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1.
2023 11th International Conference on Information and Education Technology, ICIET 2023 ; : 391-394, 2023.
Artigo em Inglês | Scopus | ID: covidwho-20241561

RESUMO

Distress in online learning issues that have caused student stress, burnout and influenced student motivation achievement in the post-COVID-19 pandemic. The survey's primary purpose was to understand the effect of academic stress, burnout, and resilience on student achievement motivation. It consisted of 152 participants of Thai and international students who filled out the questionnaires. The data were analyzed utilizing SPSS (demographic data) and Smart PLS 3. The results denoted a direct and significant influence of academic stress on burnout and resilience on achievement motivation, a positive and insignificant impact of stress on resilience and burnout on achievement motivation, and a negative and non-significant influence of stress on achievement motivation and burnout on resilience. © 2023 IEEE.

2.
Emerging Science Journal ; 6(Special Issue):1-12, 2022.
Artigo em Inglês | Scopus | ID: covidwho-1988926

RESUMO

Problem-solving skill is one of the soft skills that has become essential for employees in various organizations. Training model and educational technology were considered key success factors in delivering knowledge for personnel in the workplace to develop this skill. Problem-Based Learning (PBL) is a key driver for learning activities, which has been increasingly adopted for workplace training and has proven to be one of the best approaches to helping learners improve their problem-solving skills in the organization. Hence, this research aims to synthesize problem-based blended training via chatbot to enhance problem-solving skills in the workplace. Literature review, document analysis, and focus group technique were used as the main procedures for the first phase of model synthesis. The effectiveness of the training model was examined in the second phase by applying it to 20 employees of the flexible lamination manufacturers in Thailand from purposive sampling. The training was held for four weeks and examined with a problem-solving skill test. In addition, a follow-up test has been conducted to monitor retention skills after a four-week training period. Data analysis used the repeated-measures ANOVA test with normality and homogeneity as a prerequisite test. This study shows that the problem-based blended training model via chatbot to enhance problem-solving skills in the workplace comprises six main steps: (1) Group identification;(2) Problem identification;(3) Idea creation;(4) Learning;(5) Implementation;(6) Evaluation. The results on the implemented training model showed that problem-solving skills after training were significantly higher than those before training, and the retention of skill remained higher than that before training and did not significantly change after finishing training at a statistical significance of 0.5. As a result, the developed model is highly appropriate for implementation, particularly because the chatbot platform is involved in almost every step of this training model to accommodate learners who can easily access the training platform, repeat the training content, and feel motivated to explore new information to improve their problem-solving skills. In a post-COVID-19 period with distancing required in the workplace, this model is applicable to deliver efficiency in workplace training. © 2022 by the authors.

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