Hospitality & Tourism Management Department Spring Quarter 2026 HOST 253 (36483): AI Unveiled: An Introduction to LLMs and Generative AI Instructor: Justin Taillon (jtaillon@highline.edu) Office: 26-322 Student Hours: Monday (1:30p-2:50p), Wednesday (1:30p-5p), & Thursday (1:30p-2:50p) Appointments: Pre-Book Meetings (I recommend pre-booking meetings) Class Schedule: Online Text required: HOST courses do not rely on textbooks. All materials for this course will be provided to you electronically on Canvas Highline College: 2400 South 240th Street Des Moines, WA 98198 P: (206) 878-3710 COURSE DESCRIPTION Tools associated with Artificial Intelligence (AI)& Large Language Models (LLMs) are developing rapidly in the global business environment. Managers have a responsibility to effectively manage the impact of AI on business operations. Managers may be wise to focus on the practical uses rather than the technical designs of AI in workplace environments. This course therefore adopts a unique approach to understanding AI and LLMs. This course introduces AI in the context of the global business environment, with a focus on learners who will manage people and processes that may include AI and LLMs. Learners will become adept at prompt writing while acquiring insights to how AI and LLMs are being adopted societally through completing this course. Furthermore, the course materials lead learners to critically examine the ethical and moral questions AI adoption raises. An emphasis is placed on understanding the future of AI, how these tools can improve both personal and professional lives, and strategies for using them effectively and responsibly (including in higher education where plagiarism concerns are most pronounced). Students will be able to confidently identify when and how to use AI and LLMs to enhance productivity, creativity, and decision-making in diverse contexts. LEARNING OUTCOMES Being aware of the course learning outcomes is paramount to success in all your coursework. The learning outcomes guide the material each of your courses covers and the way the material is covered. Please make yourself aware of the elements of this course and all other pertinent courses. The course learning outcomes for all HOST classes can be viewed at this web address: http://catalog.highline.edu/ The Student Learning Outcomes for this course are as follows. Learners… • Define foundational terms and concepts related to Artificial Intelligence (AI) and Large Language Models (LLMs). • Implement prompt-writing strategies in personal and professional contexts. • Analyze societal adoption trends of AI/LLMs including implications. • Evaluate the ethical and moral considerations surrounding AI/LLMs including bias, privacy, and responsible use. • Forecast potential future use of AI/LLMs including strategic integration of these tools effectively into their careers and personal routines. • Demonstrate an ability to identify when and how to apply AI/LLMs to enhance productivity and decision-making. PARTICIPATION Hopefully participation is fun in our course together this quarter! Participation does not mean only one thing. You are a unique individual and your approach to participation can be as unique as you are. Participation is graded. You can lose or gain up to 10% of your final grade in the course. If you are going to lose more than 3% of your final grade due to a lack of participation, then a meeting will be requested beforehand. You will not lose more than 3% without being notified in advance and being given a chance to meet with your instructor(s). No student will lose more than 10% of their final grade due to a lack of participation. It is also possible to gain a maximum of 10% toward your final grade based on participation. Losing points occurs primarily through cheating such as plagiarism, not attending class when enrolled on campus, treating members of our class poorly, or submitting multiple assignments after the due date. We will have fun and your participation will likely be