Interdisciplinary and transferable concepts in bioinformatics education: observations and approaches from a UK MSc course

Bioinformatics is a highly interdisciplinary subject, with substantial and growing influence in health, environmental science and society, and is utilised by scientists from many diverse academic backgrounds. Education in bioinformatics therefore necessitates effective development of skills in interdisciplinary collaboration, communication, ethics, and critical analysis of research, in addition to practical and technical skills. Insights from bioinformatics training can additionally inform developing education in the tightly aligned and emerging disciplines of data science and artificial intelligence. Here we describe the design, implementation, and review of a module in a UK MSc-level bioinformatics programme attempting to address these goals for diverse student cohorts. Reflecting the philosophyof the field and programme, the module content was designed either as ‘diversity-addressing’ – working towards a common foundation of knowledge – or ‘diversity-exploiting’ – where different student viewpoints and skills were harnessed to facilitate student research projects ‘greater than the sum of their parts’. For a universal introduction to technical concepts, we combined a mixed lecture / immediate computational practical approach, facilitated by virtual machines, creating an efficient technical learning environment praised in student feedback for building confidence among cohorts with diverse backgrounds. Interdisciplinary group research projects where diverse students worked on real research questions were supervised in tandem with interactive contact time covering transferable skills in collaboration and communication in diverse teams, research presentation, and ethics. Multifaceted feedback and assessment provided a constructive alignment with real peer-reviewed bioinformatics research. We believe that the inclusion of these transferable, interdisciplinary, and critical concepts in a bioinformatics course can help produce rounded, experienced graduates, ready for the real world and with many future options in science and society. In addition, we hope to provide some ideas and resources to facilitate such inclusion.

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IMPACT OF JOINT COMMISSION INTERNATIONALACCREDITATION (JCIA) ON HEALTH CARE PROCESSES AND THE CHALLENGES FACED BY PHYSICIANS AND NURSES.

10.36106/ijsr/8334826 ◽

2021 ◽

pp. 34-35

Author(s):

Binu Thomas ◽

Ankur Joshi

Keyword(s):

Health Care ◽

Employee Engagement ◽

Interdisciplinary Collaboration ◽

Joint Commission ◽

Health Centers ◽

Cross Sectional ◽

Care Processes ◽

Before And After ◽

Collaboration And Communication ◽

The Impact

Purpose: To evaluate the impact of joint commission international accreditation on health care processes as well as to assess the challenges faced by the physicians and nurses . Method: Conducted a cross sectional study in 11 health centers belong to Dubai health authority. Prepared a checklist and questionnaire to assess the changes in the processes brought by accreditation as well as the challenges faced by employees respectively. Studied perceived challenges by recruiting physician (n=106) and nurses (n=194) using convenience sampling technique. Done content validity of the tools with clinical quality experts. Conducted pilot study for the questionnaire and checked the reliability using Cronbach alpha (0.924). After obtaining ethical clearance and consent from subjects, the researcher visited health centers and administered questionnaire to the participants. To evaluate the process improvements, the researcher audited documents for the availability of processes before and after accreditation using the validated checklist, which consisted of 25 processes reecting various domains of quality, employee engagement, interdisciplinary collaboration and communication. Results: Observed tremendous improvements in the availability of processes. The proportion of processes before and after the accreditation was statistically signicantly different (p <.001) for quality of health care. However for employee engagement (p=.250) and interdisciplinary collaboration and communication (p=1.000) no statistical signicance were noted even though there were signicant improvements. Majority (57.5%) of doctors and nurses perceived that the accreditation processes were challenging. Discussion: Observed processes improvements ensuring quality, employee engagement, interdisciplinary collaboration and communication after accreditation.However,majority ofthe employees perceived that, the accreditationwas challenging in terms ofworkload, communication and documentation.

