Reality-driven education or learning by doing based on the real life of an education institutionLaszlo Pitlik, Laszlo Pitlik (jun), Matyas Pitlik, Marcell Pitlik, MY-X team

Abstract: The so-called teaching can use a lot of case studies – mostly already closed ones. On the other hand, it would always be necessary to have real problems too in order to be able to demonstrate processes running in a parallel way. The reality-driven education has the advantage too, to solve problems (at least partially) during the education as such – with efforts having no real effects else at all. The paper shows both a general frame for the reality-driven activities, and real experiences about the preparing steps of an innovation action.

Keywords: customizing, life-tailored education, added-value-oriented education

IntroductionThis paper is the newest part of the series about experiences if the QuILT-based education processes. Previous articles can be downloaded here:

https://miau.my-x.hu/miau/quilt/Definitions_of_knowledge.docx + annexes like:o https://miau.my-x.hu/miau/quilt/demo_questions_to_important_messages.docx o https://miau.my-x.hu/mediawiki/index.php/QuILT-IK045-Diary o https://miau.my-x.hu/mediawiki/index.php/Vita:QuILT-IK045-Diary o https://miau.my-x.hu/mediawiki/index.php/QuILT-IK059-Diary o https://miau.my-x.hu/mediawiki/index.php/Vita:QuILT-IK059-Diary

https://miau.my-x.hu/miau/quilt/reality_driven_education.docx + annexes like:o https://miau.my-x.hu/miau/quilt/chained-translations-legal-slang.docx o https://miau.my-x.hu/miau/quilt/demo_chained_translations.docx o https://miau.my-x.hu/miau/quilt/demos_chained_translations.docx o https://miau.my-x.hu/miau/quilt/Knowledge_in_diffrent_languages..docx o https://miau.my-x.hu/mediawiki/index.php/QuILT-IK057-Diary o https://miau.my-x.hu/mediawiki/index.php/Vita:QuILT-IK057-Diary

to be continued:o ( https://miau.my-x.hu/miau/quilt/Exercises_for_critical_thinking_and_doing.docx ) o (https://miau.my-x.hu/miau/quilt/GDP_final_en.docx)

If the title of a course is “Quality, Innovation Policies and Tools in MLE” then it should be seen as quasi trivial

to speak about quality based on the objective quality aspects of the own education talking about quality/education –

o incl. analyses of accreditation materials for starting of new courses o where it is also to prove whether the authority is capable of ensuring a robust

evaluation leading to the result: each permitted course seems to have the same quality but on other ways or

to speak about innovation being involved into at least one real innovation process (c.f. global legal hackathon), or

to speak about innovation policy based on a common problem-solving process where the rational level of public expenditure for innovation tasks should be derived for arbitrary countries compared to the GDP of the countries, …

Argumentations:

each education activity (course) must be able to declare an evaluation rule set e.g. for Students ensuring objectivity (it means measurable variables and an antidiscriminative aggregation method)

o instead of Students arbitrary other objects of the education processes can also be analysed like tasks, documents, scripts, video-streams, animations, figures, pictures, teachers, courses, rooms, equipment, institutions incl. universities and/or authorities, countries, settlements for living there as Student, etc.

o especially the quality of rule sets can be a phenomenon being worth evaluating together with Students, …

to know about governmental accreditation process concerning education activities/institutions is necessary because the education as such is the most trivial and real constellation being available for hermeneutical experiments at all

the education based on the magic of words speak about phenomenon – always in an abstract level – contrary to the KNUTH-oriented approaches where knowledge (about quality) is what can be transformed into source codes – it means what can be working out as a real evaluation rule set with the expectation being objective and anti-discriminative - compared to being arbitrary subjective like nowadays in general

parallel, innovation might not be seen as a spell (c.f. magic of words) – innovation should also be measurable, real to observe in each detail – what can just be realized through being involved into real innovation processes (as far as possible running in real time during the education itself)

innovation policies have a lot of parameters: one of them is the ratio (compared to GDP) for public expenditure for innovation task of country-level

o just to speak about influence factors determining this ratio is the magic of words in it real nature

o but to be able to create models (c.f. KNUTH’s principle) is an other (more sophisticated level) of knowledge where

speaking about something without any chance for objective evaluations – can also be the source of demagogy (c.f. lack of evidence proving for declarations)

the capability to check the validity of declarations is the expected level of operativity in case of using knowledge in the real life

