Teachers' teaching level evaluation is an important component in classroom teaching and professional promotion in the institutions of higher learning in China. Many self-made questionnaires are currently being administered to Chinese college students to evaluate teachers' classroom teaching performance. Quite often, due to the absence of strong educational, and psychological measurements and theoretical foundations for these questionnaires, their dependability remains open to doubt. Evaluation time points, the number of students, major type, and curriculum type were examined in relation to college students' perceptions on their teachers' classroom teaching performance, using Teachers' Teaching Level Evaluation Scale for Colleges (TTLES-C). Data were collected in a sample of 556 students at two time points from three Chinese universities and were analyzed using multivariate generalizability theory. Results showed that evaluations at the beginning of the spring semester produced better outcomes than did evaluations at the end of the fall semester, and 20 student evaluators were sufficient to ensure good dependability. Results also revealed that the evaluation dependability of science curriculum appeared higher than that of liberal arts curriculum. Recommendations were discussed on the evaluation criteria and mode.
Intelligent Tutoring Systems (ITSs) have a great potential to effectively transform teaching and learning. As more efforts have been put on designing and developing ITSs and integrating them within learning and instruction, mixed types of results about the effectiveness of ITS have been reported. Therefore, it is necessary to investigate how ITSs work in real and natural educational contexts and the associated challenges of ITS application and evaluation. Through a systematic literature review method, this study analyzed 40 qualified studies that applied social experiment methods to examine the effectiveness of ITS during 2011–2022. The obtained results highlighted a complicated landscape regarding the effectiveness of ITS in real educational contexts. Specifically, there was an “intelligent” regional gap regarding the distribution of countries where ITS studies using social experiment methods were conducted. Compared to learning performance, relatively less attention was paid to investigating the impact of ITS on non-cognitive factors, process-oriented factors, and social outcomes, calling for more research in this regard. Considering the complexities and challenges existing in real educational fields, there was a lack of scientific rigor in terms of experimental design and data analysis in some of the studies. Based on these findings, suggestions for future study and implications were proposed.
This study used piecewise growth modeling to describe the developmental trajectories of self-rated health (SRH) in the elderly and longitudinal associations with activities of daily living (ADL), educational level, economic status, age, and gender. Data were drawn from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), collected over 12 years (from 2002 to 2014) at five waves. A total of 16,064 Chinese elders (57.4% females) were analyzed. Results showed two phases of development for SRH; specifically, the decreasing trend of SRH was from slow (in the first phase, waves 1 to 3) to fast (in the second phase, waves 3 to 5). Descriptives showed that the turning point age was at the age of 83.69 (range = 68 to 116, median age = 82 years old). ADL were positively associated with SRH within each time point (wave of data). Female elders had a higher initial state (i.e., worse) of SRH than did male elders, and poorer economic status was associated with worse initial status of SRH.
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