DESC:
FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION

(See Section 10 and Rule 13)

Title of invention:

METHOD AND SYSTEM FOR FACILITATING ENHANCED LEARNING AND GRADED ASSESSMENT

Applicant:
Tata Consultancy Services Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Nirmal Building, 9th floor,
Nariman point, Mumbai 400021,
Maharashtra, India

The following specification particularly describes the invention and the manner in which it is to be performed.

CROSS-REFERENCE TO RELATED APPLICATIONS AND PRIORITY

[001] The present application claims priority from Indian Provisional Patent Application No. 745/MUM/2015, filed on March 07, 2015, the entirety of which is hereby incorporated by reference.

FIELD OF THE INVENTION

[002] The present application generally relates to learning and assessment. Particularly, the application provides a method and system for facilitating enhanced learning and graded assessment.

BACKGROUND OF THE INVENTION

[003] Pedagogy is a discipline which deals with theory and practice of education in which it concerns about how best a teacher can convey knowledge to trainees/learners/students. Conveying the knowledge means a teaching performed by the teacher through online and offline modes. The online mode i.e., e-learning is a field in which a lot of innovations have been done for imparting the knowledge from the teacher to the trainees. However, relatively less number of solutions exist in assessing how much has the trainee learnt and what are specific strong and weak points.

[004] Further, there are several methods of pedagogy available for imparting training on programming languages in classroom environment (both physical and virtual) which has helped in improving time to learn new concepts of the programming languages. However, when it comes to solving programming exercises which require adherence to certain specifications, yardsticks have been largely restrictive with respect to assessment. One could end up in writing a code which fails during compilation or execution, which could be attributed either to improper understanding and application of concepts or the underlying specifications or a combination of both. This may occur due to various factors like errors arising out of carelessness.

[005] Lot of time and manual effort is spent by faculties in taking a deep dive for comprehensive assessment of submissions provided by the trainees in order to identify actual learning gaps. In today’s assessment process, there is a void in space of automation of evaluation against specifications derived from the programming concepts based on practices followed by the teachers or trainers, as the automation is expected to be tightly coupled with these specifications and practices. Thus, there is a need for a human-independent method and system for facilitating holistic automation for learning and assessment of the submissions without compromising with quality of learning and faculty-trainee relationship.

SUMMARY OF THE INVENTION

[006] Before the present methods, systems, and hardware enablement are described, it is to be understood that this invention is not limited to the particular systems, and methodologies described, as there can be multiple possible embodiments of the present invention which are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only, and is not intended to limit the scope of the present invention which will be limited only by the appended claims.

[007] The present application provides a method and system for facilitating learning and graded assessment.

[008] The present application provides a computer implemented method for facilitating learning and graded assessment; said method comprising steps of receiving a plurality of assessment content and a plurality of assessment rules configured by at least one faculty; receiving at least one trainee submission for assessment from at least one trainee; applying the plurality of assessment rules against each of the received trainee submission for ascertaining adherence of said trainee submission to the plurality of assessment rules; generating score and grading for each of the trainee submission according to the plurality of assessment rules and subsequently generating a report for each of the trainee submission based on the generated score and grade; and identifying in real time at least one strong learning attribute and at least one weak learning attribute for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning.

[009] The present application provides a system (102) for facilitating learning and graded assessment; said system (102) comprising a processor (202); an input/ output interface (204), electronically coupled with the processor (202); a rule database (212) accessible by the processor (202); a memory (206) embodying computer program code therein, coupled to the processor (102), wherein said computer program code comprising instructions executable by said processor (102) and configured for executing steps of receiving a plurality of assessment content and a plurality of assessment rules configured by at least one faculty; receiving at least one trainee submission for assessment from at least one trainee; applying the plurality of assessment rules against each of the received trainee submission for ascertaining adherence of said trainee submission to the plurality of assessment rules; generating score and grading for each of the trainee submission according to the plurality of assessment rules and subsequently generating a report for each of the trainee submission based on the generated score and grade; and identifying in real time at least one strong learning attribute and at least one weak learning attribute for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning.

BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and components.

