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The Networked Education Database. Matthew Pittinsky Ph.D. Candidate, Teachers College, Columbia University. NED: A Vision. Schools have long invested in student administrative systems.

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The networked education database

The Networked Education Database

Matthew PittinskyPh.D. Candidate, Teachers College, Columbia University

Ned a vision
NED: A Vision

  • Schools have long invested in student administrative systems.

  • Schools are now adopting eLearning systems equipped with gradebooks, class rosters and Web-based survey (assessment) tools.

  • Both are Internet-enabled.

  • Could “generic” and custom data be collected through school systems automatically, and anonymously, massively reducing the cost and complexity of educational research?


The Problem…

Original data collection
Original Data Collection

  • Requires precious classroom time.

  • Informed consents difficult to secure.

  • Customizing instruments for context across sites and time is costly and discourages certain types of data collection (e.g. sociometric).

  • Data entry and coding inhibits sharing and re-use.

  • Incomplete responses undermine results and inhibit certain types of data collection (e.g. full classrooms).

Major secondary datasets
Major Secondary Datasets

  • International studies (e.g. TIMSS).

  • Federal studies (e.g. NELS, HSB).

  • State data warehouses (e.g. Florida K-20 Education Data Warehouse (EDW)).

  • Sponsored private studies (e.g. AddHealth).

Secondary datasets issues
Secondary Datasets: Issues

  • Requires tough trade-off’s when operationalizing specific research questions.

    • e.g. classmate effect studies.

  • Often based on stratified samples, not whole classrooms and schools.

    • e.g. same-teacher class periods.

  • Rarely longitudinal within academic years.

  • Rarely contextualized (e.g. relationship questions that require roster).


The Solution…

Ned a dataset
NED: A Dataset

  • Classroom-level data.

  • Same-teacher data.

  • Sociometric & social-psychological data.

  • Longitudinal data.

  • Multi-site data.

  • At scale…

Ned a data collection model
NED: A Data Collection Model

  • Asynchronous (outside class time)

  • Automatic (pre-scheduled, add/drops)

  • Contextual (draws on system data to generate questions)

  • Non-duplicative (uses already stored or entered data where possible)

  • Complete (form checks)

  • Anonymous (unique ID)

  • Efficient (paperless and coded)

  • Sustainable (self-perpetuating)

How ned works
How NED Works

  • School installs NED extension and marks participating classes.

  • School’s eLearning system automatically posts survey based on schedule (w/ announcement).

  • Participant provides consent.

  • Survey is delivered through eLearning system GUI.

  • Survey draws on class context (roster, subject matter, student information, etc.) when phrasing customized questions.

  • Survey enforces certain completion rules.

  • Survey responses stored in special encrypted tables that self-delete after posting.

  • Survey responses and pre-existing data (demographic, gradebook) are packaged and securely posted to NED.

  • New students are “caught up” when added to course.

  • Teacher knows how many completes, but not who.

Participant anonymity
Participant Anonymity

  • Data arrives to NED as secondary data (anonymous and coded).

  • Survey responses are tagged with unique participant IDs.

  • Generic data tagged with same ID and automatically merged with survey responses (gradebook, demographic, course overlap).

  • Structure of unique participant ID allows for sorting by class and school, however...

  • Data arrives at NED without any knowledge of participant’s school or classroom identity.

Participant confidentiality
Participant Confidentiality

  • Survey responses are encrypted and automatically self-delete on local server.

  • No school official has access to student responses or completion status.

  • Data transmission is via secure protocol.


The Pilot…

Ned pilot
NED Pilot

  • Custom extension to the Blackboard Learning System.

  • Solicited 15 sites, 5 agreed, 3 ultimately participated.

    • All secondary schools (2 private / 1 public), 3 different states and regions.

  • 18 teachers, 37 classes, 732 participants

  • Three pre-scheduled NED survey administrations (October, January, May).

    • Each “live” for two weeks

  • NED staff know site names, but not names of participating schools (if district), teachers or class information.

  • Students provided incentive to participate.

  • Surveys included questions from other datasets to compare responses.

  • Approximately 250 development hours.

Ned status
NED Status

  • First administration launched 10-16 and ends today (10-30).

  • Several showstopper technical issues identified and resolved.

  • One site dropped out.

  • % participation and incompletes will be assessed 11-1.

Implementation issues
Implementation Issues

  • Not a standard “building block;” required custom coding.

    • Bb installations vary, affecting custom code.

  • Not Bb’s standard survey tool.

    • Survey formatting limited.

    • Save and start, adaptive, and timing features limited.

    • Low ease of use (e.g. self-reference not grayed in sociometric questions; matrix questions scroll off screen without freezing roster).

  • Gradebook entries are user-defined, without a standard taxonomy.

  • Many schools create one mega-site for all class periods.

    • Pilot leans away from core subjects.

    • Pilot leans away from same-teacher course sections.

  • Many schools do not use Bb as their gradebook or student profile of record.

  • Relying on teacher responses for student-level data not always viable (e.g. mixed age-grade classes).

Implementation issues1
Implementation Issues

  • Required “enterprise license” of Blackboard.

  • Data transmission via local SQL scripts, not Web service.

  • IP address of sending site could allow for matching of school name with unique ID schema.

  • Different participant ID’s across classes (if student changed class periods).

  • System reports fragmented and unusable without additional programming.

  • Total eligible population not included in system report.

  • Ideal survey length difficult to asses.

  • Anonymity and class time impact concerns during site solicitation.

  • Will students participate?

Future directions
Future Directions

  • Implement through standardized APIs and via eLearning system’s survey tool.

  • Pilot with larger number of sites.

  • Pilot with smaller, more frequent surveys.

  • Pilot with full site participation across all classes and grades.

  • Pilot with full age-grade population over time.

  • Include non eLearning systems (e.g. TPR) and non Bb eLearning systems.

    • Formalize vendor NED interface program.

  • Expand to higher education.

Ned imagine
NED: Imagine

  • A national dataset.

  • Fed from tens of thousands of sites.

  • Collecting unique classroom-level data.

  • Throughout the academic year and a student’s educational career.

  • With minimal site-specific maintenance.

  • Efficiently and cost effectively.

Ned team
NED Team

  • Technical

    • Tim Streightiff, lead developer

    • Linda Merryman, project director

    • Basheer Azizi, database engineer

  • Functional

    • Matthew Pittinsky, principal investigator

    • Gary Natriello, principal investigator

The networked education database1

The Networked Education Database

A Joint Research Project


Matthew Pittinsky: [email protected]

Gary Natriello: [email protected]