Search

This study examined how filters and amplifiers affect pre-service science teachers' pedagogical content knowledge (PCK) in a human and environment unit. The redefined consensus model for PCK and decision-making framework for identifying how personal and extrapersonal factors act as filters and amplifiers were selected as theoretical frameworks. Two pre-service science teachers participated in the study. While pre-interviews were used to determine participants' PCK before teaching, observations and post-interviews were used to reveal participants' PCK after teaching, and how filters and amplifiers influenced PCK. Data were analyzed deductively to examine teachers' PCK including interactions among components and the way filters and amplifiers act on PCK. Constant comparison analysis revealed five general assertions of how filters and amplifiers shaped the decision-making process when these teachers enacted their PCK. First, the number of amplifiers and filters affecting knowledge of instructional strategies (KOIS) was the highest. Second, the number of amplifiers and filters affecting knowledge of curriculum in science was the lowest. Third, the effect of filters and amplifiers on PCK components was idiosyncratic. Fourth, the more (or the less) the map was integrated; the less (or the more) amplifier and filter influenced the PCK. Fifth, the number of personal factors affecting KOIS was highest. Implications are suggested considering the effects of filters and amplifiers on teachers' PCK.

This study addresses suggestions for analyzing science teachers' pedagogical content knowledge (PCK) components and their interactions and these suggestions are expected to facilitate the analysis of science teachers' PCK, resulting in more accurate representations of PCK. Knowledge of the science curriculum, knowledge of students' understanding of science, knowledge of assessment in science, and knowledge of instructional strategies were used as specific PCK components in this study and the PCK mapping approach was used as the theoretical framework. Suggestions for PCK components' analysis are based on the similarity among PCK components and the similarity between PCK components and other knowledge domains. Furthermore, suggestions for the analysis of interaction among PCK components are related to the direction of interaction, the strength of one interaction considering its content, and categorizing the number of interactions between PCK components. These suggestions can provide new insights into the analysis of PCK components and their interactions for researchers and improve the precision and heuristic power of PCK models.

This study investigated in what ways and to what extent the interactions between the components of pedagogical content knowledge (PCK) differ for junior high school science teachers with different levels of content knowledge. Data were collected from three science teachers through semi-structured interviews and classroom observations. The participants' content knowledge was analyzed based on inductive coding and the teachers were labeled as curriculum-led, content-expert, and content-novice. Interactions among PCK components were analyzed by making an in-depth analysis of explicit PCK. This included constructing PCK maps for each participant. Then, the constant comparative method was used to clarify differences in interactions among PCK components. Five assertions were proposed based on the differences among PCK interactions: (a) the curriculum-led teacher had the most integrated PCK map and the interactions were mainly reciprocal; (b) the most frequent interactions between knowledge of assessment and the other PCK components were observed in the content-expert teacher; (c) the most frequent interactions between knowledge of curriculum and the other PCK components were observed in the curriculum-led teacher's teaching; (d) the content-novice teacher's orientation interacted with the other PCK components more than in the other two participants' teaching; (e) the main ideas of the interactions among PCK components changed depending on the teachers' content knowledge. The findings are discussed and suggestions for researchers and teachers are provided.

BACKGROUND: Low back pain (LBP) is a common public health problem resulting in workforce loss. OBJECTIVE: This study aims to evaluate the LBP status and its affecting factors among drivers in a city in southeast Turkey. METHODS: This cross-sectional questionnaire survey study was conducted among 323 drivers. The chi-square test and logistic regression analysis were used to analyze the data. RESULTS: The mean age of the drivers was 41.7±11.5 years (min: 19, max: 70), and 83.9% were married, and all were men. LBP was found in 59.4% of drivers. It was significantly higher in drivers with poor socioeconomic status, dissatisfied with their life, having a chronic illness, physically inactive, having sleep disorders, exposed to bad road conditions, prolonged vibration, high physical- psychological workload, and a family history of LBP (p < 0.05). There was no significant association between age, education level, and BMI with LBP (p > 0.05). CONCLUSION: There is limited study on this subject in Turkey. Further studies can raise awareness about this issue and create an educational plan. [ABSTRACT FROM AUTHOR]

Present study aims to translate and develop Paranormal Belief Questions (Rice, 2003) measuring students' non-scientific beliefs which threat science education. Original version of these questions was asked in Southern Focus Poll (1998). 17 questions about paranormal beliefs were administered to 114 university students from different departments. After translating and developing Paranormal Belief Questions into Turkish, factor analysis was conducted and paranormal beliefs were limited in two dimensions as classical paranormal beliefs and religious paranormal beliefs as parallel with original form. Déjà vu item that is not consistent with other paranormal beliefs was removed depending on the factor analysis. The results of the current study enable to differentiate scientific beliefs from non-scientific beliefs of students. By this way, science educators can benefit from this scale.