Decisions & practice
A learning platform should fit your teaching.
Eight questions for choosing an AI learning platform – from subject quality to everyday use.
In this article
Start with your learning goals when choosing an AI learning platform. Then use a situation from your own subject to examine the fit of the content, learning support and educator insights. Features matter when their benefit for your particular use becomes clear.
At a glance
- A specific learning goal makes offers easier to compare.
- A demonstration with your own content is more informative than a general feature list.
- Subject quality, working practices and data questions belong in the same decision.
From feature comparison to a decision.
A platform can offer many learning formats and still miss your most important need. Learners may need to clarify questions between sessions. Your team may need better insight into recurring learning barriers. Or knowledge from training may need to become more useful in unfamiliar professional tasks.
Begin by describing a specific use: the learners, the content and the action you want them to perform after learning. This creates a clearer basis for comparison than a long feature list.
Four perspectives belong together.
Our practical recommendation is to examine a platform from four perspectives: subject fit, learning support, usefulness for educators and feasibility within your organisation. A convincing offer connects these perspectives.
An attractive explanation has limited value if it misses a crucial distinction in the subject. A comprehensive course overview needs to help the team decide what to do next. A sound approach to learning also needs to work within the processes and time you have available.
Your learning goal at the centre.
The most important question: What will improve in our teaching?
EDUGEN perspective
Where guidance can help.
UNESCO’s guidance on generative AI in education and research emphasises a human-centred approach and developing people’s capacity to act. It provides orientation for educational use of technology rather than evaluating individual learning platforms.[1]
The voluntary NIST AI Risk Management Framework includes reliability, transparency and privacy among characteristics of trustworthy AI. It does not replace examining a specific offer. Such frameworks can help institutions formulate relevant questions for a selection conversation.[2]
Eight questions for your selection conversation.
Open each checkpoint for a question and a specific piece of evidence you can ask to see or discuss.
01 · Which learning goal are we supporting?
What should people better understand, assess or apply after using the platform?
Ask for this evidence: An example from your subject requiring that exact action. Agree on the expected explanation and level of challenge beforehand.
02 · Does the offer fit our material?
How are our content, terminology and required foundations reflected in the learning experience?
Ask for this evidence: A demonstration using a passage selected by you. Examine whether the representation remains accurate and understandable.
03 · What is the quality of the feedback?
Does feedback explain a discrepancy and help learners move forward?
Ask for this evidence: A correct and an incorrect attempt. Discuss the subject interpretation as well as the result label.
04 · Can educators work with it?
Which insights will we receive, and which decisions can they support?
Ask for this evidence: A view of learning needs and a specific example of how your team could use it to prepare the next session.
05 · What is the learner experience?
Do language, readability, interaction and different ways into the content fit our learners?
Ask for this evidence: A complete journey on a typical device. Include keyboard access and accessibility requirements in the discussion.
06 · How are material and data handled?
Which information is needed, where is it processed and who can access it?
Ask for this evidence: Clear information about involved services, access, retention and deletion. Clarify your requirements before sharing teaching material.
07 · How will everyday use work?
What preparation, responsibilities and support will our team need?
Ask for this evidence: An agreed process with effort, responsibilities and relevant training, including collaboration after the start.
08 · How will we judge the benefit?
Which change would actually matter for our organisation?
Ask for this evidence: Criteria agreed in advance, such as justified application in a new task or clearer insight into learning needs. Clarify the scope and cost of the offer.
Prepare a demonstration that tells you something.
Choose a manageable excerpt from your content and a challenging concept within it. Briefly describe what your learners already know and what they need to learn. This gives the questions and results shown in the demonstration a meaningful context.
Take time to read an explanation and follow a learning journey. Discuss an answer that differs from the expected result too. Examine the subject interpretation and how the experience supports learners and educators.
Afterwards, record which questions have been answered and which specific insights are still needed. This provides a stronger basis for a decision than the impression of a successful presentation alone.
The EDUGEN perspective.
We connect individual learning support, subject-specific error patterns and educator insights with the application of knowledge. Our conversation starts with your content and learning goals. Consulting, training and workshops can also support the learning concept or your team’s work.
Our aim is a use of EDUGEN whose benefit you can assess in your subject. Bring a specific challenge to the conversation so we can discuss selected insights and a relevant next step.
Sources & context
The linked sources support the statements in this article. Practical examples and recommendations are created by EDUGEN to interpret the research for teaching design.
