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SELF-DIRECTED BLENDED LEARNING MODEL ON EMOTIONAL INTELLIGENCE AND ACHIEVEMENT
(2026-01-04)
Liu, Fang
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Sriwisathiyakun, Kanyarat
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Petsangsri, Sirirat
In the era of advancing globalization, developing emotional intelligence (EI) has become essential for adolescents to manage emotional stress, build social relationships, and adapt to changing environments. This study developed a Self-Directed Blended Learning (SDBL) model incorporating Intangible Cultural Heritage music to enhance students' EI and academic achievement. The research was conducted in two phases: First, the SDBL model was designed and validated, consisting of five components (setting learning targets, planning, gathering information, online and offline learning activities, and post-lesson reflection). Five education experts evaluated the model using a 5-point Likert scale, yielding an average score of 4.84, confirming its pedagogical quality. Second, the teaching experiment was conducted at Taiyuan University of Science and Technology. A total of 112 non-music undergraduate students, who voluntarily enrolled in the Shanxi Intangible Cultural Heritage Music Appreciation course, participated in the study. The students were randomly divided into an experimental group and a control group, with 56 students in each. After the intervention, both groups completed post-tests to measure their emotional intelligence and academic achievement. Emotional intelligence was assessed using a revised 25-item version of the Schutte Self-Report Emotional Intelligence Test (SSEIT). Five experts evaluated the test's content validity using the Item-Objective Congruence (IOC) method, with scores ranging from 0.6 to 1. Academic achievement was measured using test items from a nationally recognized Intangible Cultural Heritage (ICH) database maintained by the Chinese government. Five experts reviewed these items, and their IOC scores ranged from 0.8 to 1.0. The collected data were analyzed using t-tests and MANOVA. The results showed that the experimental group performed significantly better than the control group in both emotional intelligence and academic achievement. Additionally, a positive correlation was found between the two variables. The findings demonstrate that SDBL model incorporating Intangible Cultural Heritage music can enhance EI and academic achievement while simultaneously developing cognitive and emotional competencies, offering an innovative solution for preparing students to meet future challenges.
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Integrating generative AI with the flipped classroom teaching model: enhancing emotional well-being and student achievement
(2026-01-01)
Liu, Hanchu
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Sriwisathiyakun, Kanyarat
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Petsangsri, Sirirat
Education in the modern society is undergoing rapid transformation as helping students perform better academically and feel emotionally better has become increasingly important. One way to support this is by using Generative AI (GenAI) in combination with the flipped classroom approach. This study focused on creating and testing a new teaching model called the Generative AI-Integrated Flipped Classroom (GenAI-FC) designed for mental health courses. The research was done in two main parts. In the first part, the GenAI-FC model was developed and its structure was adjusted based on feedback from experts. In the second part, the model was used with students to see how it affected their learning and emotional well-being. The results were promising as five experts reviewed the model and gave it a high-quality score of 4.68 out of 5, showing that it was strong and useful for teaching. Then, the model was tested with 95 first-year university students. After using the model, students showed clear improvement in their exam scores and emotional well-being, based on a standard questionnaire. Both scores were significantly higher after the course compared to before as the results show that the GenAI-FC model can make a real difference by helping students to learn better and also feel more supported. This suggests that using Generative AI in a flipped classroom could be a helpful way to improve education and support students’ mental health at the same time.
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Blended learning with digital story telling model of students in English courses of Chinese primary education: Need assessment analysis
(2025-01-01)
Peng, Lifei
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Petsangsri, Sirirat
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Cui, Jianming
The current study aimed 1) to assess the needs of students in English courses at primary schools in China, focusing on blended learning, digital storytelling, English communication skills, and self-efficacy; 2) to develop blended learning with a digital storytelling model. The researcher employed a stratified random sampling method to select four key public primary schools from ten key public primary schools in Tongren City, China. Furthermore, English teachers from those four selected primary schools were invited to assist in the process of distributing the questionnaires, with 100 students sampled from each school, totaling 400 participants. Descriptive statistical methods were used to analyze the collected data, examining the mean scores across 12 items. Results indicated that the mean values ranged from 3.81 to 4.63. Among these, seven items had mean scores exceeding 4.21, reflecting a high need for elements such as additional online English learning materials, English movies and videos, enhanced speaking skills, and greater confidence in learning English. The remaining five items had mean scores above 3.41, indicating a moderate level of need. Moreover, the blended learning with the digital storytelling model was composed of ten steps, including online and offline activities.
