A Predictive Model For Quality-assurance In Normal Learning Through Students Feedback In Kiambu Technical Colleges

Abstract

Quality assurance (QA) in any technical college requires monitoring and evaluation for quality learning. Feedback from students when adopted can promote QA to ensure the learning environment is enhanced continuously and consistently. The adoption of the Competence-Based Education Training (CBET) in Kenya has come with new challenges of handling data. The change of the structure for learning delivery and assessment requires monitoring and evaluation to facilitate trainees, trainers, and managers to adapt to the requirements of this approach of training. Technical and Vocational Education Training Authority (TVETA) as the regulatory agency for technical colleges has standards for monitoring the successful and full implementation of competence-based training in Kenya. The County of Kiambu is among the counties in Kenya endowed with reliable communication infrastructure and should lead the way in leveraging on Internet, mobile telephony as well as the modern data repository and analytical technologies in the execution of processes in technical colleges. The predictive model for IQA from this study will be useful in adjustments of policies and methodologies, and facilitate instituting changes or affirming instructional roles. A sample population of technical colleges in Kiambu County was used to identify the current feedback mechanisms implemented in the colleges. The variables identified for the predictive model are Instructional delivery, resource provisioning, assessment process and technology usage. The phenomenon of participatory sensing is extended in this study where the student, the mobile phone, an application embedded in the phone and the internet are combined to form a sensing mechanism to support learning. Technologies employed in this model are VADER, spark, HDFS mobile telephony and the internet, while visualization graph for multivariate data is done by Parallel coordinates graph. This model and system derived thereof will support the digital survey student accustomed to use of mobile telephony for communication and cyberspace for seeking information, in order to interact in the learning ecosystem in the phenomenon of participatory sensing. The future of quality education is to leverage technology to help both the student and the instructor or trainer, to promote Kenya's industrial and national growth by the development of a skilled workforce.