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Michael J. Munje

dblp:236/6308 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0002-9168-0923ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 81% Computational science and engineering · 19%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education › AI education
AI literacy
1.012026
The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All · AAAI 2026
Computing education › curriculum design
course design
0.312026
The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All · AAAI 2026
Computational science and engineering › active learning
flipped classroom
0.312026
The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All · AAAI 2026

Methods — techniques the papers use, named apart from their topics

non-programming assignments · 1.0flipped classroom · 1.0asynchronous learning modules · 1.0
YearPublicationVenuePosition
2026 The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All
abstract
In Fall 2023, we introduced a new AI Literacy class called The Essentials of AI for Life and Society (CS 109), a one-credit, seminar course consisting mainly of guest lectures, which was open to the entire university, including students, staff, and faculty. Building on its success and popularity, this paper describes our significant expansion of the course into a full-scale three-credit undergraduate course (CS 309), with an expanded emphasis on student engagement, interactivity, and ethics-related components. To knit together content from the guest lecturers, we implemented a flipped classroom. This model used weekly asynchronous learning modules---integrating pre-recorded expert lectures, collaborative readings, and ethical reflections---which were then unified by the course instructor during a live, interactive discussion session. To maintain the broad accessibility of the material (no prerequisites), the course introduced substantive, non-programming homework assignments in which students applied AI concepts to grounded, real-world problems. This work culminated in a final project analyzing the ethical and societal implications of a chosen AI tool. The redesigned course received overwhelmingly positive student feedback, highlighting its interactivity, coherence, and accessible and engaging assignments. This paper details the course's evolution, its pedagogical structure, and the lessons learned in developing a core AI literacy course. All course materials are freely available for others to use and build upon.
Zifan Xu, Kristen Procko, Michael J. Munje, Kristin Patterson, Lea Sabatini, Joydeep Biswas, Peter Stone 0001
AAAI3