Not all features made it into our MVP. Either because of scale, time constraints or importance in contrast to the minimum feature set. Here we want to highlight what we wish to add later and also to show a few of the ideas we deem as a fit for Valit.
Editor For Creating Individual Questionnaires
The editor will allow users to easily create custom questionnaires by selecting from a variety of question types, such as multiple-choice, open-ended, and rating scales. They can also add additional customizations, such as adding images or videos, and rearranging questions as needed. This feature will give lecturers the ability to create questionnaires tailored to their specific needs. A complementary guide will provide lecturers with best practices for creating effective evaluation questionnaires that are well-designed and likely to produce useful results.
Additional Options For Course And Feedback Rhythms
The app will provide more options for the frequency of feedback collection beyond the current weekly, bi-weekly, and monthly options. For example, lecturers may be able to select feedback collection intervals for every three months, with the ability to stop or begin new evaluation cycles for more flexibility.
More Interactive Live Feedback
The app will offer more interactive live feedback options, including an option for students to comment on problems and ask questions. Like a live chat but with an up and downvote functionality for students, so they can choose the most relevant topics to be highlighted. This will help ensure that important feedback is not overlooked, and that users can easily identify the most pressing issues. Likely most useful for online classes.
Increased Gamification And Incentives
The app will use gamification and incentives to encourage students to provide feedback. For example, students may earn rewards for providing feedback, such as badges or points that can be redeemed for prizes. Additionally, the app may include interactive elements, such as quizzes and games, to make the feedback experience more engaging and enjoyable. This increased motivation will help ensure that users are more likely to provide meaningful feedback, leading to more actionable results.
Profanity Filter
Courses with a large number of Participants might suffer from undesired language and trolling. A word Filter will be implemented as a countermeasure, but only blocking profanity so freedom of speech is still guaranteed.
Answer Clustering
A clustering algorithm will be implemented that counts the number of mentions of a specific word from evaluation free text answers and tries to predict their sentiment. This way, we can make it easier for lecturers to find hotspots and common topics from the answers they get after a class.