Students' Forms of Dialogue When Engaged with Contemporary Biological Research: Insights from University and High School Students' Group Discussions

Classroom dialogues have special educational value because they allow students to engage critically but constructively with each other’s ideas, solve scientific problems jointly and develop their scientific understanding. The present study focuses on how groups of twelfth-grade high school and university students communicate and co-operate through dialogue to solve a biological problem they have not encountered before. The specific research questions are as follows: (a) What are the dialogic structures that help students construct scientific explanations? (b) How does prior scientific knowledge support student dialogue in constructing explanations? A coding scheme was developed inductively for the analysis of participants’ utterances. We use illustrative exemplars from participants’ dialogues to discuss those aspects which might support explanatory reasoning. We focus on reasoned attention for contending opinions and striving for consensus that characterise cases of constructive dialogue. We also discuss observed objections and disagreements as triggering factors for constructive alternative explanations. Finally, we discuss the evidence showing that while prior knowledge supports student reasoning it can also hinder the ability of students to think in a creative way

Job satisfaction and employee turnover determinants in high contact services: Insights from Employees'Online reviews

We explore a special case of electronic word of mouth that of employees' online reviews to study the determinants of job satisfaction and employee turnover. We perform our analysis using a novel dataset of 297,933 employee online reviews from 11,975 US tourism and hospitality firms, taking advantage of both the review score and text. Leadership and cultural values are found to be better predictors of high employee satisfaction, while career progression is critical for employee turnover. One unit increase in the rating for career progression reduces the likelihood of an employee to leave a company by 14.87%. Additionally, we quantify the effect of job satisfaction on firm profitability, where one unit increase leads to an increase between 1.2 and 1.4 in ROA. We do not find evidence supporting the reverse relationship, that growth on firm profitability increases job satisfaction. The feedback to management in employee reviews provides specific managerial implications

Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma

PURPOSE: To determine whether differences in modeling implementation will impact the correction of leakage effects (from blood brain barrier disruption) and relative cerebral blood volume (rCBV) calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced (DSC)-MRI at 3T field strength. MATERIALS AND METHODS: This HIPAA-compliant study included 52 glioma patients undergoing DSC-MRI. Thirty-six patients underwent both non Preload Dose (PLD) and PLD-corrected DSC acquisitions, with sixteen patients undergoing PLD-corrected acquisitions only. For each acquisition, we generated two sets of rCBV metrics using two separate, widely published, FDA-approved commercial software packages: IB Neuro (IBN) and NordicICE (NICE). We calculated 4 rCBV metrics within tumor volumes: mean rCBV, mode rCBV, percentage of voxels with rCBV > 1.75 (%>1.75), and percentage of voxels with rCBV > 1.0 (Fractional Tumor Burden or FTB). We determined Pearson (r) and Spearman (ρ) correlations between non-PLD- and PLD-corrected metrics. In a subset of recurrent glioblastoma patients (n=25), we determined Receiver Operator Characteristic (ROC) Areas-Under-Curve (AUC) for FTB accuracy to predict the tissue diagnosis of tumor recurrence versus post-treatment effect (PTRE). We also determined correlations between rCBV and microvessel area (MVA) from stereotactic biopsies (n=29) in twelve patients. RESULTS: Using IBN, rCBV metrics correlated highly between non-PLD- and PLD-corrected conditions for FTB (r=0.96, ρ=0.94), %>1.75 (r=0.93, ρ=0.91), mean (r=0.87, ρ=0.86) and mode (r=0.78, ρ=0.76). These correlations dropped substantially with NICE. Using FTB, IBN was more accurate than NICE in diagnosing tumor vs PTRE (AUC=0.85 vs 0.67) (p<0.01). The highest rCBV-MVA correlations required PLD and IBN (r=0.64, ρ=0.58, p=0.001). CONCLUSIONS: Different implementations of perfusion MRI software modeling can impact the accuracy of leakage correction, rCBV calculation, and correlations with histologic benchmarks

Development and validation of a framework for the assessment of school curricula on the presence of evolutionary concepts (FACE)

