1. Gabatarwa & Bayyani
Wannan binciken yana nazarin tasirin Dabarun Koyon Kai (SRL) akan koyon Sassan Magana na Turanci (ERC), tare da mai da hankali musamman kan yiwuwar matsayin tsaka-tsaki na salon asalin mai koyo. Nahawu, musamman tsarin haɗin kai masu sarkakiya kamar sassan magana, yana da mahimmanci ga ƙwarewar harshe na biyu (L2) da ƙwarewar sadarwa. Binciken ya dogara ne akan tsarin ka'idojin ka'idar sarrafa kai a cikin koyo (Pintrich, 2004) da ci gaban asali (Erikson, 1968; Berzonsky, 2005), yana nuna cewa yadda masu koyo ke sarrafa tsarin koyonsu da kuma yadda suke fahimtar kansu na iya yin tasiri sosai ga sakamakon nahawu.
2. Hanyar Bincike
An yi amfani da ƙirar gwaji mai kama da na gaske don bincika alaƙar da aka gabatar.
2.1 Mahalarta & Tsari
Binciken ya ƙunshi masu koyon Turanci a matsayin Harshen Waje (EFL) 'yan Iran 60. An raba mahalarta ba da gangan ba zuwa ko dai Ƙungiyar Gwaji (EG) (n=30), wadda ta sami horo a dabarun SRL, ko kuma Ƙungiyar Kulawa (CG) (n=30), wadda ta bi koyarwa ta al'ada. Gwajin farko akan sassan magana ya tabbatar da daidaiton ƙungiyoyin a farkon.
2.2 Kayan Aiki & Tsarin Aiki
Tsarin aiki ya bi tsari mai tsari:
- Gwajin Farko: Ƙimar ilimin farko na ERC.
- Takardar Tambayoyi na SRL: An yi wa duk mahalarta don auna amfani da dabarun da ake da su.
- Shiga Tsakani: EG ta sami horo bayyananne akan dabarun SRL (misali, saita manufa, sa ido kan kai, tantance kai) wanda aka keɓance don koyon nahawu.
- Takardar Tambayoyi na Salon Asali (Berzonsky): An yi wa EG don rarraba masu koyo zuwa salon asali na bayanai, na al'ada, ko na ɓoyayye.
- Gwajin Ƙarshe: Maimaita tantance ilimin ERC bayan lokacin shiga tsakani.
Nazarin bayanai ya yi amfani da Nazarin Haɗin Kai (ANCOVA) da Nazarin Bambanci Guda ɗaya (ANOVA).
3. Sakamako & Nazari
3.1 Binciken Kididdiga
Sakamakon ANCOVA ya nuna babban tasiri mai mahimmanci a kididdiga don shiga tsakani na dabarun SRL akan maki na ƙarshe na ERC, tare da sarrafa makin farko (p < 0.01). Wannan yana nuna cewa masu koyo a cikin ƙungiyar gwaji, waɗanda aka horar da su a dabarun SRL, sun fi waɗanda ke cikin ƙungiyar kulawa a koyon sassan magana.
A akasin haka, sakamakon gwajin ANOVA ya nuna cewa babu ɗaya daga cikin salon asali guda uku (na bayanai, na al'ada, na ɓoyayye) da ya nuna tasirin tsaka-tsaki mai mahimmanci a kididdiga akan alaƙar tsakanin amfani da SRL da nasarar ERC a cikin wannan yanayi na musamman.
3.2 Fahimtar Girman Tasiri
An ƙididdige girman tasiri na shiga tsakani na SRL a matsayin Eta squared (η²) = 0.83. Dangane da ƙa'idodin Cohen (1988), wannan yana wakiltar girman tasiri mai girma, yana nuna cewa ilimi da amfani da dabarun SRL suna bayyana babban kaso na bambance-bambance a cikin nasarar koyon nahawu, wanda ya sa ya zama bincike mai mahimmanci a aikace ga ilimin koyarwa.
