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What is data-informed education?

Here you can learn more about what data-informed education means and what it can be used for. Data-informed education can be divided into two strands, data-informed learning and data-informed teaching. You can also read about how student data can be protected when used for these purposes.

Word list for data-informed education

Are you confused about some of the words or concepts used within data-informed education? Or do you want to know how they should be translated to Swedish? We have gathered the most important concepts in our word list.

Word list

Data-informed education (DInE) is the practice of using educational data, analytics, and insights to enhance teaching, learning, and decision-making while ensuring that human expertise, pedagogical principles, and contextual understanding remain central to the process. In contrast to data-driven education, which relies solely on quantitative metrics, data-informed education integrates data insights and professional judgment to make well-rounded, ethical, and effective educational decisions.

DInE at KTH mainly has two strands; data-informed learning (DIL) and data-informed teaching (DIT).

Data-informed learning (DIL)

Data-informed learning (DIL) is a student-centered process within data-informed education (DInE) that empowers learners to actively engage with data about their own learning to make informed decisions, reflect on progress, and adapt strategies for improvement. It supports the development of data literacy and self-regulated learning, enabling students to interpret feedback, set goals, and take ownership of their educational journey.

DIL emphasizes student agency, ensuring that the use of data is guided by learners' needs, preferences, and contexts. Ethical considerations such as privacy, security, and consent are centered on the student, ensuring that DIL benefits the student.

Data-informed teaching (DIT)

Data-informed teaching (DIT) is a teacher-centered approach within data-informed education (DInE) that leverages educational data to support continuous instructional improvement through reflective practice and professional judgment. At its core, DIT is a process that supports teacher inquiry, empowering educators to pose pedagogical questions, explore evidence, and make informed decisions about teaching strategies and learning environments.

Rather than prescribing actions based solely on metrics, DIT prioritizes teacher agency, contextual understanding, and ethical responsibility, particularly regarding student privacy, data security, and educational relevance. It embraces a student-cantered ethos while recognizing that meaningful, sustainable improvement in teaching begins with the informed insights and needs of educators.

Use cases

Using data about learners and the learning environments in data-informed learning can help us draw insights into learning, to support students and to improve many educational processes. KTH is interested in and is currently exploring the possibilities of using data-informed learning in the contexts of:

  • enhancing course (learning) design
  • improving the course throughput
  • increasing the quality of the learning provision (including e-learning support).

The primary focus of data-informed learning research and implementation at KTH is to enhance student learning and improve their educational experience; in other words, Student-centricity is the guiding principle.

Student data is protected

We take utmost care of student data. We are committed to the righteous use of student data and protecting the security of data and the student's privacy. The KTH ethics committee oversees privacy and ethics compliance with a data protection impact assessment plan in progress.

For the systematic inception of data-informed learning, we follow the JISC guidelines and code of practice for learning analytics: Code of practice for learning analytics (jisc.ac.uk) .

We also follow the ethical policy at KTH: