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Algorithms of Education: Figure Descriptions

Algorithms of Education
Figure Descriptions
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table of contents
  1. Cover
  2. Half Title Page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Introduction. Synthetic Governance: Algorithms of Education
  7. 1. Governing: Networks, Artificial Intelligence, and Anticipation
  8. 2. Thought: Acceleration, Automated Thinking, and Uncertainty
  9. 3. Problems: Concept Work, Ethnography, and Policy Mobility
  10. 4. Infrastructure: Interoperability, Datafication, and Extrastatecraft
  11. 5. Patterns: Facial Recognition and the Human in the Loop
  12. 6. Automation: Data Science, Optimization, and New Values
  13. 7. Synthetic Politics: Responding to Algorithms of Education
  14. Acknowledgments
  15. Notes
  16. Image Descriptions
  17. Index
  18. About the Authors

Figure Descriptions

  1. Figure 2. This figure is an infographic titled “The Learning Services Architecture 2019 Roadmap.” The figure is broken into two parts: on the left, four paragraphs of descriptive text; on the right a flowchart under the heading “Better Data for Better Outcomes.” The text on the left reads,

    All models of learning improvement need a foundation of accurate, comparable, and consistent data.

    The LSA is a nationally aligned set of IT practices designed to ensure that critical information about students is available when and where required.

    Schools benefit strategically from the creation of portfolios of student information that accompany the learner throughout their education.

    Schools benefit tactically from choice of solutions in the marketplace, knowing that critical student data can be shared accurately and securely between systems and organisations.

    On the right, four main graphics comprise the flowchart, beginning with

    1. an outline of Australia and its six states. Each state is marked with a green dot representing Data Hubs. The corresponding caption reads “Data Hubs established for all school systems.” Beneath the map an arrow directs readers’ attention to a checklist icon that is captioned, “Nationally agreed information contracts for school business processes.” An arrow from the checklist is directed generally toward the rest of the roadmap, which turns on the following nodes:
    2. a Data Hub, represented by a thumbnail of a server farm working in the cloud. The server farm image leads to icons of a mobile device, a bar chart, and a chat bubble. Beside these a brief caption reads, “Data is available via the Hub to support further services such as mobile apps, analytics, and parent engagement. The graphic indicates with arrows that the Hub sends to and receives information from school systems, and that this information is part of a student’s education portfolio.
    3. situated to the lower left of the Data Hub are two closely related images, one of a computer screen showing a browser window and another of a generic building representing a school. These are captioned “Schools use the local systems that beset meet their local needs.” The School Systems icon has pointers going to and coming from an image of a generic student portfolio that has its own caption: “Same common interfaces can be used between systems in schools.” Both the School Systems and Portfolio images point toward the last main graphic.
    4. the final graphic, which has arrows coming from the Hub and School Systems thumbnails, is of a generic student surrounded by a circle divided into quadrants labelled “Progress,” “Wellbeing,” “Learning,” and “Admin.” Beneath the image text reads “Data from all sources becomes, at school, part of a Student Data Entitlement.”

    Return to figure.

  2. Figure 3. This figure is a two-column text graphic titled “Information Conracts.” Each column is made up of four terms and their corresponding definitions. Each definition is decorated with a bubble containing an abbreviation of the main term. The four terms on the left are,

    Enrollment

    Foundational data about a standard: Who they are, what class they are in, who teaches them what, significant relationships, identity information. This term is abbreviated with the letter “E.”

    Attendance

    Capturing the roll for classes and whole schools. Used in school, school system and national reporting. Attendance is a lead indicator for early diagnostics of issues that may be affecting student progress. This term is abbreviated with the letters “A” and “t”: “At.”

    Assessment

    Data about how a student is progressing. Multiple sources of formative and summative data that allow better understanding of student progress. Needs to carry curriculum context when appropriate, but be flexible enough to capture ad-hoc and experimental outcomes. This term is abbreviated with the letters “A” and “s”: “As.”

    NAPLAN

    Registration of students for NAPLAN Online. Rich results data from NAPLAN online: complex adaptive test data, single nationally consistent dataset. This term is abbreviated with the letter “N.”

    The four terms on the right are,

    Wellbeing

    Events and outcomes in the social aspects of a student’s learning, including: records of behaviour, pastoral care records, records of participation and extra-curricular activities and achievements. This term is abbreviated with the letter “W.”

    Timetable

    The foundational dataset for understanding the processes of running school: What is being taught, where, by which teachers and to which students, cirtical for resource planning and allocation. This term is abbreviated with a capital and lowercase letter “T”: “Tt.”

    Finance

    Secure, consistent exchange and management of: Purchase Orders, Invoices, Payments and General Ledger transactions. This term is abbreviated with the letter “F.”

    Learning Resources

    Data from and about third-party learning tools that students and teachers use. This term is abbreviated with the letters “L” and “R”: “LR.”

