Abstract: The study focused on assessing the impacts of Artificial Intelligence (AI) through Machine Learning (ML) and Deep Learning (DL) modes in combating the COVID-19 pandemic. This study performed a systematic literature review by analyzing articles published between 2020 and 2023 using VOSviewer (version 1.6.18), MS Excel, SPSS, and the PRISMA 2020 statement. The result shows that the research began in 2020 with 105(8%) articles and increased to 480(35%) articles by 2021, in year 2022 a remarkable increase occurred to 622 (46%) publications. The publication trend declined from 46% in the year 2022 to 11% in the year 2023, this might be due to the decrease of pandemic infections. The study includes only the review of the research articles published from 2020 to 2023 and indexed in the Scopus database. The study has explored the impacts of ML and DL models in combating COVID-19 pandemic; that encompasses a rapid and adaptive response to the urgent needs of the pandemic, the discovery of disease and treatment. The study helps society to improve efficiency, enhanced convenience, and innovative solutions across various sectors, such as the ability to react to health emergencies, examine the healthcare and disease management methods. The study provides a remarkable contribution of AI in addressing the Covid-19 pandemic in work a work place and it has been used to monitor and manage the pandemic on a global scale. In addition, the study contributes to understanding the recent growth statistics of global publications that address COVID-19 pandemic.

Abstract: The main objective of this paper is to assess the possible uses of artificial intelligence (AI) tools and applications for information professionals employed by Tanzania’s higher education institutions (HEIs), particularly in the areas of end-user services and information technology where AI tools and applications may be employed. To find out what they thought about the use and adoption of AI techniques by information professionals of HEIs in Tanzanian, ten information officers were surveyed using a qualitative method. The results’ descriptive tabulation demonstrates that information professionals are knowledgeable about AI tools and applications. Information professionals use Natural Language Processing (NLP)-based applications like Google Assistant, Voice Search, and Google Translate. Pattern recognition methods, such as text data mining, are also used for online searching and information retrieval. OneDrive, Google Drive, cloud computing, and other services can all provide access to Big Data (BD). The population has very little knowledge of chatbots and robotics. The study guides how to use AI technologies and tools for information professionals who have not yet embraced or deployed them or wish to employ more advanced solutions. To establish AI laboratories for information professionals and information science in general, Tanzanian HEIs should collaborate with departments, computing units, and subject matter specialists. Lack of funding and technological know-how is one the biggest challenges facing information professionals in HEIs when implementing AI technologies and solutions.

Received December 26, 2018; Revised January 19, 2018; Accepted March 28, 2018

Abstract: Lecturers want to teach students and the students want to learn. However, there always seems to be a tussle between teaching and learning for examination on one hand and teaching and learning for comprehension and understanding on the other hand. This evokes several teaching and learning approaches. These may be summed up to be either the surface or deep learning approach respectively. The surface learning approach is characterized by rote learning whereas the deep learning approach is student-centered and allows the students to construct and apply knowledge on their own under the guidance of a lecturer. The active involvement of learners in the teaching and learning process resonates with constructivism. Constructivist principles recognize learners as the main focus of any teaching and learning situation by allowing them to explore their environment. There is a symbiotic relationship between deep learning, constructivism and self-regulated learning. It has also been noted by scholars that he Constructive Alignment theory (CA) as well as the ‘3P’ (presage, process and product) learning and teaching model are intended to stimulate the deep learning approach to academic work.