The best way to learn how to program is to do something useful, so this introduction to R is built around a common scientific task: data analysis. Our real goal isn’t to teach you R, but to teach you the basic concepts that all programming depends on. We use R in our lessons because: we have to use something for examples; it’s free, well-documented, and runs almost everywhere; it has a large (and growing) user base among scientists; and it has a large library of external packages available for performing diverse tasks. But the two most important things are to use whatever language your colleagues are using, so you can share your work with them easily, and to use that language well. We are studying inflammation in patients who have been given a new treatment for arthritis, and need to analyze the first dozen data sets of their daily inflammation. The data sets are stored in CSV format (comma-separated values): each row holds information for a single patient, and the columns represent successive days. The first few rows of our first file look like this: 0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0 0,1,2,1,2,1,3,2,2,6,10,11,5,9,4,4,7,16,8,6,18,4,12,5,12,7,11,5,11,3,3,5,4,4,5,5,1,1,0,1 0,1,1,3,3,2,6,2,5,9,5,7,4,5,4,15,5,11,9,10,19,14,12,17,7,12,11,7,4,2,10,5,4,2,2,3,2,2,1,1 0,0,2,0,4,2,2,1,6,7,10,7,9,13,8,8,15,10,10,7,17,4,4,7,6,15,6,4,9,11,3,5,6,3,3,4,2,3,2,1 0,1,1,3,3,1,3,5,2,4,4,7,6,5,3,10,8,10,6,17,9,14,9,7,13,9,12,6,7,7,9,6,3,2,2,4,2,0,1,1 We want to: load that data into memory, calculate the average inflammation per day across all patients, and plot the result. To do all that, we’ll have to learn a little bit about programming.

Data Carpentry Genomics workshop lesson to learn how to structure your metadata, organize and document your genomics data and bioinformatics workflow, and access data on the NCBI sequence read archive (SRA) database. Good data organization is the foundation of any research project. It not only sets you up well for an analysis, but it also makes it easier to come back to the project later and share with collaborators, including your most important collaborator - future you. Organizing a project that includes sequencing involves many components. There’s the experimental setup and conditions metadata, measurements of experimental parameters, sequencing preparation and sample information, the sequences themselves and the files and workflow of any bioinformatics analysis. So much of the information of a sequencing project is digital, and we need to keep track of our digital records in the same way we have a lab notebook and sample freezer. In this lesson, we’ll go through the project organization and documentation that will make an efficient bioinformatics workflow possible. Not only will this make you a more effective bioinformatics researcher, it also prepares your data and project for publication, as grant agencies and publishers increasingly require this information. In this lesson, we’ll be using data from a study of experimental evolution using E. coli. More information about this dataset is available here. In this study there are several types of files: Spreadsheet data from the experiment that tracks the strains and their phenotype over time Spreadsheet data with information on the samples that were sequenced - the names of the samples, how they were prepared and the sequencing conditions The sequence data Throughout the analysis, we’ll also generate files from the steps in the bioinformatics pipeline and documentation on the tools and parameters that we used. In this lesson you will learn: How to structure your metadata, tabular data and information about the experiment. The metadata is the information about the experiment and the samples you’re sequencing. How to prepare for, understand, organize and store the sequencing data that comes back from the sequencing center How to access and download publicly available data that may need to be used in your bioinformatics analysis The concepts of organizing the files and documenting the workflow of your bioinformatics analysis

The Mathematics Assessment Project has developed the Classroom Challenges to exemplify the types of activities needed to supplement traditional classroom practice and support the Standards. The Professional Development Modules are designed to help teachers with the practical and pedagogical challenges presented by these lessons.

Los proyectos de esta guía utilizan un enfoque centrado en los alumnos para el aprendizaje. En lugar de solo aprender acerca de la IA con videos o conferencias, los alumnos que realizan estos proyectos son participantes activos en la exploración de ella. En el proceso, los estudiantes trabajarán directamente con tecnologías innovadoras de IA, participarán en actividades no en línea para ampliar su comprensión de cómo funcionan las tecnologías de IA y crearán diversos productos auténticos
desde modelos de aprendizaje automático hasta videojuegos— para demostrar su aprendizaje.

