Investigating Trajectories of Learning & Transfer of Problem Solving Expertise from Mathematics to Physics to Engineering
Investigating Trajectories of Learning & Transfer of Problem Solving Expertise from Mathematics to Physics to Engineering
批准号:
0816207
负责人:
N. Sanjay Rebello
金额:
$100.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-01 至 2012-08-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The investigators of the project Measurement, Modeling, and Methods Category are studying how science and engineering students build towards problem solving expertise throughout a major part of their academic careers and how they transfer their knowledge and skills across undergraduate STEM courses. They are observing students' problem across 3 years of courses starting with mathematics and continuing through introduction to physics to engineering courses. The three year research plan consists of longitudinal and cross-sectional studies that take place both in-class and out-of-class and involve 3000 students through seven classes at Kansas State University. The research team is studying the following variables associated with problem solving: the problem features of structuredness, complexity, domain specificity, and dynamicity; problem representation of form, organization, and sequencing; and individual differences of domain knowledge, problem solving experience, reasoning skills, and epistemological maturity. Quantitative data and qualitative evidence are being used to study the variables. An on-line homework system created with previous NSF funding (DUE 0206923) will enable quantitative analysis of the variables with large numbers of students.The data of subjects from underrepresented groups will be analyzed and compared to the larger groups of students. Results of this project are expected to advance the knowledge and understanding of STEM teaching and learning in undergraduate education.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Research on Automated Formative Feedback of Problem-Solving Strategy Writing in Introductory Physics using Natural Language Processing
-
批准号:2300645
-
项目类别:Standard Grant
-
资助金额:$49.98万
-
财政年份:2023
-
负责人:N. Sanjay Rebello
-
依托单位:
Measuring and Modeling Visual Attention in Online Multimedia Instruction
-
批准号:2100218
-
项目类别:Standard Grant
-
资助金额:$47.2万
-
财政年份:2021
-
负责人:N. Sanjay Rebello
-
依托单位:
FIRE: Exploring Visual Cueing to Facilitate Problem Solving in Physics
-
批准号:1138697
-
项目类别:Standard Grant
-
资助金额:$40.0万
-
财政年份:2011
-
负责人:N. Sanjay Rebello
-
依托单位:
Integrating Experimentation and Instrumentation in Upper-Division Physics
-
批准号:0736897
-
项目类别:Standard Grant
-
资助金额:$14.97万
-
财政年份:2008
-
负责人:N. Sanjay Rebello
-
依托单位:
PECASE: Research on Students' Mental Models, Learning and Transfer as a Guide to Application-Based Curriculum Development and Instruction in Physics
-
批准号:0133621
-
项目类别:Continuing Grant
-
资助金额:$0.0万
-
财政年份:2002
-
负责人:N. Sanjay Rebello
-
依托单位:
Implementing the Workshop Model and other Research-based Instructional Strategies in Physics & Mathematics Courses
-
批准号:9951402
-
项目类别:Standard Grant
-
资助金额:$8.12万
-
财政年份:1999
-
负责人:N. Sanjay Rebello
-
依托单位:
海外基金