User acceptance testing (UAT) for the development and evaluation of an automated learning style detection system
Abstract
The purpose of this study is to determine the acceptable level of a proposed automated learning style detection system. This system was tested among teachers in schools based on a construct presented by the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. A prototype application named VAKLeS was developed in order to evaluate user acceptance among the respondents. A combination of NeatBeans, Java, and MySQL was used to implement the learning style-based application to present the appropriate subject matter through content or activity, format, and platform type. VAKLeS was organized into two modules: the learning style module (student module) and decision support module (teacher module). The teacher acts as the decision maker while the student is the system user. The learning style of the user is evaluated based on his or her behavior when using the application. The two modules interact together to predict the user learning style. User testing was conducted for teachers to evaluate the performance of the system in detecting user learning style. VAKLeS was evaluated based on user acceptance testing (UAT). A set of questionnaires was distributed to ten respondents, who are domain expert in pre-school teaching. The questionnaire has 26 variables consisting of four core evaluation elements: performance expectations (nine variables), effort expectancy (seven variables), social influence (six variables), and facilitating conditions (three variables). These items are related to the usage of VAKLeS and are rated based on a seven-point Likert Scale. The finding of user acceptance was based on the average score of Strongly disagree (1) and Strongly agree (7). The findings of VAKLeS testing showed that the four elements evaluated was positive significantly with 5.87 for performance expectancy, 5.93 for effort expectancy, 6.03 for social influence, and 5.90 for facilitating condition. The finding of the UAT among the domain expert indicates that the proposed VAKLeS is acceptable and can be applied as an automated system for detecting VAK learning style based on the student's behavioral pattern. Furthermore, the finding of this study also reveals that the proposed system, VAKLeS, significantly improved the ability of teachers to detect the learning style of their students.
- Publication:
-
The 4th Innovation and Analytics Conference & Exhibition (IACE 2019)
- Pub Date:
- August 2019
- DOI:
- 10.1063/1.5121098
- Bibcode:
- 2019AIPC.2138d0019M