Artificial Intelligence Approach for Covid Period StudyPal

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072

Artificial Intelligence Approach for Covid Period StudyPal

Madhumita Venkataraman1 , Hemashrree J2 , Sudharsan V3

1, 2, 3First Department of Information Science and Engineering, Kumaraguru College of Technology Coimbatore, Tamil Nadu, India***

Abstract - With the dawn of a new era where the world is dependent on digital platforms to carry out the most basic day to day tasks. Many industries have been transformed like never before. One such industry that has been constantly putting the efforts to make technology more accessible to everyone is the educational industry. There are close to 1.29 billion students around the world who faced a very confusing and tough situation during the COVID period. While systems were trying to make education more effective and reliable, students were having a hard time adapting to this new normal. They were faced by various challenges like lack of a proper network, lack of the right electronic devices, not being able to communicate effectively and many more. We would like to propose a bot named Study Pal that will accelerate the learning experience of students. Students can learn from their prescribed curriculum by invoking the bot with the grade they belong to followed by the subject name and chapter. The bot's success lies in completely educating a student without the interference of any external factor. The bot will be able to keep track of the students’ progress and works on techniques like active recall, mind - mapping, etc. Another goal we envision to achieve is to make this ML model by the implementation of federated learning. A central cloud would exist and the ML model will be downloadable at various users’ devices. There the ML model will be able to acquire the training data required for the model to learn, sending only the updated ML model to the cloud. The ML model will be democratic and will use a combination of 3 or more algorithms to get a high accuracy. A federated learning model will aid in maintaining data privacy and will also resolve the issues of bad networks or lack of a Wi-Fi network all together. The bot will provide one-on-one sessions essentially providing individual attention resulting in effective communication and understanding of concepts.

Key Words: Bot, Federated Learning, Democratic Model, Machine Learning, Deep Learning, K means clustering algorithm,Python.

1. INTRODUCTION

Artificialintelligencehasrecentlyadvancedtothepurpose thatitwillcurrentlybeemployedina rangeoffields.One suchspaceofapplicationisteachingwiththeassistanceof technologicallyadvancedbots;however,thebotsareaposh and superimposed technical being that require to be additionalresearchedtomakeandcomprehend.becauseof the interclass commonalities and uneven intraclass characteristics, bots deployed for instructional help cause

majorhurdles.becauseoftheBrobdingnagiandiversity of thearea,selectingtheproperknowledgegroupingandhave illustration technique is very critical. These bots were created to produce sensible education system and super artificialintelligence;however,theup-to-dateconditionwas created for little datasets and restricted classrooms. one amongstthekeyproblemswithexistingmachinelearning techniquesisthatthematteristhree-dimensionalinnature andcontainsgoodishhyperdimensionalfeatures.important analysis has been done on the development and study of predictorsformultidimensionalcharacteristicsthatrequire heaps of process resources to optimize. several machine learning techniques, appreciate Support Vector Machine (SVM), K-Nearest Neighbor (KNN), call Trees, Artificial NeuralNetworks(ANN),andConvolutionalNeuralNetworks (CNN), are used with many various feature description strategies for instructional bots in a variety of real-world applicationsinrecentyears.

2. LITERATURE REVIEW

[1] A large variety of industries use applications enabled with intelligent bots to bolster users. In most cases these systems are deployed with bots that proactively monitors user requests giving solutions inside short periods accurately.Thispaperprimarilydealswiththecreationofa Chatbotmodelwithintheinstructionalworld:asystemwas createdtohelpuniversitystudentsinsurecourses.themost goalwastostyleanefficientarchitecture,aframeworkfor establishingcommunication,andapplicablerepliesforthe pupils.

[2]Thepurposeofthisresearchistodevelopanautomation process for the schooling system that can answer a user's questioninplaceofahuman.It'scapableofansweringany question provided by the user. Current bots such as Facebook'schatbot,WeChat,Hike'sNatasha,Operator,and otherswereusinglocaldatabasestorespond.However,we arefocusingonboththelocalandwebdatabases,aswellas making the system scalable, user-friendly, and highly interactive.Machinelearning,naturallanguageprocessing (NLP),patternrecognition,anddataprocessingalgorithms are used in this research to increase the system's performance.

[3]Althoughtherehasbeenasurgeindesireforsocialbots, andhuman–chatbotinteractions(HCRs)havebecomemore popular, little is understood about how HCRs emerge and how they may impact users' broader social environment.

