Online learning may lead to several problems, causing academic stress that lowers student motivation. Thus, great instructor skills are needed to overcome challenges and automatically build a successful and efficient online learning process. The study examines how teacher competencies in four dimensions – Teacher’s technological pedagogical content knowledge (TPACK), teacher’s belief (TB), teacher’s self-efficacy (TSE), and teacher’s enthusiasm (TE) – affect students’ academic stress in the cognitive (CD), behavioral (BD), affective (AD), and physiological domains (PD), as well as learning motivation (SLM) and academic achievement (AA). The study uses multivariate regression analysis, the ordinal logistic regression, and the Structural Equation Model (SEM). Multivariate regression analysis is utilized to examine the effects partially and simultaneously of dependent and independent variables. The ordinal logistic regression is used for the same purpose but on the data with an ordinal scale; the final grade shows the AA variable. Whereas, SEM is used to investigate the relationship between complex variables. The sample retrieval technique is conducted using non-probabilistic sampling by the method of accidental sampling with 219 college students. Results show that TPACK, which is one dimension of a teacher’s competencies, negatively affects students’ academic stress, which is BD, AD, and PD. However, TPACK does not significantly affect CD. Adverse effects suggest increasing teacher’s competencies in integrating technology and pedagogies in the development of educational content, especially in online learning, and reducing or minimizing students’ academic stress. Besides that, TPACK also has a positive effect on SLM, and SLM in turn positively affects AA. On the other hand, the variable component of teachers’ competencies, such as TSE and TE, has a positive effect on CD. Likewise, CD positively affects AA, so indirectly, TSE and TE positively affect AA. Of every effect and relationship between independent and dependent variables studied, the variable to contribute most effectively to online learning is the TPACK variable. Keywords: online teaching, teacher’s competencies, student’s academic stress, student’s learning motivation, academic achievement, TPACK, SEM, multivariate regression, logistic ordinal regression
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