Abstract:

In rural public universities in developing countries, students and teachers face numerous challenges in the teaching and learning process in computing degree programs to achieve the learning outcomes of the course modules and finally the degree program.

The major issues that can be identified are:
(i) students having high z-scores (a statistical value which can be used to represent students’ marks) moving to urban universities for more popular courses;
(ii) poor language commutation skills of rural students;
(iii) lack of academic professionals due to various reasons (e.g., due to migration);
(iv) lack of infrastructure facilities; lack of experience of teachers, and attitudes.

The main objective of the study is to develop a model to mitigate the above issues, irrespective of the rural and urban universities and other quality factors of students. The required competency in computing is needed for computing graduates to meet industry requirements and pursue postgraduate studies. According to the current situation, students with higher z-score values will be selected for privileged universities, while those with lower z-score values will be selected for rural and less privileged universities.

Rural areas and low-privileged university undergraduates face several difficulties when finding employment or pursuing postgraduate studies due to the knowledge gap.
To address the above disparity and the knowledge gap, this study proposes a solution model to mitigate the issues with the use of pedagogies, generative and collaborative learning, and experiments through self-learning motivation and modified flipping classroom approaches in the existing environment.

The designed model was practiced with 365 students in three (3) samples as Sample 1- urban popular university, Bachelors of Computer Science, 125 students, Sample 2A: Rural university, Bachelors of Computer Science, 115 students, Sample 2B: Rural university, Bachelors of Science (computing as a subject),125 students). This study was implemented with two models as follows: Model 1: include the current existing approaches. Model 2: include generative and collaborative learning approaches with the modified flipped classroom platform, the achievement of deep learning skills through the guidance of Bloom’s taxonomy, and more technologies (such as generate learning theories etc.) to fulfill the knowledge gap in rural public university undergraduates.

Model 1 was implemented with sample 1. It was proven that the students obtained the required skills when practicing Model 1. Model 1 was implemented with sample 2A, and it was proven that the required knowledge and skills are unable to be obtained in the current context. It was proved that when implementing model 2 with sample 2B, showed very similar performance of students to those when implementing model 1 with sample 1.

For example, after implementing the newly proposed model 2 for Sample 2B, academic performance improved from 27.55% to 48.00%. It is a 20.45% increase concerning sample 2A. Based on the outcomes of the experiments, the proposed Model 2 recommends that low-z-score students and rural university students acquire the expected skills.

Keywords:

Generative Learning, Collaborative learning, Bloom’s Taxonomy, Computer Science skills, flipping classroom.