Grading of class participation may not always be accurate due 1) Unconscious bias - Implicit bias affecting student evaluation - race, gender, ability, and socioeconomic class. 2) Inaccurate memory - Grading based on recall. 3) Focus on frequency - Grading based on actual counting. These reasons often cause educators to place less emphasis on quality of responses, hence the frequency of participation does not actual mean real comprehension of the topic and the student may not always deserve the grade they receive.

What it does

PARTIn is a behavior analysis platform for educators to better monitor students' quality of participation and encourage engagement in the classroom.

How we built it

Data collection - Keywords detection & frequency of keywords Analysis - Using the collated data, PARTIn will analyze the frequency and quality of each student's response. Visualization - Data will be reflected in the form of a graph

Challenges we ran into

May discourage difficult conversations Reduce comfort in expression, due to fear of being recorded Not all students are equally ready and willing to participate in class Technical challenge - Hard to follow AWS/GoogleCloud instructions to configure API

Accomplishments that we're proud of

We hope to 1) Increase educators' ability to discern quality in class participation 2) Intentional recording will motivate students to answer critically 3) Reduce paraphrased & 'fluffy" responses 4) Allows both educators & students to track participation (frequency & quality)

What we learned

Reliability of data collected may be limited due to existing social structures, hence it is important to also be aware of intersectionality that may affect classroom behavior of students.

What's next for PARTIn

In the long run, we believe that data collected will lead to the discovery of student behavioral patterns, reduce unconscious classroom bias and minimize inaccuracy in student participation grading

Share this project: