Search

Enhancing interest in physics learning has been an important component of education policy and policy implementation for decades. However, in many countries, student interest in physics has not increased. The aim of this study was to predict situational interest using individual interest and the instructional activities students engaged in. Also, the suitability of the data collection approach to measure situational interest was assessed. A teaching module about real-world oscillations was implemented to 179 Estonian lower secondary school students. Data about situational interest were collected using the experience sampling method (ESM), which was measured three times during the module. The results indicated that gender, grade, and instructional activities did not predict situational interest. Individual interest was a significant predictor and correlation with situational interest increased with time, contrary to previous findings. The ESM approach used in this study was considered to be effective in disturbing students' study flow minimally but may have affected the amount of missing data. This study contributes to the research done on student interest in a classroom setting by indicating a more complex relationship between situational and individual interest than previously suggested.

This study contributes to the understanding of the relationship between emotions and development of scientific understanding by examining (1) how students perform in scientific sensemaking in the context of a three-cycle predict-observe-explain (POE) activity, (2) what kind of trajectories of situational epistemic emotions students show when making sense of the phenomenon, and (3) how students' performance in sensemaking is related to their emotional trajectories. Data from 109 participant students were collected in six upper secondary physics classes. Students' performance in sensemaking was evaluated based on their answers on POE items and categorised through qualitative content analysis. Situational epistemic emotions (surprise, curiosity, confusion, and boredom) were measured using a four-point Likert scale after each POE cycle. Latent class growth analysis was used to identify groups of students with distinctive emotional trajectories. The relationship between the performance in POE activity and emotional trajectories was explored by a chi-square test. The results indicate that students' inability to make relevant observations is significantly related to experienced boredom. Furthermore, students who perform better in making sense of the phenomenon are more likely to experience surprise, curiosity, and confusion. This implies that engaging students to be curious when they observe and test predictions is an important mission for curriculum designers and teachers in practice. The findings underline the importance of epistemic emotions in educational settings and the complexity of the interplay between cognitive and affective factors in learning situations.

The increased access to artificial intelligence (AI) applications has made it possible to develop more engaging and complex educational activities for students in different disciplines. This research explored expanding university students’ knowledge of scientific entrepreneurship skills using an Artificial Intelligence application. The students participated in a training experience using the conversational ChatGPT language model to generate narrative scripts for various topics on scientific discoveries and technological advances to create new products or services that offer cost-effective solutions based on science. The experience was designed employing the i4C model (identify, ideate, invent, inform). The study used a two-sample design with repeated measurements based on a pre-test and post-test. One hundred five graduate students from two master’s degree programs at the Bolivarian University of Ecuador participated during the 2022–2023 academic period. The results indicate that the students notably improved in acquiring the knowledge necessary for scientific entrepreneurial skills. The study concluded that applying AI ChatGPT with a narrative scripting strategy can create new learning opportunities for students.

Epistemic emotions (surprise, curiosity, enjoyment, confusion, anxiety, frustration and boredom) have an object focus on knowledge or knowledge construction and are thus hypothesized to affect learning outcomes. In the context of upper secondary school science, the present study clarifies this relation by examining the students’ pre- and posttest performance (n = 148 students) and their experiences of situational epistemic emotions (n = 1801 experience sampling method observations). As expected, epistemic emotions correlated with both pre- and posttest performance: curiosity and enjoyment correlated positively, and frustration and boredom correlated negatively with the performance. However, based on structural equation modeling, after controlling for the pretest performance, only boredom was found to have a significant negative effect on posttest performance. The findings underline the complexity of the interplay between emotions and learning. Thus, the state versus trait nature of epistemic emotions, and the implications for research and practice are being discussed.

This article discusses how to study protein chemistry meaningfully in the context of molecular gastronomy by supporting higher-order thinking skills. The instruction also includes several myths that the students can reflect on. Inquiry-based work is performed in the style of the Top Chef competition: the objective is to prepare the lightest and fluffiest meringue possible. The students act as so called investigating chemistry cooks. The instructions are suitable for secondary school and upper secondary school for studying chemistry of proteins, or for unifying chemistry and home economics in teaching.