[0011] Figure 1 illustrates a network implementation of a system for providing enhanced learning and graded assessment, in accordance with an embodiment of the present subject matter;

[0012] Figure 2 illustrates architecture diagram of the system, in accordance with an embodiment of the present subject matter; and

[0013] Figure 3 illustrates flow diagram for providing enhanced learning and graded assessment, in accordance with an embodiment of the present subject matter.

[0014] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION OF THE INVENTION

[0015] Some embodiments of this invention, illustrating all its features, will now be discussed in detail.

[0016] The words "comprising," "having," "containing," and "including," and other forms thereof, are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items.

[0017] It must also be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present invention, the preferred, systems and methods are now described.

[0018] The disclosed embodiments are merely exemplary of the invention, which may be embodied in various forms.

[0019] The elements illustrated in the Figures interoperate as explained in more detail below. Before setting forth the detailed explanation, however, it is noted that all of the discussion below, regardless of the particular implementation being described, is exemplary in nature, rather than limiting. For example, although selected aspects, features, or components of the implementations are depicted as being stored in memories, all or part of the systems and methods consistent with the attrition warning system and method may be stored on, distributed across, or read from other machine-readable media.

[0020] The techniques described above may be implemented in one or more computer programs executing on (or executable by) a programmable computer including any combination of any number of the following: a processor, a storage medium readable and/or writable by the processor (including, for example, volatile and non-volatile memory and/or storage elements), plurality of input units, and plurality of output devices. Program code may be applied to input entered using any of the plurality of input unit to perform the functions described and to generate an output displayed upon any of the plurality of output device.

[0021] Each computer program within the scope of the claims below may be implemented in any programming language, such as assembly language, machine language, a high-level procedural programming language, or an object-oriented programming language. The programming language may, for example, be a compiled or interpreted programming language. Each such computer program may be implemented in a computer program product tangibly embodied in a machine-readable storage device for execution by a computer processor.

[0022] Method steps of the invention may be performed by one or more computer processors executing a program tangibly embodied on a computer-readable medium to perform functions of the invention by operating on input and generating output. Suitable processors include, by way of example, both general and special purpose microprocessors. Generally, the processor receives (reads) instructions and data from a memory (such as a read-only memory and/or a random access memory) and writes (stores) instructions and data to the memory. Storage devices suitable for tangibly embodying computer program instructions and data include, for example, all forms of non-volatile memory, such as semiconductor memory devices, including EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROMs. Any of the foregoing may be supplemented by, or incorporated in, specially-designed ASICs (application-specific integrated circuits) or FPGAs (Field-Programmable Gate Arrays). A computer can generally also receive (read) programs and data from, and write (store) programs and data to, a non-transitory computer-readable storage medium such as an internal disk (not shown) or a removable disk.

[0023] Any data disclosed herein may be implemented, for example, in one or more data structures tangibly stored on a non-transitory computer-readable medium. Embodiments of the invention may store such data in such data structure(s) and read such data from such data structure(s).

[0024] The present invention provides a method and system for facilitating learning and graded assessment.

[0025] In an embodiment of the present invention, the system and the method is disclosed for facilitating enhanced learning and graded assessment. The present disclosure focuses on accessing, in a real-time, how much a trainee or a learner has learnt and what are strong and weak points of the trainee. While providing trainings on programming languages, knowledge of programming concepts and ability to apply the knowledge has to be tested. In the present disclosure, the system provides an automated and human-independent assessment method for assessing trainee submissions (also referred hereinafter as “trainee codes” interchangeably) provided by the trainees. Due to the automation, the system is enabled to provide an unbiased assessment for the all the submissions in quick turn-around time. Also, the quality of learning is improved without compromising faculty-trainee relationship.

[0026] Further, the present disclosure provides a technology-neutral and specification-neutral assessment approach i.e., the subject area for the trainee submission as well context in which correctness rules may be applied is quite broad and applicable in various learning domains e.g., engineering, mathematics, programming languages and the like. This approach results in significant reduction of time in evaluating the submissions with sufficient ability to guarantee adherence to specifications or rules associated with the programming languages. Also, this allows the faculty or the trainer in saving time from monotonous scrutiny of all the submissions, and instead enables the faculty to dedicate more time productively to coach the trainees in need of development.

