Making Learning Real: Design Principles and Evidence for Applied Learning in Schools
Category: Student Learning
Instrument Overview
Expert Notes AvailableView expert commentary on strengths and cautions for this instrument
Strengths
Sensitive to differences following instruction, meaning it can be used to collect evidence of whether an instructional intervention increased programming and physics self-efficacy.
Cautions
Limited validation outside Taiwanese students and interdisciplinary computational physics; not established for predicting achievement or evaluating programs more broadly.
The Self-Efficacy for Programming and Physics measure is a self-report questionnaire designed to assess students’ confidence in their ability to use programming and physics skills in a modeling-based learning context. It focuses on self-efficacy for tasks involved in representing and solving physics problems through programming, including abstraction, coding, and physics modeling.
The measure can be used in education research to examine students’ confidence in programming and physics and how it changes in response to STEM instruction. In Ling, Wang, & Wu (2019) the questionnaire was administered as part of a quasi-experimental study of modeling-based physics programming. Students who received the modeling-based instruction showed higher self-efficacy for modeling as well as stronger programming and physics achievement.
Organization
Topic
Collection Category(ies)
Content
Grades
Post secondary
Respondent
Student
Administration Information
Length
35 items
Psychometrics (additional guidance)
Reliability
(Cronbach's alpha)
Self-efficacy for programming: 0.726
Self-efficacy for physics: 0.775
Perceptions of programming: 0.614
Perceptions of physics learning: 0.714
Perceptions of STEM instruction: 0.813
Interests in learning programming: 0.867
Interest in physics: 0.885 and
Self-efficacy for modelling: 0.843
