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Group formation can be a stressful and time-consuming process for students and instructors. Students may feel isolated from the group due to a difference in gender, nationality, and learning expectation. They may experience stress or dissatisfaction due to a lack of the group’s performance and participation. These issues can encourage students to miss their classes or leave their assigned group to join their group of friends.
After interviewing instructors who teach in a large TEAL (technology-enabled active learning) class, we learned that a user-friendly student grouping and seat assignment tool was needed. Thus, SIGMA (Simple Interactive Group-Making Application) aims to address these issues and provide a better experience for students and instructors during the student group formation in large active learning environments.
Learning behaviour was chosen as the most effective way to form groups since it can predict students’ performance and participation. The learning behaviour questionnaire utilizes two types of scales to measure the students’ learning behaviour:
A Likert scale composes of questions from , assessment, “A survey of the Learning Behaviour of Open University Students”, and
The semantic differential scale is adapted from the “Biology Attitude Scale”.
SIGMA will ask students to take a learning behaviour survey, consisting of 28 questions to not consume too much time but have enough to collect the database. Then, it will implement the K-means algorithm to group students with similar/dissimilar learning behaviours. Below is a sample of potential survey questions.