[0027] Referring to Figure 1, a network implementation 100 of a system 102 for providing enhanced learning and graded assessment is illustrated, in accordance with an embodiment of the present subject matter. In one embodiment, the system 102 facilitates enhanced learning and graded assessment for accessing how much a trainee has learnt and what are strong and weak points of the trainee in a real-time. Although the present disclosure is explained considering that the system 102 is implemented as a software application on a server, it may be understood that the system 102 may also be implemented as a variety of computing systems, such as a laptop computer, a desktop computer, a notebook, a workstation, a mainframe computer, a server, a network server, a tablet, a mobile phone, and the like. In one implementation, the system 102 may be implemented in a cloud-based environment. It will be understood that the system 102 may be accessed by multiple users through one or more user devices 104-1, 104-2…104-N, collectively referred to as user 104 hereinafter, or applications residing on the user devices 104. Examples of the user devices 104 may include, but are not limited to, a portable computer, a personal digital assistant, a handheld device, and a workstation. The user devices 104 are communicatively coupled to the system 102 through a network 106.

[0028] In one implementation, the network 106 may be a wireless network, a wired network or a combination thereof. The network 106 can be implemented as one of the different types of networks, such as intranet, local area network (LAN), wide area network (WAN), the internet, and the like. The network 106 may either be a dedicated network or a shared network. The shared network represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like, to communicate with one another. Further the network 106 may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, and the like.

[0029] Referring now to Figure 2, the system 102 is illustrated in accordance with an embodiment of the present subject matter. In one embodiment, the system 102 may include at least one processor 202, an input/output (I/O) interface 204, and a memory 206. The at least one processor 202 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the at least one processor 202 is configured to fetch and execute computer-readable instructions or modules stored in the memory 206.

[0030] The I/O interface 204 may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. The I/O interface 204 may allow the system 102 to interact with a user. Further, the I/O interface 204 may enable the system 102 to communicate with other computing devices, such as web servers and external data servers (not shown). The I/O interface 204 can facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular, or satellite. The I/O interface 204 may include one or more ports for connecting a number of devices to one another or to another server.

[0031] The memory 206 may include any computer-readable medium or computer program product known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, a compact disks (CDs), digital versatile disc or digital video disc (DVDs) and magnetic tapes. The memory 206 may include modules 208 and data 210. The data 210 may include rule database 212 and other data 214.

[0032] Referring now to figure 3 is a flow diagram for providing enhanced learning and graded assessment, in accordance with an embodiment of the present subject matter. The steps performed by the system 102, in accordance with an embodiment of the present disclosure, may be broadly classified into two categories. i.e., generating assessment contents and rules, and the evaluating the trainee submissions received from the trainees based on the rules.

[0033] In another embodiment of the present invention, a plurality of assessment content and a plurality of assessment rules configured by at least one faculty or a trainer is received by the system 102 in order to assess the knowledge of programming concepts of the at least one trainee submission. The plurality of assessment rules are configured to take measures concerning contextual information of the trainee submission. The contextual information of the trainee submission comprises of ascertaining the correctness of said trainee submission to take measures concerning a set of business specifications defined by said plurality of assessment rules. It brings the know-how of how to deal with contextual information i.e. does the trainee submission correctly deals with the plurality of assessment rules and the set of business specifications defined by said plurality of assessment rules (faculty code) mentioned in the question text of the assessment content. The plurality of assessment rules may be stored in the rule database 212 of the system 102.

[0034] In another embodiment of the present invention, at least one trainee submission is received for assessment from at least one trainee. The trainee submission may be, but not limited to, a trainee code related to a plurality of technical domains written in at least one programming language. The system 102 may compile the trainee submission and the plurality of assessment rules.