Taƙaitaccen Sakamako Mai Muhimmanci
Tasirin SRL: Mai Muhimmanci (p < 0.01) | Girman Tasiri (η²): 0.83 (Babba)
Tsaka-tsakin Asali: Ba Mai Muhimmanci ba
4. Tattaunawa & Ƙarshe
Binciken ya nuna a zahiri cewa koyarwa bayyananne a cikin dabarun Koyon Kai yana haɓaka koyon nahawun Turanci mai sarkakiya, musamman sassan magana. Girman tasiri mai girma yana jaddada ƙarfin koyarwa na ba da ikon ga masu koyo da kayan aikin fahimi don tsarawa, sa ido, da tantance koyo. Binciken da bai nuna mahimmanci ba game da salon asali yana nuna cewa, a cikin yanayin wannan binciken, aikace-aikacen kai tsaye na dabarun koyo ya yi tasiri mai ƙarfi kuma nan take akan aiki fiye da fa'idodin asali masu faɗi. Marubutan suna ba da shawarar cewa malaman EFL, masu tsara manhaja, da masu tsara manufofi su haɗa horon dabarun SRL cikin koyarwar nahawu don inganta sakamakon koyo.
5. Cikakken Fahimta & Nazari Mai Zurfi
Cikakken Fahimta: Wannan bincike yana ba da saƙo mai bayyananne, mai aiki, kuma mai ƙarfi: koya wa masu koyo yadda ake koyon nahawu yana da tasiri nan take ga koyon haɗin kai na musamman fiye da magance salon asalinsu na tunani mai faɗi. Tasirin kai tsaye na dabarun SRL yana da ƙarfi kuma bayyananne.
Tsarin Ma'ana & Gibin Mai Muhimmanci: Ma'anar binciken—shiga tsakani da SRL, auna sakamako, a duba ko salon asali yana bayyana bambance-bambancen—yana da inganci. Duk da haka, tsallakewa daga sakamakon tsaka-tsaki maras mahimmanci zuwa rage muhimmancin rawar asali yana iya zama da wuri. Kamar yadda aka lura a cikin manyan ayyuka kan asalin mai koyon harshe na Norton da Toohey (2001), asali ba tsaka-tsaki mai tsayayye ba ne amma ƙarfi ne mai ƙarfi, wanda aka gina shi cikin yanayi wanda zai iya ba da dama ko hana samun damar koyo da shiga cikin dabarun. Tsarin binciken yana ɗaukar asali a matsayin tacewa mai tsayayye, wanda ya riga ya wanzu, yana iya rasa yadda aikin yin amfani da dabarun SRL cikin nasara zai iya sake fasalin asalin mai koyo a matsayin mai amfani da harshe mai iyawa—tsarin da Dörnyei (2009) ya haskaka a cikin Tsarin Son Kai na L2. Sakamakon maras mahimmanci na iya nuna al'amarin ma'auni/ƙirar ƙira, ba rashin alaƙar asali ba.
Ƙarfi & Aibobi: Ƙarfin binciken yana cikin tsarinsa mai tsabta na gwaji, bayyanannen aiwatar da SRL, da girman tasiri mai ma'ana wanda ke ba da labari kai tsaye ga aiki—wanda ba kasafai a cikin ilimin harshe na aikace-aikace ba. Aibin, kamar yadda aka yi jayayya, shine ra'ayi mai ragewa na asali. Idan aka kwatanta shi da ci gaba a cikin AI kamar CycleGAN (Zhu et al., 2017), wanda ke koyon fassara tsakanin yankuna ba tare da misalan haɗin gwiwa ba, wannan binciken ya yi nasarar "fassara" horon SRL zuwa ribar nahawu. Duk da haka, kamar AI na farko da ya yi watsi da mahallin, yana iya yin watsi da "yankin" na tsarin zamantakewa-tunani na mai koyo inda asali ke aiki.
Fahimta Mai Aiki: Ga masu aiki: Ai watsa horon dabarun SRL don nahawu nan take. Yana aiki. Ga masu bincike: Kada ku watsar da asali. A maimakon haka, ƙirƙiri bincike na dogon lokaci, na inganci, ko tsarin tsarin daɗaɗɗa don bincika yadda amfani da dabarun SRL da nasarar nahawu suke haɓaka tare da kuma tsara asalin mai koyo a kan lokaci. Yi amfani da hanyoyin daga ƙungiyar Douglas Fir (2016) don ɗaukar tasirin da yawa.