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TheauthorsofthispaperusedSocialPenetrationTheoryto interview18peoplewhohaddevelopedarelationshipwith asocialbotcalledReplicainordertotrulycomprehendthe HCR development process. Because of the consumers' interest, they realized that HCRs have such a deceptive element at first. The evolving HCRs are distinguished by extensive affective exploration and involvement as users' faithandengagementinconsciousnessrises.

[4]Inthebankingindustry,chatbotsaregainingtractionasa vitalinstrumentfordigitalization.However,themajorityof the studies have focused at chatbots from the customer's perspectiveand developers, withrelativelyfewlooking at bots’productsfromtheemployer’spointofview,whoplaya vital role in the deployment of chatbots in enterprises. In order to fully understand the advent of financial chatbots andforecasttheirprospectinSouthKorea,wherefinancial institutionshavemademassiveuseofchatbots,thisstudy will look into managers' perceptions of them. They conducted nearly fully interviews with supervisors of chatbot products in Korean financial firms using a core–peripheryapproachofsocialrepresentations.

[5]Inrecentyears,chatbotshavegainedpopularityacrossa widerangeofindustries,includinghealthcare,marketing, education,supportsystems,culturalheritage,entertainment, andmanymore.Thepurposeofthisarticleistodevelopa specificframework,amethodologyformanagingdiscussion, andprovideappropriateresponsestostudentsbycreatinga Chatbotmodel inthe educational field.Asystemhasbeen built for this purpose that uses artificial intelligence techniquesandindustryontologiestorecognizequestions and offer answers to students. Finally, following the implementation of the planned model, an experimental campaignwasconductedtodemonstrateitsutility.

[6]Econobox,avirtualassistantintheformofachatbotor conversational robot, was crafted available to students in 2017aspartoftheauthors'ongoingautomationofmaterial and components for learning and digital education of an intro to Microeconomics at the National University of DistanceEducation(UNED).Thisstudydiscussesthereasons for its adoption, the two-phase development process, its traitsandfunctions,theassessmentofitseffectiveness,and the involvement of educators of this type of technological innovation.

[7] Chatbotsareincreasinglybeingusedinawiderangeof onlineapplications,withthemajorityofthemusedforretail orasanassistant.Personalizationandspeedyaccessduring alltimesoftheday,throughouttheyeararesomebenefitsof thesechatbots.Chatbots'advantagescanbebeneficialinthe academic sector. They represent a new type of humanmachineinterfaceinnaturallanguage.Chatbots,ontheother hand, have received only intermittent emphasis in academics,forexample,byassistingwithstudy,course,and testorganization.

[8]Itisimpossibletooverestimatetheimportanceofspoken andwritteninformationinhumancommunication.Per an article in "The New York Times," individuals now devote morethan8hoursperdaystaringatscreensoncomputers orsmartphones.Asaresult,themajorityofhumancontact takes place through web programmes such as WhatsApp, Facebook,and Twitter,amongothers,asa form ofspeech andtextualdialogue.Thepurposeofthisworkistodesigna textual communication programme, specifically a chatbot, forusageintheeducationaldomain.Thesuggestedchatbot supports users in addressing their questions. We used a randomforestensemblelearningmethodinthepresenceof extracted characteristics from our provided dataset to constructthesystem.

[9]Chatbotsareconversationalsystemsthatcanautomate human-to-human chat exchanges. It's being designed as a voice assistant that will attract viewers by, among other things, answering inquiries, giving driving directions, and functioningasahumancompanioninsmarthomes.Inorder to get the required responses, most chatbots use artificial intelligence(AI)algorithms.Inthispaperthearchitectureof a University Chatbot that responds to user enquiries concerning university information in a timely and correct manner. This is the first University Chatbot for inquiring about school information in Myanmar, and it uses Pandorabotsasaninterpreter.

3. PROPOSED SYSTEM

Chatbotsconcentrateondiscourseanddiscussion,striving foragentinteractionpatternsthatarecomparabletothose used by humans. Chatbots must be able to analyse the contextandoffersolutionstoissues,interpretemotions,and act appropriately or contribute to the learning process through dialogue. We have planned and constructed an educationalchatbotwiththisgoalinmind,withthegoalof teaching primary school pupils (ages 4–10) the English languageaswellasafewrhymes.

StudentsareintroducedtoStudyPal,achatbotthatactsasa tutor in a theatrical capacity to better engage his or her students. StudyPal teaches without the help of a human instructor. Students conversing with StudyPal throughout theirlearningexperienceareenrichedwithproactivespeech approachesthatmightbeutilisedbyateachertoaddressthe studentinatailoredandsupportivemanner.Thefollowing aresomeexamplesofspeechinthisconversationalformat:

• Questions aid learning in a variety of ways. They encouragekidstothinkcriticallyandaskquestions in order to improve their cognitive and language talents.Inthisway,StudyPalasksspecificquestions tohelptheconversationflow(forexample,"What letterdoyouseeonthescreen?").

