How Students Use Statistical Computing in Problem Solving

As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these to...

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Veröffentlicht in:Journal of statistics and data science education Jg. 29; H. S1; S. S145 - S156
Hauptverfasser: Woodard, Victoria, Lee, Hollylynne
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Alexandria Taylor & Francis 2021
Taylor & Francis Ltd
Taylor & Francis Group
Schlagworte:
Assessment
Automation
Calculators
Cognition & reasoning
Cognitive Ability
Cognitive load
Cognitive Processes
College Science
Computational mathematics
Computer Software
Curricula
Curriculum Design
Data Analysis
Data science
Decision making
Educational Technology
Evaluative Thinking
Influence of Technology
Learning
Mathematics Education
Outcomes of Education
Pattern recognition
Problem solving
Programming Languages
Science Curriculum
Science education
Science Instruction
Short Term Memory
Software
Statistical Analysis
Statistical computing
Statistical Data
Student Evaluation
Student Needs
Students
ISSN:2693-9169, 2693-9169
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Zusammenfassung:As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well defined. As such, a framework to assess statistical computing actions was created. Using task-based interviews of students who completed a second course in statistics, the framework was used to determine the ways in which students utilize statistical computing tools, specifically R, while going through problem solving phases. Patterns that emerged are discussed. Supplementary materials for this article are available online.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2693-9169
2693-9169
DOI:10.1080/10691898.2020.1847007