Analysis of the Learning Models Needs in Hybrid Class Microteaching to Improve the Teaching Competencies
Bibliographic Data
| ID | 22122453 |
|---|---|
| Authors | Deskoni Deskoni (Sriwijaya University), Alfiandra Alfiandra (Sriwijaya University), Syafrudin Yusuf (Sriwijaya University), Yudi Pratama (0000-0003-3960-5173, Sriwijaya University), Diki Tri Apriansyah Putra (0000-0001-9728-182X, Sriwijaya University) |
| Year | 2023 |
| Volume | 10 |
| Issue | 12 |
| Pages | 541 |
| Publication date | 2023-12-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Multicultural and Multireligious Understanding (JOURNAL) |
| Journal identifiers | ISSN: 2364-5369 • E-ISSN: 2364-5369 |
| Publisher | Multidisciplinary Center (PUBLISHER) |
| DOI | 10.18415/ijmmu.v10i12.5238 |
| OpenAlex | W4390395106 |
| Language | EN |
| References cited | 1 |
The purpose of this study is to analyze the need for learning models in microteaching courses for hybrid learning environments. Quantitative descriptive techniques are the research methods used; these techniques are intended to use quantitative data to describe and analyze specific phenomena or variables in the population. This approach aims to give an accurate picture of the situation or phenomenon under study rather than to test a hypothesis or bring about change. At this point, 80 enrolled in the Economics Study Program at Sriwijaya University will participate in a survey that takes the form of a questionnaire administered by researchers to fifth-semester students. The study's findings demonstrate the continued need for high-quality instruction in hybrid classes for microteaching courses. This study includes the development of an efficient learning model for hybrid classes as well as the utilization of current technology to foster a positive microteaching environment in newly created hybrid class
Descriptive statistics · Mathematics education · Medical education · Microteaching · Population · Statistics · Teaching method · Computer Science · E-Learning and COVID-19 · Mathematics · Medicine · Online and Blended Learning · Psychology · Technology-Enhanced Education Studies · Artificial Intelligence
| Highly cited | No |
|---|