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Towards Growth-Mindset Mathematics Teaching in the Netherlands

10.29007/gdgh ◽

2019 ◽

Author(s):

Greg Alpar ◽

Marloes van Hoeve

Keyword(s):

Best Practices ◽

Personal Growth ◽

Mathematics Teaching ◽

Time Pressure ◽

Deep Understanding ◽

Growth Mindset ◽

The Other ◽

Research Projects ◽

New Era ◽

Collaboration And Communication

Mathematics is the foundation of sciences and it is important in a learner’s career success. Growth mindset in mathematics teaching is essential to reach a broader student population effectively. Shifting the focus from performance and time pressure to deep understanding and personal growth, unnecessary competition vanishes among learners. As a result, they develop a better relation with their own thinking and they gain insights into the thinking of others. At the same time, collaboration and communication emerge naturally. The fear of mathematics and making mistakes disappear, while students learn by connecting ideas and applying the already learned study material.In the academic years of 2017-2018 and 2018-2019, two Dutch research projects dealt with the application of a growth mindset in mathematics teaching. One was in secondary schools, the other one at universities. In this article, we briefly report about and reflect on the exciting results of these studies and suggest further directions for research and the development of best practices.The ideas and experiences described in this paper are urgent as currently we are at the threshold of a new era in which education and learning are (and should be) really open for everyone; with low floor and without ceilings.

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Sharing transferable methods in environmental data science: A Fuzzy changepoint approach to numerical model evaluation over Greenland.

10.5194/egusphere-egu21-8813 ◽

2021 ◽

Author(s):

Michael Hollaway ◽

Peter Henrys ◽

Rebecca Killick ◽

Amber Leeson ◽

John Watkins

Keyword(s):

Numerical Model ◽

Data Science ◽

Environmental Science ◽

Numerical Models ◽

Environmental Data ◽

Resolution Model ◽

Changepoint Analysis ◽

Temperature Records ◽

Temporal Events

<p>&#160; &#160; &#160;Numerical models are essential tools for understanding the complex and dynamic nature of the natural environment and how it will respond to a changing climate. With ever increasing volumes of environmental data and increased availability of high powered computing, these models are becoming more complex and detailed in nature. Therefore the ability of these models to represent reality is critical in their use and future development. This has presented a number of challenges, including providing research platforms for collaborating scientists to explore big data, develop and share new methods, and communicate their results to stakeholders and decision makers. This work presents an example of a cloud-based research platform known as DataLabs and how it can be used to simplify access to advanced statistical methods (in this case changepoint analysis) for environmental science applications.</p><p>&#160;&#160;&#160;&#160; A combination of changepoint analysis and fuzzy logic is used to assess the ability of numerical models to capture local scale temporal events seen in observations. The fuzzy union based metric factors in uncertainty of the changepoint location to calculate individual similarity scores between the numerical model and reality for each changepoint in the observed record. The application of the method is demonstrated through a case study on a high resolution model dataset which was able to pick up observed changepoints in temperature records over Greenland to varying degrees of success. The case study is presented using the DataLabs framework, demonstrating how the method can be shared with other users of the platform and the results visualised and communicated to users of different areas of expertise.</p>

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Making rainfall features fun: scientific activities for teaching children aged 5–12 years

Hydrology and Earth System Sciences ◽

10.5194/hess-20-1751-2016 ◽

2016 ◽

Vol 20 (5) ◽

pp. 1751-1763 ◽

Cited By ~ 3

Author(s):

Auguste Gires ◽

Catherine L. Muller ◽

Marie-Agathe le Gueut ◽

Daniel Schertzer

Keyword(s):

Environmental Science ◽

State Of The Art ◽

Scientific Output ◽

Pedagogical Practices ◽

Research Projects ◽

Scientific Culture ◽

Children's Book ◽

Current State ◽

High Level ◽

Rainy Days

Abstract. Research projects now rely on an array of different channels to increase impact, including high-level scientific output, tools, and equipment, but also communication, outreach, and educational activities. This paper focuses on education for children aged 5–12 years and presents activities that aim to help them (and their teachers) grasp some of the complex underlying issues in environmental science. More generally, it helps children to become familiarized with science and scientists, with the aim to enhance scientific culture and promote careers in this field. The activities developed are focused on rainfall: (a) designing and using a disdrometer to observe the variety of drop sizes; (b) careful recording of successive dry and rainy days and reproducing patterns using a simple model based on fractal random multiplicative cascades; and (c) collaboratively writing a children's book about rainfall. These activities are discussed in the context of current state-of-the-art pedagogical practices and goals set by project funders, especially in a European Union framework.

