playback API
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FeaturePlayback through data streams.
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Use CasesSince this atomic level data is timestamped, it is granular enough to be fed to play back (as a data fed “video”) when proper instrumentation is implemented. Sessions are captured in data and can be played back on demand to support how scores were generated and to prove micro-competencies/badges were earned. These sessions are also used for scoring training to teach machine learning algorithms what constitutes desirable rubric framed behaviors and scored utilizing the scoring harness mechanism.
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Documentation
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Step 8 Try the APIs for Yourself
Visit the Developer Welcome Screen to get started!
Simply paste the PID/AID into the fields below:
Publisher Id:
9d10ead1
Application ID: c7f16e0b559f05489e2b900f52f08a99