System for utilizing assessment without testing

• US 10,586,467 B2
• Filed: 11/21/2017
• Issued: 03/10/2020
• Est. Priority Date: 09/24/2010
• Status: Active Grant

• Current Assignee: Lexia Learning Systems LLC (Rosetta Stone Incorporated), Rosetta Stone Limited (Rosetta Stone Incorporated)
• Original Assignee: Lexia Learning Systems, Inc. (Rosetta Stone Incorporated)
• Inventors: Brooke, Elizabeth Crawford, Petscher, Yaacov, Schatschneider, Christopher
• Primary Examiner(s): Hong, Thomas J
• Application Number:
  US15/820,214
• Publication Number:
  US 20180158351A1
• Time in Patent Office: 840 Days
• Field of Search: 434322
• CPC Class Codes: G09B 19/06 Foreign languages with audible presentation of material to be studied G09B5/04
• CPC Class Codes: G09B 5/10 all student stations being capable of presenting the same information simultaneously G09B5/14 takes precedence
• CPC Class Codes: G09B 7/00 Electrically-operated teaching apparatus or devices working with questions and answers mechanically operated G09B3/00; computing arrangements G06F
• CPC Class Codes: G09B 7/02 of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student

Abstract

A system for educational assessment without testing is provided that includes one or more client systems that are connected to a network allowing students or school officials to communicate with an education framework that performs and manages educational assessment. The one or more client systems issue a message to the education framework requesting a task to be performed. The educational assessment is administered independent of one or more educators so as to avoid interruption of instruction time. A server system receives the message and the education framework proceeds to process the contents of the message. The education framework includes a plurality of programming modules being executed on the server system that provides to educators specific information used for the educational assessment based on the contents of the message. The programming modules assist in calculating and determining one or more parameters for the educational assessment of the students as well as providing specific reports to educators as to the progress of the students.

Claims

1. An apparatus, comprising:

a communication interface configured to communicate with a plurality of student client systems independent of one or more educator systems; and

a processor configured to

determine an average usage time of a language learning system over a period of time for each of a plurality of students based on messages received by the communication interface,

calculate a comparison value for each of the plurality of students by comparing the average usage time of that student to norm sample data,

periodically calculate a performance predictor for each of the plurality of students based on the comparison value for that student, the performance predictor indicating the respective student'"'"'s chance of meeting a benchmark based on the norm sample data,

store the calculated performance predictor in a database,

generate, based on the calculated performance predictor and historical data stored in the database, a skill set identification for each of the plurality of students and a prescription for each of the plurality of students, the prescription including a target usage time for that student in a next period of time and available lessons selected for that student based at least in part on the skill set identification,

receive a request from one of the one or more educator systems for a performance report, and

generate, in response to the request, a report including the performance predictor for each of the plurality of students and a quantified risk variable associated with each of the plurality of students.

2. The apparatus of claim 1, wherein the processor is configured analyze performance by one of the plurality of students of one or more daily skill activities of the respective prescription.

3. The apparatus of claim 1, wherein the benchmark is determined based on a percentage of students in the norm sample data that complete each level of one or more daily activities.

4. The apparatus of claim 1, wherein the skill set identification defines an educational level that the respective student has achieved using the language learning system.

5. The apparatus of claim 1, wherein processor is configured to customize the report based upon a type of educator.

6. The apparatus of claim 5, wherein when the type of educator is a school administrator, the processor is configured to generate the report including performance predictors associated with students of a different class than the plurality of students.

7. The apparatus of claim 1, wherein the processor is configured to assign a usage category for each of the plurality of students based on the average usage time of that student over the period of time.

8. A non-transitory computer readable medium containing instructions that when executed by a processor cause the processor to perform a method comprising:

determining an average usage time of a language learning system over a period of time for each of a plurality of students based on messages received by a communication interface, the communication interface being coupled to the processor and configured to communicate with a plurality of student client systems independent of one or more educator systems;

calculating a comparison value for each of the plurality of students by comparing the average usage time of that student to norm sample data;

periodically calculating a performance predictor for each of the plurality of students based on the comparison value for that student, the performance predictor indicating the respective student'"'"'s chance of meeting a benchmark based on the norm sample data;

storing the calculated performance predictor in a database;

generating, based on the calculated performance predictor and historical data stored in the database, a skill set identification for each of the plurality of students and a prescription for each of the plurality of students, the prescription including a target usage time for that student in a next period of time and available lessons selected for that student based at least in part on the skill set identification;

receiving a request from one of the one or more educator systems for a performance report; and

generating, in response to the request, a report including the performance predictor for each of the plurality of students and a quantified risk variable associated with each of the plurality of students.

9. The medium of claim 8, further comprising analyzing performance by one of the plurality of students of one or more daily skill activities of the respective prescription.

10. The medium of claim 8, wherein the benchmark is determined based on a percentage of students in the norm sample data that complete each level of one or more daily activities.

11. The medium of claim 8, wherein the skill set identification defines an educational level that the respective student has achieved using the language learning system.

12. The medium of claim 8, wherein the generating the report includes customizing the report based upon a type of educator.

13. The medium of claim 12, wherein when the type of educator is a school administrator, the generating the report includes generating performance predictors associated with students of a different class than the plurality of students.

14. The medium of claim 8, further comprising assigning a usage category for each of the plurality of students based on the average usage time of that student over the period of time.

15. A method, comprising:

determining, by a processor, an average usage time of a language learning system over a period of time for each of a plurality of students based on messages received by a communication interface, the communication interface being coupled to the processor and configured to communicate with a plurality of student client systems independent of one or more educator systems;

calculating a comparison value for each of the plurality of students by comparing the average usage time of that student to norm sample data;

periodically calculating a performance predictor for each of the plurality of students based on the comparison value for that student, the performance predictor indicating the respective student'"'"'s chance of meeting a benchmark based on the norm sample data;

storing the calculated performance predictor in a database;

generating, based on the calculated performance predictor and historical data stored in the database, a skill set identification for each of the plurality of students and a prescription for each of the plurality of students, the prescription including a target usage time for that student in a next period of time and available lessons selected for that student based at least in part on the skill set identification;

receiving a request from one of the one or more educator systems for a performance report; and

generating, in response to the request, a report including the performance predictor for each of the plurality of students and a quantified risk variable associated with each of the plurality of students.

16. The method of claim 15, further comprising analyzing performance by one of the plurality of students of one or more daily skill activities of the respective prescription.

17. The method of claim 15, wherein the benchmark is determined based on a percentage of students in the norm sample data that complete each level of one or more daily activities.

18. The method of claim 15, wherein the skill set identification defines an educational level that the respective student has achieved using the language learning system.

19. The method of claim 15, wherein the generating the report includes customizing the report based upon a type of educator.

20. The method of claim 19, wherein when the type of educator is a school administrator, the generating the report includes generating performance predictors associated with students of a different class than the plurality of students.

21. The method of claim 15, further comprising assigning a usage category for each of the plurality of students based on the average usage time of that student over the period of time.