System and method of using academic analytics of institutional data to improve student success
First Claim
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1. A system for associating a student-specific categorization of risk of poor academic performance to a plurality of students in at least one academic course and informing a person of the risk categorization, the system comprising at least one computer having a processor and memory containing processor-executable instructions for:
- collecting and storing data related to each student in computer memory, said data including a plurality of types of data including data selected from a first group including demographic data, personal data, extracurricular activity data, financial data, housing data, employment data, admission data, and registration data, and data selected from a second group including academic data, course management system data, course data, help resources data, technical log data, attendance data, tardiness data, unexcused absences data, workshop attendance data and training data;
permitting a user of the system to select a plurality of data types including data from the first group and from the second group, and to assign custom weights to the selected plurality of data types;
analyzing said data in a manner that takes into account the custom weight assigned to each type of data and results in a categorization of risk that a student will perform poorly academically in the at least one academic course;
associating a risk categorization with each student; and
informing a person of said risk categorization associated with the student through the computer.
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Abstract
Systems and methods that extend the use of data mining to identify students academically at risk of performing poorly or withdrawing from school altogether. In doing so, academically at-risk students are identified early and guided to resources to improve their academic performance.
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Citations
22 Claims
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1. A system for associating a student-specific categorization of risk of poor academic performance to a plurality of students in at least one academic course and informing a person of the risk categorization, the system comprising at least one computer having a processor and memory containing processor-executable instructions for:
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collecting and storing data related to each student in computer memory, said data including a plurality of types of data including data selected from a first group including demographic data, personal data, extracurricular activity data, financial data, housing data, employment data, admission data, and registration data, and data selected from a second group including academic data, course management system data, course data, help resources data, technical log data, attendance data, tardiness data, unexcused absences data, workshop attendance data and training data; permitting a user of the system to select a plurality of data types including data from the first group and from the second group, and to assign custom weights to the selected plurality of data types; analyzing said data in a manner that takes into account the custom weight assigned to each type of data and results in a categorization of risk that a student will perform poorly academically in the at least one academic course; associating a risk categorization with each student; and informing a person of said risk categorization associated with the student through the computer. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method implemented by at least one computer having a processor and memory containing processor executable instructions, for associating a categorization of risk of poor academic performance to a plurality of students in at least one academic course and electronically informing a person of the risk categorization, comprising:
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collecting and storing data related to each student in computer memory, said data including a plurality of types of data including data selected from a first group including demographic data, personal data, extracurricular activity data, financial data, housing data, employment data, admission data, and registration data, and data selected from a second group including academic data, course management system data, course data, help resources data, technical log data, attendance data, tardiness data, unexcused absences data, workshop attendance data and training data; permitting a user of the system to select a plurality of data types including data from the first group and from the second group, and to assign custom weights to the selected plurality of data types; analyzing said data in a manner that takes into account the custom weight assigned to each type of data and results in a categorization of risk that a student will perform poorly academically in the at least one academic course; associating a risk categorization with the student; and informing a person of said risk associating the risk categorization with the student through the computer. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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Specification