Teaching Artificial Intelligence Tools Required Of Undergraduates for Communication and Digital Entrepreneurship In Public Tertiary Institutions In Rivers State
Year: 2025
Type: article
Abstract: This study was on teaching artificial intelligence tools required of undergraduates for communication and digital entrepreneurship in public tertiary institutions in Rivers State. One research question guided the study and one null hypothesis was tested. Descriptive survey research design was adopted. From a population of 139 communication and entrepreneurship lecturers, a census survey sampling was employed. A four-point response options questionnaire was used for data collection, and it was validated by three experts. The reliability of the instrument was established using Cronbach’s alpha which yielded coefficient of 0.77. Mean and Standard Deviation were used to answer the research question and measure the spread in respondents` opinions, while one-way analysis of variance (ANOVA) was used to test the null hypothesis at 0.05 level of significance. Findings revealed that all the types of AI tools stated were very highly required to be taught undergraduates for communication and digital entrepreneurship activities. Also, educational attainment plays vital roles in teaching AI tools to undergraduates for communication and digital entrepreneurship activities. Consequently, it was concluded that if AI tools are included in the curriculum and taught, it will transform the programmes positively, lead to AI skills development and enable the undergraduates to acquire employability skills. Among other things, it was recommended that AI tools should be included in communication and entrepreneurship curriculum through yearly internal curriculum review by lecturers in collaboration with their institutions and five years national review by all levels of government.
Authors: Philip Festus Ukata, PhD, Endwell Onyinye Obinichi-Aaron
Institution: Captain Elechi Amadi Polytechnic, Rumuola
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6949714216
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