What is a Knowledge Credibility Score™

A FICO score for Knowledge







  

Summary

A Knowledge Credibility Score™ or KnoC™ Score, provides a naturally biased means to attribute and show measurement of qualitative effort within a domain of knowledge. One of the hardest challenges employers have is determining who to hire, and there are no resources that provide a consistent and reliable measurement. A KnoC Score is derived from time spent creating, editing, and studying knowledge that has value. When combined with a scoring system that gives credit to different types of recall strategies, will provide a concrete means to show an individual's effort within a domain of knowledge. In this way, there is a reliable and transparent perspective of how they will perform in the workplace.






  

Problem: Employers do not have a consistent and reliable method for understanding a job applicants potential.

Point 1: Employers and managers have stated in interviews that one of their largest problems in hiring is finding employees that: one, have good work ethics, and two, are competent and knowledgeable. With the decline in the current generation's birth rates, universities have struggled with keeping their enrollment numbers up and many two year institutions have shut their doors. Complaints from employers are rising that they must increase the age of their candidates and require prior work experience in order to vet prior candidates. Companies that do not employ these strategies or have the structure and resources to vet and train new hires, suffer from inefficiencies . In several interviews with hiring managers, all were in agreement that there needs to be a standardized way to gain insight into an individuals capabilities and work ethics.

Point 2: Students who have higher ethical work standards may not score high, may fail more classes, and not look as good in interviews. Additionally, some students have social anxiety and place higher value in knowledge and work ethics than appearances. The students who maximize

their studies and yet score poorly, or who may place a larger priority in projects related to their education may not look good on paper. They may fail classes and not be given the credit for the knowledge gained. In some cases, the students are redirected to another career path or drop out completely. In reality, these students have gained skills that may be superior to their peers. However, because of the evaluation system they do not gain credit. When these students leave the institution, there is no record that bears a credible mark of what they have learned. Employers that would benefit from the students in this category have no method to reach out to them, and institutions may be following the more traditional path to help their graduates. Thus, these students find it even harder than their peers to find employment.

Point 3: In the classroom and at the university grades play a major role. From the outside and to industry grades are considered private. They are also hard to measure against since there are many inconsistencies between classrooms and institutions. Most employers do not ask what a candidate's grades were while they attended the university, and many employers are hiring employees that demonstrate the right knowledge set as opposed relying solely on a candidates' diploma. What matters most to an employer is how well a candidate can do the job. A significant part of that is how well will they persevere when the job gets tough.






 

Solution: A reliable measurement for use by industry to show an individual's potential.

Hiring managers struggle with hiring. Finding good hires and avoiding bad hires will significantly help or hurt a business. Who you hire can be the difference between a highly successful company, and a failed company. Understanding and gauging individuals based on grades and diplomas has become less reliable in comparison with historical patterns. Understanding an individual's competency and work ethics can be a more reliable indicator of their potential to contribute towards the companies goals.

Value provides a distributed consensus of the credibility of created and edited materials.

There are many Scholarly articles on Credibility Scores and Credibility Evaluation Systems. One such article Credibility score based multi-criteria recommender system discusses criteria ratings created by collaborative filtering (CF) systems and multi-criteria recommender systems for use in online video (YouTube), movies (Netflix), books(Amazon) and social networks(Facebook). Filtering is based on information that is collected from similar users. One criterion is the expenditure of a scarce resource on a particular item. That item is matched with other similar items that have similar attributes

including the expense of a scarce resource by similar users. In this case, "Credibility can be considered as a user's trust among various users" -Gupta (2020). In our case the user may be a fellow student studying a similar course in either the same class or another class at a later date. It may also be a hiring manager. The validity of the information is collaborated among several students based on their willingness to give up a scarce resource, e.g. money. To the employer, value of information provides credibility that the information an individual has studied or created is valuable. It is reasonable to believe peer and non-peer students would not give up a scarce resource for invaluable information. Thus, the studied information is likely related to its subject and needed for the related area of studies. It is important to note that in this case the value of information also accounts for students who request a refund of their scarce resource if the information is not valid. When a student creates or participates in the creation of information and when other peer and non-peer students expend a resource for that information, then this is concrete evidence that the student has created or edited valuable and relevant information.






 

Study metrics verify the amount of time spent learning and interacting within a domain of knowledge.

A well-known author Malcom Gladwell argues in his book "Outliers" that highly successful people are not born with a special skill, rather they have spent a high number of hours specializing in that skill. His book has been highly criticized in regards its simplification of how 'Outliers' achieve success, however both the critics and Gladwell agree on a "Magic number" of 10,000 hours. The argument of 10,000 hours is a rough number and there must be a relation of the amount of time this occurs in, however this relation is highly accepted in the business world. The book "Outliers" is used in MBA programs and advanced business degrees. As student's study, they are accumulating hours of learning and interacting in domains of knowledge. Thus, time spent studying quality content within a domain of knowledge can be used as a partial indicator of the individual's competence in that domain.

A system that measures the time spent in a domain of knowledge should also provide a qualitative learning measurement.

Building memory, or memorialization is a key factor in learning, although it is not the only factor, learning will not happen without it. There are several study strategies that are less effective than others. Much time and research has gone into understanding learning and memorialization. Although how the mechanics of learning actually occurs is still not fully understood, there is enough evidence to indicate what are effective techniques. In several papers and in particular the article Investigating the testing effect: Retrieval as a characteristic of effective study strategies-Bae (2019) discussing the findings of a study including 338 undergraduates using several methods of study compared against Free Recall and also coupled with Free Recall.

The findings were that there was a "significant interaction between learning condition (repeated vs. single retrieval practice) and type of retrieval-based strategy. Free recall and practice quizzing were the most effective types of retrieval practice, and coupling test generation and practice quizzing with free recall led to significant benefits in performance." Significant improvements were seen when students wrote quiz questions, testing themselves using free recall, and repeated the test at least once some period of time later. The study used 7 days. The most common study strategy used by students is to take notes in class, pull them out before a quiz, and then reread the notes during a "cram" session just prior to a major exam. The paper identifies that the type of recall that is built with the common strategy relies on an association or hint. When the student is posed with a question that provides no hints, the student doesn't recall the answer. Students who rehearse using only multiple choice and true or false questions also do not create as strong of bindings, although from our metrics we see that when asked differently from the expected information can be effective. However, simply scrolling through a quiz seeing the same multiple choice and T-F questions repeatedly loses its effectiveness. Free recall questions creates strong memory bindings. A qualitative measurement that prefers stronger recall can be accomplished using a variable scoring system that prefers free-recall.

Based on the above. Value can indicate that the information that is studied provides verification that the information is relevant and necessary to a domain. Time spent learning and interacting with that knowledge is a partial indicator of competency. Further, a scoring system that indicates an individual's understanding and memorization may also measure the use of study strategies that are more effective. We can combine this into an easily accessible and visual display that may be included in a reference such as a C.V. or resume. The display shows the value that an individual has earned within a domain, it provides a display of time spent in a domain that is divided into creation of knowledge, and retrieval. And a third area is provided that displays a scoring that prefers free-recall.






 

Non-Solutions: The problem with Blockchain and Badging for Knowledge Credibility

There is a common misunderstanding about credentialing for education. Blockchain does not indicate an individual's competence. Blockchain is an immutable ledger of transactions. It's technologies help to establish that information has not changed but does not establish the quality nor validity of the information itself. It does not establish that information was learned, that information was relevant, nor that information was accurate. It does not guarantee that an institution's policies or that a proctor's methods made individual A competent within a knowledge domain. It does not guarantee that students of institution A or proctor A are more or less competent to the students of institution B or proctor B.

Blockchain does not establish a value to the information, nor does it provide transparency in student evaluations. When hiring candidates, blockchain would not provide any meaning for this problem. In the same way, badging that does not use a concrete, transparent, and equal evaluation system, bears exactly the problems that the KnoC Score is solving.






 


Sources

  1. Gupta S., Kant V., (2020) Credibility score based multi-criteria recommend system https://doi.org/
  2. Bae C.L., Therriault D.J., Redifer J.L., (2019) Investigating the testing effect: Retrieval as a characteristic of effective study strategies. https://www.sciencedirect.com
 


Change history

  1. Publish Date: February 10, 2023
  2. Edit Date: February 15, 2023, Summary added. "KnoC™ Score" added
  3. Edit Date: April 5, 2023, Added "Distributed Consensus" to "Value" for concise clarity.
  4. Edit Date: May 20, 2023, Added clarification on Blockchain and Badging. Other minor edits