• Praise and encouragement aid information retention by inspiring pupils, boosting their self-

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072

esteem, and bolstering their commitment to studying. With comments like "Oh, why not?" or "Super!," StudyPal is designed to encourage and drivestudents.You'refantastic!"

 StudyPal is an original educational teaching programme that uses an interactive educational learningenvironmenttoapplythemainprincipleof learningsubjects.Thissoftwareisprimarilybased onthe exchangeoftalksbetween a student anda virtualtutor–bot,whichinourcasetakestheshape (andperformsthejob)ofrhymesandEnglish.

 The goal of StudyPal is to define the software's functional requirements, or what functionality it mustdeliver,aswellashowthesystemwillinteract with users (students). StudyPal, in particular, satisfiesthefollowingkeyfunctionalrequirements:

• StudyPalcommunicateswiththeuser(student)via guidedandunguided(hybrid)speech.

• Theusercanchoosethedialogue'sflowusingthe providedchoices.

• The system gives a clear and easy-to-understand dialogueflowtotheuser.

• Theuser'snaturallanguage(EnglishorFrench)is recognizedbythesystem.

• In the event that the user misunderstands the message, the system alerts the user to take appropriateaction,suchasrepeatingthemessage.

• Thesystemdoesnotbreachtheprivacyprotection policy governing data recording because the information presented to the user comes from trustedsources,suchasWikipedia.

• Thesystemdatabasesafelyandanonymouslystores eachuser'shistory.

• The conversation's material includes text, image, video,andaudio.

3.1 Design of StudyPal

StudyPal is built on a hybrid chatbot model's general architectural structure (guided and free-text communication). As a result, it contains the following components:

Natural Language Understanding (NLU) engine: The user’s message goes through the component of the NLU engine, where, through tailored NLU models, the chatbot “uncovers”themeaning(purpose)oftheuser’smessageand givestheappropriateresponse.

Dialog Manager: Thiscomponentisinchargeofhandling and controlling all text and audio communications exchanged (questions/requests, answers/responses). It is essentiallythemiddlewareofthechatbotbetweentheNLU enginewiththeinformationretrievalcomponents.

Information Retrieval and Knowledge Base: In this component,thechatbotsearchestheknowledgebase(orthe Web) for the best relevant response and transmits the retrievedinformationtotheDialogManager.Essentially,this iswherealloftheinformationandknowledgethatmakesup thechatbot's'brain'isstoredandmanaged.

3.2 Development of StudyPal

StudyPal’sknowledgebase(KB)wascreated utilizingthe platform'stemplate-drivengraphicalinterface.Predefined answersweremanuallyplacedintotheKBforeachquestion designed in the dialogue. Because the bot can learn on its own,theKBisautomaticallyupdatedwithfreshinformation. Thedeveloperswhowatchthechatandcollecttheintentsof usersfromthelogfilesmustmanuallyextend/updatetheKB in this way. Furthermore, because the users' interactions with the chatbot are individualized, modification of the discourseispossible.Customizingthediscussion(and,asa result,improvinginteractions)canbedoneattheclasslevel byanalyzingtheinteractionsoftheentireclass.

TherationaleproposedbytheAlexaSkillsandGoogleHome platforms for creating adjustable components to be synthesizedforthedevelopmentofStudyPalwasfollowed during development. As a result, time and effort were devoted into identifying the required functionality and developingcomponentsthatwouldsuiteachoftheirneeds. Asaresult,thefollowingcomponentsmakeuptheprimary elementofthebotapplication:

A. Interactions

Interactionsare the fundamental aspects thatconstitute a chatbot'sbehaviour,accordingtoAlexaSkillsnomenclature. Alexa iscompatiblewithtwodifferentsortsofinteraction models:Pre-programmedvoiceinterfacemodel Foreach skillcategory,Alexahasasetofwordspre-programmed.Ina custom voice interaction model, you specify the terms or utterancesthatuserscanusetocommunicate.InStudyPal,a few more interactions were created under the custom interactions category, each defined according to the dialogue's needs and the educational scenario's requirements. In circumstances when StudyPal did not understand the user's message, reformulations of these interactionswereputbetweenthefundamentalinteractions, urgingtheusertotryagain(e.g.,repeatthequestion).

