Factors Influencing Students’ Attitudes and Readiness towards Active Online Learning in Physics
Bibliographic Data
| ID | 22048181 |
|---|---|
| Authors | Lorna Uden (0000-0002-8598-7355, University of Staffordshire), Fauziah Sulaiman (0000-0001-9584-0421, Universiti of Malaysia Sabah, corresponding author), Ronald Francis Lamun (Science Department, Labuan Matriculation College, Labuan Federal Territory 87000, Malaysia) |
| Year | 2022 |
| Volume | 12 |
| Issue | 11 |
| Pages | 746 |
| Publication date | 2022-10-26 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci12110746 |
| OpenAlex | W4307552399 |
| Language | EN |
| Citations received | 3 |
| References cited | 44 |
Many factors can influence students’ attitudes and their readiness to learn, especially with respect to learning physics online. Traditional online learning, where the teacher is the sole speaker, is inappropriate for learning physics because there must be live demonstrations and activities connecting theories with real world experiences. Online learning for physics must be active and engaging. Students would find the traditional form of online instruction difficult, because there is no physical social interaction between teacher and students. In our teaching work, we have found that factors such as computer skills/ICT skills, learning preferences, prior knowledge and motivation are important for students’ learning. What are the perceptions and attitudes of learners regarding these factors? The aim of this paper is to investigate the attitudes of students’ responses to computer/ICT skills, learning preferences, prior knowledge, and motivation pre-online learning and post-online learning in a case study. The research used a hierarchical regression for data analysis across a sample of young respondents who studied physics at Labuan Matriculation College, i.e., pre-university, in year one of their enrolment. The study involved two phases. A survey was conducted to assess the attitudes of the students prior to the implementation of active online learning. The pre-survey results showed that students considered learning preference and motivation to be important factors that would influence their active online learning. Post-survey responses and views communicated after completion of the learning revealed that all four factors have positive influence in their learning. Principles from neuroscience were used to explain why these four factors were important. The paper also provides guidelines on how teachers can use principles from neuroscience to help students to improve active online learning based on these four factors
Educational technology · Mathematics education · Perception · Preference · Computer Science · Education and Critical Thinking Development · Innovative Teaching Methods · Mathematics · Neuroscience, Education and Cognitive Function · Psychology · Artificial Intelligence
Motivating Students to Learn
Examining the relationship among student perception of support, course satisfaction, and learning outcomes in online learning
Neuroscience and education
Improved Learning in a Large-Enrollment Physics Class
Factors affecting the attitudes of students towards learning English as a foreign language
Intrinsic and Extrinsic Motivational Orientations in the Classroom
The role of knowledge in discourse comprehension
Active learning increases student performance in science, engineering, and mathematics
Active Learning to Improve Student Learning Experiences in an Online Postgraduate Course
Exploring Alternative Ways of Assessing Prior Knowledge, Its Components and Their Relation to Student Achievement
A multivariate analysis of students' experience of web based learning
Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being
Does Everyone’s Motivational Beliefs about Physical Science Decline in Secondary School
Intrinsic and Extrinsic Motivations
| Citations per year | 0.75 |
|---|---|
| Citation span | 2022 - 2025 (4) |
| Highly cited | No |