PROYECTO 1: Programación con aprendizaje automático
PROYECTO 2: Jugadores asistidos por IA en videojuegos
PROYECTO 3: Uso de la IA para planificar movimientos robóticos
PROYECTO 4: El aprendizaje automático como un servicio

Esta guía ofrece proyectos centrados en los alumnos que pueden enseñar directamente estándares de áreas de estudio en conjunto con comprensiones fundamentales de los que es la IA, cómo funciona y cómo impacta a la sociedad. Fueron considerados varios enfoques clave para diseñar estos proyectos. Entender estos enfoques sustentará su comprensión y la implementación de los proyectos de esta guía, así como su trabajo para diseñar más actividades que integren la enseñanza sobre la IA en su plan de estudios.

PROYECTO 1: Lo que la IA hace bien y lo que no hace tan bien
PROYECTO 2: Datos de entrenamiento y aprendizaje automático
PROYECTO 3: Los sentidos comparados con los sensores
PROYECTO 4: Navegación e IA

Esta guía ofrece proyectos centrados en los alumnos que pueden enseñar directamente estándares de áreas de estudio en conjunto con comprensiones fundamentales de los que es la IA, cómo funciona y cómo impacta a la sociedad. Fueron considerados varios enfoques clave para diseñar estos proyectos. Entender estos enfoques sustentará su comprensión y la implementación de los proyectos de esta guía, así como su trabajo para diseñar más actividades que integren la enseñanza sobre la IA en su plan de estudios.

PROYECTO 1: Chatbots de IA
PROYECTO 2: Desarrollo de una mirada crítica
PROYECTO 3: Uso de la IA para resolver problemas del medio ambiente
PROYECTO 4: Leyes para la IA

En esta guía, la exploración de la IA por parte de los alumnos se enmarca en el contexto de las consideraciones éticas, y en concordancia con los estándares, conceptos y profundidad adecuados para varias materias de K–12. Dependiendo del nivel de sus alumnos y la cantidad de tiempo que tenga disponible, puede completar todas las actividades de Inicio hasta las actividades de Demostraciones culminantes; puede seleccionar actividades de la lista; o puede llevar el aprendizaje de los alumnos más lejos, aprovechando las extensiones y recursos adicionales proporcionados. Para los alumnos sin experiencia previa de formación en la IA, la exposición misma a las actividades de aprendizaje guiadas creará una comprensión de su mundo que probablemente no tenían antes. Y para aquellos con conocimientos previos en informática o con la IA, los proyectos y recursos completos seguirán desafiando su razonamiento y los expondrán a nuevas tecnologías y aplicaciones de la IA en diversos campos de estudio.

PROYECTO 1: Lo justo es justo
PROYECTO 2: ¿Quién tiene el control?
PROYECTO 3: Las ventajas y desventajas de la tecnología de la IA
PROYECTO 4: La IA y el trabajador del siglo XXI

Python is a general purpose programming language that is useful for writing scripts to work effectively and reproducibly with data. This is an introduction to Python designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about Python syntax, the Jupyter notebook interface, and move through how to import CSV files, using the pandas package to work with data frames, how to calculate summary information from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from Python.

This is a collection of all the results of the REBELAH project.

The REBELAH project was designed to help foster more inclusive learning environments in adult education. Studies have shown that members of minoritized religious and ethnic groups experience trouble in educational settings, as learners from the majoritized groups feel uncomfortable when they are in their group. The REBELAH project aimed to create tools and activities that can help trainers and learners foster more inclusive and safe learning environments. These tools and activities have a particular focus on (European) cultural heritage.

These results include two handbooks (a book with activities useful during inclusiveness and heritage workshops, and a train the trainer handbook), six videos showing how heritage items and sites can be used to foster inclusivity in workshops settings, and a Google maps infosheet with 24 Prezi presentations on specific heritage items used during the project.

The handbooks are licensed under CC BY-NC-ND, and the other materials are licensed under CC BY-NC-SA.

**you will be redirected to the Dutch OER repository Edusources, from where you can access the materials**

In partnership with teachers, the Louisiana Department of Education arranged OpenSciEd (grade 6-8 science) content in a manner that stays true to the vision of the materials and provides clear guidance on how to use them in a fully remote environment. The modified materials assume that teachers will have synchronous virtual meetings with students in addition to home learning.
The site also provides a variety of resources with options for students who do not have internet access.

In this learning area, you will find step-by-step support for writing a research paper (a paper with source material) for your college courses. In Research, the Excelsior OWL will help you as you begin to write your paper, pick a topic, conduct research for articles and books, draft your work, integrate your research, and revise and edit your finished paper.