B. Connections

The Alexa Skills platform provides developers with pretrainednaturallanguageunderstandingmodelsthatmaybe

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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072

used at any moment. People in the room may now be detectedbyAmazon'sEchoandEchoDot,whichisidealfor initiatingAlexaroutines.

New models for detecting frequent phrases used by users when they are unable to answer a question, as well as modelsfordetectingnegativeandpositivehumanreactions, weredeveloped.Forexample,thefollowingcustomentitybasedNLPmodelshavebeendevelopedtoa)detectgeneral positive/negative emotions, such as boredom, happiness, andexcitement,andb)detectdisappointmentorexcitement fromStudyPalperformance(e.g.,"youarenotveryhelpfulto me,""Inolongerwanttotalktoyou,""youaresobad").

When developers wish to focus on knowledge (intents or entities)thatisn'tcoveredbythepre-trainedmodels,they'll need to create new custom models. The developer can manuallyinsertknowledge(wordsorphrases)intobespoke models or use the "Bulk insert" feature to automatically inserthugeamountsofsamplesatonce.Theterm"intent"in thebotparadigmreferstotheaim(intention)thattheuser hasinmindwhilemaking/typinganinquiry(whatheorshe truly means), whereas the term "entity" refers to the modifierthattheuserusestocharacteriseanissue/concept. Tounderstand(interpret)emotions,AlexaSkillscombines emoji and text analysis (NLU). Alexa's natural language understanding (models) iswhat allows her to understand themeaningofauser'sstatement(contextinthemodel)and respond appropriately. Alexa's natural language understanding(models)iswhatallowshertodecipherthe meaning of a user's statement (context in the model) and respond appropriately. NLU models are trained using machine-learning techniques, which teach them how to understandtheintentofusersandotherthings.

C. Prior Responses

Thebot'sdialoguerecyclesresponsesfromtheuserwhois currentlyconversingwithit.StudyPal,forexample,asksa student's name in the initial encounter and uses the response(therespondingname)laterintheconversationto personalizetheinteraction.

D. Custom Variables

Custom variables allow you to capture data/information from user interactions, which is very useful for running numerical calculations during a dialogue. They were, for example, used to gather correct/wrong responses (as positive or negative points) in order to determine each user'sfinaltestscore.

E. Athematic Operations

This capability is in charge of conducting numerical operations, and it was used to add and subtract points duringthedialogue,aswellasdeterminethefinaltestscore.

A point is added or removed depending on whether a studentanswersaquestioncorrectlyorincorrectly.

F. Embedding Media

This tool allows you to include images, videos, audio, and filesinyourconversation.Theseattachmentscanbeplaced directlyinthebotbyusingadevicescreentoentertheURL orviatheRichCardsoption.Thisoptionisaseriesofcards withanycombinationoftext,graphics,andbuttonsoneach one.Itispossibletoincorporatefilm,video,andaudiointo thedialogueforeducationalpurposesusingthismethod.

3.3 The Dialogue

Agroupofpeoplewasinvolvedinthecontinualtestingofthe overall process during the development of the StudyPal. These tests were carried out by software engineers, bot experts(ConversationalAIspecialists),languageeducators (LanguageEducationExperts/Teachers),andordinaryusers. Thesetestswereessentialinremovingissuesthatsurfaced duringtheearlyphasesofStudyPal'sdevelopment.

Finally,languageteachersprovidedfeedbackonrecognizing syntax and grammatical flaws, inadequate vocabulary, spelling errors, and other issues in English and French dialogues,whichhelpedtoimprovethedialogue'ssubstance.

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

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ThefinalflowofthedialogueimplementedinStudyPalhas been developed in the form illustrated in Figure 2 after a long series of experimentation and evaluation cycles. The discourse,ascanbeseen,ismadeupofaseriesofquestions tobeansweredandexercisestobedonebythepupils.The flow is based on general pedagogical characteristics of educationalprogrammesthatwereinvestigatedpriortothe creationofthisdiscourse.

3.4 The Platform

A number of advantages of the Alexa Skills platform have beenrecognisedbasedonhands-onexperienceduringthe creationandtestingoftheStudyPal:

Improved Interaction: Your app and its features will be more available to users with the help of Alexa Skills development.Inthelongterm,thismeansthatyourusers will no longer need to contact the app to use its features. They may easily accomplish this by employing voice commands,whichwillvastlyimprovetheuser'sexperience.

Get a leg up on the competition: Amazon Alexa skill creation will give your app a competitive advantage. As a result,yourcompanywillbeabletoboastauniquefeature that improves accessibility and makes the navigating experience more engaging. This will assist your brand in developing a distinct identity, which will aid in attracting morepotentialusers.