[0035] In another embodiment of the present invention, the system 102 may apply the plurality of assessment rule against each of the received trainee submission for ascertaining adherence of said trainee submission to the plurality of assessment rules. The system 102 may use a specification engine for checking whether the trainee submission meets the plurality of assessment rules including the business specifications. Ascertaining adherence of the trainee submission to the plurality of assessment rules comprises of assessing functional accuracy and runtime efficiency of each of the trainee submission; performing static analysis and run time analysis on each of the trainee submission; categorizing generated scores into a plurality of categories relevant to the subject matter specification; and checking correctness of the trainee submission for detecting structural flaws in the trainee submission, thus making it much harder to beat the system despite knowing test data. The specification engine itself comprises of code that acts on participant code to do analyses mentioned above. This leads to high-fidelity of results relative final answer and provides an insight into pedagogical aspects.

[0036] In another embodiment of the present invention, the static analysis of each of the trainee submission further comprises of analyzing variable names for ascertaining adherence of said trainee submission to the plurality of assessment rules, method signatures, data type and inheritance of each of the trainee submission for ascertaining adherence of said trainee submission to the set of business specifications defined by said plurality of assessment rules.

[0037] In another embodiment of the present invention, the run time analysis of each of the trainee submission further comprises of analyzing runtime exceptions thrown which is arising out of errors in the trainee submission or system preventing itself from malicious trainee submission, total runtime of trainee submission and adherence to specifications of each of the trainee submission.

[0038] In another embodiment of the present invention, the system 102 may generate score and grade each of the trainee submission according to the plurality of assessment rules and subsequently generating a report for each of the trainee submission based on the generated score and grade. The score and grade generation process for each of the trainee submission according to the plurality of assessment rules is technology neutral and subject matter specification neutral. Further, the system 102 may generate a report in a predefined format such as excel format for each of the trainee submissions corresponding to the trainee.

[0039] In another embodiment of the present invention, at least one strong learning attribute and at least one weak learning attribute is identified in real time for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning.

[0040] In another embodiment of the present invention, the trainee submission may be self-scored, when the system 102 for facilitating enhance learning and graded assessment is running online, by identifying in real time at least one strong learning attribute and at least one weak learning attribute for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning. Further, self-scoring add in immense learning value and significantly reduces time to learn.

[0041] In another embodiment of the present invention, the post deployment output of method for facilitating enhance learning and graded assessment comprises of high number of high scores of the trainee submission, low number of low scores of the trainee submission, and higher retention rates of the trainee submission post facilitated learning and graded assessment.

[0042] Although implementations for methods and system 102 for facilitating enhance learning and graded assessment have been described in language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as examples of implementations for facilitating the enhanced learning and the graded assessment.
,CLAIMS:1. A method for facilitating learning and graded assessment; said method comprising processor implemented steps of:

a. receiving a plurality of assessment content and a plurality of assessment rules configured by at least one faculty;
b. receiving at least one trainee submission for assessment from at least one trainee;
c. applying the plurality of assessment rules against each of the received trainee submission for ascertaining adherence of said trainee submission to the plurality of assessment rules;
d. generating score and grading for each of the trainee submission according to the plurality of assessment rules and subsequently generating a report for each of the trainee submission based on the generated score and grade; and
e. identifying in real time at least one strong learning attribute and at least one weak learning attribute for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning.

2. The method as claimed in claim 1, wherein the plurality of assessment content are trainee codes pertaining to a plurality of technical domains written in at least one programming language.

3. The method as claimed in claim 1, wherein the plurality of assessment rules are configured to take measures concerning contextual information of the trainee submission.

4. The method as claimed in claim 3, wherein the contextual information of the trainee submission comprises of ascertaining the correctness of said trainee submission to take measures concerning a set of business specifications defined by said plurality of assessment rules.

5. The method as claimed in claim 1, further comprises of storing the plurality of assessment rules in a rule database (212).
6. The method as claimed in claim 1, wherein ascertaining adherence of the trainee submission to the plurality of assessment rules comprises of assessing functional accuracy and runtime efficiency of each of the trainee submission; performing static analysis and run time analysis on each of the trainee submission; categorizing generated scores into a plurality of categories relevant to the subject matter specification; and checking correctness of the trainee submission for detecting structural flaws in the trainee submission.

7. The method as claimed in claim 6, wherein the static analysis of each of the trainee submission further comprises of analyzing variable names for ascertaining adherence of said trainee submission to the plurality of assessment rules, method signatures, data type and inheritance of each of the trainee submission for ascertaining adherence of said trainee submission to the set of business specifications defined by said plurality of assessment rules.

