Benefits and Challenges of Integrating Machine Learning for Effective Teaching in Universities in Anambra State

The study determined the benefits and challenges of integrating machine learning for effective teaching in universities in Anambra State. Two research questions guided the study and two hypotheses were tested at 0.05 level of significance. The descriptive survey research design was adopted for the study. The target population consisted of all 235 lecturers from the Departments of Educational Management and Policy/Foundations in the two public universities in Anambra State. A structured questionnaire which was validated by three experts was used to data collection. The instrument yielded reliability coefficients of 0.90 for cluster B1 and 0.88 for cluster B2, with an overall reliability value of 0.89. Mean, standard deviation and t-test was used to analyze data. Finding of the study revealed that integrating machine learning for effective teaching in universities in Anambra State has a lot of benefits such as reducing lecturers’ administrative workload by evaluating assessments, creating adaptive learning environments that adjust to the difficulty of course contents based on real-time assessments of student understanding, and facilitating collaborative engagement between lecturers and students. Finding of the study revealed that the challenges of integrating machine learning for effective teaching in universities are Lack of ICT infrastructure to support the integration of machine learning for effective in universities, erratic power supply and high cost of hardware and software to support machine learning integration among others. The opinions of lecturers with technology experience differed with those of lecturers without technology experience on the benefits of integrating machine learning for effective teaching in universities in Anambra State. Based on these findings, the researcher recommended among others that Government at all levels in collaboration with administrators of universities and private stakeholders should show commitment towards machine learning integration in universities by making substantial investment in the development and upgrading of ICT infrastructure in and around public universities.