Classical mechanics experiment using smartphone sensors to train science process skills
Science process skills are indispensable for science students at various levels of education. Science process skills can be trained through experimental activities. In the current pandemic era, experimental activities must allow science students to do it independently in their respective homes witho...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Conference or Workshop Item |
Published: |
2023
|
Subjects: | |
Online Access: | http://eprints.utm.my/108020/ http://dx.doi.org/10.1063/5.0125916 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.108020 |
---|---|
record_format |
eprints |
spelling |
my.utm.1080202024-10-16T07:49:44Z http://eprints.utm.my/108020/ Classical mechanics experiment using smartphone sensors to train science process skills Prasetyo Listiaji, Prasetyo Listiaji Novi Ratna Dewi, Novi Ratna Dewi Arka Yanitama, Arka Yanitama Abdul Rahman, Nor Farahwahidah H Social Sciences (General) Science process skills are indispensable for science students at various levels of education. Science process skills can be trained through experimental activities. In the current pandemic era, experimental activities must allow science students to do it independently in their respective homes without going to campus laboratories. Smartphone sensors have the potential to be used as tools in science experiments because they are easy and flexible to do anywhere. This research was focused on developing classical mechanics experiments using smartphone sensors to train science process skills. Development was carried out using the ADDIE model. The product was an experimental handbook intended for science students at universities. The experimental handbook was developed based on the science process skills approach. The results of expert validation on handbook obtained valid criteria. The product was implemented in the Fundamental Physics course in the Science Education Study Program. In the implementation stage, science process skills of science students obtained results 15.38 % low, 65.38 % medium, and 19.24 % high. Based on these results, classical mechanics experiments using smartphone sensors can train science process skills. Science students can acquire science process skills through experiments they do at home. So that classical mechanics experiments using smartphone sensors can be an offer to be applied in universities during the pandemic era. 2023 Conference or Workshop Item PeerReviewed Prasetyo Listiaji, Prasetyo Listiaji and Novi Ratna Dewi, Novi Ratna Dewi and Arka Yanitama, Arka Yanitama and Abdul Rahman, Nor Farahwahidah (2023) Classical mechanics experiment using smartphone sensors to train science process skills. In: 8th International Conference on Mathematics, Science and Education, ICMSE 2021, 5 October 2021-6 October 2021, Virtual, Online, Semarang, Indonesia. http://dx.doi.org/10.1063/5.0125916 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
topic |
H Social Sciences (General) |
spellingShingle |
H Social Sciences (General) Prasetyo Listiaji, Prasetyo Listiaji Novi Ratna Dewi, Novi Ratna Dewi Arka Yanitama, Arka Yanitama Abdul Rahman, Nor Farahwahidah Classical mechanics experiment using smartphone sensors to train science process skills |
description |
Science process skills are indispensable for science students at various levels of education. Science process skills can be trained through experimental activities. In the current pandemic era, experimental activities must allow science students to do it independently in their respective homes without going to campus laboratories. Smartphone sensors have the potential to be used as tools in science experiments because they are easy and flexible to do anywhere. This research was focused on developing classical mechanics experiments using smartphone sensors to train science process skills. Development was carried out using the ADDIE model. The product was an experimental handbook intended for science students at universities. The experimental handbook was developed based on the science process skills approach. The results of expert validation on handbook obtained valid criteria. The product was implemented in the Fundamental Physics course in the Science Education Study Program. In the implementation stage, science process skills of science students obtained results 15.38 % low, 65.38 % medium, and 19.24 % high. Based on these results, classical mechanics experiments using smartphone sensors can train science process skills. Science students can acquire science process skills through experiments they do at home. So that classical mechanics experiments using smartphone sensors can be an offer to be applied in universities during the pandemic era. |
format |
Conference or Workshop Item |
author |
Prasetyo Listiaji, Prasetyo Listiaji Novi Ratna Dewi, Novi Ratna Dewi Arka Yanitama, Arka Yanitama Abdul Rahman, Nor Farahwahidah |
author_facet |
Prasetyo Listiaji, Prasetyo Listiaji Novi Ratna Dewi, Novi Ratna Dewi Arka Yanitama, Arka Yanitama Abdul Rahman, Nor Farahwahidah |
author_sort |
Prasetyo Listiaji, Prasetyo Listiaji |
title |
Classical mechanics experiment using smartphone sensors to train science process skills |
title_short |
Classical mechanics experiment using smartphone sensors to train science process skills |
title_full |
Classical mechanics experiment using smartphone sensors to train science process skills |
title_fullStr |
Classical mechanics experiment using smartphone sensors to train science process skills |
title_full_unstemmed |
Classical mechanics experiment using smartphone sensors to train science process skills |
title_sort |
classical mechanics experiment using smartphone sensors to train science process skills |
publishDate |
2023 |
url |
http://eprints.utm.my/108020/ http://dx.doi.org/10.1063/5.0125916 |
_version_ |
1814043580442869760 |
score |
13.209306 |