Positive and negative impact of technology on the learning process

5. Learning analytics and ethical challenges

One of the most important benefits of educational technology is the application of learning analytics . Tools integrated into learning management systems (LMS) allow teachers to see student progress and activity, identify those who are lagging behind, and intervene in a timely manner. Such a data-driven approach supports individualized support and evidence-based educational decision-making.

However, on the other hand, a number of ethical questions arise. The collection, processing and interpretation of educational data opens dilemmas related to privacy, transparency and consent. The question arises to what extent it is justified to monitor the digital traces of students, how the data is used and who has access to the analyses. In this sense, it is necessary to ensure high standards of data protection, a clear informed consent policy and responsible use of technology.

In the higher education context, learning analytics can be an extremely useful tool for monitoring progress, encouraging engagement, and adjusting support for students. An example of good practice is the use of analytics for formative monitoring, for example, a teacher can regularly review which activities students most often skip or which tasks they stay on longer than expected and based on this, adjust the content or further clarify problematic parts. Also, individual messages of support to students who show signs of reduced engagement can have a certain motivational effect.

In order to use learning analytics in an ethical and responsible manner, several steps are recommended. The first step is transparency, students should be clearly informed about what data is being collected, for what purpose and who has access to it. The second is minimal collection, and therefore only those data that are necessary to improve the learning process should be collected, not for monitoring. Third, a degree of caution is needed in interpretation, as activity data should not be interpreted solely as indicators of success, as quantitative traces do not always reflect the depth of understanding.

Teachers should develop data literacy, the ability to critically understand and use educational data. This includes an awareness of the limitations of algorithms, potential biases, and the need to combine quantitative and qualitative data. In this way, learning analytics can be used as a tool of support rather than control, contributing to a culture of trust, autonomy, and responsible use of technology in education.