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ENGL 271 — INTRODUCTION TO POETRY

5 credits CIM Verified
1
Objectives
10
Matches
0
Reviewed
12
Occupations
Your experience with this course
Top occupation matches for this course
36.5% Interpreters and Translators 4t
49.4% Poets, Lyricists and Creative Write 4t
45.1% News Analysts, Reporters, and Journ 4t
34.5% Art Therapists 3t
39.3% Actors 3t

Learning Objectives & Matches

LO1 CIM

Use literary terms

10 O*NET task matches
Batch:
Archivists 3.1/5
49% ok

Select and edit documents for publication and display, applying knowledge of subject, literary expression, and presentation techniques.

Poets, Lyricists and Creative 4.7/5
49% ok

Write fiction or nonfiction prose, such as short stories, novels, biographies, articles, descriptive or critical analyses, and essays.

News Analysts, Reporters, and 4.0/5
45% ok

Determine a published or broadcasted story's emphasis, length, and format, organizing material accordingly.

Correspondence Clerks 4.0/5
45% ok

Read incoming correspondence to ascertain nature of writers' concerns and to determine disposition of correspondence.

Poets, Lyricists and Creative 4.5/5
44% ok

Choose subject matter and suitable form to express personal feelings and experiences or ideas, or to narrate stories or events.

English Language and Literatur 4.2/5
42% ok

Prepare and deliver lectures to undergraduate or graduate students on topics such as poetry, novel structure, and translation and adaptation.

Poets, Lyricists and Creative 4.7/5
41% ok

Develop factors such as themes, plots, characterizations, psychological analyses, historical environments, action, and dialogue to create material.

Editors 4.1/5
40% ok

Write text, such as stories, articles, editorials, or newsletters.

Actors 4.7/5
39% ok

Work closely with directors, other actors, and playwrights to find the interpretation most suited to the role.

Editors 4.4/5
39% ok

Develop story or content ideas, considering reader or audience appeal.

Source: Course learning outcomes from EWU's official Course Inventory Management (CIM) system. O*NET task matches are computed by comparing each learning outcome statement against every O*NET task statement using sentence-embedding similarity; faculty review confirms which matches count as preparation evidence.