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KTH Internal report on the 2024 E-learning survey
KTH, School of Industrial Engineering and Management (ITM), Learning, Digital Learning.ORCID iD: 0000-0002-5222-970X
KTH, School of Industrial Engineering and Management (ITM), Learning, Digital Learning.ORCID iD: 0000-0002-6175-9200
KTH, School of Industrial Engineering and Management (ITM), Learning, Digital Learning.ORCID iD: 0000-0002-6854-785x
KTH, School of Industrial Engineering and Management (ITM), Learning, Digital Learning.
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2026 (English)Report (Other (popular science, discussion, etc.))
Abstract [en]

This report contains a large potion of the result of the KTH e-learning surveys, administered inDecember 2024. One survey was sent out to teachers and one to students. The main purpose ofthe surveys is to gain insights of how teachers and students perceive the current digital learningenvironment and also explore around challenges, within a near future, concerning digital learningin higher education. The themes of those challenges in these surveys were generative AI and digitalassessment. The data gathered and the report will also be used to make informed decision for thework that is carried out within the E-learning object at KTH.

The aim of this report has been to present the result in a straightforward way, mainly with graphsand comments on those visualisation of the data. Thus, no deep statistical analysis will be presentedin this report. The survey was divided into the following parts: demography, digital education,generative AI, digital assessment. The data collection yielded responses from 314 teachers and 1291 students, corresponding to response rates of 19% and 6%, respectively.

The result from the digital education part indicates that teacher think KTH has succeeded well withdigital education in 2024 and that they are offered well-functioning digital infrastructures and toolsto conduct high-quality digital education. Furthermore, students think that the education at KTHuses digital opportunities in a good way and that the education is of high quality. Both groups alsoagree in general that KTH should continue developing digital education.

Students report that they are very familiar with AI chatbots and are also often using these tools fortheir studies. Teachers are less familiar, and 25% report that they use AI chatbots weekly or moreoften in their role as a teacher, whereas 37% have never used i. The wide availability of AI chatbotshas also led many students to change their study habits, and about two-thirds of the teachers havemade some changes to their teaching practice. The most commonly perceived usefulness and reported use of AI chatbots for teachers was help with creating materials for teaching or examination,whilst students perceive it as useful and use it in their studies to pose questions that they have, findinformation and summarize text. Students think that AI chatbots increase cheating, but few reportthat they have used AI chatbots in a way they were not allowed to. About one quarter of the teacherreported that they have made moderate or significant changes in their assessment practices.

The results from the part focused on digital assessment showed that slightly more than half of teachers (54%) had created at least one digital assessment during 2024, while 62% of students had takenat least one digital exam. The main reasons for using digital assessment were the ability to providetimely, frequent feedback and to save time and resources. Among students who prefer digital assessment, 63% cited quick feedback and many also found digital exams to be easier to complete andsubmit. Students who preferred paper-based exams emphasized feeling more comfortable (66%)and better able to focus (61%). Teachers who used digital assessment reported technical problemsduring exams as their main challenge, a concern echoed by students, who worried about log-inissues, lost internet connections, and needing to troubleshoot on their own.

Place, publisher, year, edition, pages
Stockholm, 2026. , p. 55
Series
TRITA-ITM-RP ; 2026:1
Keywords [en]
Digital learning, Generative AI, Digital assessment
National Category
Pedagogy
Identifiers
URN: urn:nbn:se:kth:diva-375772OAI: oai:DiVA.org:kth-375772DiVA, id: diva2:2030343
Note

QC 20260130

Available from: 2026-01-20 Created: 2026-01-20 Last updated: 2026-01-30Bibliographically approved

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KTH_Internal_report_on_the_2024_E-learning_survey(21375 kB)441 downloads
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Enoksson, FredrikDavis, Richard LeeKarunaratne, ThashmeeLand, AnnaYoon Blomstervall, JeonginBern, Caroline

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