Welcome to the course! To ensure complete transparency in how your performance will be evaluated, please review the detailed grading rubrics below. Your final grade is composed of your Midterm Evaluation (Ongoing Assessment) and your Final Project (Google Colab Corpus).
PART 1: MIDTERM EVALUATION (100 Points)
I. Attendance & Class Participation (20 Points)
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Attendance (15 pts): Calculated based on your completion of the Attendance Check (Choice module) for each session.
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In-Class Engagement (5 pts): Evaluated based on your active participation in class activities, Mentimeter, Kahoot, and group work.
II. Engagement with Learning Materials (20 Points)
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Resource Coverage (10 pts): The percentage of available course materials (Files, Pages, URLs, Books) you have successfully opened and reviewed.
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Deep Learning (10 pts): Evaluated based on meaningful engagement with the materials, not just quickly clicking through them.
III. Chapter Quizzes (20 Points)
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Average Score (15 pts): The average score of all chapter quizzes, converted to a standard scale.
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Learning Improvement (5 pts): Points awarded for demonstrating consistent growth and improvement across quizzes.
IV. Assignments (25 Points)
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Your assignments are graded holistically based on five criteria:
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Submission Status: Was the file successfully submitted?
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Timeliness: Was it submitted before the deadline?
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Completeness: Does it meet all required instructions?
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Quality: Relevance, coherence, and correctness of the work.
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V. Forum Discussions & Social Learning (15 Points)
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Points are awarded for active participation in course forums, including posting original thoughts, answering peer questions, and maintaining a high quality of academic discourse.
🌟 Bonus points (Up to +5 Points): Awarded to students who demonstrate excellent, consistent weekly study habits (e.g., perfect attendance, completing 100% of reading materials).
PART 2: FINAL PROJECT – LINGUISTIC CORPUS & NLP (10 Points scaled to 100%)
Your final submission is a practical coding project demonstrating your mastery of the course's computational modules.
I. Submission Requirements & Critical Rules (Pass / Fail)
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You must build a linguistic corpus containing a minimum of 50,000 tokens using Google Colab.
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You must submit exactly ONE PDF file alongside the link to your code folder on Google Drive.
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CRITICAL PENALTY: Make absolutely sure we can access your Google Drive folder. You will get a ZERO for your final project if the instructors cannot open your link.
II. Part A: Replication of Sample Results (8 Points / 80%)
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Your workbook must successfully display all the results shown in the provided sample file.
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You must strictly use the exact same headings and labels as the sample file.
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Chapter 1 (Introduction): You must print your full name and age, total corpus tokens, and generate random text. You must also provide accurate concordancing results, lexical diversity scores, and various frequency/dispersion plots (e.g., nouns, verbs, adjectives). You must successfully filter specific words using pattern matching.
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Chapter 2 (Meaning and Ambiguation): You must extract WordNet attributes for selected words and write a script to disambiguate an ambiguous word within a sentence context.
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Chapter 3 (Part of Speech Tagging): You must extract specific sentences, perform POS tagging on them, and display the overall POS statistics for your entire corpus.
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Chapter 4 (Text Classification): You must extract specific sentences from your corpus and display them dynamically using Bag of Words and TF-IDF matrix visualizations.
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Chapter 5 (Syntax and Grammar): You must use the Spacy library to visually parse a selected sentence using Dependency Grammar.
III. Part B: Python Project Upgrade (2 Points / 20%)
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You must successfully upgrade a Python project from your textbook.
IV. AI Policy (Allowed & Encouraged)
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Unlike traditional essay writing, you are encouraged to use AI tools to assist you in coding, debugging, and building this final computational project.