Steve Polyak, Ph.D.

Steve Polyak, Ph.D.

Iowa City-Cedar Rapids Area
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Publications

  • WATCH-PD: Detecting Early-Stage PD Status using Feature Engineering and Machine Learning in Remote Sensor-Based Assessments

    MOVEMENT DISORDERS 37, S3-S3

    Wearable technologies produce real-time high-dimensional sensor data that track behavior, physiology, and mobility. Feature engineering and machine learning routines can produce disease and behaviorally relevant digital endpoints when applied to these rich data sources. Together, wearable technologies and data science offer opportunities to remotely monitor disease progression in patients with greater frequency, reliability, and objectivity.

  • Computational Psychometrics Approach to Holistic Learning and Assessment Systems

    Frontiers in Education

    Learning and assessment systems have grown and taken shape to incorporate concepts from both models for assessment and models for learning. In this paper we argue that a third dimension is necessary. Not only is it important to understand what the capabilities of a learner are, and how to grow and expand these capabilities, but we must consider where the learner is headed; we need to consider models for navigation. This holistic perspective of learning and assessment systems is encapsulated in…

    Learning and assessment systems have grown and taken shape to incorporate concepts from both models for assessment and models for learning. In this paper we argue that a third dimension is necessary. Not only is it important to understand what the capabilities of a learner are, and how to grow and expand these capabilities, but we must consider where the learner is headed; we need to consider models for navigation. This holistic perspective of learning and assessment systems is encapsulated in the extended learning and assessment system, a framework for conducting research. Fundamental to this framework is the role of computational psychometrics to facilitate the abstraction from raw data to conceptual models. We provide several examples of research projects and describe how they fit into the described framework.

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  • The Argument for a “Data Cube” for Large-Scale Psychometric Data

    Frontiers in Education

    In recent years, work with educational testing data has changed due to the affordances provided by technology, the availability of large data sets, and by the advances made in data mining and machine learning. Consequently, data analysis has moved from traditional psychometrics to computational psychometrics. Despite advances in the methodology and the availability of the large data sets collected at each administration, the way assessment data is collected, stored, and analyzed by testing…

    In recent years, work with educational testing data has changed due to the affordances provided by technology, the availability of large data sets, and by the advances made in data mining and machine learning. Consequently, data analysis has moved from traditional psychometrics to computational psychometrics. Despite advances in the methodology and the availability of the large data sets collected at each administration, the way assessment data is collected, stored, and analyzed by testing organizations is not conducive to these real-time, data intensive computational methods that can reveal new patterns and information about students.
    In this paper, we propose a new way to label, collect, and store data from large scale educational learning and assessment systems (LAS) using the concept of the “data cube.” This paradigm will make the application of machine-learning, learning analytics, and complex analyses possible. It will also allow for storing the content for tests (items) and instruction (videos, simulations, items with scaffolds) as data, which opens up new avenues for personalized learning. This data paradigm will allow us to innovate at a scale far beyond the hypothesis-driven, small-scale research that has characterized educational research in the past.

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  • Computational Psychometrics for the Measurement of Collaborative Problem Solving Skills

    Frontiers in Psychology

    Polyak ST, von Davier AA and Peterschmidt K (2017) Computational Psychometrics for the Measurement of Collaborative Problem Solving Skills. Front. Psychol. 8:2029. doi: 10.3389/fpsyg.2017.02029

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  • Computational Psychometrics for the Measurement of Collaborative Problem Solving Skills

    KDD Conference 2017

    This paper describes a psychometrically-based approach to the measurement of collaborative problem solving skills, by mining and classifying behavioral data both in real-time and in post-game analyses. The data were collected from a sample of middle school children who interacted with a game-like, online simulation of collaborative problem solving tasks. In this simulation, a user is required to collaborate with a virtual agent to solve a series of tasks within a first-person maze environment…

