User Scenario: Remote/Online Use of Equipment as a Technique for Gathering Student Data
Keith Andrew—Eastern Illinois University
Cameron Dorey - University of Central Arkansas
Ahmed Elgamal—University of California, San Diego
Scenario 1: Use of expensive or unique instrument by students at remote schools for individual or collaborative investigation (pedagogy or research).
Motivation: Solve real problems for students who do not have the necessary equipment, in lieu of a simulated exercise (or no exercise at all).
Example: NMR (nuclear magnetic resonance) or SEM (scanning electron microscope), both instruments would cost $200K or more.
Procedure:
Student submits sample (after s/he has done all possible sample prep at her/his school).
Instrument time is scheduled at both schools.
Possible modes of data acquisition are
- Virtual interaction
- Operator interaction (remote observation)
- Data messaging
Data archived at instrument site for subsequent use/review
Student uses data back at her/his site
Example: Shaker table for structural analysis controlled over internet, an instrument which is not found in many high school educational settings, but can demonstrate important structural engineering principles.
Procedure:
Student submits model of structure to be tested, technician at site sets up experiment
Student controls experiment remotely with video feedback
Major interest to 7-12 grade students, college structural dynamics classes
Scenario 2: Unsupervised remote collection of data in the field over a long time frame.
Motivation: Time/logistical constraints prohibit real-time on-site monitoring by experimenter.
Example: Monitoring of riverbed erosion
Procedure:
Monitoring would take place over an extended time period
Robust camera/recording equipment is needed, with the capability of unmonitored time-lapse photography
Experimenter retrieves collected data or it is transmitted automatically from site at intervals
Student analyzes data on campus, data is compared to local simulation
Scenario 3: Multiple groups comparing data
Motivation: Gather data from large-scale spatial region
Motivation: Logistical constraints prevent one student/group from conducting all experiments
Example: Weather-related data collection over the length of a river
Procedure:
Monitoring takes place simultaneously at several sites
Data shared between sites, analyses of data compared between sites
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