IN-SESSIONAL ENGLISH-II

Course Description

This course is the continuation of ENGL031. In this respect this course provides a further general revision on grammatical structures such as active and passive voice, adverbial clauses, and connectors to ensure that students are equipped with the required higher level of background knowledge to achieve academic reading and writing tasks successfully. Regarding writing skills students are introduced to sentence structures, basic components of paragraphs such as topic sentence, topic and controlling idea, supporting sentences, and concluding sentences. Students are expected to reflect the acquired knowledge by writing a short descriptive paragraph about themselves. This course also provides the opportunity to improve students’ reading skills through a variety of higher level reading passages.

IN-SESSIONAL ENGLISH-II

Evaluation Tools (Active Term)

Course outcomes

1. 01 The students will be able to learn
2. 02 Acquiring an introductory knowledge of Turkish
3. 03 Acquiring skills to communicate with his/her friends
4. 04 Ability to use Turkish in shopping, travel and other daily needs

Course Syllabus

Reference Books & Course Materials

1. 01 Haugnes, N. & Maher, B. (2020). NorthStar: Reading & Writing Level 2, Fifth Edition, Pearson.

Learning Outcomes

1. L01 By the end of the course students will be able to recognize basic components of a paragraph such as topic sentence, topic, controlling idea, supporting sentences etc.
2. L02 extend their reading skills through a variety of higher level reading passages.
3. L03 analyze various reading passages by employing necessary reading techniques such as skimming, scanning, inferring and etc.
4. L04 reflect the acquired knowledge by writing a short descriptive paragraph about themselves.

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