Monday, June 13, 2016

SLA2016 : Teaching Data Literacy

There was a lot of content in this session and much of it went by too fast.  I hope the presenters place their presentations online.
Elaine Lasda
Elaine Lasda

Elaine Lasda - Teaching data literacy to undergraduates (Her presentation is online here.)

University of Albany has a strong literacy component to its curriculum.  It fits into the curriculum in different ways,including information literacy for math and statistics, e.g., UNL 299.  

Data Literacy Concepts:
  • Quality
  • Context 
  • Authority
  • How is it created, documented, etc.  
Lasda began her lesson for the class with a hands-on assignment. She used data from New York State and noted that NYS has very good data available. She then does a lecture.  Over time she has shortened the lecture, because the lecture has not gone over well.  In the future, rather than a lecture she is going to use discussion question.  She had ended her guest lecture with a survey/assessment.

Lasda is looking to expanding this class/concept to other disciplines.

Michael Fosmire - Teaching Data Literacy at the Graduate Level

DIL: the problem
Students should know this by now
Students don't know what they should know
Students weren't introduced to this as undergrads

DIL competencies:
  • Database and data formats
  • Understand principles of relational databases
  • Understand standard formats of discipline
  • Under appropriate formats for research questions
  • Discovery and acquisition of data
  • Locate and utilize disciplinary data repositories
  • Evaluate quality of data located
  • Recognize practices
  • Recognize  standards
  • Data conversion and interoperability
  • Can migrate data
  • Understand benefits of standard formats
  • Understand risk of loss and corruption
  • Curation and reuse
  • Data Management and organization 
  • Data preservation
  • Data process and analysis
  • Data quality and documentation
  • Data visualization 
  • Ethics and attribution
  • Metadata and data description
What is unique abut grad students?  They are highly motivated. Need guidance. Do not want busy work.

In terms of instruction the options are:
  • Workshops - target, at the point of need,hands-on 
  • Create a "Data Day" - might do during a semester break because graduate students frequently stay in town then.
  • Get a GRIP on your research promotion and programs
  • More depth, more engagement 
  • Includes a portal
  • Http://
  • Credit bearing courses
  • Data methods , etc.
  • Geoinformatics course - from locate to deposit
  • Data Methods course
  • Research lab consultations
  • Interview
  • Plan - introduce the concepts in relation to the research lab itself.  Scaffold the topics.
  • Deploy
  • Created specific activities for the students.
Stefanie Maclin-Hurd, EBSCO

Talked about training staff on data and specifically on the use of ILS data.

Updated: 06/17/2016& 6/26/2016

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