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Designing Data Science Workshops for Data-Intensive Environmental Science Research

Journal of Statistics Education ◽

10.1080/10691898.2020.1854636 ◽

2020 ◽

pp. 1-31

Author(s):

Allison S. Theobold ◽

Stacey A. Hancock ◽

Sara Mannheimer

Keyword(s):

Data Science ◽

Environmental Science ◽

Science Research ◽

Data Intensive

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Training Data: How can we best prepare instructors to teach data science in undergraduate biology and environmental science courses?

10.1101/2021.01.25.428169 ◽

2021 ◽

Author(s):

Nathan Emery ◽

Erika Crispo ◽

Sarah R. Supp ◽

Andrew J. Kerkhoff ◽

Kaitlin J. Farrell ◽

...

Keyword(s):

Higher Education ◽

Data Science ◽

Environmental Science ◽

The United States ◽

Training Data ◽

Quantitative Literacy ◽

Career Stage ◽

Student Background ◽

Institutions Of Higher Learning ◽

Barriers To Teaching

AbstractThere is a clear and concrete need for greater quantitative literacy in the biological and environmental sciences. Data science training for students in higher education necessitates well-equipped and confident instructors across curricula. However, not all instructors are versed in data science skills or research-based teaching practices. Our study sought to survey the state of data science education across institutions of higher learning, identify instructor needs, and illuminate barriers to teaching data science in the classroom. We distributed a survey to instructors around the world, focused on the United States, and received 106 complete responses. Our results indicate that instructors across institutions use, teach, and view data management, analysis, and visualization as important for students to learn. Code, modeling, and reproducibility were less valued by instructors, although there were differences by institution type (doctoral, masters, or baccalaureate), and career stage (time since terminal degree). While there were a variety of barriers highlighted by respondents, instructor background, student background, and space in the curriculum were the greatest barriers of note. Interestingly, instructors were most interested in receiving training for how to teach code and data analysis in the undergraduate classroom. Our study provides an important window into how data science is taught in higher education as well as suggestions for how we can best move forward with empowering instructors across disciplines.

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Unlocking the Power of Artificial Intelligence and Big Data in Medicine

Journal of Medical Internet Research ◽

10.2196/16607 ◽

2019 ◽

Vol 21 (11) ◽

pp. e16607 ◽

Cited By ~ 8

Author(s):

Christian Lovis

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Big Data ◽

Decision Support ◽

Data Science ◽

Global Environment ◽

Data Driven ◽

Cross Linking ◽

Science And Society ◽

Slowing Down

Data-driven science and its corollaries in machine learning and the wider field of artificial intelligence have the potential to drive important changes in medicine. However, medicine is not a science like any other: It is deeply and tightly bound with a large and wide network of legal, ethical, regulatory, economical, and societal dependencies. As a consequence, the scientific and technological progresses in handling information and its further processing and cross-linking for decision support and predictive systems must be accompanied by parallel changes in the global environment, with numerous stakeholders, including citizen and society. What can be seen at the first glance as a barrier and a mechanism slowing down the progression of data science must, however, be considered an important asset. Only global adoption can transform the potential of big data and artificial intelligence into an effective breakthroughs in handling health and medicine. This requires science and society, scientists and citizens, to progress together.

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Introduction to the Special Issue on Advanced Technologies in Assessment: A Science-Practice Concern

Personnel Assessment and Decisions ◽

10.25035/pad.2020.01.002 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Cornelius König ◽

Andrew Demetriou ◽

Philipp Glock ◽

Annemarie Hiemstra ◽

Dragos Iliescu ◽

...

