The Predictive Potency of Internet of Things Cybersecurity Technology on Classroom Assessment Practices in Higher Institutions of Learning in Nigeria

The potential of Internet of Things Cybersecurity Technology (IoTCST) to improve classroom assessment practices has drawn a lot of attention in education. Because IoT has the potential to increase evaluation processes' efficiency, objectivity, and correctness, its implementation in education has drawn attention. IoTCST can be used to enhance grading and student assessment. IoTCST innovation in education has progressed from idealized lab settings to more complicated real-world learning environments. This study investigated the predictive potency of IoTCST on three classroom assessment practices in Nigerian Higher Institutions of Learning. We adopted correlation research design for the study involving 386 (Male = 177 & Female = 209) students who participated in the study through multistage sampling procedure. Two instruments were used for data collection—The Internet of Things Cybersecurity Technology Questionnaire (IoTCSTQ) and Higher Education Classroom Assessment Practices Scale (HECAPS). The reliability estimates of the instruments were established to be 0.78 and 0.82 respectively using the Cronbach Alpha method. The data collected were analyzed using regression analysis and ANOVA statistics. The findings of the study showed that adoption of IoTCST significantly predicts classroom assessment practices in Higher Institutions of Learning in Nigeria. This study has established that adoption of IoTCS technologies as measured by the HECAPS is predicted by the three assessment practices investigated by the study.