6. Tsarin Fasaha & Ƙirar Lissafi
Ana iya wakiltar babban nazarin ta hanyar ƙirar tsaka-tsaki da aka gwada ta hanyar ANCOVA da ANOVA. Babban ƙirar ANCOVA don tantance tasirin shiga tsakani na SRL shine:
$Y_{post, i} = \beta_0 + \beta_1 (Group_i) + \beta_2 (Y_{pre, i}) + \epsilon_i$
Inda $Y_{post}$ shine makin ƙarshe, $Group$ shine maɓalli mai banza (0=Kulawa, 1=Gwaji), $Y_{pre}$ shine makin farko (haɗin kai), kuma $\epsilon$ shine kalmar kuskure. $\beta_1$ mai mahimmanci yana nuna tasirin magani.
Nazarin tsaka-tsaki na salon asali (M) akan hanyar tsakanin SRL (X) da ERC (Y) yana bin ma'anar Baron & Kenny (1986), wanda aka gwada ta hanyar raba ANOVA/regression a cikin ƙungiyar gwaji:
- Hanya a: Tasirin X akan M. (Shin salon asali ya sami tasiri ta kasancewa cikin ƙungiyar SRL? Ba a gwada shi kai tsaye a nan).
- Hanya b: Tasirin M akan Y, tare da sarrafa X. An gwada shi ta hanyar ANOVA akan makin ƙarshe tare da Salon Asali a matsayin abu.
- Sakamakon maras mahimmanci na Hanya b ya kai ga ƙarshe cewa babu tsaka-tsaki.
Girman tasiri, Partial Eta Squared ($\eta_p^2$), an ƙididdige shi kamar haka: $\eta_p^2 = \frac{SS_{effect}}{SS_{effect} + SS_{error}}$ don tasirin da aka bayar a cikin ANCOVA.
7. Sakamakon Gwaji & Hoto
Ana iya ganin sakamako masu mahimmanci ta hanyar manyan ginshiƙai guda biyu:
Hoto 1: Kwatanta Makin Farko da na Ƙarshe (EG vs. CG)
Taswira mai tarin sanduna wanda ke nuna matsakaicin maki ga duka ƙungiyoyin a gwajin farko da na ƙarshe. Sandunan Ƙungiyar Gwaji a gwajin ƙarshe za su fi na kowa girma sosai, suna nuna babban tasirin magani a zahiri. Sandunan Ƙungiyar Kulawa na gwajin ƙarshe zai nuna ɗan girma kaɗan daga gwajin farko.
Hoto 2: Makin Ƙarshe ta Salon Asali (Ƙungiyar Gwaji Kawai)
Taswira mai sanduna wanda ke nuna matsakaicin makin ƙarshe na masu koyo waɗanda aka rarraba su zuwa salon asali na Bayanai, na Al'ada, da na ɓoyayye a cikin EG. Sandunan za su nuna ƙananan bambance-bambance, marasa mahimmanci a tsayi, suna tabbatar da sakamakon ANOVA cewa salon asali bai yi alaƙa da tsari da sakamako a cikin wannan samfurin ba bayan shiga tsakani na SRL.
Fassara: Labarin na gani a bayyane yake: "magani" na SRL yana ɗaukaka dukan EG, yana haifar da bambanci mai tsanani tsakanin ƙungiyoyi. A cikin wannan EG mai ɗaukaka, salon asali bai haifar da ƙarin rarrabuwa a cikin aiki ba.
8. Tsarin Nazari: Misalin Hali
Yanayi: Malamin EFL, Ms. Chen, tana son amfani da wannan binciken a cikin ajinta na matsakaici wanda ke fuskantar wahala tare da sassan sifa.
Aiwatar da Tsarin:
- Bincike (Gwajin Farko): Ms. Chen ta yi gwajin bincike gajere akan sassan sifa don kafa tushe.
- Akwatin Kayan Aiki na Dabarun (Shiga Tsakani): Maimakon kawai bayyana ƙa'idodin nahawu, ta keɓe mintuna 15 a kowane darasi na tsawon makonni 2 don horon dabarun SRL:
- Tsarawa: "A ƙarshen wannan mako, zan iya gane sunan da ake gyara a cikin jimlolin aiki 5."
- Sa Ido: Koyar da tambayoyin kai: "Shin na yi amfani da 'who' don mutane da 'which' don abubuwa?" "Shin wannan sashen yana buƙatar karin suna na batun?"