    This paper describes a psychometrically-based approach to the measurement of collaborative problem solving skills, by mining and classifying behavioral data both in real-time and in post-game analyses. The data were collected from a sample of middle school children who interacted with a game-like, online simulation of collaborative problem solving tasks. In this simulation, a user is required to collaborate with a virtual agent to solve a series of tasks within a first-person maze environment. The tasks were developed following the psychometric principles of Evidence Centered Design (ECD) and are aligned with the Holistic Framework developed by ACT. The analyses presented in this paper are an application of an emerging discipline called computational psychometrics which is growing out of traditional psychometrics and incorporates techniques from educational data mining, machine learning and other computer/cognitive science fields. In the real-time analysis, our aim was to start with limited knowledge of skill mastery, and then demonstrate a form of continuous Bayesian evidence tracing that updates sub-skill level probabilities as new conversation flow event evidence is presented. This is performed using Bayes’ rule and conversation item conditional probability tables. The items are polytomous and each response option has been tagged with a skill at a performance level. In our post-game analysis, our goal was to discover unique gameplay profiles by performing a cluster analysis of user’s sub-skill performance scores based on their patterns of selected dialog responses.

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  • IMS Competencies and Academic Standards Exchange (CASE) Service Version 1.0

    IMS Global

    The Competencies and Academic Standards Exchange (CASE) Service specification is the definition of how systems achieve the exchange of information about learning standards and/or competencies. The key aim is to replace the current ways of documenting a learning standard and competency, typically a PDF or HTML document, by one which is machine readable both syntactically and semantically. Further, using this new specification it will be possible to electronically exchange these definitions so…

    The Competencies and Academic Standards Exchange (CASE) Service specification is the definition of how systems achieve the exchange of information about learning standards and/or competencies. The key aim is to replace the current ways of documenting a learning standard and competency, typically a PDF or HTML document, by one which is machine readable both syntactically and semantically. Further, using this new specification it will be possible to electronically exchange these definitions so that applications, systems and tools can readily access this data.

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  • Book Chapter in "Systems Modeling for Business Process Improvement"

    Artech House

    Effective application of Information Technology (IT) can be the key to achieving organizational change and improvements that directly impact your company's success in today's highly competitive business environment. In this practical new book, you discover cutting edge approaches for developing system models that bridge the traditional gap between Information Systems and Software Engineering and let you more effectively manage change and outcomes.

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  • Rationale in Planning: Causality, Dependencies and Decisions

    Knowledge Engineering Review, Volume 13, Issue 03, pp 247-262, Cambridge Univ Press

    Traditional approaches to plan representation have focused on the generation of a sequence of actions and orderings. Knowledge rich models, which incorporate plan rationale, provide benefits to the planning process in a number of ways. The use of rationale in planning is reviewed in terms of causality, dependencies, and decisions. Each dimension addresses practical issues in the planning process, and adds value to the resultant plan. The contribution of this paper is to explore this…

    Traditional approaches to plan representation have focused on the generation of a sequence of actions and orderings. Knowledge rich models, which incorporate plan rationale, provide benefits to the planning process in a number of ways. The use of rationale in planning is reviewed in terms of causality, dependencies, and decisions. Each dimension addresses practical issues in the planning process, and adds value to the resultant plan. The contribution of this paper is to explore this categorisation, and to motivate the need to explicitly record and represent rationale knowledge for situated, mixed-initiative planning systems.

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Patents

  • SYSTEMS AND METHODS FOR INTERACTIVE DYNAMIC LEARNING DIAGNOSTICS AND FEEDBACK

    Filed US 15/802,404

    Other inventors

Courses

  • Computer Career Program

    IPD 397

  • Data Visualization and D3.js

    Udacity

  • Design Serverless Architecture with AWS and AWS Lambda, Packt, Michael Haberman, Safari Books Online

    -

  • Emerging Trends & Technologies in the Virtual K-12 Classroom (University of California, Irvine)

    Coursera

  • HTML/CSS Master Status

    codeschool.com

  • HTML5 Game Development

    Udacity

  • Introduction to Enterprise Architecture

    OpenUniversitiesAustralia

  • Introduction to High-Performance and Parallel Computing

    Univ. of Colorado Boulder

  • Introduction to Programming in Swift 5

    DP859CTMVRUL

  • Introduction to Recommender Systems (University of Minnesota)

    Coursera

  • Javascript Master Status

    codeschool.com

  • Machine Learning (Stanford)

    Coursera

  • Metadata: Organizing and Discovering Information (University of North Carolina at Chapel Hill)

    Coursera

  • Practical Machine Learning (Johns Hopkins University)

    Coursera

  • Software Engineering for SaaS

    Coursera

  • Stanford iPhone Development

    ITunes U

  • Understanding User Needs, University of Michigan

    Coursera 2019

Projects

  • GlucoseReady

    Innovation lead on GlucoseReady™, a comprehensive solution designed to revolutionize cardiometabolic disease clinical trials.

