Transcript Virtual Chemistry Lab

Virtual Chemistry Laboratory
David Yaron, Donovan Lange, Michael Karabinos,
Rea Freeland and D. Jeff Milton
Department of Chemistry, Carnegie Mellon University
Gaea Leinhardt and Karen Evans
Learning Research and Development Center, University of Pittsburgh
Funded by the National Science Foundation (CCLI and NSDL Programs)
and the Howard Hughes Medical Institute
Goals
• Shift current chemistry courses so that they
– Promote inquiry
– Promote chemical literacy
• Methods
– Homework for college classes and capstone activities for high
school classes
– Community building and support activities
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Learning challenges and interventions
• Promoting flexibility and applicability
– From mathematical procedures to chemical phenomena (use in
chemistry)
• Virtual laboratory
– From chemical phenomena to real world
(transfer to real world)
• Scenario based learning
• Promoting coherence
– Scenarios that touch down at various points in the course
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Use in chemistry: Virtual laboratory
• Flexible simulation of
aqueous chemistry
• New mode of
interaction with
chemical concepts
• Ability to “see” inside
a solution removes
one level of indirection
in chemical problem
solving
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Authoring a virtual lab activity
• Add chemical species and reactions (if desired)
– Can create “fictional” proteins, drugs etc.
• Create Stockroom Solutions
• Specify available functionality
– Viewers
• For example, turn off “Solution Contents” for exercises involving unknowns
– Transfer mode
• Precise: student enters exact amount to transfer
– Facilitates comparison with paper and pencil problems
• Realistic: simulates accuracy attainable in real lab
– Forces student to use correct apparatus (buret for titration)
• HTML problem description can be included
• Of 35 current problems, 15 are by community of users
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Virtual lab problem types
• Check paper-and-pencil work
– Encourages students to see connection between calculations and
an experimental procedure
– Provides intermediate results
• Virtual experiments
“Measure the free-energy of binding between the DNA base pairs”
– Requires experimental design
– Involves use of concepts to achieve goals
• DGo related to equilibrium constant K
– Relates material to an interesting system
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Goal oriented problems
• Typical textbook problem
“What is the pH of a buffer made by mixing 10ml of 0.10M HAc with 12ml of
0.10M NaAc?”
– Textbook author makes the interesting choices
– Student just does the calculation; leads to a narrow focus on skills
• Virtual lab (goal oriented) problem
“The stockroom contains a cyanine dye that binds to DNA when it is
protonated. Create a solution in which 50% of the dye will be bound to
DNA.”
– Involves mix of experimental design and paper-and-pencil calculations
– Realistic feedback (Did you achieve your goal?)
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Puzzle problems
“The stockroom contains 1M solutions of A, B, C and D. What is the
reaction between these chemical species?”
• Possible because the virtual lab allows students to rapidly
do experiments and to see “inside” solutions.
• Represents a new mode of interaction with the material.
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Observational studies with virtual lab
• Situation
– 30-35 students working alone or in pairs
– 2-3 instructors
• Outcomes
– Can give insight into student difficulties and nature of their
qualitative understanding
– Unanticipated error types provide opportunities for instructional
design
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Observational studies: Student difficulties
Typical textbook problem
“When 10ml of 1M A was
mixed with 10ml of 1M B, the
temperature went up by 10
degrees. What is the heat of the
reaction between A and B?”
Virtual lab problem
“Construct an experiment to
measure the heat of reaction
between A and B?”
• Students who could perform the textbook procedure on exams, had
difficulty designing the experiment, and needed help from human
tutor. The procedure is apparently not triggered in response to
relevant prompt.
• Virtual lab activities may reinforce activation.
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Observational studies: Unanticipated errors
“The virtual lab contains 1M solutions of A, B, C, and D. Construct
experiments to determine the reaction between these reagents”
• Intent was to give practice with determining reaction coefficients
A + 2B  3C + D
• Observation
When A is mixed with B, some A remains, so the reaction must be:
A+BC+D+A
Reveals misunderstanding of limiting reagent concept (even though they could
easily perform textbook limiting reagent problems)
• This type of mistake is good opportunity for Elicit-Confront-Resolve
instructional strategy
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Observational studies: Qualitative reasoning
• Challenge problem involving multiple interacting chemical equilibria
(“a weak acid dye binding to DNA”)
• Student strategies were much more sophisticated than instructors
anticipated based on students ability to manipulate these concepts
algebraically
• Suggests the new manipulatives of the virtual lab have potential for
supporting and assessing qualitative understanding
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Transfer to real world: Scenarios
• Scenario based learning
– Embed the procedural knowledge of the course in a scenario
that highlights its utility
– Scenarios that touch down at various points in the course
may promote coherence
– Examples: forensics, biological and medicinal chemistry,
environmental chemistry, space exploration/colonization
• Outcome of design process
– Attempt to organize scenario development lead to a “concept
map” of the domain
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Scenarios: Examples
• Mixed reception
– Murder mystery activity for first few weeks of high-school/college
chemistry
– Illustrates that contextualization can be done early in course
• Arsenic poisoning of wells in Bangladesh
– Scenario that touches down at various points in the course
(stoichiometry, titration, spectroscopy)
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Scenarios: Design process
• Concept map of chemistry benchmarked against
– CA state content standards
– Best selling textbooks
- Nobel prizes
- NY Times/Scientific American
• Reveals flaw in current course structure
– Top level: Three subdomains in which chemists work
• Scientific literature spread equally between these three
subdomains
– Lower levels: Toolbox
• Textbooks and standards found only in Toolbox and Analyze
subdomain
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Chemistry Concept Map
EXPLAIN
Hypothesis
Generation
Hypothesis
Testing
ANALYZE
Goal
(What do you
want to know?)