    The graphic carries the following caption: “Secure and Private Under the LSA data is exchanged between schools, school authorities and service providers in accordance with respective privacy, security and duty of care obligations. NSIP neither collects or stores education data.”

    Return to figure.

  3. Figure 4. This is an organizational chart titled ”Organising structure.” The top row is made up of three elements, reading from left to right as “Australian Curriculum (abbreviated as ‘AC’),” “National Literacy and Numeracy Learning Progressions (abbreviated as ‘NLNLPs’),” and “Measurement Scale.” These three entities appear as tiles linked to one another by horizontal lines. From the center tile (National Literacy and Numeracy Learning Progressions) this group collectively connects to the next row: a series of five “Modules” under the heading of “Machine Linked and Aligned Across.” Each module sits atop a series of three to five “Functions and assets,” all grouped inside a heading that reads “Single Sign On for teachers and Students.” The modules and their associated functions are defined in the following five lists:

    Assessment bank: Item authoring and progression/curriculum mapping

    • Activity and observation questionnaires
    • Assessment items
    • External assessments (via API)

    Learning progress tracker

    • Collection of assessment and observation data
    • Detailed progress tracking
    • Detailed progress visualisation

    Online test creation and delivery

    • Adaptive test sequencing engine
    • Diagnostic feedback engine

    Suggestion engine

    • Metadata harvesting and indexing
    • Ranked suggestions for identified learning needs
    • Analytics and artificial intelligence

    Digital resources

    • Metadata aligned to AC and NLNPs
    • Student resources
    • Teaching resources
    • Parent resources
    • Professional learning

    The modules and their associated functions are followed by a heading that reads “Access.” Within the Access section are horizontal lines associated with different users and which span the width of one or more module, visually indicating what kinds of users have access to different modules. Those user access relationships are as follows:

    • Learning management systems have access to the “Suggestion engine” and “Digital resources” modules.
    • Teachers have access to the “Learning progress tracker,” “Online test creation and delivery,” “Suggestion engine,” and “Digital resources” modules.
    • ACARA and contractors have access to the “Assessment bank” module.
    • Students can access the “Online test creation and delivery,” “Suggestion engine,” and “Digital resources” modules—and by agreement the “Learning progress tracker” module.
    • Parents, as well as Authorised school staff can access the “Suggestion engine” and “Digital resources” modules—and by agreement the “Learning progress tracker” and “Online test creation and delivery” modules.

    Return to figure.

  4. Figure 5. This line chart has an X-axis titled “Information Maturity” and a Y-axis titled “Organizational Value.” The chart displays a single trend line with seven data points that consistently increases from the lower left to the upper right in the shape of a gentle parabolic curve. In addition to the X- and Y-axis labels, there are several headings atop the chart and just above the X-axis that further contextualize the data points.

    The first five data points fall under the “Reactive” label, which itself is divided into two portions: “Tactical Use” and “Focused Delivery”:

    Tactical Use

    • Standard and ad-hoc reports (dated 2013)
    • Dashboards (no date)
    • Data exploration and visualisation (dated 2015)

    Focused Delivery

    • Advanced Visualisation (no date)
    • Predictive Analyses (dated 2019)

    The last three of these nodes (“Data exploration and visualisation,” “Advanced Visualisation,” and “Predictive Analyses”) are also associated with a heading that reads “This strategy.”

    The final two nodes of the chart fall under the “Proactive” label that is itself split into two portions: “Strategic” and “Drives Action.”

    Strategic

    • Predictive Modelling (no date)

    Drives Action

    • Optimisation (no date)

    Return to figure.

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The University of Minnesota Press gratefully acknowledges support for the open-access edition of this book from the University of Sydney, the Australian Research Council, and the Social Sciences and Humanities Research Council (SSHRC) of Canada.

A different version of chapter 2 was previously published as Sam Sellar, “Acceleration, Automation, and Pedagogy: How the Prospect of Technological Unemployment Creates New Conditions for Educational Thought,” in Education and Technological Unemployment, ed. M. A. Peters, P. Jandric, and A. J. Means, 131–44 (Dordrecht: Springer, 2019). A different version of chapter 4 was previously published as Kalervo N. Gulson and Sam Sellar, “Emerging Data Infrastructures and the New Topologies of Education Policy,” Environment and Planning D: Society and Space 37, no. 2 (2019): 350–66; and as Sam Sellar and Kalervo N. Gulson, “Dispositions and Situations of Education Governance: The Example of Data Infrastructure in Australian Schooling,” in Education Governance and Social Theory: Interdisciplinary Approaches to Research, ed. A. Wilkins and A. Olmedo, 63–79 (London: Bloomsbury Academic, 2018); Bloomsbury Academic is an imprint of Bloomsbury Publishing PLC. A different version of chapter 6 was published as Sam Sellar and Kalervo N. Gulson, “Becoming Information Centric: The Emergence of New Cognitive Infrastructures in Education Policy,” Journal of Education Policy 36, no. 3 (2021): 309–26, available at https://www.tandfonline.com.

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