Teaching Statement

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Teaching Experience

Faculty Mentor
Carnegie Mellon University School of Computer Science

Independent Study: Foundations of Computer Programming Research (Spring 2023, 2 Students)

Course description: This course focuses on how people learn computer programming languages, such as Python, HTML, CSS, and Javascript. Few programming environments offer learners the option to solve the same problem across different programming problem types. Codespec, a programming tutor, supports learners in solving a programming problem as a pseudocode Parsons problem, a Parsons problem, a Faded Parsons problem, a fix-code problem, or a write-code problem. The goal of this course is for students to understand the foundations of computing education and human-computer interaction research on computer programming through project-based learning (PBL)—an approach used to help students develop knowledge and skills through engaging projects set around challenges and problems they may face in the real world.

Graduate Student Instructor
University of Michigan School of Information

Data Science Ethics (Spring 2022, 47 Students)

The course introduces the ethical challenges that data scientists face and can help to resolve using case-based reasoning within four domains that are central to data science: data privacy, bias, data provenance, and accountability.

Learning Analytics and Educational Data Science (Summer 2022, 45 Students)

The course examines the application of data science to better understand and improve learning. Anchored in the fields of learning analytics and educational data mining, this course analyzes the unique opportunities and challenges associated with applying data science methods to data stemming from schools, universities, and myriad learning opportunities.

Fundamentals of Human Behavior (Fall 2020, 112 Students)

Surveyed basic principles of cognitive and social psychology relevant to the design and use of information systems. Focuseed on important findings in psychological science and their implications for the design and use of information systems. Topics included the basics of human perception, memory capacity and organization, the development of skill and expertise, and the characteristics of everyday reasoning and decision making. For example, a central problem in information science is how to label information stored for later recall. By examining how human memory operates, we can gain some insight into possible schemes that may be compatible with human users. This survey of what we know about the human mind offers ideas about how to exploit mental capacities in the design and use of information systems.

Needs Assessment and Usability Evaluation (Winter 2019, 156 Students)

This course covered the key concepts of evaluation and a variety of methods used to determine the goals of a system or service. Students were asked to perform organizational analyses, assess task/technology and service fit, determine ease of learning of new or existing services or systems, determine ease of use, assess aspects of performance (including information retrieval), and evaluate the success in accomplishing the user/organizational goals. Methods included observation, survey, interviews, performance analysis, evaluation in the design/iteration cycle, usability tests, and assessment of systems in use.

Graduate Teaching Assistant
Syracuse University School of Information Studies

Introduction to Information-Based Organizations (Spring 2015, 38 Students)

This course covered: organizational behavior; groups and teams; leadership and management; human resources; organizational development; change management; interactions between people and technology in work organizations; and the impact of information technology on organizational effectiveness.