In lpantano/dummychapter1:

Insert Workshop Title

Instructor(s) name(s) and contact information

Provide names and contact information for all instructors.

Workshop Description

Along with the topic of your workshop, include how students can expect to spend their time. For the description may also include information about what type of workshop it is (e.g. instructor-led live demo, lab, lecture + lab, etc.). Instructors are strongly recommended to provide completely worked examples for lab sessions, and a set of stand-alone notes that can be read and understood outside of the workshop.

Pre-requisites

List any workshop prerequisites, for example:

• Basic knowledge of R syntax
• Familiarity with the GenomicRanges class
• Familiarity with xyz vignette (provide link)

List relevant background reading for the workshop, including any theoretical background you expect students to have.

• List any textbooks, papers, or other reading that students should be familiar with. Include direct links where possible.

Workshop Participation

Describe how students will be expected to participate in the workshop.

R / Bioconductor packages used

List any R / Bioconductor packages that will be explicitly covered.

Time outline

An example for a 45-minute workshop:

| Activity | Time | |------------------------------|------| | Packages | 15m | | Package Development | 15m | | Contributing to Bioconductor | 5m | | Best Practices | 10m |

Workshop goals and objectives

List "big picture" student-centered workshop goals and learning objectives. Learning goals and objectives are related, but not the same thing. These goals and objectives will help some people to decide whether to attend the conference for training purposes, so please make these as precise and accurate as possible.

Learning goals are high-level descriptions of what participants will learn and be able to do after the workshop is over. Learning objectives, on the other hand, describe in very specific and measurable terms specific skills or knowledge attained. The Bloom's Taxonomy may be a useful framework for defining and describing your goals and objectives, although there are others.

Learning goals

Some examples:

• describe how to...
• identify methods for...
• understand the difference between...

Learning objectives

• analyze xyz data to produce...
• create xyz plots
• evaluate xyz data for artifacts

A note about learning goals and objectives (#bloom)

While not a new or modern system for thinking about learning, Bloom's taxonomy is one useful framework for understanding the cognitive processes involved in learning. From lowest to highest cognitive requirements:

1. Knowledge: Learners must be able to recall or remember the information.
2. Comprehension: Learners must be able to understand the information.
3. Application: Learners must be able to use the information they have learned at the same or different contexts.
4. Analysis: Learners must be able to analyze the information, by identifying its different components.
5. Synthesis: Learners must be able to create something new using different chunks of the information they have already mastered.
6. Evaluation: Learners must be able to present opinions, justify decisions, and make judgments about the information presented, based on previously acquired knowledge.

To use Bloom's taxonomy, consider the following sets of verbs and descriptions for learning objectives:

1. Remember: Memorize, show, pick, spell, list, quote, recall, repeat, catalogue, cite, state, relate, record, name.
2. Understand: Explain, restate, alter, outline, discuss, expand, identify, locate, report, express, recognize, discuss, qualify, covert, review, infer.
3. Apply: Translate, interpret, explain, practice, illustrate, operate, demonstrate, dramatize, sketch, put into action, complete, model, utilize, experiment, schedule, use.
4. Analyze: Distinguish, differentiate, separate, take apart, appraise, calculate, criticize, compare, contrast, examine, test, relate, search, classify, experiment.
5. Evaluate: Decide, appraise, revise, score, recommend, select, measure, argue, value, estimate, choose, discuss, rate, assess, think.
6. Create: Compose, plan, propose, produce, predict, design, assemble, prepare, formulate, organize, manage, construct, generate, imagine, set-up.

knitr::opts_chunk$set(echo = TRUE)

How to add figures

r knitr::include_graphics(system.file(package='dummychapter1', 'vignettes', 'fig.png'))

How to add citations

Cite like that: [@paper1]

R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)

Including Plots

You can also embed plots, for example:

plot(pressure)

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

lpantano/dummychapter1 documentation built on May 31, 2020, 8:06 p.m.