- Tantancewa: Yin amfani da cakuda mai sauƙi don ayyukan bitar takwarorinsu: "1. Kalmomin dangin da suka dace? 2. An sanya sashen daidai? 3. Ma'ana a bayyane?"
- Aiki Mai Jagora: Dalibai suna kammala ayyukan yayin "yin tunani da babbar murya" game da amfani da dabarunsu.
- Ƙima & Tunani (Gwajin Ƙarshe): An ba da sabon gwajin sashen sifa. Ms. Chen kuma ta nemi ɗalibai su rubuta ɗan gajeren tunani akan wace dabara ta fi taimakawa, tare da haɗa aiki da tsari.
Sakamakon Da Ake Tsammani: Biye da binciken, Ms. Chen na iya tsammanin gagarumin ci gaba gabaɗaya a cikin daidaiton ajin tare da sassan sifa, tare da ribar da aka fi danganta da kayan aikin dabarun da aka bayar, maimakon ƙoƙarin bayyana da kuma biyan bukatun nau'ikan asalin ɗalibai daban-daban don wannan ƙwarewar ta musamman.
9. Aikace-aikace na Gaba & Jagororin Bincike
- SRL Mai Haɓaka Fasaha: Haɓaka ƙa'idodin koyo masu daidaitawa (kamar dandamali kamar Duolingo amma mai da hankali kan dabara) waɗanda ke ƙarfafa tsarawa, sa ido, da tantancewa don batutuwan nahawu. Waɗannan na iya amfani da algorithms don ƙarfafa amfani da dabara a lokuta mafi kyau.
- Bincike na Dogon Lokaci na Ƙanana: Yin amfani da hanyoyin samfurin gogewa (ESM) ko allunan nazarin koyo don bin diddigin sauye-sauyen amfani da dabarun SRL, hasashen asali na ɗan lokaci (misali, "Ina jin kamar mai koyo mai iyawa a yanzu"), da nasarar aikin nahawu na ƙanana a cikin kwanaki ko makonni, ɗaukar ƙarfin da aka rasa a cikin ƙirar farko-ƙarshe.
- Gabaɗaya Tsakanin Harsuna: Gwada ko babban tasirin SRL akan ERC ya kasance don koyon wasu tsarin nahawu masu sarkakiya (misali, yanayin ƙaddara, muryar wucewa) a cikin Turanci ko a cikin wasu harsuna masu kaddarorin haɗin kai daban-daban.
- Haɗawa da Ka'idojin Ƙarfafawa:: Haɗa horon SRL tare da shiga tsakani daga Ka'idar Ƙaddamar da Kai ('yancin kai, iyawa, alaƙa) ko Tsarin Son Kai na L2 don ƙirƙirar kunshin "koyon koyo" mai cikakkiyar fahimta wanda zai iya yin tasiri kai tsaye ga asali ta hanyar da za a iya aunawa.
- Ƙirƙirar Sashen Horar da Malamai: Ƙirƙirar albarkatun ci gaban ƙwararru dangane da shaidar wannan binciken don taimaka wa malamai su haɗa koyarwar dabarun fahimi cikin inganci cikin manhajojin nahawu na yau da kullun.
10. Nassoshi
- Aliasin, S. H., Kasirloo, R., & Jodairi Pineh, A. (2022). The efficacy of self-regulated learning strategies on learning english grammar: the mediating role of identity styles. Journal of Psychological Science, 21(115), 1359-1374.
- Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.
- Berzonsky, M. D. (2005). Ego identity: A personal standpoint in a postmodern world. Identity, 5(2), 125-136.
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
- The Douglas Fir Group. (2016). A transdisciplinary framework for SLA in a multilingual world. Modern Language Journal, 100(S1), 19-47.
- Dörnyei, Z. (2009). The L2 Motivational Self System. In Z. Dörnyei & E. Ushioda (Eds.), Motivation, language identity and the L2 self (pp. 9-42). Multilingual Matters.
- Norton, B., & Toohey, K. (2001). Changing perspectives on good language learners. TESOL Quarterly, 35(2), 307-322.
- Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385-407.
- Zhu, J. Y., Park, T., Isola, P., & Efros, A. A. (2017). Unpaired image-to-image translation using cycle-consistent adversarial networks. Proceedings of the IEEE International Conference on Computer Vision (pp. 2223-2232).