Evolution is a key concept of biology, fundamental to understand the world and address important societal problems, but research studies show that it is still not widely understood and accepted. Several factors are known to influence evolution acceptance and understanding, but little information is available regarding the impacts of the curriculum on these aspects. Very few curricula have been examined to assess the coverage of biological evolution. The available studies do not allow comparative analyses, due to the different methodologies employed by the authors. However, such an analysis would be useful for research purposes and for the development of appropriate educational policies to address the problem of a lack of evolution acceptance in some countries. In this paper we describe the steps through which we developed a valid and reliable instrument for curricula analysis known as FACE: “Framework to Assess the Coverage of biological Evolution by school curricula.” This framework was developed based on the “Understanding Evolution Conceptual Framework” (UECF). After an initial pilot study, our framework was reformulated based on identified issues and experts’ opinions. To generate validity and reliability evidence in support of the framework, it was applied to four European countries’ curricula. For each country, a team of a minimum of two national and two foreign coders worked independently to assess the curriculum using this framework for content analysis. Reliability evidence was estimated using Krippendorf's alpha and resulted in appropriate values for coding the examined curricula. Some issues that coders faced during the analysis were discussed and, to ensure better reliability for future researchers, additional guidelines and one extra category were included in the framework. The final version of the framework includes six categories and 34 subcategories. FACE is a useful tool for the analysis and the comparison of curricula and school textbooks regarding the coverage of evolution, and such results can guide curricula development.info:eu-repo/semantics/publishedVersio

Exploring demographic information in social media for product recommendation

In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users’ preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users’ public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users’ preferences than the competitive baselines

EuroScitizen Working Group 2 I Identifying needs and opportunities to improve the contribution of formal education to public literacy on evolution

EuroScitizen is a COST Action and involves a research network whose aim is to identify strategies to raise levels of scientific literacy about evolution in Europe. EuroScitizen comprises five working groups (WG) and this poster summarizes the current achievements of WG2 on formal education. WG2 aims to identify the needs and opportunities to improve the teaching of evolution since the first school years in distinct countries and enhance the contribution of formal education to European public scientific literacy on this important topic. To achieve these objectives we are studying: i) the school curricula and ii) textbooks of the participating countries; iii) teachers’ content knowledge, pedagogical content knowledge, attitudes and beliefs about teaching evolution and effective methodologies and strategies to empower teachers about evolution education; and iv) strategies to promote evolution understanding in elementary school students. This poster presents some of the current achievements of WG2, such as: i) publication of a paper about the development and validation of a framework for the assessment of school curricula on the presence of evolutionary concepts (FACE); ii) comparison of the content of most adopted textbooks in the schools of 8 countries, from the 1st to the 9th grade, about the presence of evolution Big Ideas; iii) identification of teachers’ best practices in evolution education and teacher’ training actions about evolution education; and iv) the publication of a study about the evolutionary concepts that elementary school students most often used after a pedagogical intervention. The next steps of the WG2 are also presented.info:eu-repo/semantics/publishedVersio

Ranking online consumer reviews

YesProduct reviews are posted online by the hundreds and thousands for popular products. Handling such a large volume of continuously generated online content is a challenging task for buyers, sellers and researchers. The purpose of this study is to rank the overwhelming number of reviews using their predicted helpfulness scores. The helpfulness score is predicted using features extracted from review text, product description, and customer question-answer data of a product using the random-forest classifier and gradient boosting regressor. The system classifies reviews into low or high quality with the random-forest classifier. The helpfulness scores of the high-quality reviews are only predicted using the gradient boosting regressor. The helpfulness scores of the low-quality reviews are not calculated because they are never going to be in the top k reviews. They are just added at the end of the review list to the review-listing website. The proposed system provides fair review placement on review listing pages and makes all high-quality reviews visible to customers on the top. The experimental results on data from two popular Indian e-commerce websites validate our claim, as 3–4 newer high-quality reviews are placed in the top ten reviews along with 5–6 older reviews based on review helpfulness. Our findings indicate that inclusion of features from product description data and customer question-answer data improves the prediction accuracy of the helpfulness score.Ministry of Electronics and Information Technology (MeitY), Government of India for financial support during research work through “Visvesvaraya PhD Scheme for Electronics and IT”