Abstract
<jats:p>Formulation of the problem. This article explains how, within the course Physical Foundations of Information Systems, concepts of signal, interference, and communication channel can be connected to practical metrics of data transmission quality using instructional technical tools (software-defined radio, SDR, and simple radio modules). The aim is to systematize practices of (a) detecting and describing electromagnetic interference (EMI) and (b) assessing data transmission reliability, thereby providing a methodological bridge between physical manifestations in the radio environment and network-level outcomes (PER/PRR/throughput/latency/outages). Materials and methods. The review is conducted as a scoping review, which enables integration of heterogeneous sources: engineering studies on technology coexistence in the 2.4 GHz ISM band, educational publications on SDR laboratories, and standards used as reference points for measurement rigor. Results. The main results include: a taxonomy of EMI observation practices, a taxonomy of reliability metrics, and a correspondence matrix “EMI practice - reliability metric,” complemented by an implementation framework for laboratory work and a minimal package of reproducibility artifacts. The article delineates the limits of SDR use: the device is treated as an educational observation tool, while standards are used as a source of requirements for procedural validity rather than as a basis for certification measurements. Scientific novelty lies in a conceptual systematization of EMI detection/description practices and reliability assessment practices, in a form suitable for teaching the Physical Foundations of Information Systems course using instructional technical tools. Conclusions. The systematization of practices is presented as a correspondence matrix between types of EMI observations and reliability metrics, enabling the design of laboratory tasks with a predefined causal mechanism and transparent requirements for outcomes. Further research could focus on adapting the matrix for blended and distance-learning formats. It is important to expand the scope beyond a single range and a single class of devices: comparing learning outcomes and typical interpretation errors across different technologies (e.g., Wi-Fi, Bluetooth) and different environmental conditions will help refine the universal and specific elements of the proposed matrix and framework.</jats:p>