Faculty-led Inquiry into Reflective and Scholarly Teaching (FIRST)

 

Date of this Version

Spring 5-25-2025

Document Type

Portfolio

Comments

Copyright 2025, Hongzhi Guo. Used by permission

Abstract

This course portfolio was developed for CSCE 478/878: Introduction to Machine Learning, offered by the School of Computing at the University of Nebraska–Lincoln, as part of the Faculty-led Inquiry into Reflective and Scholarly Teaching (FIRST) project. The course provides an introduction to foundational machine learning concepts, models, and programming tools. It enrolls both undergraduate and graduate students from a wide range of academic backgrounds, including computer science, computer engineering, software engineering, biological systems engineering, chemical engineering, business-related fields, etc. Offered in Spring 2025, the course was peer-reviewed to support continuous improvement in teaching. The primary goals of this portfolio are to enhance the instructor’s teaching practices and contribute to the development of high-quality course materials for the broader curriculum. This document outlines key components of the course, including its objectives, structure, teaching strategies, instructional resources, and student activities. In addition to presenting the course content, the portfolio evaluates student learning outcomes through formal assessments and peer feedback. The diversity of the student cohort informed efforts to tailor the course design and pedagogy to a range of learning needs. The final section of the portfolio offers a critical reflection on the course’s effectiveness, which identifies strengths and areas for improvement based on assessment data, peer observations, and the instructor’s own experiences.

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