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- All Subjects: App
- Creators: Balasooriya, Janaka
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Member of: Theses and Dissertations
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
I created a flash unit on American Ethnic Literature and delivered it in a high school classroom. The purpose was to introduce students to ethnic literature and to highlight the value of ethnic literature as a form of cultural agency and an authentic record of cultural history. I did research on the importance of ethnic literature, why it has been absent from the standard curriculum, and why it should be a part of the standard curriculum. Because of ethnic literature's importance and absence, I constructed the unit for secondary education and created a micro-unit on ethnic fiction and a micro-unit on ethnic poetry. I delivered the micro-unit on ethnic fiction at Metro Tech High School, gathered data, and reflected on the outcomes. Based on the outcomes, I revised the unit for future teaching and application.