SYNTHESIZE
Functional
Motifs
Process
Structural
Motifs
(How to determine
What you have)
Assembly
Motifs
TOOLBOX
Representational
Systems
Quantification
Systems
Challenges for active content in digital libraries
• Simulation and visualization tools often require a flexible
development environment such as JAVA
• Evidence of a problem
– Thousands of applets are available on the web
– Indicates nascent developer community
– But most applets are used only by team that developed them
• Root of the problem
– Current development approach puts too much of the process in
the hands of programmers rather than educators
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Student interface as a dividing line
• Programmers develop components
– Produce materials for use by instructors and curriculum
developers
– Takes advantage of their ability to produce interactive, domainspecific learning objects
• Curriculum designers provide student interface
– Provide student interface, guidance and scaffolding
– Takes advantage of classroom and pedagogical expertise
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Configuration as authoring
• A component that save its state to a file serves as a
domain-specific “authoring tool”.
• Configuration file specifies
– Available chemicals,
instruments, and
visualization tools
– User interface features
Other examples: Physletts (Davidson), Interactive Physics
2000, VGEE earth science project (UCAR)
Matlab, Mathematica, and SPSS can also be viewed as
using “configuration as authoring”
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Linked active content
• Allow assembly of multiple components each of which is
configurable and saves its state to a file
Simulation
Image maps
with hotspots
that send
messages to
the simulation
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
CREATE digital library architecture
Linked Active Content
Software Components
Planets.xml
File that specifies number of
planets to show, scale etc.
Control_panel1.xml
simulation
start
reset
File containing image and links
to start and reset simulation.
Image map 1
Control_panel2.xml
File containing image and
links to set fuel parameters.
Image map 2
• Content files and software are stored separately in the
digital library collection
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Mixed reception
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Promoting reuse and maintenance
• Reuse
– CreateStudio allows you to step through an activity in preview
mode to where you want to make a change
– Switch to edit mode to make a change and the
– Save modified content back to library
• Maintenance benefits of separating content from software
– Can update viewers without needing to change content
– Can tag and search content files
• Supports iterative approach to development
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
CreateStudio as an authoring portal for the NSDL
• Component (viewer) discovery
– Search NSDL for viewers
– Search for activities that use a particular viewer (for examples)
• Content discovery
– Search for movies when using a movie player
– Search for virtual lab configurations
• Publish into the library
• Extract from library, edit, and republish into the library
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Current dissemination strategies
• Web site (http://ir.chem.cmu.edu/)
– 1000 page requests per day, 80 instructors on mailing list, 36
requests to become test sites in past year
– >7000 students have performed one or more activity in the virtual
lab
• Booths at conferences
– Demonstrate materials for about 75 instructors per day of 3 to 4
day conference
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Community partners
• Most active sites
– University of British Columbia (4200 students over 3 semesters)
– Florida Atlantic University (1500 students over 2 semesters)
– University of West Virginia (150 students over 2 semesters)
• All three sites recruited at conferences, with no prior
affiliation
• Sites attracted by ability to author/customize
– UBC, FAU: ability to customize to existing physical lab program
– UWV: enabling technology for own curriculum development
• Of 35 activities on web site, 15 were developed by user
community
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Using DLs to build educational communities
• Community must share a specific educational goal
• DLs can combine expertise through remote and
asynchronous collaboration
– Learning technology: As with the CREATE architecture
– Learning science: Design of components (virtual lab), DL
organization (concept map), and assessment tools (instruments
and tracing technologies)
– Domain/classroom experience: By having teachers author
material, can shortcut (develop-assess-disseminate) cycle
• DLs can support an iterative development process
– Carnegie Mellon’s OLI is developing technology to collect data
online and use this to inform the development process
Chemistry Virtual Laboratory
http://ir.chem.cmu.edu/
Carnegie Mellon
Credits: Programmers / Writers/ Educational Research
Carnegie Mellon
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Donovan Lange
D. Jeff Milton
Michael Karabinos
Rea Freeland
Giancarlo Dossi
Katie Chang
Emma Rehm
Erin Fried
Jason Chalecki
Greg Hamlin
Chemistry Virtual Laboratory
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Brendt Thomas
Stephen Ulrich
Jason McKesson
Aaron Rockoff
Jon Sung
Jean Vettel
Rohith Ashok
Joshua Horan
LRDC, University of Pittsburgh
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Gaea Leinhardt
Karen Evans
http://ir.chem.cmu.edu/
Carnegie Mellon