Task: evaluation of innovation ideasIdentifying expectationsCompetition: https://globallegalhackathon.com/

Task: text analysis

Objective: identifying elements of the potential evaluation rule set

Method: knowledge engineering (filtering keywords based on intuitive interpretation)

Example:

Source: “Bringing the legal industry together with tech and innovation, world-wide, with one purpose: Rapid development of solutions for improving the legal industry world-wide.”

Instinctive hermeneutical layers:

purpose: the competition should have aims, expectations, objectives rapid: the development should be rapid – it means

o time is limitedo working methodology is efficiento yet: holistic solution should be given/approximated

improving: it should be proven and in ideal case also measurable o what is improved at all?o how many is the difference between the starting (well-known) positions and the

achieved/planned positions? legal industry: it is a kind of K.O.-criteria

o what is a legal-focus?o is a task legal enough?

world-wide: the solution might not be limited in spaceo problem-focus should be e.g.

content free and/or language-free culture-free, …

Checking of the idea based on a short descriptionShort description:

Project-acronym: gLAWball or later G-LAW-GLE (c.f. Google) Project’s short description: Developing a content-free and language-free smart filtering

mechanism supporting distribution tasks in case of customer’s questions being flexible extendable/specifiable for similar (legal or other) processes e.g. of authorities/institutions/legal enterprises using already given artificial intelligence engines in long term not just partially

Checking based on the previous chapter:

world-wide: OK (content-free, language-free, flexible) legal: OK (arbitrary scalable focus, targeted customers: e.g. authorities) improving: OK (AI-based solutions always ensure an increasing of efficiency based on the

KNUTH’s principle – knowledge is what can be transformed into source codes) rapid: OK (solution based on already existing AI-engines – automation steps will be partially

offered)

Detailed structure of the ideaPhases/steps:

Components of the basic situation:o there is always a huge stream on not professional formulated questions sent e.g. to

authorities/experts for statementso there are FAQ-services answering for types of questionso the classification of questions is made now by human expertso the classification processes are rel. expensive and rel. slow

Layers needing improvements:o the classification of questions sent from customers should be automated at least

partially without needing content-depending knowledge (transfers)o cost-factors and/or time-factors should be shifted towards competitive ratios

Filters being supportable through cyborgso 1. level: filtering not-interpretable questions

definition: a question should be classified as not-interpretable if a chained translation process highlights suspicions (see demo)

output: an estimated index of interpretability (0-100%) for each question methods:

online translation services can be involved (e.g. Google-Translate: https://translate.google.com/ (API vs C-URL-call) or Google spreadsheets with a translation function: https://miau.my-x.hu/miau2009/index_tki.php3?_filterText0=*spreadsheet

index-creation can be executed in an naïve (expert-driven) way (like scores in the school) or based on AI (COCO – component-based online comparison for objectivity) for anti-discriminative online analyses in an automated way (c.f. MY-X-FREE: https://miau.my-x.hu/myx-free/coco/) being available as C-URL-service

o objects: questionso attributes: types of translation-anomalies (the less the

better)o values: amounts of anomalies (pieces) belonging to a

category cyborg-effects (human-machine-interactions):

qualitative chained translations can be managed in an automated way

interpretations of the first and final text versions can be generatedo at first already by less qualified HRo in long term: through AI-engines (e.g. COCO-ONLINE) based

on similarity aspects of text variants demo: https://miau.my-x.hu/miau/quilt/reality_driven_education.docx