  • BrainBaseline

    BrainBaseline accelerates clinical trials via accessible and unrivaled mobile measurement.

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  • ACT Alexa Skill

    -

    Each year approximately 2 million high school students take the leading US admissions test, the ACT. The ACT measures what students learn in high school to determine their academic readiness for college. In the lead up to taking the test, students will typically review skills through test preparation and practice activities. In order to maximize their time, it is beneficial to diagnose what the student appears to have mastered and identify specific areas needing more review based on prior…

    Each year approximately 2 million high school students take the leading US admissions test, the ACT. The ACT measures what students learn in high school to determine their academic readiness for college. In the lead up to taking the test, students will typically review skills through test preparation and practice activities. In order to maximize their time, it is beneficial to diagnose what the student appears to have mastered and identify specific areas needing more review based on prior assessment results and ongoing practice activity. This diagnosis can then be used to drive a recommendation engine that can formulate personalized lists of open educational resources. This enables a pathway for self-directed learning and review based on feedback and access to targeted instructional content.

    It has been estimated that the worldwide smart speaker installed base will grow to more than 207 million units by the end of 2019. The two major players in this space are Amazon and Google. Both companies’ smart speaker platforms allow for the development of voice-based solutions that can leverage automatic speech recognition technology to enable the development of custom voice assistants. ACTNext, the innovation group within ACT, leveraged these capabilities by building a voice-driven learning solution. The learning assistant acts as a coach that can access a student’s mastery diagnostics and can provide ongoing advice on where the student should review next. For smart speaker solutions with a screen it can even access and deliver instructional content directly to the learner. The assistant also knows all about the assessment and enables conversations about what is on the test, when and where to take it and can also set reminders to ensure they are on track to complete the assessment.

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  • Recommendations and Diagnostics (RAD) API

    -

    RAD API is used to continuously track evidence of learning, diagnose mastery & generate personalized recommendations. RAD is built on a scaleable, industry-accepted Amazon AWS serverless lambda architecture backed by high performance DynamoDB data access. The solution is an ACT Software as a Service (SaaS) capability that has been integrated into ACT Academy as the initial learning & assessment client.

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  • ACT Labs

    -

    Establishing the ACTLabs architecture and technical infrastructure to support ongoing and future corporate prototyping and evaluation efforts, including but not limited to the innovation needs in Assessment Design and Test Development

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  • ACT Profile

    -

    ACT Profile is a first-of-its-kind college and career planning community, built on 30+ years of ACT research.

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  • PearsonAccess Next

    -

    Pearson's unified interface for managing large-scale assessments.

    See project

  • Technology Readiness Tool

    -

    A tool for schools, districts and states in the SBAC/PARCC consortiums to determine readiness for large scale online testing.

    See project

  • ePEN - Electronic Performance Evaluation Network

    -

    NCS Pearson's Electronic Performance Evaluation Network (ePEN) is an image-based performance scoring system that uses the Internet to transmit electronic images of student responses to trained scorers at individual workstations. ePEN manages all aspects of the performance assessment scoring process electronically, increasing efficiency and flexibility.

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  • Britannica.com

    -

    Facts matter. A leader in encyclopedias.

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  • ACT Academy

    -

    ACT Academy is the go-to place to get FREE, personalized practice for the ACT. Providing detailed diagnostics and recommendations.

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Honors & Awards

  • Corridor Business Journal 2023 - Corridor Leaders 250

    Corridor Business Journal

    Selected as a featured area leader for the Iowa City / Corridor area in 2023

  • Corridor Business Journal 2022 - Corridor Leaders 250

    Corridor Business Journal

    Selected as a featured area leader for the Iowa City / Corridor area in 2022

Organizations

  • Randonneurs USA / Iowa Randonneuring

    Regional Brevet Administrator (RBA) for Iowa / Super Randonneur

    - Present

  • Boy Scouts of America

    Pack 2000 Committee Chairman

    -

  • FIRST LEGO League (FLL)

    Coach

    -

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