Complementary Note-taking is a research project examining how features of a digital application can be designed to promote purposeful interactions while note-taking.
The following is a concise explanation (compared to the full document) of my final project in the Master of Graphic Design program at NC State. The investigation establishes opportunities for a note-taking interface to focus on the intentions of the student while continuing to employ technological features. The primary research question is: how can a digital interface promote purposeful interactions during note-taking in order to strengthen a college student’s encoding capabilities while engaging with lecture-based coursework?
100 Word Summary
This research examines how features of a digital note-taking application can be designed specifically for the note-taking activity. Digital note-taking applications are increasingly common as students continue to use personal computing devices in classrooms. These applications enhance note-taking with technological benefits, however, they are not designed to complement the cognitive goals of the student. This inquiry-based project involved crafting primary and secondary research questions, performing a literature review on desired topics, and designing a conceptual framework to guide our thinking and research. Finally, I designed three studies using a persona (two summarized below) to approach different aspects of the topic.
Year: 2020
Personal Focus Areas:
Design Research / Writing / Systems Thinking / Framework Design / Layout Design / Presentation Design /
The framework for this investigation is based on (1) Craik and Lockhart’s (1972) levels of processing, (2) activity theory, and (3) five characteristics of note-taking.
My Persona
Note-taking is subjective; every student will transcribe, organize, and review their notes as they deem necessary and beneficial to them. Thus, I research and design my studies with a generalist mindset. However, I use a persona and scenario of a student to show the concepts from each study and explain how the interface will act and be experienced. Throughout the studies, I design individual features within a note-taking application referred to as “NoteMode.” Avery Barnett is a second-semester freshman at North Carolina State University. She is currently enrolled in the Exploratory Studies program and will be choosing a major after this semester. Last semester, Avery took notes in varying forms, sometimes in a notebook and other times in Google Docs; typically choosing based on her mood or focus-level on the given day. Avery knows she needs to be more consistent with her note-taking habits and feels she is more proficient taking notes digitally.
The scenario focuses on Avery’s spring semester of her freshman year. The events within the scenario occur throughout the first seven weeks of the semester. The timeline (above) explains how the three studies will be approached throughout moments of the scenario.
Adapting Linear Organization
This study focuses on the possible organizational strategies within a note-taking interface. This includes how the interface itself is formatted as well as organization features in order to guide the user while taking notes.
The interface implements a collapsing and expanding feature within the interface. This allows the collection of notes to be viewed in various modes— zooming in and out depending on the task at hand.
A consistent page structure is necessary to stimulate effective note-taking strategies within the overall concept of organizing the collection of notes.
Enhancing Annotation Capabilities
This study combines student annotations with machine learning algorithms to identify relationships across a collection of notes. The data generated from the process is then used to populate graphic organizers, providing the student a visual and spatial depiction of the selected notes.
This study combines student annotations with machine learning algorithms to identify relationships across a collection of notes. The data generated from the process is then used to populate graphic organizers, providing the student a visual and spatial depiction of the selected notes.
The framework, shown above, explains the machine learning process in regards this note-taking interface. First, a selection of notes is used as input data for the system.