Emotions and self-efficacy toward simple machines learning through a STEM practice

Introduction This study explores the impact of an interactive physics class on the emotions and self-efficacy of elementary education students, specifically in their future roles as educators using STEM-based pedagogical methods. The research aims to understand how such an approach affects students’ emotional responses and confidence in teaching STEM topics. Methods The sample included 97 fourth-year prospective elementary teachers. Participants completed pretests and posttests measuring emotions and self-efficacy related to both course content and the pedagogical approach. Results Findings indicated a significant increase in both positive emotions and self-efficacy following the interactive class. Male students reported higher levels of positive emotions and self-efficacy than their female peers. Furthermore, students with backgrounds in sciences and technology showed greater improvement compared to those from social science backgrounds. A positive correlation between emotions and self-efficacy was observed. Discussion The manipulative, collaborative, and interdisciplinary nature of the physics class likely contributed to the observed positive changes in emotions and self-efficacy. Network analysis suggested that reducing boredom could enhance emotional responses, given its role in affecting both positive and negative emotions. On the other hand, it has been observed that uncertainty could be beneficial in STEM activities due to their relationship with self-efficacy.

Authors

Institutions

Publication Details

Journal
Frontiers in Education
Published
2024-11-13
DOI
https://doi.org/10.3389/feduc.2024.1393711
Citations
2
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Emotions and self-efficacy toward simple machines learning through a STEM practice

Aurora Muñoz‐Losa, José María Merino
2 citations
Frontiers in Education
Online Learning and Analytics
0.82
article

Emotions and self-efficacy toward simple machines learning through a STEM practice

Aurora Muñoz‐Losa, José María Merino
article en
2 citations

Abstract

Introduction This study explores the impact of an interactive physics class on the emotions and self-efficacy of elementary education students, specifically in their future roles as educators using STEM-based pedagogical methods. The research aims to understand how such an approach affects students’ emotional responses and confidence in teaching STEM topics. Methods The sample included 97 fourth-year prospective elementary teachers. Participants completed pretests and posttests measuring emotions and self-efficacy related to both course content and the pedagogical approach. Results Findings indicated a significant increase in both positive emotions and self-efficacy following the interactive class. Male students reported higher levels of positive emotions and self-efficacy than their female peers. Furthermore, students with backgrounds in sciences and technology showed greater improvement compared to those from social science backgrounds. A positive correlation between emotions and self-efficacy was observed. Discussion The manipulative, collaborative, and interdisciplinary nature of the physics class likely contributed to the observed positive changes in emotions and self-efficacy. Network analysis suggested that reducing boredom could enhance emotional responses, given its role in affecting both positive and negative emotions. On the other hand, it has been observed that uncertainty could be beneficial in STEM activities due to their relationship with self-efficacy.

Frontiers in EducationVol. 9
Universidad de Extremadura (ES)
Quality Education
Openalex Percentile: Top 18%
Online Learning and Analytics
0.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.