COURSE RECOMMENDATION SYSTEM AND METHOD

• US 20130011821A1
• Filed: 04/06/2012
• Published: 01/10/2013
• Est. Priority Date: 04/07/2011
• Status: Active Application

• Current Assignee: Tristan Denley
• Original Assignee: Tristan Denley
• Inventors: Denley, Tristan
• Application Number:
  US13/441,063
• Publication Number:
  US 20130011821A1
• Time in Patent Office: Days
• US Class Current: 434/350
• CPC Class Codes: G06Q 50/20 Education

Abstract

A system for assisting a student or other user to identify courses that best fit the student'"'"'s or user'"'"'s talents and program of study. Ratings can be shown as a number of stars, a number, a letter, or similar indicator. The system combines three criteria to produce each list of courses that it recommends: courses that apply directly to the student'"'"'s program of study, courses that are the most central to the university curriculum (centrality ranking), and courses that the model predicts the student will achieve the best grades in (grade prediction). The recommended course list may be displayed in a web-based interface that allows each student to find information on his/her recommended course curricula and requirements, as well as class availability in upcoming semesters. Majors or concentrations can also be evaluated and recommended.

Claims

1. A machine for recommending courses, comprising:

a microprocessor or processor coupled to a memory, wherein the microprocessor or processor is programmed to recommend courses by;

predicting the final grade a student user will receive in one or more courses that the student user has not yet taken; and

determining a list of recommended courses for the student user to take based in part on the final grade predictions.

2. The machine of claim 1, wherein the recommended course list is displayed to the student user through an Internet web browser interface.

3. The machine of claim 1, wherein the list of recommended courses is restricted to courses in the student user'"'"'s field of study or major.

4. The machine of claim 3, wherein the list of recommended courses is further based in part on the centrality of each course to an educational institution'"'"'s core curriculum.

5. The machine of claim 1, wherein the final grade prediction for a particular class for the student user is based on the history of prior grades in that class by other students.

6. The machine of claim 1, wherein the final grade prediction for a particular class is based upon the history of prior grades in classes by other students, and the history of prior grades in classes by the student user.

7. The machine of claim 1, wherein the final grade prediction is determined by creating a matrix of grades achieved by students in courses, the matrix comprising a column for every course offered by an educational institution and a row for every student of record.

8. A machine for evaluating a major or concentration at an educational institution, comprising:

a microprocessor or processor coupled to a memory, wherein the microprocessor or processor is programmed to evaluate a major or concentration by;

identifying fingerprint classes for a given major based upon those classes that appear disproportionately often in the transcripts of graduates in that major as compared to graduates as a whole from that educational institution;

determining the grades a student user has received for every fingerprint class the student user has already taken;

predicting the grades a student user will receive for the fingerprint classes the student user has not yet taken; and

averaging the received grades and the predicted grades to determine a predicted grade point average for that student user for that major.

9. The machine of claim 8, further wherein predicted grade point averages for the student user are determined for multiple majors or concentrations.

10. The machine of claim 9, wherein the list of majors and predicted grade point averages are displayed to the student user through an Internet web browser interface.

11. The machine of claim 9, wherein the majors with the highest predicted grade point averages are displayed to the student user as recommended majors.

12. The machine of claim 8, wherein the step of identifying fingerprint classes is based on transcripts of graduates in the last ten years.

13. The machine of claim 8, wherein the step of identifying fingerprint classes comprises selecting the ten classes that appear most frequently.

14. The machine of claim 8, wherein the grade prediction for a particular class the student user has not yet taken is based on the history of past grades in that specific class by other students, the history of past grades in some or all other classes by other students, the history of past grades in other classes by that particular student, or a combination thereof.

15. The machine of claim 14, wherein the final grade prediction is determined by creating a matrix of grades achieved by students in courses, the matrix comprising a column for every course offered by an educational institution and a row for every student of record.

16. A method of recommending courses, comprising the steps of:

predicting, using a microprocessor or processor in a computing device, the final grade a student user will receive in one or more courses that the student user has not yet taken; and

determining a list of recommended courses for the student user to take based in part on the final grade predictions.

17. The method of claim 16, further comprising the step of displaying the list of recommended courses to the student user.

18. The machine of claim 16, wherein the list of recommended courses is restricted to courses in the student user'"'"'s field of study or major.

19. The machine of claim 16, wherein the list of recommended courses is further based in part on the centrality of each course to an educational institution'"'"'s core curriculum.

20. The machine of claim 16, wherein the grade prediction for a particular class the student user has not yet taken is based on the history of past grades in that specific class by other students, the history of past grades in some or all other classes by other students, the history of past grades in other classes by that particular student, or a combination thereof.