Understanding the relationship between student attitudes and student learning

Abstract

Student attitudes, defined as the extent to which one holds expertlike beliefs about and approaches to physics, are a major research topic in physics education research. An implicit but rarely tested assumption underlying much of this research is that student attitudes play a significant part in student learning and performance. The current study directly tested this attitude-learning link by measuring the association between incoming attitudes (Colorado Learning Attitudes about Science Survey) and student learning during the semester after statistically controlling for the effects of prior knowledge [early-semester Force Concept Inventory (FCI) or Brief Electricity and Magnetism Assessment (BEMA)]. This study spanned four different courses and included two complementary measures of student knowledge: late-semester concept inventory scores (FCI or BEMA) and exam averages. In three of the four courses, after controlling for prior knowledge, attitudes significantly predicted both late-semester concept inventory scores and exam averages, but in all cases these attitudes explained only a small amount of variance in concept-inventory and exam scores. Results indicate that after accounting for students' incoming knowledge, attitudes may uniquely but modestly relate to how much students learn and how well they perform in the course.

Validity of Colorado Learning Attitudes about Science Survey for a high-achieving, Finnish population

“…In many cases, students even know what physicists would say in the situations probed, but do not agree with them [1]. In addition to being important in themselves, attitudes that align with experts also somewhat predict learning [2][3][4][5]. Instruments such as Views about Science Survey (VASS) [6], Maryland Expectations about Science Survey (MPEX) [7], and the Colorado Learning Attitudes about Science Survey (CLASS) [8] have been developed to measure these attitudes.…”

“…Cahill et al [12] identified two categories for learning, using 25 statements, and proceeded to validate those with a confirmatory factor analysis (CFA). CLASS scores have been found to correlate weakly with learning outcomes [2,4,5] and experiencing high levels of challenge, interest, and skill at the same time (optimal learning moments) [13].…”

Structure Building Predicts Grades in College Psychology and Biology

“…More targeted predictors focus on what knowledge and skills a student needs to succeed in a particular subject matter, such as the Force Concept Inventory (FCI). This inventory measures student understanding of force and related kinematics, and correlates with performance in introductory physics classes at both the high school and university levels (Hestenes, Wells, & Swackhamer, ; Savinainen & Scott, ; see also Cahill et al, , extending these findings to second semester introductory university courses, using the Brief Electricity and Magnetism Assessment [BEMA] as a predictor of course performance). However, while such measures can be extremely useful within specific classes, they are limited in their ability to generalize across subject areas.…”

Combining Surveys and Sensors to Explore Student Behaviour

“…These expert-like beliefs are often seen as a desired learning goal as such. They have also been shown to correlate weakly with learning [28][29][30]. They also correlate with experiencing high levels of challenge, interest and skill at the same time (optimal learning moments) [31].…”