Wednesday, August 14, 2013
A teacher's information space
When I was in school, teachers taught with a book and handouts from the Ditto machine with their intoxicating fumes. Maybe a filmstrip once a year. Some classrooms had a dictionary for reference in case of emergencies.
When I entered college, textbooks were augmented with additional readings from books put on reserve in the library. By the time I left college, books on reserve were replaced by xeroxed (the only term used at the time) copies of papers and articles handed out in class. The volume of those handouts grew to rival the size of the textbook.
Today, thanks to the Internet and per-student computers, tablets and smartphones, the available teaching resources are unlimited. And that's just content resources. There has also been a "big data" explosion of information about the performance of students on each question of standardized tests. Correlate that to special populations, demographics, individual intervention and tutorial history...and the information opportunities go on.
Teachers themselves create their own big data explosions, particularly through the use of video for flipped classes and student assignments that assume video as available as construction paper once was.
How does a teacher manage his or her information space?
Managing abundant information is not a new problem, although it's new that it has become a fundamental part of the job for so many people. It has become a fundamental part of the job of teaching.
Just as with libraries and museums, the first step is to make collections. If the resources are expected to vanish from where they are now, you'll need collections of copies. Otherwise, collections of links are sufficient and a lot easier to deal with. Google starts as a collection of links, YouTube starts as a collection of copies.
As collections grow they become more useful with meta data:
- Attributes such as date, source, property rights, etc.
- Representative icons or logos
- Social evidence of value
- Where is this used?
- How frequently has it been used?
- Is it "liked"?
- Is it rated and what is the aggregate rating?
- Can the ratings and uses be weighted by the reputations of those making the decisions?
- Has it been peer reviewed?
Interfacing data collections
Whatever we collect, it's almost certain that there are related collections. How readily can we absorb other collections into our own?
- How readily can another collection be copied into our own?
- In addition to copying items of the collection, can we copy subsets of the collection?
- Must we copy items one-by-one?
- Can items be copied by category, tag, attribute or property (e.g., copy the top 10% most liked items)?
- Can we copy the meta data along with the item?
- Can we copy on demand or is copying more of a batch process?
An example of interfaced data collections is between Google Calendar and the School Site Manager calendar. Some schools maintain both. We have the ability to pull events from Google Calendar into the database for School Site Manager calendar. The Google and Edclick databases are not integrated (see next section) but they are interfaced.
Integrating data collections
Databases are collections where the data has been structured in such a way to facilitate query and manipulation: selection, updates and joining. That is to say that the meta data in one collection can be mapped to the meta data in another so that an item in one can reliably be matched to an item in the other. Collections are integrated when they can operate as if they were a single database.
Teachers have access to student data in their online gradebooks as well as data about student performance on standardized tests. These databases come from different sources but they are integrated if the teacher can do a query like comparing classroom grades with standardized test scores.
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