A collection of course syllabi from any discipline featuring content to examine or improve open and reproducible research practices. Email to join project, access articles, or add other syllabi.

Course description: A research-based course on the use of language for thinking, problem-solving and communicating across subject areas. Includes best-practice teaching strategies that will enable all students to become independent learners.

The Mars Education lesson plans section is here to serve as a resource for educators, grades K-12 to download and utilize in formal classroom settings.
For questions on the Mars Education Lessons please contact us.
All of the Mars Education Program lesson plans include elements of inquiry-based learning that are aligned to Common Core and Next Generation Science Standards (NGSS) as well as problem-based learning and the Biological Sciences Curriculum Study (BSCS) 5-E instructional model.
The STEM lessons included in this section of the website are the very lessons that we apply throughout our educator conferences and professional development training sessions.
To get a more thorough understanding and deeper knowledge of these lessons as an in classroom instructional tool, educators may want to consider attending an ASU Mars Education Conference.

Online training programme for activities and specialized educators on how to use the methodology and tools developed under the project : It targets youth activists and specialized educators who want to involve youth people in civic participation projects, with the goal of training more youth activists and educators.  

Open Science, the movement to make scientific products and processes accessible to and reusable by all, is about culture and knowledge as much as it is about technologies and services. Convincing researchers of the benefits of changing their practices, and equipping them with the skills and knowledge needed to do so, is hence an important task.This book offers guidance and resources for Open Science instructors and trainers, as well as anyone interested in improving levels of transparency and participation in research practices. Supporting and connecting an emerging Open Science community that wishes to pass on its knowledge, the handbook suggests training activities that can be adapted to various settings and target audiences. The book equips trainers with methods, instructions, exemplary training outlines and inspiration for their own Open Science trainings. It provides Open Science advocates across the globe with practical know-how to deliver Open Science principles to researchers and support staff. What works, what doesn’t? How can you make the most of limited resources? Here you will find a wealth of resources to help you build your own training events.

An ecosystem of free open source tools for improving the rigor and reproducibility of research is thriving. Information professionals at research institutions must stay informed about what tools are available and how they compare. Ideally, information professionals can also onboard researchers to kickstart adoption of these tools. However, developing quality curriculum to train researchers on new tools requires expertise in the tool itself, which leaves many researchers without training on tools that may benefit their research.
This course will train participants to run hands-on, quality modules designed to onboard researchers to four free open source tools. Participants will experience each module, practice the exercises, and explore the training material needed to run the module themselves. An instructor guide that includes the module outline, objectives, description, frequently asked questions, pre- and post-participant surveys, target audience, and instructions for running a successful module is provided for each tool taught.

This course will train participants to run modules on unique aspects of four free open source tools for researchers:

Binder: Share your computational environment, code, and research notebooks.
Renku: Document and share your analysis pipelines.
Open Science Framework: Create a centralized, structured workspace for your research materials.
KnitR: Knit your R code with your analysis narrative in one executable research notebook and capture your dependencies.

Many participants already run short-duration training events at their institutions. This course is ideal for those participants who wish to improve the quality and variety of the training they already offer to researchers. Participants who do not currently run short-duration training events at their institutions will benefit from the course by learning an accessible and efficient way of getting started with these four modules.

The Project Teaching Integrity in Empirical Research (TIER) develops methods and tools for enhancing research transparency through teaching. These can be used by faculty who teach quantitative methods or supervise student research. TIER further provides guidance to students who want to adopt transparent and replicable research practices independently.

Materials for the University of Glasgow Institute of Neuroscience and Psychology’s undergraduate and MSc methods courses + Experiences, insights, and materials for teaching R across all undergraduate and postgraduate levels.

About Stats of DOOM

Support Statistics of DOOM! This page and the YouTube channel to help people learn statistics by including step-by-step instructions for SPSS, R, Excel, and other programs. Demonstrations are provided including power, data screening, analysis, write up tips, effect sizes, and graphs. Help guides and course materials are also provided!

When I originally started posting my videos on YouTube, I never really thought people would be interested in them - minus a few overachieving students. I am glad that I've been able to help so many folks! I have taught many statistics courses - you can view full classes by using the Learn tab in the top right. I have also taught cognitive and language courses, some with coding (see the NLP and Language Modeling courses), and some without (see Other Courses). I hope this website provides structure to all my materials for you to use for yourself or your classroom.

Each page has an example syllabus, video lectures laid out with that syllabus (if I have them!), and links to the appropriate materials. Any broken links can be reported by sending me an email (linked at the bottom). Stats Tools was designed for learning statistics, which morphed into learning coding, open science, statistics, and more! Recommendations, comments, and other questions are welcome with the general suggestion to post on the specific video or page you have a question on. I do my best to answer, but also work a full-time job.

These resources wouldn't be possible without the help of many fantastic people over the years including:

All the Help Desk TAs: Rachel E. Monroe, Marshall Beauchamp, Louis Oberdiear, Simone Donaldson, Kim Koch, Jessica Willis, Samantha Hunter, Flora Forbes, Tabatha Hopke
Research colleagues: K.D. Valentine, John E. Scofield, Jeff Pavlacic
And more! Pages with specific content made by others are noted on that page.

lab.js is a free, open, online study builder for the behavioral and cognitive sciences. (it works great in the lab, too)