The geometrical growth and sudden transformation of technologies as a result of Covid-19 have provided an evolutionary means of learning online with sophisticated and enabling devices with a click. Teaching and learning online, though enabling flexibility and interactivity between the teacher and students, yet requires regulations and policies that coordinate and balance different expectations of learners and teachers. These standards and values called ethics are to be adhered to achieve the desired online goals, while avoidance of them would be mounted to immoral attitudes and behaviours that weaken online activities. The study discusses and identifies ideal ethics expected in online teaching and learning from all online activities stakeholders. It further explains how violating the regulations and policies would weaken the effective and efficient running of training, skills, and lectures online. The interview instrument was used to collect data from the students in form of focus groups, while students were asked open-ended questions using Google form on social media platforms. To ensure validity and reliability of the instruments, researcher colleagues validated the content and structure of the instruments before being subjected to reliability statistics to ensure a high-reliability index. The administration was done within three weeks. The results gotten were collated and analyzed with charts and pictorials for easy interpretation and visualization. The results establish that online participants should always respect and strictly adhere to codes and conducts that will give room for convenient teaching and learning and also encourage a high rate of retention in learners. To sum up, policies and regulations to run smooth teaching and learning online should always be read to involve participants each time to access learning online as a prerequisite to accessibility
Everybody is confronted daily with cluster of decisions that must be appropriately taken in the process of making accurate decision; individuals are faced with and most often fall prey to series of common biases, fallacies, and many other decision making odds. In determining which algorithm to apply for analysis (with machine learning algorithms/models) open to critical steps to be taken and also highly depend on many factors ranging from the type of problem at hand, the condition to choose a model and to the expected outcomes. The study looks at how artificial intelligent approach with expert system would be helpful in making timely decision on which type of algorithm(s) is/are capable to be applied and implemented to have desired results. The study also uses VisiRule software to model series of successful channels to arrive at a good decision making means. The use of VisiRule (Artificial Intelligent Based Expert System) was employed to give directional path ways to the selection of appropriate algorithms from supervised and unsupervised machine learning to different classification methods, regression methods, clustering approaches, dimensionality reduction methods, and association rules. The outcome of this study demonstrates the easy way through paths to select relevant and most appropriate model or algorithm that best fit the analysis at hand with detailed explanation of each alternative option. The use of VisiRule software has proven the easy way to achieve decision making problems without any codes requirement for such actions. Decision making challenges could be resolved by just implementing artificial intelligent rule-based expert system which require less time, coding free, and highly achievable accurate outcomes.
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