Difference between revisions of "Mapping Visual and Verbal Information: Integrated Hints in Geometry (Aleven & Butcher)"
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**Problem-solving items isomorphic to the practiced problems ([[retention]]) | **Problem-solving items isomorphic to the practiced problems ([[retention]]) | ||
**Problem-solving items unlike those seen during problem practice ([[transfer]]) | **Problem-solving items unlike those seen during problem practice ([[transfer]]) | ||
+ | **Generative items testing [[conceptual knowledge]], not practiced in tutor ([[transfer]]) | ||
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*Log data collected during tutor use, used to assess: | *Log data collected during tutor use, used to assess: | ||
**[[Learning curve]]s | **[[Learning curve]]s |
Revision as of 20:48, 30 March 2007
Contents
Using Elaborated Explanations to Support Geometry Learning
Vincent Aleven and Kirsten Butcher
Summary Table
PIs | Vincent Aleven & Kirsten R. Butcher |
Other Contributers | Graduate Students: Carl Angioli (CMU HCII), Michael Nugent (Pitt, Computer Science) Research Programmers/Associates: Octav Popescu (Research Programmer, CMU HCII), Grace Lee Leonard (Research Associate, CMU HCII), Thomas Bolster (Research Associate, CMU HCII) |
Study Start Date | Planned Start: April 24, 2007 |
Study End Date | Expected End: June 1, 2007 |
LearnLab Site | Central Westmoreland Career & Technology Center (CWCTC) |
LearnLab Course | Geometry |
Number of Students | Expected: 120 |
Total Participant Hours | Expected: 480 |
DataShop | (Study not yet completed. Log data will be provided to the DataShop when available) |
Abstract
Does integration of visual and verbal knowledge during learning support deep understanding? Can robust learning be supported implicitly by representations that link relevant knowledge components in visual and verbal materials? The overall goal of this project is to gain a better understanding of 1) visual and verbal knowledge components in a problem-solving environment and, 2) how instructional support to promote connections between visual and verbal knowledge components can support the development of deep understanding. Ultimately, we are interested in coordination and integration processes in learning with visual and verbal knowledge components, and how these processes may support robust learning.
We are using the Geometry Cognitive Tutor as a research vehicle for our project. In geometry, visual information is represented pictorially in a problem diagram and verbal/symbolic information is represented in text that contains given and goal information as well as in conceptual rules/principles of geometry. The goal of the research described here is to determine if implicit instructional events that use visual cues to map between text and diagrams can support knowledge retention and transfer. These visual cues are instantiated in the Geometry Cognitive Tutor by using colored highlighting to connect textual references of geometric features in instructional hints to the visual depictions of those features in the geometry diagram (screen shots provided below, in the Independent Variables section). This in vivo study will take place April - June, 2007.
Background & Significance
A central question in theories of learning with multimedia sources, and for the Coordinative Learning research cluster, is how students coordinate between multiple representations. Existing theories of multimedia learning (e.g., Mayer, 2001; Schnotz, 2002) assume that successful learning is supported by cognitive processes that operate between separately encoded visual and verbal representations. Laboratory research in learning with scientific diagrams has shown that simplified diagrams support [[retention] and mental model development more than detailed diagrams, and that simplified representations better support integration of textual information (Butcher, 2006). Indeed, other research has found that a multimedia interface that required learners to integrate text labels in a diagram improved knowledge retention and transfer for complex information (Bodemer, Ploetzner, Feuerlein, & Spada, 2004).
Taken together, these studies raise an important question regarding coordinative learning: Is coordination best supported by supporting successful mapping between text and visual information or by the construction of an integrated visual-verbal representation? The current study addresses this question using a 2 (Integrated Hint vs. Standard Hints) X 2 (Contiguous Representation vs. Noncontiguous Representation).
In the current study, successful mapping is supported with Integrated Hints. Integrated Hints use color-coded highlighting to link diagrammatic features to corresponding textual instructional explanations. In geometry, learners must map between relevant text and pictorial representations (e.g., to connect the text "angle ABC" to the visual depiction of this angle in a diagram) as they learn to recognize and apply relevant geometric principles/rules. Thus, one might expect mapping cues to support robust learning by helping students to form an integrated representation of critical knowledge components.
The current study supports construction of an integrated visual-verbal representation with a contiguous problem-solving interface (see [[Contiguous Representations for Robust Learning (Aleven & Butcher). One might expect the contiguous representation to support robust learning in geometry because it eases the cognitive load required to maintain and use the location and value of solved quantities to reason about related features.
Glossary
See Visual-Verbal Learning Project Glossary
Research questions
- Does mapping support in the form of Integrated Hints support students' retention and transfer of knowledge components?
- Do contiguous representations in geometry support students' retention and transfer of knowledge components?
- Are the effects of Integrated Hints or contiguous representations stronger for transfer than for retention?
- Do Integrated Hints and contiguous representations interact in their support for robust learning, as measured by performance on transfer items?
Independent Variables
Dependent variables
- Pretest, normal post-test, and transfer test measuring student performance on:
- Problem-solving items isomorphic to the practiced problems (retention)
- Problem-solving items unlike those seen during problem practice (transfer)
- Generative items testing conceptual knowledge, not practiced in tutor (transfer)
- Log data collected during tutor use, used to assess:
- Learning curves
- Time on task
- Error rates
- Latency of responses
Hypothesis
- Placeholder
Findings (Anticipated)
- Study Summary
Placeholder
Explanation
Placeholder
Further Information
Connections
Interactive Communication as Support for Visual-Verbal Integration:
Our research is investigating multiple methods with which student learning can be supported by interactions with pictorial information during geometry learning. Our work also includes more a more explicit method for supporting student integration visual and verbal knowledge components. This method involves interactive support for students' elaborated explanations during geometry learning. Research investigating this explicit support is part of the Interactive Communication Cluster: LINK
Annotated Bibliography
- Poster from PSLC Advisory Board visit, Fall 2005
- Presentation to NSF Site Visitors, Spring 2006
- Presentation to the PSLC Advisory Board, Fall 2006 Link to Powerpoint slides
References
Placeholder
Future Plans: June 2007 - December 2007
- (Carnegie Learning): Gather log data and assessment data from classrooms.
- (Carnegie Learning): Anonymize log data and assessments, then provide to DataShop
- Score student performance on assessments
- Analyze log data and learning outcomes
- Prepare manuscript
- Integrate results into final project report for PSLC