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Enhancing Key Digital Competence in Pre-service Kindergarten Teachers: A Design-Centered SPOC Blended Learning Model
(2025-01-01)
Lu, Lingming
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Sitthiworachart, Jirarat
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Petsangsri, Sirirat
As our world becomes increasingly digital, educators must possess strong digital skills to effectively prepare their students for the future. However, traditional teacher education programs often neglect the cultivation of digital competence. To address this gap, this study developed a Design-Centered SPOC Blended Learning (DCSBL) model to enhance the digital competence of pre-service kindergarten teachers. The DCSBL model integrates elements of blended learning, design-based learning, and digital competency training strategies. A quasiexperimental study was conducted to evaluate the effectiveness of this model. The results indicated that the experimental group, which received DCSBL instruction, significantly outperformed the control group in terms of digital skills achievement (DSA) and Self-evaluation of key digital competence (KDC). Furthermore, qualitative analysis of student reflections revealed that DCSBL stimulated students’ learning motivation, engagement, and sense of achievement. However, the study also highlighted the increased cognitive load and meta-cognitive demands associated with the DCSBL Model. To realize the full potential of competency-based education, teaching assessment must be reformed. The development of digital competence for teachers should be combined with a “micro-certification” system. This approach can provide a more flexible and personalized pathway for educators to acquire and validate their digital skills.
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Blended Learning Needs Analysis of Students in the SPOC Era: Local University Perspective in China
(2025-01-01)
Lu, Lingming
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Sitthiworachart, Jirarat
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Petsangsri, Sirirat
With the development of the new generation of information technology, blended learning has entered the SPOC era, teachers and students can become the designers of the blended course. This also places higher demands on teachers and students' digital competence. Learning needs analysis is the most important step in SPOC-based blended learning. This article takes local university students in China as the survey object, and conducts a questionnaire survey on four aspects: individual learning aspirations, learning process needs, learning environment needs and learning ability gaps. The results show that today's university students have a strong willingness to blended learning, the demand for teaching resources is diversified, the learning process fails to fully give full play to the advantages of blended learning, the teaching evaluation needs to be reformed, and the gap between individuals is large. The study suggests that the current blended teaching should build high-quality learning resources, strengthen the interaction between online and offline teaching, pay more attention to the process and diversity evaluation of students.
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Application of Generative Artificial Intelligence (GenAI) to Enhance English Listening Skill for Undergraduate Chinese Student
(2025-01-01)
Chu, Weifang
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Khwankaew, Apichaya
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Zhao, Shujuan
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Ye, Chuanjian
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Petsangsri, Sirirat
This research aims to develop a GenAI learning activity for English news listening proficiency based on the ADDIE model and to study the effectiveness of the GenAI learning activity on English news listening proficiency for 42 first-year undergraduates of Chuxiong Normal University. This study followed the five steps of the ADDIE model: analysis, design, development, implementation, and evaluation. The data were analyzed using descriptive statistics. The result of the students demonstrating significant improvement in their English listening proficiency, evidenced by the increase in post-test mean scores, was substantial (p < 0.05). Moreover, our learning activity is designed for students to effectively use GenAI to generate pictures, helping them better understand news content and vocabulary in various contexts.
