I want to analyze the research problem in education data mining, with machine learning algorithms, I want to build a model that suggest school students which domain to select for higher education, with evaluating the dataset of student as well as the dataset of higher education of the same student.
To analyze the research problem in education data mining and build a model that suggests school students which domain to select for higher education, you can consider the following research questions:
How can machine learning algorithms be used to analyze student datasets and higher education datasets to provide personalized recommendations for domain selection?
What features and variables from the student dataset and higher education dataset are most relevant in predicting the optimal domain for individual students?
How can the accuracy and reliability of the recommendation model be measured and evaluated?
What are the potential limitations and biases in using data mining and machine learning algorithms for making domain suggestions for students?
How can the recommendation model be designed to take into account individual student preferences, aptitudes, and career aspirations?
How can the recommendation model be continuously updated and improved based on feedback from students and the evolving landscape of higher education?
What ethical considerations should be taken into account when using education data mining and machine learning algorithms for domain selection recommendations?
By addressing these research questions, you can develop a comprehensive understanding of the challenges and opportunities in using education data mining and machine learning algorithms to suggest domain choices for school students pursuing higher education.
Impact of social media on students in post covid period.
Impact of mobile usage on students in higher education post covid period
- Badges
- Science topic
- Similar topics
- Philosophy
- Esthetics
- Interpretation