In this elementary textbook, Philip S. Peek draws on his twenty-five years …
In this elementary textbook, Philip S. Peek draws on his twenty-five years of teaching experience to present the ancient Greek language in an imaginative and accessible way that promotes creativity, deep learning, and diversity. The course is built on three pillars: memory, analysis, and logic. Readers memorize the top 250 most frequently occurring ancient Greek words, the essential word endings, the eight parts of speech, and the grammatical concepts they will most frequently encounter when reading authentic ancient texts. Analysis and logic exercises enable the translation and parsing of genuine ancient Greek sentences, with compelling reading selections in English and in Greek offering starting points for contemplation, debate, and reflection. A series of embedded Learning Tips help teachers and students to think in practical and imaginative ways about how they learn. This combination of memory-based learning and concept- and skill-based learning gradually builds the confidence of the reader, teaching them how to learn by guiding them from a familiarity with the basics to proficiency in reading this beautiful language. Ancient Greek I: A 21st-Century Approach is written for high-school and university students, but is an instructive and rewarding text for anyone who wishes to learn ancient Greek.
Data Carpentry lesson from Ecology curriculum to learn how to analyse and …
Data Carpentry lesson from Ecology curriculum to learn how to analyse and visualise ecological data in R. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with ecology data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R.
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