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Integrating Artificial Intelligence in Career Counseling based on Needs Assessment of Chinese Undergraduate Students
(2025-01-01)
Zhou, Kangkang
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Sriwisathiyakun, Kanyarat
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Petsangsri, Sirirat
Purpose: This research focused on the needs of undergraduate students for effective career services in higher education institutes in Nanjing, China. Furthermore, the researcher also developed an AI Career Counseling Platform by integrating AI into a student career counseling service to meet the identified needs of students. Methods: This study consisted of two phases. In the first phase, a needs assessment survey was conducted to identify specific needs, preferences, and challenges of 384 undergraduate students selected by a multistage sampling method in Nanjing City, China. In phase two, the AI Career Counseling Platform was developed and subsequently evaluated by a panel of five experts. Results: Key findings from the needs assessment reveal three areas of particular importance to undergraduate students with a strong need for job-seeking counseling (mean score: 4.75), access to an alumni network (mean score: 4.84), and Entrepreneurship information (mean score: 4.72). Based on these insights, the platform Zhidada was developed. The expert panel further evaluated the platform, categorizing it as "Most Appropriate," with an average score of 4.75 for overall quality and technical development and a content suitability score of 4.74. Implications: This research significantly contributed to advancing the AI Career Counseling Platform by integrating students into career counseling services and expert insights, thus laying a strong foundation for enhancing career services in higher education.
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Effects of Cloud-based Gamified Instruction Integrating Peer Assessment on Primary Students' English Writing and Critical Thinking
(2025-01-01)
Eang, Norphealey
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Petsangsri, Sirirat
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Morris, John
English writing and critical thinking are not only fundamental to academic success but also play a crucial role for the holistic development of primary students. This study investigated the effects of a cloud-based gamified instruction integrating peer assessment on primary student English writing and critical thinking. A pre- and post-test with a delayed pos-test research design was used; thirty-five grade sixth students participated in the study. The research instruments included writing and critical thinking tests. The data were analyzed using repeated measures ANOVA. There was a significant improvement writing from a pre-test through and post-test and delayed post-test (F = 853.76, p < 0.001). The F-value indicated a significant difference between pre- and post-test, but there was little difference between post- and delayed post-tests. The high effect size (η = 0.96) confirmed the effectiveness of the intervention on writing. Similarly, analysis also indicated a significant effect the intervention on the critical thinking improvement over time (F = 632.89, p < 0.001). The high effect size (η = 0.95) emphasized the practical significance of the improvements across the three time points. This confirmed the positive effects of the cloud-based gamified instructional model on writing and critical thinking.
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VIDEO CAMERAS IN DISTANCE CLASSES: EFFECTS ON STUDENT ATTITUDES AND VALIDITY OF MEASUREMENT TOOLS
(2025-01-01)
Alim, Syahrul
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Petsangsri, Sirirat
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Morris, John
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Abdillah, Fairus
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Umar, Muhammad Fitrah Ramadhan
Turning the camera on during online classes is one method to generate two-way interactions between the teacher and the students. The present study seeks to uncover factors that are thought to impact student attitudes. This study explored how demographics influenced student attitudes toward using cameras in distance classes. We analysed data from 388 undergraduates in Indonesia and Thailand. The Mann-Whitney Test, Kruskal-Wallis Test, t-test, and analysis of variance (ANOVA) were used to analyse the data. Results indicated that gender, field of study, GPA, and personality traits affected student attitudes, while ethnicity and religion had no effect on student attitudes. Instrument??? Conclusion???.
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The Use of AI Counselling to Enhance Self-Esteem in the Job Seeking Process for Chinese Undergraduate Students
(2024-01-01)
Petsangsri, Sirirat
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Zhou, Kangkang
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Sriwisathiyakun, Kanyarat
Purpose: This study aimed to find the effectiveness of using AI career counseling platform comprising career guidance, entrepreneurship guidance, Job-seeking guidance and alumni networks to enhance Chinese undergraduate students’ self-esteem in the job seeking process. Methods: One-group pretest-posttest experimental design was utilized in this study, with a group of 60 undergraduate students, selected by purposive sampling method to participate in experiment. Furthermore, dependent t test was used to analyze the obtained data. Results: The result showed that there was a significant difference between pretest and posttest of students’ self-esteem with P value as 0.00, the means score of satisfaction towards AI career counseling platform ranged from 4.35 to 4.58. Implications for research and practice: This study demonstrated that the AI career counseling platform is effective to enhance students’ self-esteem. In addition, the study also showed that students were very satisfied with using AI career counseling platform. Consequently, it is recommended that the AI career counselling platform be sustained and further developed to enhance undergraduate students’ self-esteem in the process of job seeking.

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