Through this project, my team and I sought out to improve some of the most pervasive problems with the Teaching Assistant program in the Computer Science department at Carnegie Mellon University. Over the course of a month and a half, the team performed a variety of research skills including but not limited to: Observation, Interpretation, Visioning, Affinity Diagramming, and Model Consolidation in order to solve to major problems of the Teaching Assistant program.
Below is the Final Presentation my team on our solution to some of the main problems we observed with the Teaching Assistant program.
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How to Increase TA Effectiveness
TA's value collaboration but can be unprepared and unmotivated to help their students.
Without training, TA's don't know the best practices and don't know the best ways to approach and solve common problems that arise in the class. Some TA's are new to this type of role and are unsure of how to best support their students. For instance, some students we observed were concerned about being wrongfully accused of cheating. Others had grading questions that the TA could not answer. There are also information silos between the TAs due to a lack of communication between classes and sections.
The first part of our solution involves different aspects of TA training. There will be a TA-led training before the semester begins. This training will involve various scenarios that TA's might face in their classes. There will also be a collection of online resources, including training videos past TA questions and answers, that current TA's can access at anytime throughout the semester if they need support. There will be in-person workshops a couple times throughout the semester and a final workshop at the end of the semester.
The second part of our solution is an information sharing system similar to Piazza, named Castello. TA's can post questions when they need help or HW corrections to alert other TA's of a problem. They can also respond to other TA's posts. We saw that Piazza was a very effective way for students to get responses due to the competitive nature of the TA's, who wanted to respond as quickly as possible to student questions. Every week, the post will be compiled into a weekly digest that is emailed out to the TA's. A leaderboard will reward TA's for contributing accurate and timely posts to Castello. This system helps maintain a way for TA's to search for common problems that have existed in past semesters.
The third part of our solution is a mentorship system that pairs more experienced TA's with newer ones. It would also pair them based on their knowledge of the course material. In our external research, we found that mentorship relationships are valuable to both sides of the relationship.
The following is a model scenario with TA's explaining how our solution would play out in real life.
This is the background information on our two TA's in this scenario.
How Janet and Brad prepare for their upcoming Teaching Assistant positions.
During the year, Janet utilizes two resources in our solution to help solve a problem in office hours: Castello and the mentorship program.
Questions asked by TA's will be sent out in an email digest so that all TA's are informed of the answer decreasing the information silos that previously existed.
Castello draws on the competitive nature that exists among TA's naturally.
In defense of our solution.
Some questions we still need to answer are the following:
How are mentors assigned? Will they be matched by currently existing Head TA's? Is it based on experience level? Class? Friendship? How formal will the relationships be?
How are comments verified? Does the head TA have to confirm it before corrections are posted?
Appendix: Key Issues and Hot Ideas from Walking the Affinity Diagram.
Appendix: Key Issues and Hot Ideas from Walking the Sequences.
Appendix: Key Issues and Hot Ideas from Walking the Flow Model.
Appendix: Examples of External Research - Support for the Mentoring Program.
Appendix: UAR examples Part 1.
Appendix: UAR examples Part 2.
Download Final Presentation