Collaborative Online International Learning in an undergraduate genetics course

Collaborative Online International Learning (COIL) is a teaching and learning paradigm that promotes the development of intercultural competence across shared multicultural learning environments. Through the use of internet-based tools and online pedagogies, COIL fosters meaningful exchanges between university-level educators and students with peers in geographically distant locations and from different lingua-cultural backgrounds. In the winter term 2018, the 2nd year undergraduate course at the University of Ottawa will engage with other undergraduate courses in COIL modules to achieve “capstone” experiences by engaging students in the evaluation of topics relating to social, cultural and environmental impacts of genetics. The COIL modules will explore human genetic and reproductive technologies that are rapidly being integrated into our lives and how the uses of these technologies provoke legal, ethical, and social questions. Issues pertaining to the use of genetic medicine, prenatal screening, newborn screening, pharmacogenomics, equal access to genetic services, and genetic discrimination are a few examples that will be explored. The course modules will be designed to be part of a blended learning experience that will include planned videoconference collaborative classes, joint online interactions and assignments, and regular scheduled face-to-face campus classes between each university’s faculty and students. The objective of this session is to elicit interest in COIL and to recruit possible partners to engage in collaborative online international learning opportunities

Designing Advanced Seminar Research Courses in Science

Advanced seminar research courses in sciences provide students with valuable capstone experiences. They impart opportunities to develop practical skills required for entry into scientific careers. While course objectives and learning outcomes may vary across disciplines, educational programs, departments, and institutions, seminar courses encourage students to hone professional competencies for research investigations, scientific literacy, communication, and critical thinking. Students demonstrate these skills via collaborative discussions, peer evaluation, and formulation of integrative reports. Designing and assessing the effectiveness of such courses involves the feedback from students, faculty, and administration. In this session, presenters will discuss two models which are implemented in different academic settings to reveal strategies for the design, delivery, and evaluation of research seminar courses. The presenters will elaborate upon their respective seminar courses. Course outlines (syllabi), lesson planning, student activities, formative and summative assessments, rubrics, and administrative logistics will be discussed

Optimizing safe, comfortable ICU care through multi-professional quality improvement: just DO it

Translating research to the bedside can present significant challenges in the complex ICU environment. In this issue of Critical Care, de Jong and colleagues report on a quality improvement project (NURSE-DO) that led to a decrease in severe pain and serious adverse events during nursing care procedures in their ICU. In this commentary we describe three aspects of this quality improvement study that we think contributed to the overall success of the NURSE-DO project: the hospital environment and culture; multi-professional partnerships; and an evidence-based structured approach

Does group composition impact group scores in two-stage collaborative exams?

Recently, two-stage exams were introduced in two large second year genetic courses (\u3e250 students) at two different universities. The courses follow similar formats and use course learning outcomes, activities, and materials developed by the two instructors. Two-stage exams are those in which students first write an exam individually, followed immediately by a second stage in which they write the same, or similar, exam as part of a small group. Student exam grades comprised 85% individual score and 15% group score. Typically, exam scores improved in the group portion, however, the extent of the improvement varied between groups, and for several group scores were lower than the average of members’ individual scores. The goal of this project is to identify factors that may influence learning and student performance gains (Group Score – Average of Members’ Individual Scores) in the collaborative component. To determine group-composition factors that impact group scores, we compared individual and group scores from midterm and final exams, of fixed (group members stayed the same throughout all 3 exams) and dynamic (composition of group members changed in at least one exam) groups. Preliminary results show that while group composition does not have a significant effect on predicting group score, the average individual performance of students in a group impact student gains (the difference between a group’s score and the average of the members’ individual scores). We hope to use this opportunity to discuss different approaches to assess factors impacting performance on collaborative exams

Semantic descriptor for intelligence services

The exposition and discovery of intelligence especially for connected devices and autonomous systems have become an important area of the research towards an all-intelligent world. In this article, it a semantic description of functions is proposed and used to provide intelligence services mainly for networked devices. The semantic descriptors aim to provide interoperability between multiple domains' vocabularies, data models, and ontologies, so that device applications become able to deploy them autonomously once they are onboarded in the device or system platform. The proposed framework supports the discovery, onboarding, and updating of the services by providing descriptions of their execution environment, software dependencies, policies and data inputs required, as well as the outputs produced, to enable application decoupling from the AI functions

An Evaluation of the Performance of Tag SNPs Derived from HapMap in a Caucasian Population

The Haplotype Map (HapMap) project recently generated genotype data for more than 1 million single-nucleotide polymorphisms (SNPs) in four population samples. The main application of the data is in the selection of tag single-nucleotide polymorphisms (tSNPs) to use in association studies. The usefulness of this selection process needs to be verified in populations outside those used for the HapMap project. In addition, it is not known how well the data represent the general population, as only 90–120 chromosomes were used for each population and since the genotyped SNPs were selected so as to have high frequencies. In this study, we analyzed more than 1,000 individuals from Estonia. The population of this northern European country has been influenced by many different waves of migrations from Europe and Russia. We genotyped 1,536 randomly selected SNPs from two 500-kbp ENCODE regions on Chromosome 2. We observed that the tSNPs selected from the CEPH (Centre d'Etude du Polymorphisme Humain) from Utah (CEU) HapMap samples (derived from US residents with northern and western European ancestry) captured most of the variation in the Estonia sample. (Between 90% and 95% of the SNPs with a minor allele frequency of more than 5% have an r (2) of at least 0.8 with one of the CEU tSNPs.) Using the reverse approach, tags selected from the Estonia sample could almost equally well describe the CEU sample. Finally, we observed that the sample size, the allelic frequency, and the SNP density in the dataset used to select the tags each have important effects on the tagging performance. Overall, our study supports the use of HapMap data in other Caucasian populations, but the SNP density and the bias towards high-frequency SNPs have to be taken into account when designing association studies

Fostering clinical reasoning in physiotherapy: Comparing the effects of concept map study and concept map completion after example study in novice and advanced learners

Background: Health profession learners can foster clinical reasoning by studying worked examples presenting fully worked out solutions to a clinical problem. It is possible to improve the learning effect of these worked examples by combining them with other learning activities based on con