MTA-SZTE Research Group on Artificial Intelligence

Protocol for cyclic DNA-damaging treatments to generate high mutational burden in the human A549 cell line

Here, we present a protocol that describes iterative exposure of the human lung cancer cell line A549 to DNA-damaging agents to progressively increase mutational burden. We describe steps for controlled cytotoxic dosing, metabolic activation, and repeated treatment cycles of up t...

Artificial intelligence in improving reading comprehension of K-12 students: A systematic literature review

The educational use of artificial intelligence (AI) has expanded rapidly in recent years, offering new possibilities for individualized instruction and learner support. Despite its growing relevance, AI’s effectiveness in the development of reading comprehension among K-12 studen...

Measuring multidimensional student engagement beyond western contexts: A mixed-methods validation study in Mongolian higher education

Student engagement is a multidimensional construct critical for academic success in higher education, yet most measurement instruments were developed in Western contexts and lack validation for non-Western settings, particularly regarding agentic engagement. This study adapted an...