(chained translation exercises in annex) hermeneutic sub-layer:

questions with low risk potential will be sent to level Nr.2 for customers of questions with high risk potential, an appropriate

expert/service/course/FAQ will be offered (c.f. law for all) specific innovation

the chained translation is capable of generating a kind of genetic code of the analyzed text

a single (rel. long) text (e.g. a conversation) can be interpreted based on this genetic code concerning its inner development (c.f. idea of Plato: the ideal text becomes more and more understandable – it means: the chained translations deliver less and less signs about instability of the sentences

generation of production function is also possible based on a set of texts (e.g bids, tenders) with conclusion like income-, revenue-, cost-

level, duration, etc. – where the estimations of the models classify new cases according to the conclusion variables

o 2. level: filtering questions with massive lack of legal key words definition: a question should be classified as non-precise enough if it does

not have appropriate legal keywords (enough) output: an estimated index of exactness (0-100%) for each question being

filtered in the 1. level with a high interpretability index methods:

it is necessary to prepare a set of legal keywords by human experts (later: it is also possible to search for additional keywords based on a huge corpus of legal texts and text mining techniques)

index-creation can be executed in an naïve (expert-driven) way (like scores in the school) or based on AI (COCO – component-based online comparison for objectivity) for anti-discriminative online analyses in an automated way (c.f. MY-X-FREE: https://miau.my-x.hu/myx-free/coco/) being available as C-URL-service

o objects: questionso attributes: types of keyword-anomalies (like lack of

abbreviations, lack of specific expressions, etc).o values: amounts of anomalies (pieces) belonging to a

category cyborg-effects:

at first: the definitions for categories of keyword-anomalies should come from human experts and the classification of cases should also be made manual-driven

later: the classification task can be automated step by step demo: http://miau.gau.hu/miau/140/la140.doc /

https://miau.my-x.hu/miau2009/index.php3?x=e0&string=letra hermeneutic sub-layers:

questions with low risk potential will be sent to level Nr.3 for customers of questions with high risk potential, an appropriate

expert/service/course/FAQ will be offered (c.f. law for all)o 3. level: filtering questions with massive lack of consistence between keywords

definition: a question should be classified as non-consistent enough if it does have not-appropriate-enough combinations of legal keywords

output: an estimated index of consistency (0-100%) for each question being filtered in the 2. level with a high exactness index

methods: it is necessary to prepare a set of preferred combination of legal

keywords by human experts (later: it is also possible to search for additional keyword-connections based on a huge corpus of legal texts and text mining techniques)

index-creation can be executed in an naïve (expert-driven) way (like scores in the school) or based on AI (COCO – component-based online comparison for objectivity) for anti-discriminative online analyses in an automated way (c.f. MY-X-FREE: https://miau.my-x.hu/myx-free/coco/) being available as C-URL-service

o objects: questions

o attributes: types of keyword-anomalies (like lack of abbreviations, lack of specific expressions, etc).

o values: amounts of anomalies (pieces) belonging to a category

cyborg-effects: expected/preferred combinations of legal keywords should be

defined in advance by human experts the calculation layers for exploring of similarities can always be run

in an automated way demo: the logic of the level Nr. 2 and level Nr. 3 can be seen as similar

enough not needing new demonstrations in order to prove the robustness of this level

hermeneutic sub-layers: questions with low risk potential will be sent to level Nr.4 for customers of questions with high risk potential, an appropriate

expert/service/course/FAQ will be offered (c.f. law for all)o 4. level: filtering questions with similar topics (grouping questions)

definition: a question should be classified as typical enough for the predefined patterns if it does have high level similarities

output: an estimated index of similarity (0-100%) for each question being filtered in the 3. level with a high consistency index

methods: it is necessary to prepare a set of preferred combination of keywords

being characteristic for a type of a problem by human experts (later: it is also possible to search for additional keyword-connections based on a huge corpus of legal texts and text mining techniques)

index-creation can be executed in an naïve (expert-driven) way (like scores in the school) or based on AI (COCO – component-based online comparison for objectivity) for anti-discriminative online analyses in an automated way (c.f. MY-X-FREE: https://miau.my-x.hu/myx-free/coco/) being available as C-URL-service

o objects: questionso attributes: types of similarity-anomalieso values: amounts of anomalies (pieces) belonging to a

category cyborg-effects:

expected/preferred combinations of typical keywords should be defined in advance by human experts

the calculation layers for exploring of similarities can always be run in an automated way

demo: http://miau.my-x.hu/miau/239/konzisztencia_alapu_hibridizacio_v1.docx

hermeneutic sub-layers: questions (still without any answers) will be grouped questions without similar objects will have an own group with only