Functionality enhancements: The Alexa Skill Kit is constantly updated with new features and updates. As a resultoftheAlexaSkilldevelopmentprocess,yourbusiness application will have a greater scope for growth and functionality enhancement. In the long run, this will help yourcompanystaycurrentandmeetthechangingneedsof itscustomers.

MarketAcceptance:AlexaSkillsdevelopmentispickingup speed, and investors are starting to sing its praises. Your brand will be recognised as progressive and innovative if yougetstartedwithAlexaSkillsearly.Inthelongterm,this will enable you to ensure that your services are covered positivelyinthemedia.

large market: Alexaisemployedasavoiceassistantbythe majorityofdevices.You'llbeabletotapintoAlexa'slarge marketanduserbasewitheaseifyoudevelopAlexaskills.It eventually translates to improved outreach and a higher likelihoodofconversions.

However,dependingonthecommunicationroutesusedto engagewithStudyPal atthe timeofourresearch withthe platform, there were certain challenges and limits. Furthermore,importingdata,suchasamovieoranaudio clip,didnotworkproperly.

Fig -2:Workflow

4. METHODOLOGY

The voice of the user is captured using a speaker. This speakercouldbeontheuser’sdevicelikemobilephoneor laptop. It could also be utilized via Google home or Alexa. Simultaneouslywedefinetheintentsforthebotaswell.We thenproceedtocollectalltherealenduserutteranceswhich isstoredinadatabase.

Theseutterancesarethenmappedtotherespectiveintents. Theseintentsarethedividedandlabelledtoencapsulatethe training and test data sets. This is then passed on to a trainingclassifier whichispassedontothe bot.Afterthis process the test data is implanted on the trained bot to measuretheperformanceofthebot.Iftheperformanceis provedtobegoodthenourbothasstartedlearningandis ready to use. However, if not the bot is updated using

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training data again on iteration until its performance is standardized.

4.1 System Requirements

Model development

• TensorFlow

• Model and environment development software –AWS

Importing to virtual software

• DevelopedmodelisimportedintoAWS

• ThisisdoneinordertointegratethemodeltoAlexa

5. CONCLUSIONS

The bot is used to assist students in attaining quality education with just a command. It keeps track of the students’ progress and uses methods like active recall for effectivestudying.Studentsofdifferentlearningpaceswill findthisusefulastheyhavethelibertytomoveandstudy lessonsattheirownpace.Thoughlearningforstudentscan bedividedinvarioussubjectsinbothschoolandcollege,our botwillfocusonprovidingalearningjourneystartingfrom kindergarten to the 8th grade. The goal of Study Pal is to provide quality education to every student in the nation irrespectiveoftheirsocioeconomicandfinancialstatus.

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BIOGRAPHIES

Madhumita Venkatraman has completed her BE Information Science and EngineeringbypassinginFirstClasswith Distinction from kumaraguru college of Technology College in Coimbatore, Tamil Nadu. During her time in college, she undertooknumerousinternships Shealso participated with her team in the Smart India Hackathon, a national wide held competition for innovators. She and her were successfully selected to represent Kumaraguru institutions as well. In additiontothissheiscurrentlyonherway topursuehermastersinDataScienceatthe prestigiousUniversityofMelbourne.

Hemashrree has completed her BE Information Science and Engineering by passinginFirstClasswithDistinctionfrom kumaragurucollegeofTechnologyCollege in coimbatore, Tamil Nadu. She did her diploma in computer networking in PSG college of technology with Distinction. Duringhertimein college, sheundertook internship in various sectors like AWS, Mobile applications development and networking. She also completed and certified in CCNA. She also participated with her team in the Smart India Hackathon, a national wide held competition for innovators. She and her were successfully selected to represent

Kumaraguru institutions as well. In additiontothissheiscurrentlyonherway as a software developer at Mobiveil Technologies.

Sudharsan has completed his BE Information Science and Engineering by passinginFirstClasswithDistinctionfrom kumaragurucollegeofTechnologyCollege in Coimbatore, Tamil Nadu. He did his diplomainElectronicsandcommunication engineering in Thyagaraja college of technology with Distinction. During his timeincollege,heundertookinternshipin salzer Electronics Limited And other sectors like python development, networkingandSQL. Healsoparticipated withhisteamintheSmartIndiaHackathon, a national wide held competition for innovators. He and his were successfully selected to represent Kumaraguru institutionsaswell.Inadditiontothisheis currently pursuing a development course onhiswayasasoftwaredeveloper