パーソナルツール
現在の場所: ホーム 担当教員 Kramer, Brandon Syllabus2019 Advanced Seminar 4

←講義で検索へ     ←時間割で検索へ

科目名 Advanced Seminar 4  Science and Society
担当教員 Kramer, Brandon
授業の目的、または到達目標 To introduce and explore the theories and techniques which support all findings in the social sciences. Students will learn about basic methods of data analysis, and how to critically look at results and “facts” presented in current media and advertising.

By the end of the course, students should be able to:
* perform and explain the core procedures underlying data analysis within the social sciences
* critically interpret data presented in current topics and advertising
* create appropriate data collection instruments, and analyze the data collected from them
授業の概要 This course will cover the basic procedures for data analysis in the social sciences. Some elementary techniques and concepts will be introduced, with ample time for practice and implementation using real data. While this knowledge is developing, students will practice critical interpretation of data presented in current topics and advertising. Finally, students will practice creating their own data collection instruments and collecting original data, which they will analyze and present.

科目群/ベンチマーク Advanced レベル必修 ENG2840 (716生以降)
授業の形態 Lectures, group and class discussions, group data collection projects, homework modules, online coursework, presentations, and reflection papers.
時間割   概要 宿題(予習・復習等)
1
  • Introduction to Social Sciences; Introduction to Numeracy
  • Reading (1 hour)
  • Module 1 Worksheet (1 hour)
2
  • Collecting Data: Sampling from a Population
  • Reading (30 min)
  • Module 2 Worksheet (30 min)
  • Data Collection (1.5 hours)
3
  • Describing Quantitative Data: Histograms, Central Tendency, and Standard Deviation
  • Reading (30 min)
  • Response Paper 1 (2 hours)
4
  • Relationships between Variables: Correlations
  • Reading (30 min)
  • Module 3 Worksheet (1 hour)
5
  • Relationships between Variables: P-values and Hypothesis testing
  • Reading (30 min)
  • Data Collection (2 hours)
6
  • Displaying Data with APA Tables and Figures
  • Reading (30 min)
  • Response Paper 2 (2 hours)
7
  • Comparing Groups or Variables: T-tests and P-values
  • Reading (30 min)
  • Data Collection (2 hours)
8
  • Experimental Design: How Inferences are Made
  • Reading (30 min)
  • Response Paper 3 (2 hours)
9
  • Introduction to Qualitative Data Collection
  • Reading (30 min)
  • Data Collection (2 hours)
10
  • Qualitative Data Analysis: Data- and Concept-driven Coding
  • Reading (30 min)
  • Response Paper 4 (2 hours)
11
  • Introduction to Mixed Methods Analysis
  • Reading (30 min)
  • Data Collection (2 hours)
12
  • Data Review and Presentation Preparation
  • Reading (30 min)
  • Data Analysis (2 hours)
13
  • Presentation Preparation and Practice
  • Presentation Preparation and Practice (3 hours)
14
  • Research Presentations
  • Summary and Reflection Paper (2.5 hours)
  • Peer Review (30 min)
15
  • Reflection and Wrap-up
  • Respond to any remaining feedback (1 hour)
準備学習 Class will be conducted assuming that all students have completed all assigned materials. Students must do the assigned modules, tasks, and readings before class, and prepare for weekly discussions. Readings and homework must be completed before class. Data collection and analysis for multiple projects will be done in groups. Response and reflection papers will be based on these projects and must be completed alone. Out-of-class assignments should take at least 2 to 3 hours for every hour in class, so students should manage their time accordingly.

A detailed syllabus will be provided in the first class. Any changes to this syllabus will be announced at that time.
教科書 Free readings and sources of online learning will be utilized, and additional notes and activities will be provided.
参考文献 Additional learning resources will be used in this class and provided for students to watch or read and try to understand. These materials will be difficult, and students will be expected to be proactive if they are unable to comprehend these resources and ask for help from fellow students or the teacher to understand the material.
成績評価方法・基準 Evaluation is based on the following categories:
*Class work & quizzes: 40% (includes in-class work, homework, presentations, quizzes, discussions);
*Research presentation(s): 20%;
*Written summary & reflection of research: 10%;
*Reflection & response papers: 30% (x 4)

Written feedback on all assignments (comments and suggested corrections) will be given online through Google Classroom. Students are expected to use this feedback to improve their work.
備考 使用言語:英語