Question types: Open (text-based responses)

Summary

Open question types where participants enter free-text in response to a question or prompt, for example gather ideas from students.

Longer form responses can be automatically grouped using an AI tool, or participants can vote on responses.

Using open question types

Staff at York use open question types for a range of purposes and within a range of session types. See the drop-down below for examples.

Case studies: How are staff at the University using open questions to support teaching and learning?

Staff use open questions for:

• preparing students for teaching by gathering their pre-conceptions or views on the subject.
• gathering anonymous questions and feedback.
• using the AI summarising tool to support analysis of and feedback on open responses in larger sessions.
• encouraging inclusive engagement in seminars, for example by eliciting initial responses to key questions from across the whole group, allowing a greater range of insights and avoiding a possible tendency for the quickest or loudest respondents to set the agenda.
• using initial responses as a springboard for discussion and further exploration to support students in vocalising their ideas and engaging in debate.
• gathering short answer exam questions from individuals and groups for discussion and formative feedback.
• gathering student responses to key questions before seminars to prepare students to engage.

Examples include

• Using Mentimeter in History Lectures
  Henrice Altink in History uses word clouds and open responses to elicit students’ existing knowledge at the start of lectures which she refers to as the lecture content is introduced. This helps her to tailor the content to the group. She also uses open questions at the end of the lecture to elicit key learning points, encouraging reflection and summarising skills.
• Using Mentimeter to support participation in larger seminars
  David Worsley in Philosophy encourages students to engage in peer discussions during his seminars and submit their ideas, summaries, and questions anonymously. He then uses the collated responses to structure whole group discussion and address key issues.
• Using Mentimeter for 'flipped' workshops in Biology
  Gareth Evans in Biology uses open response questions for group work activities in his flipped workshops. After reviewing content and dealing with questions, he provides short answer exam questions for groups to respond to and come up with an agreed response. He then gives feedback on the responses and provides further teaching as needed.scales and MCQ questions for knowledge checking and self assessment in his flipped workshops.
• Using Mentimeter for Learning and Feedback in Languages
  Elia Lorena López in Language and Linguistic Science who uses open questions to gather and share student contributions during language learning sessions, providing feedback on common grammatical and syntactical errors in the responses.

You can see more examples of how staff have used the different question types in Mentimeter from the case studies page. This allows you to browse the examples by question type, as well as purpose, session type and subject area.

Details about the open question types available in Mentimeter are available below with links to how-to guides.

Word clouds

Word cloud slides allow students to add words or short phrases in response to a question or prompt. These are then collated with the most frequent additions shown with the largest size.

This can be useful to collate and share short individual anonymous responses, for example to elicit ideas, examples, suggestions, feedback and reflection. These can then be used as a start point for further discussion.

Open-ended questions

Open ended questions allow you to elicit longer anonymous responses from individuals.

Possible uses include:

• eliciting longer form questions, feedback, examples etc.
• knowledge check questions on lecture content or a check in point to engage students
  
• collate ideas and examples following group work. In the following example, groups posted their response to a series of questions, identifying their table number for further discussion of noteworthy responses:
  

AI tool: open response grouping

Open responses can provide you with rich qualitative data, but it can be challenging to make sense of open responses in live sessions. An AI-powered grouping tool is automatically available on any open-ended question slide with more than 10 responses (press the spacebar to activate this). The grouping tool provides you with a start point for taking stock of the range of responses your students have made, allowing you to give more comprehensive feedback. You can drill down to see the comments within each group, move comments to different groups as needed, and revert back to ungrouped responses (by pressing the spacebar once again).

Using AI tools effectively

AI-generated content is a starting point for your own content development rather than a finished product. You must always carefully check that output is accurate and appropriate for your intended use and adapt as needed.

See our general guide to Artificial Intelligence tools for more details on using AI responsibly.

Instructions on the grouping tool can be found on Mentimeter’s Group responses to your Open Ended questions using AI page.

UoY feedback on the AI grouping tool

“I’m really impressed with this functionality. It would be particularly useful when there are a lot of responses to look through live. I sometimes struggle to take in and parse the responses in a session so I can summarise and provide feedback to the participants.”
(Gareth Evans, Senior Lecturer, Biology)

The AI grouping tool was trialled by a group of teaching staff on previously-collected responses in large lectures (to gather ideas on the subject matter) and workshops (to seed discussion and gather group responses to short answer practice questions).

Overall, the grouping tool output was seen as accurate and helpful. Testers felt it made it easier to give feedback and discuss responses in live sessions, especially for larger numbers of responses and relatively general rather than very specialised subject matter.

However, there were some ‘outliers and oddities’ grouped in seemingly arbitrary or incorrect ways.

For more detailed feedback and examples of the generated groupings, see our
Introducing the AI open response grouping tool in Mentimeter blog post.

Voting on open responses

You can switch on voting on open text responses, making this ideal for a brainstorming or prioritising session, allowing everyone to contribute ideas and then to vote on the contributions made.

To use voting in a session:

1. Set up: Create an Open Ended question slide and add your question as normal in the question field under the Content options. In the slide settings, toggle on Enable voting on responses and set the desired Votes per participant.
   

Alternatively, you can activate voting by selecting the insights button and choosing 'Vote'. This allows you to set up voting immediately (1 vote per participant) making it a useful option if you decide that it would be helpful for participants to be able to vote on responses in the moment.

1. Gather responses: Present your slide for participants to provide open responses as normal. Responses can be displayed immediately or hidden until a time of your choosing using the shortcut key H.
   
2. Begin voting: When you are satisfied with the number of open responses received, press Enter to begin the voting. Until this point participants who have submitted their responses will see a message telling them that the presentation is not yet open for votes.
   
3. Participants vote: the message Voting in progress appears under the question. Participants select response(s) to vote for, which are then shown by a tick (select the option again to de-select). Once they have made their selections, press the Submit votes button.
   
4. Show voting results: once sufficient votes are received, press Enter again to show the voting results on the screen and participant devices, ordered by the number of votes from most to least.
   

Warning

By default, Mentimeter is completely anonymous. For strategies to reduce the likelihood of any misuse of anonymous open questions, and to limit the impact of any inappropriate or offensive responses, please see the Using open text responses safely and dealing with inappropriate or offensive posts page, and see the Anonymity in Mentimeter page for key considerations and options for de-anomymising Menti.