Designing blended learning with AI

AI can be a great help when planning and designing blended learning units. It supports you in formulating comprehensible learning objectives, competence-oriented tasks, structuring units and creating texts. This means that learners always know exactly what they have to do, how and by when during the self-study phases without encountering comprehension problems.

Below we give you a few tips on how you can use AI to achieve successful learning experiences.

Legal aspects

Copyright: Many AI tools allow you to upload files that are subject to copyright. Unless it is your own, self-created material or the material has been openly published, you may not upload it to an AI tool under any circumstances.


Data protection: Most tools, especially the well-known ones, are not data protection compliant. Never enter student names or other personal data. Also bear in mind that data that you disclose about yourself can be used by the system as training data.

Optimize semester planning

It doesn't work without good planning! The module handbooks often don't provide any specific information and the learning objectives need to be better formulated so that students understand them. Often you have to take over a course and you don't get any information on planning, just a few deficient sets of slides. This is where generative AI can help you.

Formulate learning objectives more comprehensibly
Learning objectives should be broken down into broad and detailed objectives that are achieved step by step, week by week. Only if learning objectives are formulated correctly and precisely will learners understand what is expected of them. Generative AI can support you here. Enter your overarching learning objectives for the semester and let the AI convert them into competence-oriented and operationalized objectives.
Example for the AI prompt:

Reformulate the following objectives [insert] for the seminar [x] with the target group [y] so that they correspond to the pattern 'The students can (name learning object; name conditions and aids if necessary) (operator of the learning objective taxonomy)'. Assign the learning objectives to the six taxonomy levels. 
Formulate sub-goals/fine learning objectives
Once you have received and checked the objectives, you can break them down further.
Example for the AI prompt:

Formulate six consecutive sub-goals, i.e. broad and detailed goals, in all six competence levels of the learning goal taxonomy according to Anderson/Kratwohl for the following learning goal: [insert]. Follow the pattern 'The students can (learning object) + (operator of the learning objective taxonomy levels).
Optimize assessment criteria
Use AI to get inspiration for formulating and categorizing your assessment criteria. You can also have the comprehensibility of your already formulated criteria checked. It is important to specifically ask the AI for constructive feedback, as it otherwise tends to give more polite, less helpful feedback.
Example of an AI prompt:

Check the clarity of the following assessment criteria for [insert topic] and give me specific feedback to improve it. The target audience is students in [insert semester]. The criteria are: [insert evaluation criteria].

 

Compile content efficiently

Once you have defined and specified the learning objectives, you need to compile the content for the semester. Especially if you have opted for a blended learning model with a mandatory or even upstream self-learning phase, the content must be structured in a comprehensible and understandable way.

Have lessons structured
Once the learning objectives have been precisely formulated and distributed over the semester, it is time to fill the appropriate lessons with content. AI can also help here. Have an outline created for a lesson.
Example of the AI prompt:

Outline a learning unit for my students of [x.] semester in subject [y] on topic [z]. The following learning objectives should be achieved: [insert].
Have teaser texts written for learning units
A short summary or introduction is helpful for long or extensive lessons for the self-study phase. This serves as an overview and motivates learners. You can have such summaries created with generative AI.
Example of an AI prompt:

Create a short summary for a learning unit on the topic [insert topic], which is to be worked on in self-study. The summary should highlight the most important points and motivate learners to work through the material.
Create symbol images for learning units
Icon images help to quickly find and better anchor learning content in a digital learning scenario. Use AI to create suitable images. Describe the content of the chapter or unit as precisely as possible and use the previously generated summary.
Example of an AI prompt:

Create an icon image for a learning unit on the topic [insert topic]. The image should visualize the central content of the unit and be easily recognizable.

 

Effective session design

Now that the content has been defined according to the learning objectives, the sessions must also be designed. The more activities and tasks, the greater the learning effect. We help with the activities with our method box, while the AI helps with suggestions for the session schedule and introductions as well as tasks.

Have a schedule drawn up
How do I start, what do I finish with and what do I do in between? These are questions that concern many teachers. AI can help here by structuring a topic and suggesting suitable learning activities.

Example of an AI prompt:

Create a flowchart for a 90-minute session on the topic [insert topic]. The plan should be divided into phases (introduction, deepening as well as turning over what has been learned and conclusion) and take the following learning objectives into account: [insert learning objectives for the session]

 

Formulate introductions
A good introduction to a new topic or session is crucial for attention and cognitive processing of the subject matter. Let the AI make suggestions and, if necessary, formulate them in full.

Example of an AI prompt:

Formulate an engaging introduction for a lesson on [insert topic] that grabs students' attention and increases their interest in the topic.

 

Have a case study created for competence-oriented tasks
Case studies are ideal for developing tasks at the Apply, Analyze or Evaluate competence levels. With the right description, the AI can generate an almost finished case study. Enter a specifically formulated learning objective and the task derived from it.

Example of an AI prompt:

Generate a case study for a competence-oriented task in the subject [insert subject]. The case study should encourage learners to apply the concepts they have learned to a real-life situation.

 

Tasks for formative assessment and quizzes/MC tasks
Quiz formats or multiple-choice tasks are suitable for checking whether what has been learned has been understood. The AI can create complete MC tasks. Pay attention to how you present these in context - e.g. with PINGO or ZOOM-Quiz (ONE LINK for both to digital quiz tools). I just can't find them right now, somehow they've disappeared from the Zoom subpage. You can also enter an MC question with correct answers and have the AI bring it into a uniform structure and syntax. You can also create distractors with similar syntax.

 

Example of an AI prompt:

Create a multiple-choice question on the following topic: [insert topic]. The question should contain four possible answers, one of which is correct, and three plausible distractors with similar syntax.