seen in a positive light so long as you put forth a positive effort. Student and Visitor Exchange Program This course does not comply with the Student and Visitor Exchange Program (SEVP) requirements for F-1 international students. International students can still enroll in the course under certain circumstances, though. ASSIGNMENT PROTOCOLS All final exams take place face-to-face in courses that are scheduled face-to-face. The time and location of your final exam will be dictated by the College. Hybrid, flexible, and online asynchronous courses have final exams that take place online. These final exams stay open for a minimum of 48 hours in my classes. Instructors cannot move final exam locations or times. You are responsible for knowing the time and location of your final exam. This can be located on Highline.edu. You are eligible for an Incomplete if you complete the course except for the Final Exam and the instructor agrees to an Incomplete. Incompletes can be made up later in agreement with the instructor. You will not be given an Incomplete if you choose to depart campus early. For example, flight dates are not a reasonable excuse for missing a final exam. Assignment Grading ASSIGNMENT No. % / ea. Total Assessments 10 10 100 TOTAL 100 All submission and quiz assignments will be submitted on Canvas. The instructor will not micro-manage your submissions. Do not expect to be notified of your failure to keep up in the course unless you fall behind drastically. Assignment Explanations Assessments: There are eleven assignments in this course. Your ten highest grades count toward your final grade in the course. Your lowest grade is dropped. Each assignment is worth the same amount of your final grade in the course: 10%. All assignments can be completed multiple times. You can earn the grade you want in this course! Your first submission will normally be graded within 7-10 days. You can then re-do the assignment. I grade re-submissions close to the end of the quarter. Language AI You may use AI tools such as Chat GPT. This is an AI course; you should use AI tools extensively. You cannot plagiarize though. If you are unsure whether you understand plagiarism then please visit this site to learn about plagiarism. You can read more about plagiarism in this department in the departmental syllabus (attached to this course syllabus). A foundational element of this course is to learn about plagiarism. If you are unsure of what constitutes plagiarism, then you are in the right course. Please follow the course material and speak with the instructor if you have questions about plagiarism, including how it is explained and forwarded as course content. Please do not plagiarize. You will be held accountable.

ホスピタリティ＆ツーリズムマネジメント学科 2026年春学期 HOST 253（36483）： AIの解明：LLMと生成AI入門 担当教員：Justin Taillon（jtaillon@highline.edu ） オフィス：26-322 学生対応時間：月曜（1:30〜2:50）、水曜（1:30〜5:00）、木曜（1:30〜2:50） 面談：事前予約推奨 授業形式：オンライン 教科書：HOSTの授業では教科書は使用しません。すべての教材はCanvas上で提供されます。 ハイラインカレッジ住所： 2400 South 240th Street Des Moines, WA 98198 電話：(206) 878-3710 授業概要（COURSE DESCRIPTION） 人工知能（AI）および大規模言語モデル（LLMs）に関連するツールは、グローバルなビジネス環境において急速に発展しています。 マネージャーは、AIが業務に与える影響を効果的に管理する責任があります。 この授業では、AIの技術的な仕組みよりも、実際のビジネス現場での活用に重点を置きます。 学生は以下を学びます： AIとLLMの基礎理解 プロンプト作成スキル 社会におけるAIの普及の理解 倫理的・道徳的問題の検討 また、AIを適切かつ責任を持って使う方法を学び、 生産性・創造性・意思決定を向上させる能力を身につけます。 学習到達目標（LEARNING OUTCOMES） 学生は以下ができるようになります： AIとLLMの基本用語・概念を定義する プロンプト作成戦略を実践する 社会におけるAIの普及を分析する 倫理的問題（バイアス・プライバシーなど）を評価する AIの将来の活用を予測する AIを使って生産性や意思決定を向上させる 参加（PARTICIPATION） 参加は成績評価に含まれます。 最終成績の最大±10％に影響します。 減点の主な理由： 不正行為（盗用など） 出席しない 他の学生への不適切な態度 課題の遅延提出 ただし、事前通知なしに3％以上減点されることはありません。 留学生に関する注意 この授業は、Student and Visitor Exchange Program（SEVP）の要件には適合していません。 ただし、条件によっては履修可能です。 課題ルール（ASSIGNMENT PROTOCOLS） 対面授業の期末試験は対面で実施 オンライン授業はオンラインで実施 試験は最低48時間開放 ※飛行機の都合などは欠席理由として認められません 成績配分（Assignment Grading） 評価課題：10回（各10％） 合計：100％ 課題について（Assessments） 全11回の課題（上位10回の成績が採用） 最低点は自動的に除外 再提出可能（好きな点数を狙える） AIの使用について AIツール（例：ChatGPT）は使用可能です。 ただし： 盗用は禁止 学科のルールに従う必要あり この授業では、 「AIを使いながら、盗用を理解すること」 が重要な学習目的です。