This study was conducted to examine English teachers' TPACK perceptions in light of web 2.0 tools usage, workload, and technostress levels. The participants were 170 English teachers and the data were collected using snowball sampling and analyzed by applying MANOVA, and Multiple Regression with descriptive analyses. The results revealed that English teachers have positive TPACK perceptions with a moderate level of technostress and workload and they use web 2.0 tools, although not very often. Considering TPACK perception and web 2.0 tools usage, significant differences were realized based on workload and technostress levels. Teachers with low technostress are more eager to use web 2.0 tools, teachers using more web 2.0 tools have more positive TPACK perceptions and more web 2.0 tools usage increases teachers' workload. Web 2.0 tools usage, workload, and technostress levels are significant predictors of TPACK perception. Implications are discussed in terms of theoretical insights, practices for technology-integrated language learning environments, and further research directions.

Online learning environments contain many of the variables of face-to-face learning environments. However, the inability to be in the same physical environment may cause problems due to the student’s self-management of the process. At this point, self-regulation strategies (hereafter, SRS), also used in face-to-face learning, are essential in improving the process. This study (n=24) aims to present a broad perspective of the studies based on students’ SRS by focusing on online EFL/ESL learning research articles published in the last five (2018-2022) years. The studies determined by a search string and eligibility criteria were included in this systematic review using the PRISMA coding scheme guidelines and MAXQDA was employed for content analysis. 12 strategies were identified (self-evaluation, goal setting, time management, help-seeking, task strategy, environmental structuring, self-efficacy, strategic planning, self-observation/monitoring, self-satisfaction, achievement motivation, effort regulation/persistence) and 15 key attributes were found to support the student’s use of SRS in online language learning environments (motivation, interaction-feedback, metacognition, use of digital tools, pedagogical support, autonomous learning, good learning experience, positive belief, the reflection of the process, self-efficacy, authenticity, scaffolding, cultural interest, critical thinking, the flexibility of time). This study can serve as a guide when designing online environments for self-regulated language learning.