IN-SESSIONAL ENGLISH LANGUAGE-II

Course Description

This course is the continuation of ENGL033 with more detailed information. Students will be able to acquire their academic reading skills such as finding the main idea, skimming, scanning, understanding the text by reading comprehension and answering relevant questions, inferring meaning by ordering information, finding suffixes and similar meanings, guessing meaning from texts, recognizing parts of speech in sentence structures and identifying text organization through matching pieces of information. In effective written skills aims to develop critical thinking, which enables students respond to ideas in a well-organized written format. They identify process paragraphs, narrative paragraphs and opinion paragraphs. The writing goals are divided into two: rhetorical focus, language and grammar focus.

IN-SESSIONAL ENGLISH LANGUAGE-II

Evaluation Tools (Active Term)

Course outcomes

1. 01 1- apply necessary reading strategies which are skimming and scanning, and understanding the reading texts.
2. 02 2- differenciate the main ideas of the reading texts and statements from the supporting details.
3. 03 3- identify three sections of essay writing. (The sentence and the paragraph, Descriptive Paragraphs, Example Paragraphs)

Course Syllabus

Reference Books & Course Materials

1. 01 English, A. K. & English, M. L. NorthStar 3. Reading & Writing. 5th Ed. Pearson, 2020

Learning Outcomes

1. L01 1- apply necessary reading strategies which are skimming and scanning, and understanding the reading texts.
2. L02 2- differenciate the main ideas of the reading texts and statements from the supporting details.
3. L03 3- identify three sections of essay writing. (The sentence and the paragraph, Descriptive Paragraphs, Example Paragraphs)

Program Outcomes

1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix