Pane kudiwa kuri kukura kwekudzidza kunotarisa vadzidzi (SCL) muzvikoro zvepamusoro, kusanganisira mazino. Zvisinei, SCL haina kushandiswa kwakawanda mudzidzo yemazino. Saka, chidzidzo ichi chine chinangwa chekusimudzira kushandiswa kweSCL mukurapa mazino nekushandisa tekinoroji yemuchina wekusarudza (ML) kuronga nzira yekudzidza yakasarudzwa (LS) uye nzira dzekudzidza dzinoenderana (IS) dzevadzidzi vemazino sechishandiso chinobatsira pakugadzira gwara reIS. Nzira dzinovimbisa vadzidzi vemazino.
Vadzidzi vemazino vanosvika 255 vanobva kuYunivhesiti yeMalaya vakapedza bvunzo yeIndex of Learning Styles (m-ILS) yakagadziriswa, iyo yaive nezvinhu 44 zvekuvaisa muzvikamu zvavo zveLS. Ruzivo rwakaunganidzwa (runonzi dataset) runoshandiswa mukudzidza kwemuti wesarudzo unotariswa kuti uenzanise otomatiki maitiro ekudzidza evadzidzi neIS yakakodzera. Kururama kwechishandiso chekurudziro cheIS chakavakirwa pakudzidza kwemuchina kunozoongororwa.
Kushandiswa kwemamodheru emuti wesarudzo mukuita mapping otomatiki pakati peLS (input) neIS (target output) kunobvumira runyorwa rwemazano ekudzidza akakodzera emudzidzi wega wega wemazino. Chishandiso chekurudziro cheIS chakaratidza kururama kwakakwana uye kurangarira kururama kwemuenzaniso wese, zvichiratidza kuti kufananidza LS neIS kune hunhu hwakanaka uye hunhu hwakananga.
Chishandiso chekurudziro cheIS chakavakirwa pamuti wesarudzo weML chakaratidza kugona kwacho kuenderana nemazvo maitiro ekudzidza evadzidzi vemazino nenzira dzakakodzera dzekudzidza. Chishandiso ichi chinopa sarudzo dzakasimba dzekuronga makosi kana mamodule anotarisana nevadzidzi anogona kusimudzira ruzivo rwekudzidza rwevadzidzi.
Kudzidzisa nekudzidza mabasa akakosha muzvikoro zvedzidzo. Pakugadzira sisitimu yedzidzo yehunyanzvi yepamusoro, zvakakosha kutarisa zvinodiwa nevadzidzi pakudzidza. Kudyidzana pakati pevadzidzi nenzvimbo dzavanodzidza kunogona kuonekwa kuburikidza neLS yavo. Tsvagiridzo inoratidza kuti kusawirirana kunoitwa nevadzidzisi pakati peLS neIS dzevadzidzi kunogona kuva nemigumisiro yakaipa pakudzidza kwevadzidzi, zvakaita sekudzikira kwekutarisa uye chido. Izvi zvinokanganisa mashandiro evadzidzi zvisina kunanga [1,2].
IS inzira inoshandiswa nevadzidzisi kupa ruzivo nehunyanzvi kuvadzidzi, kusanganisira kubatsira vadzidzi kudzidza [3]. Kazhinji, vadzidzisi vakanaka vanoronga nzira dzekudzidzisa kana kuti IS dzinoenderana neruzivo rwevadzidzi vavo, pfungwa dzavari kudzidza, uye danho ravo rekudzidza. Mupfungwa, kana LS neIS zvikabatana, vadzidzi vachakwanisa kuronga nekushandisa hunyanzvi hwakati kuti vadzidze zvinobudirira. Kazhinji, chirongwa chezvidzidzo chinosanganisira shanduko dzakasiyana-siyana pakati pezvikamu, zvakaita sekudzidzisa kuenda kukudzidzira kwakatungamirirwa kana kubva pakudzidzira kwakatungamirirwa kuenda kukudzidzira kwakazvimiririra. Nekufunga izvi, vadzidzisi vanobudirira vanowanzo ronga kudzidzisa nechinangwa chekuvaka ruzivo nehunyanzvi hwevadzidzi [4].
Kudiwa kweSCL kuri kukura muzvikoro zvepamusoro-soro, kusanganisira vanachiremba vemazino. Maitiro eSCL akagadzirirwa kusangana nezvinodiwa nevadzidzi pakudzidza. Izvi zvinogona kuitika, semuenzaniso, kana vadzidzi vachitora chikamu muzviitiko zvekudzidza uye vadzidzisi vachiita sevanopa mazano uye vane basa rekupa mhinduro dzinokosha. Zvinonzi kupa zvekushandisa pakudzidza nezviitiko zvinoenderana nedanho redzidzo revadzidzi kana zvavanoda zvinogona kuvandudza nzvimbo yekudzidza yevadzidzi uye kukurudzira ruzivo rwakanaka rwekudzidza [5].
Kazhinji, maitiro ekudzidza kwevadzidzi vemazino anopesvedzerwa nemaitiro akasiyana-siyana ekiriniki avanofanira kuita uye nzvimbo yekiriniki yavanokudziridza hunyanzvi hwekudyidzana nevamwe. Chinangwa chekudzidziswa ndechekugonesa vadzidzi kusanganisa ruzivo rwekutanga rwekurapa mazino nehunyanzvi hwekurapa mazino uye kushandisa ruzivo rwavakawana mumamiriro matsva ekiriniki [6, 7]. Tsvagiridzo yekutanga muhukama huripo pakati peLS neIS yakawana kuti kugadzirisa nzira dzekudzidza dzakanangana neLS inodiwa kwaizobatsira kuvandudza maitiro edzidzo [8]. Vanyori vanokurudzirawo kushandisa nzira dzakasiyana-siyana dzekudzidzisa nekuongorora kuti dzienderane nekudzidza nezvinodiwa nevadzidzi.
Vadzidzisi vanobatsirwa nekushandisa ruzivo rweLS kuvabatsira kugadzira, kugadzira, uye kushandisa dzidziso dzichawedzera ruzivo rwakadzama rwevadzidzi uye kunzwisisa nyaya yacho. Vaongorori vakagadzira maturusi akati wandei ekuongorora LS, akadai seKolb Experiential Learning Model, Felder-Silverman Learning Style Model (FSLSM), uye Fleming VAK/VARK Model [5, 9, 10]. Sekureva kwemabhuku, aya mamodheru ekudzidza ndiwo anonyanya kushandiswa uye anonyanya kudzidzwa. Mubasa rekutsvagisa razvino, FSLSM inoshandiswa kuongorora LS pakati pevadzidzi vemazino.
FSLSM imhando inoshandiswa zvakanyanya pakuongorora kudzidza kunochinjika muinjiniya. Kune mabasa akawanda akabudiswa musainzi yehutano (kusanganisira mushonga, ukoti, pharmacy uye mazino) anowanikwa uchishandisa mamodheru eFSLSM [5, 11, 12, 13]. Chishandiso chinoshandiswa kuyera zviyero zveLS muFLSM chinonzi Index of Learning Styles (ILS) [8], chine zvinhu makumi mana nemana zvinoongorora zviyero zvina zveLS: kugadzirisa (kushanda/kufungisisa), kuona (kuona/kunzwisisa), kuisa (kuona). /kutaura) uye kunzwisisa (sequential/global) [14].
Sezvakaratidzwa paMufananidzo 1, chikamu chega chega cheFSLSM chine sarudzo huru. Semuenzaniso, muchikamu chekugadzirisa, vadzidzi vane "active" LS vanosarudza kugadzirisa ruzivo nekudyidzana zvakananga nezvinhu zvekudzidza, kudzidza nekuita, uye vanowanzo dzidza mumapoka. LS "yekufungisisa" inoreva kudzidza kuburikidza nekufunga uye inosarudza kushanda yega. Chikamu che "kunzwisisa" cheLS chinogona kukamurwa kuita "kunzwa" uye/kana "pfungwa." Vadzidzi "vekunzwa" vanoda ruzivo rwakajeka uye maitiro anoshanda, vanotarisa chokwadi zvichienzaniswa nevadzidzi "vekunzwa" vanosarudza zvinhu zvisingawanzoonekwi uye vane hunyanzvi uye vane hunyanzvi. Chikamu che "input" cheLS chinosanganisira vadzidzi "vekuona" uye "vekutaura". Vanhu vane "visual" LS vanosarudza kudzidza kuburikidza nezviratidzo zvinoonekwa (senge madhayagiramu, mavhidhiyo, kana zviratidzo zviripo), nepo vanhu vane "verbal" LS vanosarudza kudzidza kuburikidza nemashoko ari mutsananguro dzakanyorwa kana dzemuromo. Kuti "vanzwisise" zviyero zveLS, vadzidzi vakadaro vanogona kukamurwa kuita "sequential" uye "global". "Vadzidzi vanotevedzana vanosarudza nzira yekufunga yakatevedzana uye vanodzidza nhanho nhanho, nepo vadzidzi vepasi rose vanowanzova nenzira yekufunga yakazara uye vanogara vachinzwisisa zviri nani zvavari kudzidza."
Munguva pfupi yapfuura, vaongorori vazhinji vakatanga kutsvaga nzira dzekuwana otomatiki data-based, kusanganisira kugadzira maalgorithms matsva nemamodeli anokwanisa kududzira huwandu hwakawanda hwedata [15, 16]. Zvichibva padata rakapihwa, supervised ML (machine learning) inokwanisa kugadzira mapatani nefungidziro dzinofanotaura mhedzisiro yeramangwana zvichibva pakuvakwa kwemaalgorithms [17]. Zvichitaurwa zviri nyore, matekiniki ekudzidza kwemuchina anotarisisa anoshandura data rekuisa uye anodzidzisa maalgorithms. Zvino inogadzira range inoronga kana kufanotaura mhedzisiro zvichibva pamamiriro akafanana edata rekuisa rakapihwa. Chinhu chikuru chakanaka che supervised machine learning algorithms kugona kwayo kugadzira mhedzisiro yakanaka uye inodiwa [17].
Kuburikidza nekushandisa nzira dzinotungamirirwa nedata uye mamodheru ekudzora muti wesarudzo, kuongororwa otomatiki kweLS kunogoneka. Miti yesarudzo yakataurwa kuti inoshandiswa zvakanyanya muzvirongwa zvekudzidzisa muminda yakasiyana-siyana, kusanganisira sainzi yehutano [18, 19]. Muchidzidzo ichi, modheru iyi yakadzidziswa zvakananga nevagadziri vehurongwa kuti vaone LS yevadzidzi uye vanokurudzira IS yakanakisa kwavari.
Chinangwa chechidzidzo ichi ndechekugadzira nzira dzekuendesa IS zvichibva paLS yevadzidzi uye kushandisa nzira yeSCL nekugadzira chishandiso chekurudziro cheIS chakarongedzwa kuLS. Mafambiro ekugadzira chishandiso chekurudziro cheIS senzira yeSCL anoratidzwa muMufananidzo 1. Chishandiso chekurudziro cheIS chakakamurwa kuita zvikamu zviviri, kusanganisira nzira yekupatsanura LS uchishandisa ILS uye chiratidziro cheIS chakakodzera vadzidzi.
Zvikuru sei, hunhu hwezvishandiso zvekurudziro yekuchengetedzwa kwemashoko zvinosanganisira kushandiswa kwetekinoroji dzewebhu uye kushandiswa kwekudzidza kwemuchina wekusarudza. Vagadziri vemasisitimu vanovandudza ruzivo rwemushandisi nekufamba-famba kwavo nekuzvigadzirisa kumidziyo yemafoni senge nharembozha nemapiritsi.
Kuedza uku kwakaitwa muzvikamu zviviri uye vadzidzi vekuFaculty of Dentistry paYunivhesiti yeMalaya vakapinda muchirongwa ichi vachizvidira. Vatori vechikamu vakapindura ku-m-ILS yemudzidzi wemazino online muChirungu. Muchikamu chekutanga, seti yedata yevadzidzi makumi mashanu yakashandiswa kudzidzisa algorithm yekudzidza kwemuchina wekusarudza. Muchikamu chechipiri chemaitiro ekugadzira, seti yedata yevadzidzi mazana maviri nemakumi mashanu nemashanu yakashandiswa kuvandudza kururama kwechishandiso chakagadzirwa.
Vatori vechikamu vese vanowana ruzivo rwepamhepo pakutanga kwechikamu chimwe nechimwe, zvichienderana negore redzidzo, kuburikidza neMicrosoft Teams. Chinangwa chechidzidzo chakatsanangurwa uye mvumo yakawanikwa. Vatori vechikamu vese vakapihwa link yekuwana m-ILS. Mudzidzi wega wega akarairwa kupindura zvinhu zvese makumi mana nemana zviri pamubvunzo. Vakapihwa vhiki imwe chete yekupedzisa ILS yakagadziriswa panguva nenzvimbo zvakavanakira panguva yekuzorora kwesemester isati yatanga. M-ILS yakavakirwa pachishandiso chepakutanga cheILS uye yakagadziriswa vadzidzi vemazino. Kufanana neILS yekutanga, ine zvinhu makumi mana nemana zvakagoverwa zvakaenzana (a, b), zvine zvinhu gumi nechimwe nechimwe, zvinoshandiswa kuongorora zvikamu zvechikamu chimwe nechimwe cheFSLSM.
Munguva yekutanga yekugadzira zvishandiso, vaongorori vakanyora mamapu nemaoko vachishandisa data revadzidzi vemazino makumi mashanu. Sekureva kweFSLM, sisitimu iyi inopa huwandu hwemhinduro "a" na "b". Pachikamu chimwe nechimwe, kana mudzidzi akasarudza "a" semhinduro, LS inorongwa seActive/Perceptual/Visual/Sequential, uye kana mudzidzi akasarudza "b" semhinduro, mudzidzi anorongwa seReflective/Intuitive/Linguistic. / global learner.
Mushure mekuyera mashandiro ebasa pakati pevaongorori vedzidzo yemazino nevagadziri vemasystem, mibvunzo yakasarudzwa zvichibva paFLSSSM domain ndokuiswa muML model kuti vafanotaura LS yemudzidzi wega wega. "Marara apinda, marara abuda" chirevo chinozivikanwa mumunda wekudzidza kwemuchina, nekusimbiswa pamhando yedata. Hunhu hwedata rinopinda hunosarudza kururama uye kururama kwemuchina wekudzidza. Munguva yechikamu cheinjiniya yefeature, seti itsva yefeature inogadzirwa iyo iri huwandu hwemhinduro "a" na "b" zvichibva paFLSSM. Nhamba dzekuzivikanwa kwenzvimbo dzemishonga dzakapihwa muTafura 1.
Verenga mamaki zvichibva pamhinduro uye sarudza LS yemudzidzi. Pamudzidzi wega wega, mamaki acho anobva pa1 kusvika pa11. Mamaki kubva pa1 kusvika pa3 anoratidza kuenzana kwezvido zvekudzidza mukati mechikamu chimwe chete, uye mamaki kubva pa5 kusvika pa7 anoratidza kusarudzwa kuri pakati nepakati, zvichiratidza kuti vadzidzi vanowanzoda nzvimbo imwe chete vachidzidzisa vamwe. Imwe shanduko pachikamu chimwe chete ndeyekuti mamaki kubva pa9 kusvika pa11 anoratidza kusarudzwa kwakasimba kune rimwe divi kana rimwe [8].
Pachikamu chimwe nechimwe, mishonga yakakamurwa kuita "active", "reflective" uye "balanced". Semuenzaniso, kana mudzidzi achipindura "a" kakawanda kupfuura "b" pachinhu chakasarudzwa uye mamaki ake akadarika muganhu we5 wechinhu chinomiririra chiyero cheProcessing LS, iye/iye ndewechikamu che "active" LS. . Zvisinei, vadzidzi vakaiswa muchikamu che "reflective" LS pavakasarudza "b" kupfuura "a" mumibvunzo gumi nerimwe chaiyo (Tafura 1) uye vakawana mapoinzi anopfuura mashanu. Pakupedzisira, mudzidzi ari mumamiriro e "equilibrium." Kana mamaki asingapfuure mapoinzi mashanu, saka iyi i "process" LS. Maitiro ekupatsanura akadzokororwa kune mamwe ma LS dimensions, kureva kuona (active/reflective), kuisa (kuona/kutaura), uye kunzwisisa (sequential/global).
Mamodheru emuti wesarudzo anogona kushandisa zvikamu zvakasiyana zvemaficha nemitemo yesarudzo pamatanho akasiyana ekuita kwekuisa muzvikamu. Inoonekwa sechishandiso chinozivikanwa chekuisa muzvikamu nekufanotaura. Inogona kumiririrwa uchishandisa chimiro chemuti chakadai sechati yekuyerera [20], umo mune ma node emukati anomiririra bvunzo nemaitiro, bazi rega rega rinomiririra mhedzisiro yebvunzo, uye node yega yega yeshizha (node yeshizha) ine label yekirasi.
Purogiramu iri nyore yakavakirwa pamitemo yakagadzirwa kuti iwane mamaki uye inyore LS yemudzidzi wega wega zvichibva pamhinduro dzake. Yakavakirwa pamitemo inotora chimiro chechirevo cheIF, apo "KANA" inotsanangura chinotanga uye "ZVINO" inotsanangura chiito chinofanira kuitwa, semuenzaniso: "Kana X ikaitika, saka ita Y" (Liu et al., 2014). Kana seti yedata ichiratidza hukama uye modhi yemuti wesarudzo yakadzidziswa zvakanaka uye yakaongororwa, nzira iyi inogona kuva nzira inoshanda yekushandura maitiro ekuenzanisa LS neIS otomatiki.
Muchikamu chechipiri chekuvandudza, seti yedata yakawedzerwa kusvika pa255 kuti ivandudze kururama kwechishandiso chekurudziro. Seti yedata yakakamurwa muchikamu che1:4. 25% (64) yeseti yedata yakashandiswa kune seti yekuedza, uye yasara 75% (191) yakashandiswa seseti yekudzidzisa (Mufananidzo 2). Seti yedata inofanira kupatsanurwa kudzivirira modhi kuti isadzidziswe uye iedzwe pane seti yedata imwechete, izvo zvinogona kukonzera modhi kuti irangarire pane kudzidza. Modhi inodzidziswa pane seti yekudzidzisa uye inoongorora mashandiro ayo pane seti yekuedza—data iro modhi isati yamboona.
Kana chishandiso cheIS chagadzirwa, chishandiso ichi chichakwanisa kupatsanura LS zvichienderana nemhinduro dzevadzidzi vemazino kuburikidza newebhu. Sisitimu yekubatsira kuchengetedzwa kwemashoko pawebhu inovakwa uchishandisa mutauro wePython programming uchishandisa Django framework se backend. Tafura 2 inoratidza maraibhurari anoshandiswa mukugadzira sisitimu iyi.
Dataset iyi inoiswa mumuenzaniso wemuti wesarudzo kuti iverenge uye ibudise mhinduro dzevadzidzi kuti dzigoisa muzvikamu zvezviyero zveLS zvevadzidzi.
Matrix yekuvhiringidzika inoshandiswa kuongorora kururama kwealgorithm yekudzidza kwemuchina wekusarudza pane seti yedata yakapihwa. Panguva imwe chete, inoongorora mashandiro emuenzaniso wekupatsanura. Inopfupikisa fungidziro yemuenzaniso uye inoienzanisa nemazita chaiwo edata. Mhedzisiro yekuongorora yakavakirwa pamitengo mina yakasiyana: True Positive (TP) - modhi yakafanotaura zvakanaka chikamu chakanaka, False Positive (FP) - modhi yakafanotaura zvakanaka chikamu chakanaka, asi true label yaive negative, True Negative (TN) - modhi yakafanotaura nemazvo kirasi isina kunaka, uye false negative (FN) - Modhi inofanotaura kirasi isina kunaka, asi true label yakanaka.
Aya mavalues anoshandiswa kuverenga ma performance metrics akasiyana-siyana e scikit-learn classification model muPython, anoti precision, precision, recall, uye F1 score. Heano mienzaniso:
Kuyeuka (kana kuti kunzwisisa) kunoyera kugona kwemuenzaniso kuronga nemazvo LS yemudzidzi mushure mekupindura mibvunzo ye m-ILS.
Kunyatsojeka kunonzi chiyero chechokwadi chekusava nechinhu. Sezvamunoona kubva mufomura iri pamusoro, ichi chinofanira kunge chiri chiyero chekusava nechinhu kwechokwadi (TN) kune kuva nekusava nechinhu kwechokwadi uye kuva nenhema (FP). Sechikamu chezvishandiso zvinokurudzirwa zvekuisa muzvikamu zvemishonga yemudzidzi, chinofanira kukwanisa kuziva zvakarurama.
Seti yekutanga yedata revadzidzi makumi mashanu vakashandiswa kudzidzisa modhi yeML yemuti wesarudzo yakaratidza kururama kushoma nekuda kwekukanganisa kwevanhu mutsanangudzo (Tafura 3). Mushure mekugadzira chirongwa chiri nyore chakavakirwa pamitemo chekuverenga otomatiki mamakisi eLS netsanangudzo dzevadzidzi, huwandu huri kuwedzera hwedatasets (255) hwakashandiswa kudzidzisa nekuyedza sisitimu yekukurudzira.
Mumatrix ye multiclass confusion, zvinhu zve diagonal zvinomiririra huwandu hwekufungidzira kwakarurama kwerudzi rwega rwega rweLS (Mufananidzo 4). Uchishandisa modhi yemuti wesarudzo, sampuro dzese makumi matanhatu neina dzakafanotaurwa nemazvo. Saka, muchidzidzo ichi, zvinhu zve diagonal zvinoratidza mhedzisiro inotarisirwa, zvichiratidza kuti modhi inoita zvakanaka uye inofanotaura nemazvo label yekirasi ye LS classification yega yega. Saka, kururama kwese kwechishandiso chekurudziro i100%.
Kukosha kwekururamisa, kunyatsojeka, kurangarira, uye chibodzwa cheF1 zvinoratidzwa muMufananidzo 5. Kune sisitimu yekurudziro inoshandisa modhi yemuti wesarudzo, chibodzwa chayo cheF1 i1.0 "chakakwana," zvichiratidza kunyatsojeka uye kurangarira kwakakwana, zvichiratidza kunzwisisika kwakakosha uye kukosha kwakanangana.
Mufananidzo 6 unoratidza kuratidzwa kwemuenzaniso wemuti wesarudzo mushure mekunge kudzidziswa nekuyedzwa kwapera. Mukuenzanisa kuri padivi nepadivi, muenzaniso wemuti wesarudzo wakadzidziswa une zvinhu zvishoma waratidza kururama kwakanyanya uye kuratidzwa kwemuenzaniso kuri nyore. Izvi zvinoratidza kuti hunyanzvi hwezvinhu hunotungamira mukuderedza zvinhu idanho rakakosha mukuvandudza mashandiro emuenzaniso.
Nekushandisa decision tree supervisory learning, mapping pakati peLS (input) neIS (target output) inogadzirwa otomatiki uye ine ruzivo rwakadzama rweLS yega yega.
Zvakabuda zvakaratidza kuti 34.9% yevadzidzi 255 vaida imwe (1) LS sarudzo. Vazhinji (54.3%) vaive nesarudzo mbiri kana kupfuura dzeLS. 12.2% yevadzidzi vakataura kuti LS yakaenzana (Tafura 4). Kuwedzera kune LS huru sere, kune misanganiswa makumi matatu nemana yeLS classifications yevadzidzi vemazino veUniversity of Malaya. Pakati padzo, kuona, kuona, uye musanganiswa wekuona nekuona ndizvo LS huru dzakataurwa nevadzidzi (Mufananidzo 7).
Sezvinoratidzwa kubva paTafura 4, ruzhinji rwevadzidzi rwaiva nepfungwa huru (13.7%) kana kuti kuona (8.6%) LS. Zvakataurwa kuti 12.2% yevadzidzi vaisanganisira kuona nekuona (perceptual-visual LS). Izvi zvakawanikwa zvinoratidza kuti vadzidzi vanosarudza kudzidza nekurangarira kuburikidza nenzira dzakagara dziripo, kutevedzera maitiro chaiwo uye akadzama, uye vanoteerera. Panguva imwe chete, vanofarira kudzidza nekutarisa (vachishandisa madhayagiramu, nezvimwewo) uye vanowanzo kurukura nekushandisa ruzivo mumapoka kana vega.
Chidzidzo ichi chinopa ruzivo rwematekiniki ekudzidza kwemuchina anoshandiswa mukuchera data, nekutarisa pakufanotaura nekukurumidza uye nemazvo LS yevadzidzi uye kukurudzira IS yakakodzera. Kushandiswa kwemuenzaniso wemuti wesarudzo kwakaratidza zvinhu zvine chekuita nehupenyu hwavo uye ruzivo rwedzidzo. Ialgorithm yekudzidza kwemuchina inotariswa inoshandisa chimiro chemuti kupatsanura data nekupatsanura seti yedata muzvikamu zvidiki zvichienderana nezvimwe zvinodiwa. Inoshanda nekupatsanura data rekuisa muzvikamu zvidiki zvichienderana nekukosha kwechimwe chezvinhu zvinoisa munodhi yega yega yemukati kusvika sarudzo yaitwa panodhi yemashizha.
Manodhi emukati memuti wesarudzo anomiririra mhinduro zvichibva pane zvinopihwa zvedambudziko re m-ILS, uye manodhi emashizha anomiririra kufanotaura kwekupedzisira kweLS classification. Mukudzidza kwese, zviri nyore kunzwisisa huwandu hwemiti yesarudzo inotsanangura uye inofungidzira maitiro esarudzo nekutarisa hukama huripo pakati pezvinhu zvinopihwa uye kufungidzira kwekubuda.
Muminda yesainzi yemakombiyuta neinjiniya, maalgorithms ekudzidza kwemuchina anoshandiswa zvakanyanya kufanotaura mashandiro evadzidzi zvichibva pamapoinzi avo ekupinda mubvunzo [21], ruzivo rwevanhu, uye maitiro ekudzidza [22]. Tsvagiridzo yakaratidza kuti algorithm iyi yakafanotaura mashandiro evadzidzi nemazvo uye yakavabatsira kuziva vadzidzi vari panjodzi yematambudziko edzidzo.
Kushandiswa kwemaalgorithms eML mukugadzira masimulator evarwere chaiwo ekudzidzisa mazino kwakataurwa. Iyi simulator inokwanisa kuburitsa nemazvo mhinduro dzemuviri dzevarwere chaivo uye inogona kushandiswa kudzidzisa vadzidzi vemazino munzvimbo yakachengeteka uye inodzorwa [23]. Zvimwe zvidzidzo zvakati wandei zvinoratidza kuti maalgorithms ekudzidza kwemuchina anogona kuvandudza mhando uye kushanda zvakanaka kwedzidzo yemazino neyekurapa uye kutarisirwa kwevarwere. Maalgorithms ekudzidza kwemuchina akashandiswa kubatsira mukuongorora zvirwere zvemazino zvichibva pane data sets dzakadai sezviratidzo nehunhu hwemurwere [24, 25]. Kunyange hazvo zvimwe zvidzidzo zvakaongorora kushandiswa kwemaalgorithms ekudzidza kwemuchina kuita mabasa akadai sekufanotaura mhedzisiro yemurwere, kuziva varwere vane njodzi huru, kugadzira zvirongwa zvekurapa zvemunhu [26], kurapwa kwemazino [27], uye kurapwa kwecaries [25].
Kunyangwe mishumo pamusoro pekushandiswa kwekudzidza kwemuchina mukurapa mazino yakaburitswa, kushandiswa kwayo mukudzidzisa mazino kuchiri kushoma. Saka, chidzidzo ichi chaive nechinangwa chekushandisa modhi yemuti wesarudzo kuona zvinhu zvine chekuita neLS neIS pakati pevadzidzi vemazino.
Zvakabuda muchidzidzo ichi zvinoratidza kuti chishandiso chekurudziro chakagadzirwa chine kururama kwakanyanya uye kururama kwakakwana, zvichiratidza kuti vadzidzisi vanogona kubatsirwa nechishandiso ichi. Uchishandisa nzira yekupatsanura data, inogona kupa mazano akagadzirirwa iwe pachako uye kuvandudza ruzivo rwedzidzo nemigumisiro yevadzidzisi nevadzidzi. Pakati pazvo, ruzivo rwunowanikwa kuburikidza nezvishandiso zvekurudziro runogona kugadzirisa kusawirirana pakati penzira dzekudzidzisa dzinodiwa nevadzidzisi uye zvinodiwa nevadzidzi pakudzidza. Semuenzaniso, nekuda kwekubuda otomatiki kwezvishandiso zvekurudziro, nguva inodiwa yekuona IP yemudzidzi uye kuienzanisa neIP inoenderana ichaderedzwa zvakanyanya. Nenzira iyi, mabasa ekudzidzisa akakodzera uye zvinhu zvekudzidzisa zvinogona kurongwa. Izvi zvinobatsira kukudziridza maitiro akanaka ekudzidza evadzidzi uye kugona kwavo kutarisisa. Imwe ongororo yakashuma kuti kupa vadzidzi zvinhu zvekudzidza uye mabasa ekudzidza anoenderana neLS yavo yavanoda kunogona kubatsira vadzidzi kubatanidza, kugadzirisa, uye kunakidzwa nekudzidza munzira dzakawanda kuti vawane mukana wakakura [12]. Tsvagiridzo inoratidzawo kuti pamusoro pekuvandudza kutora chikamu kwevadzidzi mukirasi, kunzwisisa maitiro ekudzidza evadzidzi kunoitawo basa rakakosha mukuvandudza maitiro ekudzidzisa nekutaurirana nevadzidzi [28, 29].
Zvisinei, sezvakaita tekinoroji yemazuva ano, kune matambudziko nemiganhu. Izvi zvinosanganisira nyaya dzine chekuita nekuchengetedzwa kwedata, rusaruro uye kururamisira, uye hunyanzvi hwehunyanzvi nezvishandiso zvinodiwa kugadzira nekushandisa maalgorithms ekudzidza kwemuchina mudzidzo yemazino; Zvisinei, kufarira kuri kukura uye kutsvagisa munzvimbo iyi zvinoratidza kuti matekinoroji ekudzidza kwemuchina anogona kuve nemhedzisiro yakanaka padzidzo yemazino uye masevhisi emazino.
Zvakabuda muchidzidzo ichi zvinoratidza kuti hafu yevadzidzi vemazino vane tsika ye "kuona" mishonga. Rudzi urwu rwevadzidzi runofarira chokwadi nemienzaniso chaiyo, kutungamira kunoshanda, kushivirira kune zvakadzama, uye kufarira "kuona" LS, uko vadzidzi vanosarudza kushandisa mifananidzo, mifananidzo, mavara, nemamepu kuratidza pfungwa nepfungwa. Zvakabuda pari zvino zvinoenderana nezvimwe zvidzidzo zvinoshandisa ILS kuongorora LS muvadzidzi vemazino nevezvekurapa, vazhinji vavo vane hunhu hwe LS yekuona nekuona [12, 30]. Dalmolin nevamwe vake vanoti kuzivisa vadzidzi nezve LS yavo kunovabvumira kusvika pakukwanisa kwavo kudzidza. Vaongorori vanoti kana vadzidzisi vakanzwisisa zvizere maitiro edzidzo evadzidzi, nzira dzakasiyana-siyana dzekudzidzisa nemabasa zvinogona kuitwa izvo zvichavandudza mashandiro evadzidzi neruzivo rwekudzidza [12, 31, 32]. Zvimwe zvidzidzo zvakaratidza kuti kugadzirisa LS yevadzidzi kunoratidzawo kuvandudzwa muruzivo rwekudzidza nekushanda kwevadzidzi mushure mekuchinja maitiro avo ekudzidza kuti aenderane ne LS yavo [13, 33].
Mafungiro evadzidzisi anogona kusiyana maererano nekushandiswa kwenzira dzekudzidzisa zvichibva pahunyanzvi hwevadzidzi hwekudzidza. Kunyange hazvo vamwe vachiona mabhenefiti enzira iyi, kusanganisira mikana yekuvandudza hunyanzvi, kupa mazano, uye rutsigiro munharaunda, vamwe vanogona kunetseka nezvenguva nerutsigiro rwemasangano. Kuedza kuenzana kwakakosha pakugadzira mafungiro anotarisa vadzidzi. Vakuru vedzidzo yepamusoro, vakaita sevatungamiriri vemayunivhesiti, vanogona kuita basa rakakosha mukusimudzira shanduko yakanaka nekuunza maitiro matsva uye kutsigira kukura kwevadzidzisi [34]. Kuti vagadzire hurongwa hwedzidzo yepamusoro hune simba uye hunopindura, vagadziri vemitemo vanofanira kutora matanho akashinga, akadai sekuchinja mitemo, kupa zviwanikwa mukubatanidzwa kwetekinoroji, uye kugadzira hurongwa hunokurudzira nzira dzinotarisa vadzidzi. Matanho aya akakosha kuti pave nemigumisiro inodiwa. Tsvagiridzo yazvino pamusoro pedzidziso dzakasiyana yakaratidza zvakajeka kuti kubudirira kwekudzidzisa kwakasiyana kunoda mikana yekudzidziswa nekusimudzirwa kwevadzidzisi [35].
Chishandiso ichi chinopa rutsigiro rwakakosha kune vadzidzisi vemazino vanoda kutora nzira inotarisa vadzidzi pakuronga mabasa ekudzidza anobatsira vadzidzi. Zvisinei, chidzidzo ichi chakaganhurirwa pakushandisa mamodheru eML emuti wesarudzo. Mune ramangwana, data rakawanda rinofanira kuunganidzwa kuti rienzanise mashandiro emamodheru akasiyana ekudzidza kwemuchina kuti rienzanise kururama, kuvimbika, uye kururama kwezvishandiso zvekurudziro. Pamusoro pezvo, pakusarudza nzira yakakodzera yekudzidza kwemuchina pabasa rakati, zvakakosha kufunga nezvezvimwe zvinhu zvakaita sekuoma kwemuenzaniso uye kududzirwa kwawo.
Dambudziko rekudzidza uku nderekuti rakangotarisa pakugadzira ma LS ne IS pakati pevadzidzi vemazino. Saka, hurongwa hwekurudziro hwakagadzirwa huchakurudzira chete avo vakakodzera vadzidzi vemazino. Kuchinja kunodiwa kuti vadzidzi vedzidzo yepamusoro vashandiswe.
Chishandiso chitsva ichi chinokurudzira kudzidza kwemuchina chinokwanisa kurongedza nekufananidza LS yevadzidzi neIS inoenderana, zvichiita kuti ive chirongwa chekutanga chedzidzo yemazino kubatsira vadzidzisi vemazino kuronga mabasa ekudzidzisa nekudzidza akakodzera. Ichishandisa nzira yekuongorora data, inogona kupa mazano akagadzirirwa iwe pachako, kuchengetedza nguva, kuvandudza nzira dzekudzidzisa, kutsigira nzira dzakanangana, uye kukurudzira kufambira mberi kwehunyanzvi. Kushandiswa kwayo kuchasimudzira nzira dzekudzidzisa mazino dzinotarisana nevadzidzi.
Gilak Jani Associated Press. Kuenzanisa kana kusawirirana pakati pemaitiro ekudzidza emudzidzi nemaitiro ekudzidzisa emudzidzisi. Int J Mod Educ Computer Science. 2012;4(11):51–60. https://doi.org/10.5815/ijmecs.2012.11.05
Nguva yekutumira: Kubvumbi-29-2024