one element belonging to this groupo 5. level: filtering questions being already answered for already grouped questions

in general: the steps of level Nr. 4. should be repeated for the question set having already answers

hermeneutic sub-layers: if groups of questions without answers will suddenly have just one

new element where already an answer are available then the questions without answers can be answered through the explored/stored answer and the group-elements can be published as a common element of a FAQ-service

if groups of questions without answers will suddenly have more new elements where already more answers are available then

o at first: the answers should be interpreted by human experts in order to explore inconsistencies

o if there are no inconsistencies then the questions without answers can be answered through the explored/stored answers and the group-elements can be published as a common element of a FAQ-service

o but in case of inconsistencies, each element of the group should be re-analyzed by human experts before publishing any answers for any questions

o 6. level: evaluation FAQ-items having a high customer’s satisfaction level definition: in case of already published answers, there can be existing a lot of

responses having different characteristics and/or values (like general likes or additional remarks with different lengths, etc.) – all these inputs should and can be aggregated to a satisfaction-index

output: satisfaction-index-values for each FAQ-element (questions + answers)

methods: at first, responses of customers should be analyzed a lot of types of responses should be identified incl. calculation

schemes for attribute’s values based on a lot of attributes, it is to prove whether each evaluated

FAQ-element can be seen as an object with the same satisfaction level

cyborg-effects: attributes will be defined by human experts aggregation processes can be executed in an automated way

demo: each demonstration URL before can be interpreted as a kind of appropriate item here and now because all the automated evaluations can work with COCO-engines

hermeneutic sub-layers: either each FAQ-element can have the same satisfaction level or not

o the FAQ-elements with the lowest satisfaction level should be interpreted at once by human experts

o the further FAQ-elements need no further checks…o 7. level: in case of questions being still not answered

identifying experts being able to derive answers

definition: experts should be classified as appropriate enough if they have the best similarity index values in case of a given question (without answers – in case of each filtered level)

output: expert-question pairs where one expert can have more questions and vice-versa

methods:o it is necessary to have a profile about experts based on the

same keywords as in case of each filtering stepo if experts can be described like questions then experts can

become elements of the groups of questions before in case of grouping

experts delivered already answers could have been identified as an attribute of an answered question

experts without answers will be handled like questions before in case of grouping

cyborg-effects:o at first: the description of experts should be executed by

human expertso each further step can be executed in an automated way

demo: see cases of grouping questions hermeneutic sub-layers:

o experts will be part of groups of questions either through previous answers or through being interpreted like questions

o experts must not have any question and vice-versao inconsistent is the system (the descriptions in the expert’s

profiles), if an expert with one/more answers could not be identified just based on its profile-keywords

formulating claims to authorities (in case of under-regulated phenomena) in general: if experts can not create appropriate answers then it is

necessary to identify the core problems in the legal texts if the core problems could be identified then it is necessary to

formulate claims for the authorities this kind of activity is - at first – an entirely human-driven action (but

see also the following possibilities based on expert systems) creating expert systems about question being well-regulated as online

service for customers in general: questions, group of similar questions about a not all too

much complex phenomenon (where it is possible to interpret this phenomenon as a combinatorial space), expert systems can be derived

o in a manual (expert-driven) way and/oro in an inductive way (maybe just as a kind of logical test)

demo: o https://miau.my-x.hu/myx-free/ego/ (online tool for creating

expert system in a manual way)

o demo: https://miau.my-x.hu/miau/245/real_exs_check.xlsx (steps for checking logical consistence in case of already closed expert systems)

hermeneutic sub-layers:o expert systems are the most user-friendly FAQso supporting

interpretations before new changes additional layers, etc.

creating expert systems about question being under-regulated as a kind draft solution for experts of the authorities

in general: in case of under-regulated legal phenomena, experts can have ideas how a regulation could be made in the most consistent way – therefore it is possible this version(s) to demonstrate in form of expert systems

hermeneutic sub-layers:o based on the KNUTH’s principle, a legal text is qualitative

enough just in form of an expert systemo therefore, the common future needs more and more expert

systems (c.f. robot-judges)…

Screen-shots about the drafts for the different levels(at first see demonstration URLs and their background files)

