%Research articles are the typical means scientists use for publishing their scientific results. Therefore, it is important that science students acquire genre knowledge about research articles. This will not only help them with reading science texts but will also provide them with knowledge about the way scientists obtain scientific findings. However, studies have shown that students have difficulties with reading original scientific texts. To support students in acquiring this skill, we have developed a model, the Scientific Argumentation Model (SAM), which can be used as a heuristic in secondary or higher education. This model is based on ideas from argumentation theory and genre analysis and consists of descriptions of seven rhetorical moves that play an important role in a research article’s argumentation: motive, objective, support, counterargument, refutation, main conclusion, and implication. The relations between these moves are depicted in an argumentation scheme. In this study, SAM was validated by investigating its use on research articles from astronomy and biomedical science. The average frequencies of motives, main conclusions, implications, and support chains seem somewhat higher in astronomy papers than in biomedical papers. This might be explained by the different natures of these two disciplines.
@incollection{van2016scientific,
  title={Scientific Argumentation Model (SAM): A heuristic for reading research articles by science students},
  author={van Lacum, Edwin and Koeneman, Marcel and Ossevoort, Miriam and Goedhart, Martin},
  booktitle={Insights from Research in Science Teaching and Learning},
  pages={169--183},
  year={2016},
  publisher={Springer}
}

@article{akaike1974new,
  title={A new look at the statistical model identification},
  author={Akaike, Hirotugu},
  journal={IEEE transactions on automatic control},
  volume={19},
  number={6},
  pages={716--723},
  year={1974},
  publisher={Ieee}
}


%Abstract
%Background
%The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored.
%Methodology
%This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks.
%Conclusions
%Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets.
@article{lloyd2007maximum,
  title={Maximum likelihood estimation of the negative binomial dispersion parameter for highly overdispersed data, with applications to infectious diseases},
  author={Lloyd-Smith, James O},
  journal={PloS one},
  volume={2},
  number={2},
  pages={e180},
  year={2007},
  publisher={Public Library of Science}
}

@book{cowan1998statistical,
  title={Statistical data analysis},
  author={Cowan, Glen},
  year={1998},
  publisher={Oxford university press}
}

%The ability to read research articles is considered an essential skill for undergraduate students. However, previous works on explicitly training engineering undergraduates in reading the specific genre is scarce. This paper presents the findings of a qualitative pre-test/post-test think-aloud study that aimed to explore the possible reading behavior changes of four Greek undergraduate engineering students who received genre analysis and metacognitive strategy training for one academic semester. Our findings suggest that the course enhanced students' familiarity with the research article genre and benefited their reading strategy use.
@inproceedings{seiradakis2018training,
  title={Training undergraduate engineering students to read research articles: A qualitative think-aloud study},
  author={Seiradakis, Emmanouela and Spantidakis, Ioannis},
  booktitle={Global Engineering Education Conference (EDUCON), 2018 IEEE},
  pages={1208--1213},
  year={2018},
  organization={IEEE}
}

%The aim of this study is to evaluate a teaching strategy designed to teach first-year undergraduate life sciences students at a research university how to learn to read authentic research articles. Our approach—based on the work done in the field of genre analysis and argumentation theory—means that we teach students to read research articles by teaching them which rhetorical moves occur in research articles and how they can identify these. Because research articles are persuasive by their very nature, we focused on the rhetorical moves that play an important role in authors’ arguments. We designed a teaching strategy using cognitive apprenticeship as the pedagogical approach. It was implemented in a first-year compulsory course in the life sciences undergraduate program. Comparison of the results of a pretest with those of the posttest showed that students’ ability to identify these moves had improved. Moreover, students themselves had also perceived that their ability to read and understand a research article had increased. The students’ evaluations demonstrated that they appreciated the pedagogical approach used and experienced the assignments as useful. On the basis of our results, we concluded that students had taken a first step toward becoming expert readers.
@article{lacum2014teaching,
  title={A teaching strategy with a focus on argumentation to improve undergraduate students’ ability to read research articles},
  author={Lacum, Edwin B Van and Ossevoort, Miriam A and Goedhart, Martin J},
  journal={CBE—Life Sciences Education},
  volume={13},
  number={2},
  pages={253--264},
  year={2014},
  publisher={Am Soc Cell Biol}
}