Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   discuss the results of a study of students' academic performance in first year general education courses. Using data from 566 students who received intensive academic advising as part of their enrollment in the institution's pre-major/general education program,  investigate individual student, organizational, and disciplinary factors that might predict a students' potential classification in an Early Warning System as ll as factors that predict improvement and decline in their academic performance. Disciplinary course type (based on Biglan's [7] typology) was significantly related to a student's likelihood to enter below average performance classifications. Students re the most likely to enter a classification in fields like the natural science, mathematics, and engineering in comparison to humanities courses.  attribute these disparities in academic performance to disciplinary norms around teaching and assessment. In particular, the timing of assessments played a major role in students' ability to exit a classification. Implications for the design of Early Warning analytics systems as ll as academic course planning in higher education are offered.
['Michael Geoffrey Brown', 'R. Matthew DeMonbrun', 'Steven Lonn', 'Stephen J. Aguilar', 'Stephanie D. Teasley']
I am writing a research paper on a idea What and when: the role of course type and timing in students' academic performance
[{"from": "human", "value": "I am writing a research paper on a idea What and when: the role of course type and timing in students' academic performance"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   discuss the results of a study of students' academic performance in first year general education courses. Using data from 566 students who received intensive academic advising as part of their enrollment in the institution's pre-major/general education program,  investigate individual student, organizational, and disciplinary factors that might predict a students' potential classification in an Early Warning System as ll as factors that predict improvement and decline in their academic performance. Disciplinary course type (based on Biglan's [7] typology) was significantly related to a student's likelihood to enter below average performance classifications. Students re the most likely to enter a classification in fields like the natural science, mathematics, and engineering in comparison to humanities courses.  attribute these disparities in academic performance to disciplinary norms around teaching and assessment. In particular, the timing of assessments played a major role in students' ability to exit a classification. Implications for the design of Early Warning analytics systems as ll as academic course planning in higher education are offered."}]