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DATA-DRIVEN APPROACH IN HIGHER EDUCATION: EVIDENCE-BASED SOLUTIONS FOR BOOSTING STUDIES EFFICIENCY FOR STEM STUDENTS
ITMO University (RUSSIAN FEDERATION)
About this paper:
Appears in: EDULEARN24 Proceedings
Publication year: 2024
Pages: 6240-6245
ISBN: 978-84-09-62938-1
ISSN: 2340-1117
doi: 10.21125/edulearn.2024.1478
Conference name: 16th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2024
Location: Palma, Spain
Abstract:
"Innovative Economics and Technological Entrepreneurship." The essence of this discipline is that throughout the semester, we work with students on a project using one of the forms of flexible methodology or Agile. The first feature of the course is adapting the assessment of task complexity into story points (SP) on a 100-point scale, where 1 point is roughly equivalent to 1 hour of work. The second point is working with the motivation of each participant in the discipline. And the third aspect is the need for the project team to find initial users for their solution as quickly as possible. Further details will be provided in order.

Motivation on the course is built with a focus on maximizing participant engagement. Teams are formed by course instructors based on the results of DISC testing, ensuring that each component is present in the team (the test can be taken here). Also taken into account is the student's interest in Art & Science, GreenTech, IT, Life Science, FoodTech, FashionTech, and Transport Infrastructure. With a fixed team, participants are recommended to have the freedom to choose their project, which serves as motivation for its completion. Team roles are also self-assigned based on tasks of interest. Mentors actively assist in selecting project themes by sharing their expertise. This process takes 2 weeks.

A weekly analog of a daily standup meeting is held with questions for each team member - what has been accomplished during the week, what will be done by the next meeting, and what is hindering task completion? Each team member sets their own task. At this point, the mentor's main task becomes controlling task complexity for each team member to take up 3-4 hours of work time. Occasionally allowing small tasks but never highly complex ones; otherwise, the mentor smoothly adjusts task volume. This typically takes 15 minutes per team. Task equivalence helps maintain motivation within the entire team.

The course uses a 100-point grading system composed of: 20 points for the final presentation, 10 points for intermediate presentations, and 70 points for weekly meetings with mentors. There are approximately 16 sessions per semester, each equally weighted at 5 points. The mentor monitors task complexity to keep it around three hours plus an additional hour and a half of student engagement per week. It is assumed this can be achieved for small tasks.

Mentors do not delve deeply into grading nuances but follow these rules: completed tasks receive full points; partially completed tasks receive half points; incomplete tasks receive zero points. This speeds up individual performance evaluation and eliminates room for point discussions.

Mentors are advised to conduct public reports for each team and assign grades promptly so that others can see tasks and grades among teams.

If within the first five sessions a mentor notices that a team's progress has been slow for two consecutive weeks, they suggest changing the project theme and offer alternative options or transitioning to another mentor.

The mentor sets a goal for the team to quickly create a prototype of their idea and find users who will describe their experience interacting with the project. For mentors, the main outcome for teams should be user feedback, regardless of whether it is positive or negative. It is assumed that teams will learn to rapidly create prototypes and analyze user feedback.
Keywords:
Project-based learning, team composition, DISC typology, pedagogical interventions, student performance.