Abstract:Increasing research on teacher professional development (TPD) has found teachers' self-reflection to be key for improving teaching effectiveness. Although video methodology, as often used in TPD, provides crucial insight concerning situated learning, teachers are often reticent to participate in TPD protocols due to discomfort over being videotaped. This longitudinal study explored emotion-related behaviors by assessing the nonverbal expressions exhibited by teachers during a 1-year videobased TPD program high… Show more
“…Affective state can be a critical mediator of teachers' attention, motivation and cognitive participation influencing how they engage in TPD type activities, including those which involve viewing of video from their own classrooms (Pekrun, 2006;C.-F. Chang et al, 2018). We have not been able to locate any studies on teachers' emotional responses to 360-degree video of their own classrooms.…”
“…Affective state can be a critical mediator of teachers' attention, motivation and cognitive participation influencing how they engage in TPD type activities, including those which involve viewing of video from their own classrooms (Pekrun, 2006;C.-F. Chang et al, 2018). We have not been able to locate any studies on teachers' emotional responses to 360-degree video of their own classrooms.…”
“…Previous research has focused on the emotions generated by teachers' interactions with partners in PD (Borko et al, 2008;10.3389/fpsyg.2022.1033988 Frontiers in Psychology 04 frontiersin.org Kleinknecht and Schneider, 2013;Parr and Hawe, 2017;Chang et al, 2018), with the interactions primarily taking the form of video-based teaching observation, discussion, and reflection. For example, Kleinknecht and Schneider (2013) showed that othersviewing corresponds to a more profound analysis of problematic events and higher emotional engagement, such as disappointment and anger, in their study of five pairs of mathematics teachers independently analyzing teaching video processes in a web-based environment.…”
Section: Teacher Emotions In Professional Development Programsmentioning
confidence: 99%
“…The findings also revealed that self-viewing necessitates more pre-existing scaffolding than others-viewing. In contrast, the emotions generated by teacher–mentor interactions have piqued the interest of only a few scholars ( Chang et al, 2018 ; Sun and Yang, 2021 ). Sun and Yang (2021) found in their study that teachers in PD felt confident when they received expert guidance and felt anxious when they believed they could not perform well.…”
Section: Literature Reviewmentioning
confidence: 99%
“…This distinction is necessary from a research perspective. Because teacher identity develops after participating in a PD program, shifting from custodians or imparters of existing knowledge to learners of content knowledge or pedagogical knowledge that PD points to, the disruption and reconstruction of identity bring new emotions ( Kleinknecht and Schneider, 2013 ; Chang et al, 2018 ), such as vulnerability ( Yoo and Carter, 2017 ). Furthermore, in PD programs, teachers’ interactions with mentors and companions are also more different from those of colleagues and administrators at the school level; rich and particular emotions can arise from these interactions ( Borko et al, 2008 ; Kleinknecht and Schneider, 2013 ; Chang et al, 2018 ; Weddle et al, 2019 ).…”
Teacher emotions are essential for teaching effectiveness and teachers’ professional development. Studying teacher emotions during a program in today’s world is crucial, where teachers are commonly involved in professional development programs. From an ecological perspective, this study employed a case study method to examine the emotions of two Chinese high school mathematics teachers in a 4-year teaching improvement program. Semi-structured interviews, teacher emotion logs, researcher memos, and informal dialogues were all used to collect data. This study aimed to better understand the emotions that Chinese high school mathematics teachers developed and the processes that generated them in their interactions with various ecosystems within a specific professional development program overlay. The study’s findings revealed that the two teachers triggered 65 emotions in their interactions with the various ecosystems over 4 years—A describing 51 and B describing 46—with an overall predominance of positive emotions. They triggered the broadest range of emotions in the mesosystem, particularly during interactions with program companions. During the early, medium, and late stages, their internal psychological factors and interactions with each system changed, resulting in significant changes in their emotions. They all went through phases of mixed sadness and happiness, ending in a state of delight and calmness. Finally, we recommended teachers’ professional development based on the study’s findings.
“…In the field of teacher professional development, we found that more and more research is focusing on teachers' learning processes, especially incorporating physiological and psychological data. For example, Chang et al (2018) explored teachers' emotional experiences by coding the nonverbal expressions of their recorded videos. Wolff et al (2016) investigated differences in how expert and novice teachers perceive problematic classroom scenes with eye-tracking technology.…”
Teachers’ engagement in online learning is a key factor in improving the effectiveness of online teacher training. This paper introduces a multimodal learning analytics approach that uses data on brain waves, eye movements and facial expressions to predict in-service teachers’ engagement and learning outcomes in online synchronous training. This study analyzed to what extent the unimodal and multimodal data obtained from the in-service teachers (n = 53) predict their learning outcomes and engagement. The results show that models using facial expressions and eye movements data had the best predictive performance on learning outcomes. The performance varied on teachers’ engagement: the multimodal model (integrating eye movements, facial expressions, and brain wave data) was best at predicting cognitive engagement and emotional engagement, while the one (integrating eye movements and facial expressions data) performed best at predicting behavioral engagement. At last, we applied the models to the four stages of online synchronous training and discussed changes in the level of teacher engagement. The work helps understand the value of multimodal data for predicting teachers’ online learning process and promoting online teacher professional development.
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