Factors affecting students’ continuance intention to use teaching performance assessment application from technology continuance theory

Abstract

<p><span lang="EN-US">This study aims to determine university students’ continuance intention in using an android-based teaching performance assessment (TPA) application. For the data gathering instrument, we employed an online structured questionnaire. Two hundred and forty students from four faculties were selected and assigned a five-scale survey. All completed questionnaires were analyzed using analysis of moment structure (AMOS). The findings show that the factors of productivity, performance, relevancy, quality and mobility of the android-based TPA have significantly influenced students’ continuance intention to use the application. The results highlighted that when an android-based system was developed based on the criteria, the long-term use of the android-based TPA application can be consistently maintained to improve universities’ teaching quality assessment. However, our study needs to improve in that the university students may evaluate teaching staffs who are not teaching a subject in their class because all teaching staff has appeared in the application database. In addition, further research needs to limit each lecture based on a specific course to be assessed by a particular student’s class.</span></p>

Multi-criteria Assessment of a Student’s Individual Profile

“…Kureichik et al [9] in their work explore an approach to the design of intelligent distance learning systems based on rules and precedentbased inference technologies. Noordin et al [10] consider teaching effectiveness assessment in which expert systems should model the expert's decision-making process as a deductive process using rule-based inference. Yusu et al [11] demonstrate a systematic overview of sequential learning using neural network and its models, where a set of rules can be built into the system that based on input data.…”