Reading Like a Computer

Course Learning Outcomes

By the end of this course, students will:

  1. Compare basic techniques of computer-assisted analysis of texts — Understand different computational approaches to text analysis and when each is appropriate.

  2. Compare and contrast different forms of reading — Analyze the relationships between human reading, non-human (computational) reading, and hybrid forms that combine both.

  3. Articulate computational thinking — Develop an understanding of how computational approaches enable new ways of thinking about texts and problems, recognizing questions of bias and scale.

  4. Integrate visuals into analytical writing — Develop skills in visual communication, using visualizations critically and with clarity to support written arguments.

  5. Practice effective communication in multiple formats — Develop multimodal communication skills through written responses, web-based publishing, synchronous discussions.

  6. Debate possible futures of reading — Engage in informed discussion about how technology might shape the future of reading, interpretation, and knowledge-making.

Alignment with NYUAD Core Program Learning Outcomes

The course outcomes map to the following NYUAD Core Program Learning Outcomes:

1. Critical Inquiry and Analysis

Students will critically examine contemporary topics through:

  • Qualitative analysis (close reading, interpretation)
  • Quantitative methods (computational analysis, data visualization)
  • Contextual reasoning (historical, social, cultural contexts)
  • Creative approaches (experimentation, novel applications of tools)

Relevant Course Outcomes: TBA

2. Communication and Expression

Students will communicate effectively for various audiences through:

  • Public web-based writing
  • Participation in synchronous discussions
  • Recorded tutorials and multimedia formats
  • Academic and non-academic writing styles

Relevant Course Outcomes: TBA

3. Self-Understanding and Intercultural Competency

Students will demonstrate awareness of:

  • Their own assumptions about reading and interpretation
  • Diverse perspectives on technology and data
  • Global disparities in cultural representation

Relevant Course Outcomes: TBA

4. Conceptual and Ethical Complexity

Students will identify and reflect critically on:

  • Ethical implications of computational analysis
  • Limitations and possibilities of algorithms
  • Power dynamics in data collection and interpretation

Relevant Course Outcomes: TBA