Keyword(s):

Psychological Assessment ◽

Data Science ◽

Interdisciplinary Collaboration ◽

The European Union ◽

Special Issue ◽

Assessment Practice ◽

Science Practice ◽

Personnel Assessment ◽

Advanced Technologies ◽

Computer Scientists

This article is based on conversations from the project “Big Data in Psychological Assessment” (BDPA) funded by the European Union, which was initiated because of the advances in data science and artificial intelligence that offer tremendous opportunities for personnel assessment practice in handling and interpreting this kind of data. We argue that psychologists and computer scientists can benefit from interdisciplinary collaboration. This article aims to inform psychologists who are interested in working with computer scientists about the potentials of interdisciplinary collaboration, as well as the challenges such as differing terminologies, foci of interest, data quality standards, approaches to data analyses, and diverging publication practices. Finally, we provide recommendations preparing psychologists who want to engage in collaborations with computer scientists. We argue that psychologists should proactively approach computer scientists, learn computer scientific fundamentals, appreciate that research interests are likely to converge, and prepare novice psychologists for a data-oriented scientific future.

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Interdisciplinary Collaboration: Librarian Involvement in Grant Projects

College & Research Libraries ◽

10.5860/crl.78.3.272 ◽

2017 ◽

Vol 78 (3) ◽

pp. 272 ◽

Cited By ~ 7

Author(s):

Marci D. Brandenburg ◽

Sigrid Anderson Cordell ◽

Justin Joque ◽

Mark P. MacEachern ◽

Jean Song

Keyword(s):

Translational Research ◽

Interdisciplinary Research ◽

Interdisciplinary Collaboration ◽

University Of Michigan ◽

Research Projects ◽

Literature Searching ◽

Funding Program ◽

Excellent Research ◽

The University ◽

Student Assistants

Librarians are excellent research collaborators, although librarian participation is not usually considered, thereby making access to research funds difficult. The University of Michigan Library became involved in the university’s novel funding program, MCubed, which supported innovative interdisciplinary research on campus, primarily by funding student assistants to work on research projects. This article discusses three different MCubed projects that all benefited from librarian involvement. These projects spanned across many areas from translational research to systematic reviews to digital humanities. Librarian roles ranged from mentoring and project management to literature searching.

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The in-house psychologist: do we speak the same language? Short report of a qualitative practice project

Health Psychology Research ◽

10.4081/hpr.2013.635 ◽

2013 ◽

Vol 1 (1) ◽

pp. 9

Author(s):

Birgitte Schoenmakers ◽

Jan De Lepeleire

Keyword(s):

Treatment Strategy ◽

Interdisciplinary Collaboration ◽

Treatment Strategies ◽

Patient Characteristics ◽

Total Sample ◽

Practice Research ◽

Short Report ◽

Section Design ◽

General Practices ◽

Collaboration And Communication

Interdisciplinary collaboration is gaining importance. Although general practices (GP’s) have a comprehensive experience in collaboration with psychologists, research on this topic is scarce. In house referrals to a psychologist are assumed to lower the thresholds for patients and GP’s. In this study it was investigated whether the GP’s reasons to refer in were accordance with the treatment strategy of the residing psychologist. The study is performed in a retrospective, observational cross section design. The studied population were the residing psychologist and GP’s. Both were asked to complete a questionnaire. Outcome measures where the referral reasons of the GP’s and the treatment strategy of the psychologist. A total sample of 92 patients of 6 GP’s was studied. Over 60% of the patients were referred for counseling but only in 25% of the cases this proposal was carried out by the psychologist. Overall, the referral reasons of the GP’s were not in accordance with the treatment strategy of the psychologist. A close collaboration and communication between general practitioners and psychologists is both difficult and indispensable. This practice research demonstrated that the referral motives of the GP’s usually do not correspond to the treatment policy of the psychologist. This observation is partly explained by a lack of understanding of the GP in the treatment strategies of the psychologists. Another part of the explanation is that there is a pre-selection of the GPs referrals rather influenced by patient characteristics than by pathology.

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