Adaptive support for representational competencies during technology-based problem solving in chemistry
Bibliographic Data
| ID | 21633096 |
|---|---|
| Authors | Martina A Rau (0000-0001-7204-3403, University of Wisconsin–Madison, corresponding author), Miranda Zahn (0000-0002-2527-1750, University of Wisconsin–Madison), Edward Misback (0009-0003-9474-0826, University of Wisconsin–Madison), Tiffany Herder (0000-0002-9683-3992, University of Wisconsin–Madison), Judith Burstyn (University of Wisconsin–Madison), Judith N Burstyn (0000-0003-3245-5563, University of Wisconsin–Madison) |
| Year | 2021 |
| Volume | 30 |
| Issue | 2 |
| Pages | 163-203 |
| Publication date | 2021-03-15 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of the Learning Sciences (JOURNAL) |
| Journal identifiers | ISSN: 1050-8406 • E-ISSN: 1532-7809 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10508406.2021.1888733 |
| OpenAlex | W3139226479 |
| Language | EN |
| Citations received | 8 |
| References cited | 66 |
Background: A key aspect of STEM learning is the use of visual representations for problem solving. To successfully use visuals, students need to make sense of how they show concepts and to fluently perceive domain-relevan information in them. Adding support for sense making and perceptual fluency to problem-solving activities enhances students’ learning of content knowledge. However, students need different types of representational-competency supports, depending on their prior knowledge. This suggests that adaptively assigning students to sense-makingand perceptual-fluency support might be more effective than assigning all students to the same sequence of these supports.Method: We tested this hypothesis in an experiment with 44 undergraduate students in a chemistry course. Students were randomly assigned to a ten-week sequence of problem-solving activities that either provided a fixed sequence of sense-making support and perceptual-fluency support or adaptively assigned these supports based on students’ problem-solving interactions.Findings: Results show that adaptive representational-competency supports reduced students’ confusion and mistakes during problem solving while increasing their learning of content knowledge.Contribution: Our study is the first to show that adaptive support for representational competencies can significantly enhance learning of content knowledge. Given the pervasiveness of visuals, our results may inform general STEM instruction
Cognitive psychology · Confusion · Fluency · Mathematics education · Perception · Sequence learning · Chemistry · Computer Science · Innovative Teaching and Learning Methods · Psychology · Science Education and Pedagogy · Visual and Cognitive Learning Processes · Artificial Intelligence
Performance and learning differences inside and outside Immersive virtual learning (IVR)
Measuring representational competence – analyses of dimensionality and the relationship to general content knowledge
Technology‐Embedded Argument‐DrivenInquiry in Preservice Chemistry Teacher Education
Representational-competency supports in the context of an educational video game for undergraduate astronomy
Inoculating students against misleading data visualizations with perceptual training and informative feedback
The effectiveness of personalized technology-enhanced learning in higher education
Improving participation equity in dialogic collaborative problem solving
Analysing students' concept mapping style and its association with task performance in computer‐based inquiry learning
Learning by Collaborating
The Knowledge‐Learning‐Instruction Framework
Construction and interference in learning from multiple representation
Active‐Constructive‐Interactive
The Expertise Reversal Effect
Eliciting Self‐Explanations Improves Understanding
Self‐Explanations
The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems
Structure‐Mapping
DeFT
Why a Diagram is (Sometimes) Worth Ten Thousand Words
Why Minimal Guidance During Instruction Does Not Work
The Cambridge Handbook of the Learning Sciences
Perceptual learning and the technology of expertise Studies in fraction learning and algebra
Mind over machine
Perceptual Learning in Development
| Citations per year | 2 |
|---|---|
| Citation span | 2022 - 2026 (5) |
| Highly cited | No |