8. The method as claimed in claim 6, wherein the run time analysis of each of the trainee submission further comprises of analyzing runtime exceptions thrown which is arising out of errors in the trainee submission or system preventing itself from malicious trainee submission, total runtime of trainee submission and adherence to specifications of each of the trainee submission.

9. The method as claimed in claim 1, wherein the report for each of the trainee submission is generated in a predefined format.

10. The method as claimed in claim 1, wherein the score and grade generation process for each of the trainee submission according to the plurality of assessment rules is technology neutral and subject matter specification neutral.

11. The method as claimed in claim 1, further comprises of self-scoring of the trainee submission by identifying in real time at least one strong learning attribute and at least one weak learning attribute for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning.

12. The method as claimed in claim 1, further comprises of high number of high scores of the trainee submission, low number of low scores of the trainee submission, and higher retention rates of the trainee submission post facilitated learning and graded assessment.

13. A system (102) for facilitating learning and graded assessment; said system (102) comprising:

a. a processor (202);
b. an input/ output interface (204), electronically coupled with the processor (202);
c. a rule database (212) accessible by the processor (202);
d. a memory (206) embodying computer program code therein, coupled to the processor (102), wherein said computer program code comprising instructions executable by said processor (102) and configured for executing steps of:

i. receiving a plurality of assessment content and a plurality of assessment rules configured by at least one faculty;
ii. receiving at least one trainee submission for assessment from at least one trainee;
iii. applying the plurality of assessment rules against each of the received trainee submission for ascertaining adherence of said trainee submission to the plurality of assessment rules;
iv. generating score and grading for each of the trainee submission according to the plurality of assessment rules and subsequently generating a report for each of the trainee submission based on the generated score and grade; and
v. identifying in real time at least one strong learning attribute and at least one weak learning attribute for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning.

14. The system as claimed in claim 13, wherein the plurality of assessment content are trainee codes pertaining to a plurality of technical domains written in at least one programming language.

15. The system as claimed in claim 13, wherein the plurality of assessment rules are configured to take measures concerning contextual information of the trainee submission.

16. The system as claimed in claim 13, wherein the contextual information of the trainee submission comprises of ascertaining the correctness of said trainee submission to take measures concerning a set of business specifications defined by said plurality of assessment rules.

17. The system as claimed in claim 13, wherein the rule database (212) is adapted for storing the plurality of assessment rules.

18. The system as claimed in claim 13, wherein ascertaining adherence of the trainee submission to the plurality of assessment rules comprises of assessing functional accuracy and runtime efficiency of each of the trainee submission; performing static analysis and run time analysis on each of the trainee submission; categorizing generated scores into a plurality of categories relevant to the subject matter specification; and checking correctness of the trainee submission for detecting structural flaws in the trainee submission.

19. The system as claimed in claim 18, wherein the static analysis of each of the trainee submission further comprises of analyzing variable names for ascertaining adherence of said trainee submission to the plurality of assessment rules, method signatures, data type and inheritance of each of the trainee submission for ascertaining adherence of said trainee submission to the set of business specifications defined by said plurality of assessment rules.

20. The system as claimed in claim 18, wherein the run time analysis of each of the trainee submission further comprises of analyzing runtime exceptions thrown which is arising out of errors in the trainee submission or system preventing itself from malicious trainee submission, total runtime of trainee submission and adherence to specifications of each of the trainee submission.

21. The system as claimed in claim 13, wherein the report for each of the trainee submission is generated in a predefined format.

22. The system as claimed in claim 13, wherein the score and grade generation process for each of the trainee submission according to the plurality of assessment rules is technology neutral and subject matter specification neutral.

23. The system as claimed in claim 13, further comprises of self-scoring of the trainee submission by identifying in real time at least one strong learning attribute and at least one weak learning attribute for each of the trainee submission based on the generated score and grading for each of the trainee submission according to the plurality of assessment rules for facilitating enhanced learning.

24. The system as claimed in claim 13, further comprises of high number of high scores of the trainee submission, low number of low scores of the trainee submission, and higher retention rates of the trainee submission post facilitated learning and graded assessment.