METHODS, SYSTEMS AND USER INTERFACES FOR BEHAVIORAL LEARNING

• US 20170263144A1
• Filed: 05/15/2015
• Published: 09/14/2017
• Est. Priority Date: 05/15/2014
• Status: Active Application

• Current Assignee: Changebud Pty Limited
• Original Assignee: Changebud Pty Limited
• Inventors: HORAN, CHRIS
• Application Number:
  US15/310,367
• Publication Number:
  US 20170263144A1
• Time in Patent Office: Days
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• CPC Class Codes: G09B 5/065 Combinations of audio and video presentations, e.g. videotapes, videodiscs, television systems
• 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
• CPC Class Codes: G09B 7/06 of the multiple-choice answer-type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers

Abstract

Disclosed are methods, systems and user interfaces for provision of behaviour change coaching in an electronic form that provides resilience training, and other types of behavioral learning programs.

Claims

1. A method of behavior learning, comprising:

receiving input of at least one event factor value;

generating, in response to the received event factor value, at least one activity prescription value based at least in part on the at least one event factor value, the at least one activity prescription value based at least in part on a strength value; and

generating an output of one or more suggested activities based on at least one of the at least one of the event factor value, the at least one activity prescription value, and the strength value.

2. The method of claim 1, wherein the at least one activity prescription value provided in response to the received event factor value includes a plurality of activity prescription values.

3. The method of claim 1, further comprising:

receiving input of a plurality of event factor values;

in response to the received plurality of event factor values, providing a plurality of activity prescription values; and

generating an ordered suggested activities output based at least in part on the plurality of activity prescription values.

4. The method of claim 3, wherein the event factor values are weighted by at least one of a predetermined parameter, received goal input values, a received intensity value, and a received control value.

5. The method of claim 1, wherein the one or more suggested activities includes multiple suggested activities, the multiple suggested activities provided in an order over time.

6. The method of claim 1, wherein the event factor value is detected by a sensor and the suggested activity is provided as output in response to the detection of the event factor value by the sensor.

7. The method of claim 1, wherein at least one of the event factor values, the activity prescription values, and the suggested activities are customizable.

8. The method of claim 1, further comprising at least one of time stamping and location stamping the received event factors.

9. The method of claim 1, wherein the event factor values are selected from triggers, impacts, and behaviors.

10. The method of claim 1, further comprising receiving a goal value input, and wherein the generating the at least one activity prescription value is based on the event factor value and the goal value input.

11. The method of claim 1, wherein goal value input can be aligned with personal values in a plurality of domains.

12. A method of resilience training, comprising:

receiving an event factor value as input;

correlating to the event factor value to a suggested activity; and

generating an output that includes the suggested activity, wherein the suggested activity provides a habit value,

wherein the habit value is associated with a response field which when populated provides a tracking habit value.

13. The method of claim 12, the method further comprising:

receiving the tracking habit value as input;

correlating the tracking habit value to particular parameters; and

generating a progress value as output.

14. The method of claim 13, further comprising using the progress value to initiate social reinforcement.

15. The method of claim 12, further comprising;

processing the tracking input value with a plurality of tracking aggregated input values likewise received;

generating a success report value as output.

16. The method of claim 12, wherein the event factors values are customizable.

17. The method of claim 12, wherein the event factor values are representative of triggers, impacts, and behaviors.

18. The method of claim 12, wherein the event factor value inputs are received from an electronic detection element and the activity values are provided as output in response to the event factor values.

19. A method of e-learning comprising:

presenting content modules relating to event factor values representative of triggers, impacts, and behaviors;

correlating the content modules to a mobile application having attributes, wherein at least some of the attributes are demonstrated in the content modules; and

providing exercises within the modules based on the correlated content modules and mobile application having attributes, the exercises within the modules including information about the use of the mobile application.

20. The method of claim 19, further comprising providing a tracking system of the exercises, the tracking system configured to determine whether the exercises have been processed.

21. The method of claim 19, further comprising:

receiving an event factor value input via an e-learning application;

populating a back-end of a mobile application with the event factor value received via the e-learning application;

providing a suggested activity corresponding to the event factor value; and

transmitting suggested activity output that is based on the suggested activity, the suggested activity output configured to be transmitted to a mobile application operating on a mobile device.