Activity Design for First-Year Students with Access to AI
Robert Collier

School of Computer Science, Carleton University
Ottawa, Ontario, Canada
RobertCollier3@cunet.carleton.ca

ABSTRACT
We have entered a new era of accessible AI and educators should
be urged to embrace an opportunity to provide an early introduction
to this technology, without abandoning their legitimate concerns
about academic misconduct. With this short paper, the author will
discuss two stages in the evolution of a "portfolio game"
assignment suite for an introductory computer science course that
demonstrated techniques to ensure that students learn to work
alongside AI-based tools effectively, legitimately, and ethically.

CCS CONCEPTS
• Social and Professional Topics → Computing Education

KEYWORDS
ChatGPT, AI in Education, Programming, Teaching
ACM Reference Format: Robert Collier. 2025. Activity Design
for First-Year Students with Access to AI. In The 27th
Western Canadian Conference on Computing Education
(WCCCE’25), April 28–29, 2025, Calgary, AB, Canada. 2
pages. https://doi.org/10.60770/znfj-0613

1

Introduction

It is a reasonable concern in computer science that exclusively
supervised assessment can be inauthentic and unrepresentative of
what students may face in the future. Unsupervised activities
remain an important part of evaluation, but since a significant body
of experience is often not required for admission, assignments in
first-year are typically small and target fundamental outcomes. This
same simplicity results in activities that can often be completed
easily by the AI-based tools now available [1]. For large courses
especially, there is thus an immediate need for assessments that
support introductory student learning with the presence and use of
AI-based tools, while still minimizing concerns about plagiarism.

2

Assignment Suite Development

This author believes that ensuring students receive an early
introduction to AI is critical, both for ensuring that they are fully
prepared for their future and for allowing them to take advantage
of opportunities yet to present themselves. The assignment suites
discussed in this paper originated in 2023 with a fellowship project,
and even at that time it was not unreasonable to claim that the era
of accessible AI-based tools had arrived [2], with students already
This work is completed in its entirety by the author. All rights
reserved.
WCCCE ’25, April 28–29, 2025, Calgary, AB
© 2025 Copyright held by the author
https://doi.org/10.60770/znfj-0613

having access to - but no training in – many free tools. One aim of
the project was thus to provide an early introduction to these tools.

2.1

Initial Project Iteration (Fall 2023)

The first-year student was the target of the fellowship project,
because this student has entered a new discipline with many topics
to learn and few reasons not to exploit a free tool to circumvent
challenges they encounter. Thus, the key tenets of the project were
to teach the fundamentals, provide an "entry-point" to the discourse
saturating the media, and introduce the idea of being an effective
user of these tools. The course would then be free to demonstrate
how AI can be used to solve problems and improve productivity.
The course was designed such that it would not employ any AI for
the first several weeks, and students are taught that the individual
who simply "tosses" a request to an AI and then copy-pastes the
result without analysis or reflection is not making themselves
integral to the process. Thus, the initial activities were redesigned
to emphasize "scaffolding" (i.e., rough work) and techniques were
employed to make the assignments somewhat "AI-resistant".
Although the notion of AI-resistance may be in its infancy,
specifications were delivered using diagrams (currently more
difficult to communicate to the tools available) and with specific
library constraints (i.e., requirements to employ libraries that are
procedurally-generated on an individual basis for the current
offering and are thus “unknown” to any AI-based tools). Further
procedural generation techniques add variation to the pool of
activities assigned, but it should be emphasized that this was
originally introduced here to combat student-to-student plagiarism.
By the middle of the course, pair programming techniques were
introduced and practiced, explicitly so that students could begin to
view an AI-based tool as a rudimentary assistant, requiring the
guidance and oversight of a "navigator". Following introductions
to synthetic text generation and some of the mathematics behind
neural networks, students were provided an introduction to prompt
engineering and a review of tasks selected to illustrate the strengths
and weaknesses of these tools (from a developer’s perspective).
2.1.1 Student Reception and Analysis. Although the options for
quantitative analysis were limited by the lack of a "control" section,
a review of average grades revealed nothing anomalous, and an
anonymous survey was used to gather reactions. Several students
commented about their enjoyment of the introduction:
"...AI learning (like ChatGPT) was fun and interesting..."
…but the student reactions to the use of procedurally generated
assignments were mixed:
"...in depth w/o being too 'deep' for a beginner course..."
"...not the biggest fan of procedurally-generated assignments..."
Additionally, there was a recurring criticism about the lack of
clarity in the assignment specifications:

WCCCE’25, April, 2025, Calgary, Alberta Canada
"...assignment details are vague or open to interpretation..."
This led the author to suspect that efforts made to impede illicit AI
use might inadvertently impede comprehension as well. This in turn
motivated the next stage in the evolution of the project – a suite of
six assignments that can be assembled into a "portfolio game" that
students can use to showcase the skills they have developed.