Heat exchangers are commonly used in process industries; however, fouling, such as sedimentation of particulate material is a significant challenge hindering the efficient use of heat exchangers in a wide range of industrial processes. This research studied the prevention of sedimentation in tube heat exchanger header sections, which typically are the critical areas for sediment accumulation. Numerous flow modifiers were explored, of which the most advantageous ones are presented in this paper. The study included construction and analysis of a miniature, validation of the used CFD model, and finally simulating an industrial scale heat exchanger. This research considered both flow fields and wall shear stresses for reducing sedimentation. The study showed that CFD models are capable of describing flow fields and their spatial variations in heat exchangers especially in their header sections. The selected flow modifier setups increased wall shear stresses in critical areas and hence reduced sedimentation. The presented solution consisted of utilizing different flow modifiers, filling elements, and their combinations. Industry should consider utilizing flow modifiers in heat exchangers as a potential solution to prevent sedimentation. Industrial cases are worth analyzing by using miniatures and CFD modeling. Analyses should pay special attention to flow fields and wall shear stresses. Heat exchangers include also other fouling mechanisms beside sedimentation; however, further study is required to clarify how flow modifiers influence these mechanisms. [ABSTRACT FROM AUTHOR]

The concentrations of swine epithelial antigen (SEA), swine urinary antigen (SUA) and swine feed antigen (SFA) were measured in swineries. SEA seems to be the most prevalent of the constituents measured. In the serum samples of the subjects studied, specific IgG antibodies against the antigens were frequently encountered. However, a difference was seen in the distribution of anti-SUA-IgG antibodies between swinery workers and a control group of students. The influence of the level of specific dust concentrations on specific antibody titers was studied statistically. Positive correlations were observed between stationary site SUA concentrations and anti-SUA-IgG and anti-SEA-IgG titers, respectively, pointing to an association between exposure and humoral response in swinery work. Consequently, our results suggest that the measurement of antibodies against SUA or its components could offer a basis for the estimation of the level of swinery work-related respiratory exposure and for monitoring the quality of the working environment in swineries.

Sensitization of dairy farmers to bovine-derived allergens and factors influencing this process were studied during the indoor cattle-feeding season. Eighteen typical family farms in eastern Finland were included in the study. Samples of airborne particulate material from stationary sites and the breathing zones of farmers were analyzed for bovine epithelial antigen (BEA) by the immunochemical enzyme-linked immunosorbent assay (ELISA) inhibition test. The levels of specific IgG and IgE antibodies against BEA and bovine urinary antigen (BUA) were measured from serum samples collected from farmers three times during the study. An association was found between anti-BUA IgG titers and BEA concentrations in the breathing zone. No major changes were observed between the antibody levels of sera collected at different times. In the samples from subjects with allergic rhinitis, however, a slight tendency toward descending anti-BUA IgE titers was found.

The aim of this study was to measure the total concentrations of dust in piggeries and to analyze the components of the dust. Dust samples were taken from 15 fattening pig and/or sow farms situated in southern Finland. Total concentrations of dust were measured by the gravimetric method; the organic portion of the total dust was determined by ashing, mass distribution determined by Cascade Centripeter sampler, count distribution by optical analyzer, and toxic metals of the total dust by atomic absorption spectrophotometer. The mean concentrations of total dust at stationary sampling sites were higher on fattening pig farms (9.4 +/- 1.7 mg/m3) (mean +/- SE) than on sow farms (5.2 +/- 1.2 mg/m3). The concentrations in the breathing zone were 8.6 +/- 2.7 mg/m3 and 7.9 +/- 3.2 mg/m3, respectively. The proportion of organic dust was about 90% in the dust of pig units. The mass median aerodynamic diameter of the dust particles in pig fattening units was 11 micron. Concentrations of toxic metals (nickel, cobalt, copper, zinc, chromium, cadmium) were very low.