The Research Data Management Academy (RDMLA) is a global, free online professional development program for librarians, information professionals, or other professionals who work in a research-intensive environment. The curriculum focuses on the knowledge and skills needed to collaborate with researchers and other stakeholders on data management. RDMLA features a unique partnership between a library and information science academic program, academic health sciences and research libraries, and industry publisher. All of the content is hosted on Canvas Network, freely available, and open for reuse under a CC-BY-NC-SA license.

This module dwells on a number of methods (including old and new) available for research evaluation. The module comprises the following four units:
Unit 1. Introduction to Research Evaluation Metrics and Related Indicators.
Unit 2. Innovations in Measuring Science and Scholarship: Analytical Tools and Indicators in Evaluation Scholarship Communications.
Unit 3. Article and Author Level Measurements, and
Unit 4. Online Citation and Reference Management Tools.
Brief overviews of the units are presented below.
Unit 1 encompassed and discussed citation analysis, use of citation-based indicators for research evaluation, common bibliometric indicators, classical bibliometric laws, author level indicators using authors' public profiles, article level metrics using altmetric tools. It is to be noted that author level indicators and article level metrics are new tools for research evaluation. Author level indicators encompasses h index, citations count, i10 index, g index, articles with citation, average citations per article, Eigenfactor score, impact points, and RG score. Article level metrics or altmetrics are based on Twitter, Facebook, Mendeley, CiteULike, and Delicious which have been discussed. All technical terms used in the Unit have been defined.
Unit 2 deals with analytical tools and indicators used in evaluating scholarly communications. The tools covered are The Web of Science, Scopus, Indian Citation Index (ICI), CiteSeerX, Google Scholar and Google Scholar Citations. Among these all the tools except Indian Citation Index (ICI) are international in scope. ICI is not very much known outside India. It is a powerful tool as far Indian scholarly literature is concerned. As Indian journals publish a sizable amount of foreign literature, the tool will be useful for foreign countries as well. The analytical products with journal performance metrics Journal Citation Reports (JCR®) has also been described. In the chapter titled New Platforms for Evaluating Scholarly Communications three websites i.e. SCImago Journal & Country Rank (SJR) [ScimagoJR.com], eigenFACTOR.org, JournalMetrics.com and one software called Publish or Perish (POP) Software have been discussed.
Article and author level measurements have been discussed in Unit 3. Author and researcher identifiers are absolutely essential for searching databases in the WWW because a name like D Singh can harbour a number of names such as Dan Singh, Dhan Singh, Dhyan Singh, Darbara Singh, Daulat Singh, Durlabh Singh and more. The ResearcherID.com, launched by Thomson Reuters, is a web-based global registry of authors and researchers that individualises each and every name. Open Researcher and Contributor ID (ORCID) is also a registry that uniquely identifies an author or researcher. Both have been discussed in this Unit. Article Level Metrics (Altmetrics) has been treated in this Unit with the discussion as to how altmetrics can be measured with Altmetric.com and ImpactStory.org. Altmetrics for Online Journals has also been touched. There are a number of academic social networks of which ResearchGate.net, Academia.edu, GetCited.org, etc. have been discussed. Regional journal networks with bibliometric indicators are also in existence. Two networks of this type such as SciELO – Scientific Electronic Library Online, and Redalyc have been dealt with.
The last unit (Unit 4) is on online citation and reference management tools. The tools discussed are Mendeley, CiteULike, Zotero, Google Scholar Library, and EndNote Basic. The features of all the management tools have been discussed with figures, tables, and text boxes.
This is Module Four of the UNESCO's Open Access Curriculum for Researchers.
Full-Text is available at http://unesdoc.unesco.org/images/0023/002322/232210E.pdf

This lesson in part of Software Carpentry workshop and teach novice programmers to write modular code and best practices for using R for data analysis. an introduction to R for non-programmers using gapminder data The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop. A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.

In the Rhetorical Styles area of the Excelsior OWL, you’ll learn about different rhetorical styles or, essentially, different strategies for developing your essays and other writing assignments. These basic strategies are not all encompassing but will provide you with a foundation and a flexibility to help you as you engage in writing assignments in your introductory writing classes and beyond.

Rock the Boat is an open-access multimedia resource designed to provoke dialogue about graduate supervision relationships within universities, and their impact on student and faculty wellbeing. Drawing upon the tradition of Research-based Theatre, Rock the Boat draws attention to graduate supervision as a vital form of pedagogy, and as rife with challenges — especially relating to equity, inclusion and diversity.

