Adaptive Micro-Learning Model Based on Dhamma Using Mixed Reality to Develop Students to Be Good Citizens
Saved in:
| Title: | Adaptive Micro-Learning Model Based on Dhamma Using Mixed Reality to Develop Students to Be Good Citizens |
|---|---|
| Language: | English |
| Authors: | Kitiya Promsron, Prachyanun Nilsook, Pallop Piriyasurawong |
| Source: | International Education Studies. 2025 18(2):123-136. |
| Availability: | Canadian Center of Science and Education. 1595 Sixteenth Ave Suite 301, Richmond Hill, Ontario, L4B 3N9 Canada. Tel: 416-642-2606 Ext 206; Fax: 416-642-2608; e-mail: ies@ccsenet.org; Web site: http://www.ccsenet.org/journal/index.php/ies |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Junior High Schools Middle Schools Secondary Education Elementary Education Grade 6 Intermediate Grades |
| Descriptors: | Learning Activities, Electronic Learning, Learning Modules, Citizenship Education, Prosocial Behavior, Student Development, Altruism, Sharing Behavior, Expertise, Middle School Students, Grade 6, Academic Achievement, Prior Learning, Learning Objectives, Buddhism, Religious Factors, Cooperative Learning, Peer Teaching, Video Technology, COVID-19, Pandemics |
| ISSN: | 1913-9020 1913-9039 |
| Abstract: | The COVID-19 pandemic forced school closures globally, leading to significant learning regression in academic performance, skills, and ethical development. This study aims to: 1) synthesize and develop an adaptive micro-learning model based on Dhamma principles using mixed reality (MR), 2) compare pre- and post-test results, and 3) assess the model's impact on students' good citizenship. Participants included 19 experts and 39 Grade 6 students. The methodology involved synthesizing and developing an adaptive micro-learning model, comparing pre- and post-study scores, and evaluating academic achievement and good citizenship development. The study identified seven key steps in the adaptive micro-learning model: 1) testing prior knowledge (Dhammannuta), 2) reporting prior knowledge results (Atthanyuta), 3) explaining learning objectives (Attanyuta), 4) outlining the learning path (Mattanyuta), 5) video-based learning (Kalanyuta), 6) collaborative learning via MR (Parisanyuta), and 7) peer knowledge exchange (Pukkalanyuta). The model's effectiveness was rated highly ([x-bar] = 4.78, S.D. = 0.34). Students' good citizenship scores significantly improved, increasing from a pre-test average of 15.87 points (52.90%) to a post-test average of 25.72 points (85.73%), with statistical significance at the 0.01 level. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1465085 |
| Database: | ERIC |
| Abstract: | The COVID-19 pandemic forced school closures globally, leading to significant learning regression in academic performance, skills, and ethical development. This study aims to: 1) synthesize and develop an adaptive micro-learning model based on Dhamma principles using mixed reality (MR), 2) compare pre- and post-test results, and 3) assess the model's impact on students' good citizenship. Participants included 19 experts and 39 Grade 6 students. The methodology involved synthesizing and developing an adaptive micro-learning model, comparing pre- and post-study scores, and evaluating academic achievement and good citizenship development. The study identified seven key steps in the adaptive micro-learning model: 1) testing prior knowledge (Dhammannuta), 2) reporting prior knowledge results (Atthanyuta), 3) explaining learning objectives (Attanyuta), 4) outlining the learning path (Mattanyuta), 5) video-based learning (Kalanyuta), 6) collaborative learning via MR (Parisanyuta), and 7) peer knowledge exchange (Pukkalanyuta). The model's effectiveness was rated highly ([x-bar] = 4.78, S.D. = 0.34). Students' good citizenship scores significantly improved, increasing from a pre-test average of 15.87 points (52.90%) to a post-test average of 25.72 points (85.73%), with statistical significance at the 0.01 level. |
|---|---|
| ISSN: | 1913-9020 1913-9039 |