These materials have been put together to help students and youth to learn the basics of judging and evaluating dairy cattle using various methods. This resource was designed to be used with other resources to help teach basic dairy cattle judging and evaluation. There are numerous 4-H, Cooperative Extension and Breed Association booklets freely available, referred to in the document. However, this resource differs as it is intentionally full of visual examples and videos. The objective is to provide educators with additional resources to help beginning cattle judges understand visual evaluation and comparative judging techniques, as well as breed standards, linear scoring, oral reasons and the basics of fitting and showmanship.

This course introduces effective techniques for conducting interviews and is designed to help you develop and strengthen your skills as an interviewer. It does not assume any existing experience conducting interviews, but will quickly take you past the basics and into best practices that incorporate the Lean Research principles of rigor, relevance, respect, and right-size. The course focuses specifically on conducting interviews in “the field”— contexts in which we may be in an unfamiliar setting or culture, such as when traveling abroad or conducting research in a place we haven’t been before.
This course is part of the Open Learning Library, which is free to use. You have the option to sign up and enroll in the course if you want to track your progress, or you can view and use all the materials without enrolling.

Through continued practice, students will be able to corageously seek truth in a world of 'fake news'

This course presents the main concepts of decision analysis, artificial intelligence, and predictive model construction and evaluation in the specific context of medical applications. The advantages and disadvantages of using these methods in real-world systems are emphasized, while students gain hands-on experience with application specific methods. The technical focus of the course includes decision analysis, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks), and techniques to evaluate the performance of such systems.

This course presents the main concepts of decision analysis, artificial intelligence and predictive model construction and evaluation in the specific context of medical applications. It emphasizes the advantages and disadvantages of using these methods in real-world systems and provides hands-on experience. Its technical focus is on decision support, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks, rough sets), and techniques to evaluate the performance of such systems. It reviews computer-based diagnosis, planning and monitoring of therapeutic interventions. It also discusses implemented medical applications and the software tools used in their construction. Students produce a final project using the machine learning methods learned in the course, based on actual clinical data.
Lecturers
Prof. Stephan Dreiseitl
Prof. Ju Jan Kim
Prof. Bill Long
Prof. Marco Ramoni
Prof. Fred Resnic
Prof. David Wypij

The OER Accessibility Evaluation Rubric is an evaluation tool for faculty, librarians, instructional designers, and other stakeholders in open educational resources to determine the accessibility of the OER they are creating and/or adopting for use in their courses.

A one page review form with 8 overall criteria and tagging suggestions to provide a basic and quick overview of an OER.

Pour ses 20 ans, l’Institut de Pédagogie universitaire et des Multimédias (IPM) change de nom et devient le Louvain Learning Lab (LLL). C’est dans le cadre de cet anniversaire que l’équipe qui le compose a choisi de rédiger un carnet pédagogique à destination des enseignants de l’enseignement supérieur et universitaire. Ce carnet propose, au départ de questions formulées par des enseignants et d’interviews, des fiches synthétiques portant sur quatre grands thèmes : la conception d’un cours, l’approche-programme, les technologies au service de l’apprentissage et le développement du projet pédagogique de l’enseignant et de ses compétences. L’équipe du LLL propose non pas un traité qui prendrait par la main en expliquant dans le grand détail les sujets incontournables… mais bien un carnet pour laisser le lecteur explorer la pédagogie universitaire à sa guise en lui signalant diverses ressources. Les trajectoires sont laissées au choix des lecteurs comme autant d’invitations à réfléchir et, surtout, à partager avec des collègues ou en équipe programme.

The Problem Solving Profile is a tool to help evaluate and/or assess instructional projects or courses that may have technology components or are technology enabled.The Problem Solving Profile contains questionnaires of one page length, or a short web survey, that measures proclivities of problem solving styles that learners exhibit.This site contains PowerPoint presentations on the use of the Problem Solving Profile, sample Profiles, research papers on the use of the Problem Solving Profile and a Frequently Asked Question page (FAQ).The Problem Solving Profile has been used at the University of Michigan since the early 1990s and has been used for determining groups of learners problem solving profiles and then using the information to help modify and improve learning processes. It has been used in evaluating:Distance learning in business administrationTeacher education computer competenciesDistance learning in nursing and midwifery and Advanced research methods courses in designing evaluation for new technology in instruction

Students use real-world data to calculate the potential for solar and wind energy generation at their school location. After examining maps and analyzing data from the online Renewable Energy Living Lab, they write recommendations as to the optimal form of renewable energy the school should pursue.

Students use real-world data to evaluate whether solar power is a viable energy alternative for several cities in different parts of the U.S. Working in small groups, they examine maps and make calculations using NREL/US DOE data from the online Renewable Energy Living Lab. In this exercise, students analyze cost and availability for solar power, and come to conclusions about whether solar power is a good solution for four different locations.

Students use real-world data to evaluate the feasibility of solar energy and other renewable energy sources in different U.S. locations. Working in small groups, students act as engineers evaluating the suitability of installing solar panels at four company locations. They access data from the online Renewable Energy Living Lab from which they make calculations and analyze how successful solar energy generation would be, as well as the potential for other power sources at those locations. Then they summarize their results, analysis and recommendations in the form of feasibility plans prepared for a CEO.

Open textbook presenting the research process for lower-level undergraduate students: developing topics, understanding sources, developing search strategies, academic integrity, and MLA and APA documentation styles.

Associated lessons plans are also available for download and adaptation in the Guttman Community College OER collection in CUNY Academic Works.

This rubric was developed by BCcampus. This work is licensed under a Creative Commons Attribution 3.0 Unported license.The rubric allows reviewers to evaluate OER textbooks using a consistent set of criteria. Reviewers are encouraged to remix this rubric and add their review content within this tool. If you remix this rubric for an evaluation, please add the title to the evaluated content and link to it from your review.Template image attribution: "layers" (CC BY-SA 2.0) by theilr

The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.

By the end of this unit teachers should be able to:

Deepening Knowledge 2. (b) Develop and apply knowledge-based and performance-based assessment standards that allow teachers to assess students' understanding of the major processes, skills, and concepts related to the subject matter.

بحلول نهاية هذه الوحدة ، يجب أن يكون المعلمون قادرين على:

تعميق المعرفة 2. (ب) تطوير وتطبيق معايير تقييم قائمة على المعرفة والأداء تسمح للمعلمين بتقييم فهم الطلاب للعمليات والمهارات والمفاهيم الرئيسية المتعلقة بالموضوع.