Una introducción a R utilizando los datos de Gapminder. El objetivo de esta lección es enseñar a las programadoras principiantes a escribir códigos modulares y adoptar buenas prácticas en el uso de R para el análisis de datos. R nos provee un conjunto de paquetes desarrollados por terceros que se usan comúnmente en diversas disciplinas científicas para el análisis estadístico. Encontramos que muchos científicos que asisten a los talleres de Software Carpentry utilizan R y quieren aprender más. Nuestros materiales son relevantes ya que proporcionan a los asistentes una base sólida en los fundamentos de R y enseñan las mejores prácticas del cómputo científico: desglose del análisis en módulos, automatización tareas y encapsulamiento. Ten en cuenta que este taller se enfoca en los fundamentos del lenguaje de programación R y no en el análisis estadístico. A lo largo de este taller se utilizan una variedad de paquetes desarrolados por terceros, los cuales no son necesariamente los mejores ni se encuentran explicadas todas sus funcionalidades, pero son paquetes que consideramos útiles y han sido elegidos principalmente por su facilidad de uso.

The following are lessons from the Middle School Paleontology kits that do not require the fossils within the kit. All lessons meet both Colorado State Academic Standards and Next Generation Science Standards (NGSS). For more information regarding kits, visit this page https://museumofwesternco.com/museum-education-kits/. Overview URL for the Middle School Paleontology Kit Module from Museums of the West in Grand Junction, CO. Lessons 1, 2, 3 and 5 can be completed without access to the Fossil Kit. District 51 personnel can request a kit to complete Lesson 4. For a Teacher's Guide to the Module, visit: https://museumofwesternco.com/wp-content/uploads/2020/08/Paleontology-Teacher-Background-Info.pdf

1). Identify the sampling method used in a study and discuss its implications and potential limitations.
2). Critically evaluate the reliability and validity of results published in mainstream media.
3). Summarize and describe the distribution of a categorical variable in context.

Researchers, scholars and scientists main business is scholarly communication. We communicate about our work to others, as we push the boundaries of what we know and the society knows. We question established notions and truths about science. We share our findings with others, and in a way that is popularly known as scholarly communication which emerged with the publication of first journal in 1665. However, the term gained popularity only in the 1970s, as access to peer reviewed and scholarly communication became difficult. This module has four units covering introduction to scholarly communication, peer reviewed journals, electronica journals and databases and the Serials Crisis. At the end of this module, the learner is expected to be able to:
- Explain philosophy, mission, and objectives of scholarly communication
- Describe the process of scholarly communication
- Identify different channels of scholarly communication
- Discuss the dysfunctioning of the scholarly communication
In Unit 1, Introduction to scholarly communication, we have discussed different aspects of scholarly communication – particularly its genesis, importance and ethics of academic publishing, and different communication channels available in academic publishing. Some of these channels are commonly described as primary sources as they provide first-hand testimony or direct evidence concerning a topic under investigation. Historically, scientific journals were initiated by learned societies and other scholarly communities for reporting results of concluded research works or scientific discoveries. Now many forprofit publishers have started publishing research journals.
Unit 2, Communicating with Peer Review Journals, covers two important academic publishing channels, namely peer reviewed journals, conferences and their proceedings. This Unit also highlights different methods and procedures of peer reviewing for publishing primary literature emanated from research studies. The peer reviewing is essential for validating quality of research findings conveyed by researchers, which are subject to fulfilment of ethical standards and appropriate research design, sampling and other methodological issues.
In Unit 3, Electronic journals and databases, we have discussed the emergence of electronic journals in academic and research environment due to wide proliferation of information and communication technologies (ICT) in research communications and academic publishing. Scientific communities and scientific communications from the global South are getting substantive attentions through adaptation of electronic journals and electronic academic databases in the process of research communications.
In Unit 4, the Serials Crisis, we discuss the cost of peer reviewed publications and the problems faced by researchers in developing countries. The focus of this unit is on highlighting the problems and discusses possible solutions including the emergence of open access as one of the solutions. Open access journal publishing helps in mitigating some of the problems associated with serials crisis.
This is Module One of the UNESCO's Open Access Curriculum for Researchers.
Full-Text is available at http://unesdoc.unesco.org/images/0023/002319/231938e.pdf