Computer Science is taught by Mrs. Taricco. The course begins with web development, where we learn to code using HTML and CSS. We then transition into Java programming through labs and exercises that cover topics such as arrays, ArrayLists, iteration, and decision-making. Many of these assignments are challenging and closely align with the AP Computer Science A curriculum. In addition, students participate in the American Computer Science League (ACSL) competition throughout the year.
Line Art
This program creates an optical
illusion that looks like curved arcs, but it is actually made
entirely of straight lines. I used for loops with Java Applet drawing
tools to generate the repeated line patterns that form this effect.
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Stars
Stars is another AWT program, but
this time it uses static arrays rather than for loops. The program
creates ten stars with random sizes and locations, resulting in a
different arrangement each time the code is run.
For our Apps for Good project, my group created Law of Signs, a gamified learning app designed to help beginners learn American Sign Language (ASL). Our group noticed that communication barriers often exist between hearing people and deaf or hard-of-hearing individuals, especially because many hearing people are not fluent in ASL. To help address this problem, we designed an app that teaches users the ASL alphabet through short video-based lessons and interactive practice.
The problem our group discovered was that many people are interested
in learning ASL, but existing learning tools can feel boring,
noninteractive, or overly dependent on videos without strong visuals
or practice features. Our target audience is complete beginners who
want an easier and more engaging way to start learning ASL.
Our app helps this audience by breaking lessons into
smaller sections and allowing users to practice identifying signed
letters. This makes the learning process feel more like a game
instead of just watching long videos.
Our MVP focuses on teaching the English alphabet in ASL. The app presents video lessons in small groups of five letters, lets users practice by identifying the letter being signed, and tracks progress so users can see what they have completed. The goal of the MVP was to create a simple, usable version of the app that teaches the core concept before adding more advanced features.
We used technology to make ASL learning more interactive. The app
includes lesson pages, practice pages, account creation, and saved
progress. Our poster also shows Supabase as the tool used for
storage, allowing user progress to be saved if the user is connected
to an account.
Future extensions could include a computer-vision-based
answer system, more vocabulary, basic words and phrases, and avatars
that teach signs instead of only using videos.
Our process began with research into the problem and current market.
We identified that many ASL learning resources are not very
interactive, rely heavily on videos, or do not provide enough visual
engagement. After defining our target audience as beginners
interested in ASL, we designed the app around short lessons and quick
practice.
During the design stage, we planned the app architecture.
Users can create an account, navigate to the home page, choose a
lesson, practice the signs, and save their progress. During
implementation, we built pages for lessons, practice, account
features, and progress tracking. We also connected storage through
Supabase so that user data could be saved.
For testing, we focused on whether users could move through
lessons, practice letters, receive feedback, and complete practice
sets. If the user answered correctly, the app allowed them to
continue. If the user answered incorrectly, the app prompted them to
try again. This helped us check that the main learning loop worked
properly.