2.2

Current Project Iteration (Winter 2025)

It was believed that shifting away from disparate assignments
towards a concrete task might address some of the concerns. Thus,
with inspiration from the classic educational game "The Oregon
Trail", the portfolio game project was introduced. Since this game
can be easily experienced by students (by playing it), their
introduction can be supplemented with a complete picture of how
their final product might appear. Furthermore, as the game can be
summarized as experiencing the decision-making tasks of a
complex journey [3], it was easy to introduce several random
variations on this theme (e.g., an "Undersea Voyage" to explore
marine biology, an "Ancient Odyssey" for world mythology, etc.).
The first assignment tasks students with basic input/output
operations (i.e., receiving names, displaying instructions, etc.) and
the creation of a title screen using a simplified pygame "wrapper"
library. Since the "wrapper" is procedurally generated, it differs
from student to student and is not easily communicated to tools like
ChatGPT, essentially "forcing" students to read documentation.
"Scaffolding" design activities are also included early on, with an
arithmetic pipeline (i.e., initial supplies purchase) and branching
structures (i.e., choice of character class, etc.) covered in the second
assignment. Input validation and counter-controlled loops are
introduced to meet the outcomes of the third assignment, and
further updates to the graphics library "wrapper" are included so
that a "game loop" depiction of the journey (that can be interrupted
to access an action menu) is then possible. The fourth assignment
requires refactoring to support an introduction to procedural design
and, like many of the tasks described previously, specific details
(e.g., into what function signatures to refactor) are procedurally
generated and vary with each student. Data structures are the focus
of the fifth assignment (with an emphasis on string processing in
their "random event" system), and by the sixth and final
assignment, students are using ChatGPT for code and content
generation. To clarify, the final assignment tasks students to have
ChatGPT generate textual descriptions for the landmarks visited, as
well as snippets of code that provide "minigame" activities to
replenish resources. The use of ChatGPT for this assignment is
mandatory, with students required to submit transcripts of their
"conversations" for evaluation. Thus, upon completion of the suite,
students have progressed through the fundamentals to the eventual
integration of AI as part of a practical and reflective process.
2.2.1 Student Reception and Analysis. At the time of authoring this
short paper, the winter semester of 2025 is ongoing, but an
unsolicited email received in the fifth week included some
exceptionally positive feedback:
"…the satisfaction each week of submitting something that
actually works…is really satisfying. It gives me that extra "oomph'
each week of something I can be proud of to keep me going…"

R. Collier
This prompted the author to conduct a mid-semester evaluation,
with an emphasis on the assignment suite. Of the 31 participants,
21 reported a "better-than-neutral" response (on a five-point Likert
scale) for their enjoyment of the course so far. Please note that the
current cohort is 90.4% non-CS students (historically having a
lower level of enjoyment overall).
To establish specifically the reactions of those students that are
enjoying the course, of those 21 students, the responses to the
statements "I have enjoyed the assignments so far", "the
assignments are of an appropriate level of difficulty", and "the
assignments are well-aligned with the lectures and
demonstrations", had median values 3 (neutral), 4 (agree), and 4
(agree), respectively, and are summarized in Figure 1, below.

Figure 1: Likert scale results for students enjoying the course.
The author recognizes that further investigation is warranted
(especially into the reactions of those students that did not enjoy the
course overall) and is awaiting more detailed feedback, to be
received after the current semester has concluded.
Since many techniques were introduced to reduce the amount of
unauthorized AI-based tool use, it should also be reported that 10
of the 31 survey participants admitted to the use of ChatGPT in
some form (even though we have not yet reached the point in the
semester where such use is authorized). This has, regrettably,
increased over the results reported after the Fall 2023 semester,
where only 9.4% of participants admitted to illicit AI use. The
author intends to address this with the next iteration of this activity.

3

Conclusion

The work (and need) to integrate AI-based tool use into the
computer science curriculum is ongoing. Nevertheless, the author
believes that an emphasis on scaffolding and procedurally
generated constraints (like "wrapper" libraries), combined with a
concrete and satisfying "target" project, can be used to effectively
assess students receiving an introduction to computer science,
without resorting to exclusively supervised assessment techniques.

REFERENCES

[1] Majeed Kazemitabaar, Justin Chow, Carl Ka To Ma, Barbara J. Ericson, David
Weintrop, and Tovi Grossman. 2023. Studying the effect of AI Code Generators
on Supporting Novice Learners in Introductory Programming. In Proceedings of
the 2023 CHI Conf. on Human Factors in Computing Systems (CHI ’23), ACM,
Hamburg, Germany. DOI: doi.org/10.1145/3544548.3580919
[2] Michael Neumann, Maria Rauschenberger, and Eva-Maria Schön. 2023. "We
Need To Talk About ChatGPT": The Future of AI and Higher Education. In 2023
IEEE/ACM 5th Int. Workshop on Software Engineering Education for the Next
Generation (SEENG), 29-32. DOI: doi.org/10.1109/SEENG59157.2023.00010
[3] Mohammed Alburaiki. 2018. What Led The Oregon Trail to Be a Successful
Educational Game. (March 2018). Retrieved December 26, 2024 from
https://medium.com/moegamedesign/what-led-the-oregon-trail-to-be-asuccessful-educational-game-e928052e88b1