(This paper was used as the core of a project presented to the NSF in the form of a proposal for The NSF 2026 Idea Machine)
or a short video).
Nowadays MOCCs represent the most accurate instrument for classification of physics problems and developing a tool for objective measuring learning outcomes of students taking physics courses. The same principle also can be used for developing an analogues tool for measuring learning outcomes of student taking any STEM course.
All like problems have a MOCC with the same vertices but different links used to solve a problem. Each MOCC describes a set of like problems. Each like problem (in general – any problem) can be stated in a general (i.e. abstract) language which does not depend on the specific physical situation describe in the problem (click here for the example). A problem which is stated in a general language and which is like to all problems in a set of like problems is the root problem of the set; any specific problem in a set can be seen as a variation of the root problem.
Dr. Valentin Voroshilov
Education Advancement Professionals
The links to all six my applications to the NSF 2026 Big Idea Machine (from August 31, 2018 to October 26, 2018):
1. Entry125253: High Frequency Data Streams in Education
2. Entry124656: objective measures of physics knowledge
3. Entry125317: National database teacher PD
4. Entry124655: role of NSF in funding education
5. Entry125719: The new type of a science course for science teachers.
6. Entry126205: The development of the uniform standard for measuring content knowledge in physics.
To learn more about my professional experience:
The voices of my students
"The Backpack Full of Cahs": pointing at a problem, not offering a solution
Essentials of Teaching Science
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