Google Spreadsheets – with GoogleTranslate()With absolute parameters for languages

With relative parameters for languages

Text mining possibilities

Statistics being delivered through text mining calculations can be used for similarity analyses…

Business planIn case of a valid (tested, functionable) “idea”, the business aspects can be proved for the first (potential) customer. If a project can ensure revenue already in the first level (c.f. genetic pattern of one single text based on chained translation effects for analysing inner coherence of the single sample) through efficient rapid working methods, then it is not relevant to plan in detail. The efficient and rapid working method is able to demonstrate for each partner that the HR-allocation and its

cost-level can be reduced at once. The saved cost makes possible to have real expectation about royalties.

Marketing planThe relevant costumers are private persons and/or enterprises where the thinking methodology is open for relevant innovation like genetic code of texts and their analyses based on the hidden similarities. Therefore: the service of the G-LAW-GLE team should just be publishes in each not-expensive way to reach appropriate customers who must work together with the G-LAW-GLE team in order to understand in the needed deepness what a customer may expect based on a small set of documents and what is just realistic if more data are available. Based on small data sets, it is possible to search for ideals (see https://en.wikipedia.org/wiki/Platonic_idealism). Based on huge data sets, it is also possible to create estimations (deriving so-called production functions) for potential income from the given customer, for the length of the needed co-operation, etc.

Risk analysisThe real risk in the logic of the G-LAW-GLE service is, how can be reduced the HR-demand for a given customer – assumed there is a lot of parallel customers waiting for co-operation and the G-LAW-GLE team has a limited HR-capacity?

ConclusionsThe above-mentioned phenomena can be interpreted from the point of view of the

innovators customers innovation agencies being responsible for generation of ideas investors etc. and the politicians too: how this kind of activities should be regulated in order to ensure an

optimal functionality?

Potential anomalies in the evaluation processes of innovation events/contests:

to be conform on the surface to the judging rubrics > to have real competences to create a useless simulation (draft, mock-up) of the planned functionality > valid references to estimate invalid costs, incomes > to have real information value added/increased

efficiency to have a relative innovation (specific problem, not scalable solution, geo-dependent,

language/culture-dependent) > to have a real research potential (context-free, language-free)

to speak about innovation > to have real innovation to speak about AI > to have AI in the core business to speak about hoped big-data > to define real data assets and appropriate methodologies to speak about big services (like IBM Watson) > to have own solutions and real development

potential to have appropriate connections > to have professional references to be seemingly conscious > to have real experiences to speak about robots > to be capable of substituting real jobs through robots to speak about evaluation variables > to be transparent and objective to speak about mentoring > to be capable of understanding real innovations to accepted invalid estimations > to be honest about facts and quality aspects of estimations

AnnexPublic GLH-impulsesFurther text elements about the competition “GLH” in order to collect/identity variables for interpreting plans of potential innovators:

https://attendeehelp.globallegalhackathon.com/ https://hackathon.wolterskluwer.hu/hackathon/tippek/ https://attendeehelp.globallegalhackathon.com/article/95-rules-and-guidlines

Source: https://hackathon.wolterskluwer.hu/wp-content/uploads/sites/14/2018/02/hackathon.wolterskluwer.hu-zsurizes-folyamata-glh-judging-rubric-013018.pdf

Further task for the futureReality-driven tasks can always be identified based on daily analyses of the running communications:

Task: decision support scenes based on accreditation documentsTask: Useful reportsTask: Anti-discriminative test of institutions/course-plansTask: Estimation of expenditure level for innovationhttp://miau.gau.hu/miau/178/kfi/innoswotion_1.doc

http://miau.gau.hu/miau/164/KFI2012IV.doc

https://miau.my-x.hu/miau/173/gdp/GDP-elemzes_final.doc

Task: Analysis of the European Song Contest – Whether the geopolitical and musical effects can be separated from each other?https://eurovision.tv/events

https://we.tl/XUDj5T4jUM

Task: Analysis of the potential decisions of average people concerning MIT’s moral-machine?http://moralmachine.mit.edu/