Measurement invariance of information,communication and technology (ICT) engagement and its relationship with student academic literacy: Evidence from PISA 2018

The present study aimed to examine the measurement invariance of the information, communication and technology (ICT) engagement questionnaire in the Programme for International Student Assessment (PISA) across countries, and further to explore the effects of ICT engagement on student literacy. The sample included 98,758 15-year-old students from 16 countries in PISA 2018. The multi-group confirmatory factor analyses results indicated that the ICT engagement questionnaire was invariant at the residual level so that meaningful cross-country comparisons can be made at the observed level. Furthermore, the multi-level model results indicated that perceived ICT autonomy was a positive predictor, while use of social media was a negative predictor of student literacy across the countries. However, the relations of interest in ICT and perceived ICT competence to student literacy were inconsistent, with some countries showing positive and linear relationships, while others negative and linear relationships.     

PRO-ESPRIT 算法在声表面波标签识别中的应用

The surface acoustic wave (SAW) identification (ID)-tags have great potential for application in radio frequency identification (RFID) due to their characteristics of wireless sensing and passive operation. In the measurements based on the frequency domain sampling (FDS), to expand the range of detection and allow the system work in harsh environments, it is necessary to enhance the identification capability at low SNR. In addition, to identify the tags in real time, it is important to reduce identification time. Therefore, estimation of signal parameters based on the Procrustes rotations via the rotational invariance technique (PRO-ESPRIT) is adopted. Experimental results show that good identification capability is achieved with a relatively faster measurement speed.