The future-oriented AI tool for formative assessment
Learnlab works actively to promote assignments where students are encouraged to work together, to be exploratory and active, rather than summative tests as a basis for assessment. With Learnlab, students can demonstrate creative learning and receive valid assessments along the way with the support of AI – which will be able to motivate and guide the students, freeing up time for the teacher.
The main questions Learnlab seeks answers to are: How can we develop a school with less focus on tests, and start focusing on the student’s conceptual understanding and their productions as a basis for assessment? How to shift the focus from summative to formative assessment that promotes students’ voices? How to use technology in ways that contributes to an increased desire to learn and motivation?
From summative to formative assessment using AI
Learnlab uses an AI-driven module for formative assessment which summarizes their product and gives the student suggestions for further development. Also, the module helps the student with self-assessment and feedback from the teacher. If AI is used as help to document competence, the students’ work with creative, self-determined productions can be linked to the curriculum without the focus on ranking and measuring. This must be done within the framework of a GDPR where students use the school’s SSO to log in.
We have developed semantic AI-models, that uses the objectives of the curriculum as framework for feedback. The student can use this as assistance for improving their work, or as guidance during the learning process. Teachers can also use these models as a starting point for subject-specific feedback adapted to the individual student.
Suggestions for improvements, and summary of competence
With Learnlab, the school gets a tool for learning analysis in “my folder”, where all assessment information is collected per student and sorted into different periods or terms. In this folder, both students and teachers can search for student productions sorted by curriculum objectives and the most important concepts in each subject. This teaching tool means that the students’ work, both individual and collective, can be included in constructive assessments along the way and a grade can also be given without the use of summative tests.
Learnlab can also create subject-specific suggestions for the student, which can be moderated by the teacher. Suggestions could be improvements to the existing product, a summary of the competence the student has shown, or an overview of the student’s conceptual understanding in the subject.
This is how Learnlab AI works
The model below shows how Learnlab’s AI is based on data from student’s production in one of the well-known ecosystems for learning, as well as Learnlab’s production tools. Learnlab’s AI reads all types of files, audio, images, text, and video, and connects this to curriculum objectives and concepts to further generate feedback for the student.
All feedback can be read aloud in most languages using Immersive Reader.