Laura Mendoza

Dr. Laura Mendoza

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 July 2025 in Behavioral Sciences
Verified
Journal Article
Open access
PDF file
FSFei Sun
Fei Sun
LMLaura Mendoza
Laura Mendoza
JWJunju Wang
Junju Wang
HLHongbin Li
Hongbin Li
Approaches to writing play an important role in both the writing processes and outcomes. However, little is known about whether L2 writers adopt different combinations of approaches in academic writing contexts and what factors predict such combinations. Hence, this study aimed to identify different profiles of approaches to writing in an L2 academic context and examine how they are predicted by writing self-efficacy and large language model (LLM) acceptance. To this end, a total of 578 Chinese graduate students were recruited to participate in the study. Latent profile analysis revealed three distinct writing profiles: unorganized (Profile 1), dissonant (Profile 2), and deep and organized (Profile 3), with the majority of students categorized under the dissonant profile. Additionally, multinomial logistic regression analysis revealed that writing self-efficacy positively predicted profile membership, with the strongest effect observed for Profile 3, followed by Profile 2 and then Profile 1. LLM acceptance also positively predicted profile membership, with the strongest effect for Profile 2, followed by Profile 3 and then Profile 1.

2 February 2022 in System
Verified
Journal Article
Open access
LMLaura Mendoza
Laura Mendoza
TLTuula Lehtonen
Tuula Lehtonen
SLSari Lindblom-Ylänne
Sari Lindblom-Ylänne
HHHeidi Hyytinen
Heidi Hyytinen

14 January 2026 in Acta Psychologica
Verified
Journal Article
Open access
FSFei Sun
Fei Sun
JWJunju Wang
Junju Wang
LMLaura Mendoza
Laura Mendoza
HLHongbin Li
Hongbin Li
Self-efficacy plays a central role in L2 academic writing. However, limited attention has been paid to how technology-related factors and emotions jointly shape learners' self-efficacy in L2 academic writing. Drawing on control-value theory and self-efficacy theory, this study investigates the relationships among large language model (LLM) acceptance, enjoyment, anxiety, and self-efficacy in L2 academic writing. A total of 643 Chinese EFL graduate students participated in the study, with data collected via an online questionnaire. Structural equation modelling was employed to examine hypothesized direct and indirect relationships. The results of the direct effects analysis showed that LLM acceptance positively predicted self-efficacy, enjoyment, and anxiety. Moreover, enjoyment positively predicted self-efficacy, whereas anxiety negatively predicted it. The results of the indirect effects analysis further revealed that enjoyment served as a complementary mediator, whereas anxiety acted as a competitive mediator in the link between LLM acceptance and self-efficacy. These findings highlight the dual emotional pathways through which LLM acceptance shapes self-efficacy and offer pedagogical insights into fostering students' self-efficacy in the L2 academic writing context.

9 May 2026 in International Journal of Multilingualism
Verified
Journal Article
Closed access
FSFei Sun
Fei Sun
LMLaura Mendoza
Laura Mendoza
JWJunju Wang
Junju Wang
LMLinyuan Ma
Linyuan Ma

2 September 2023 in International Journal of Educational Development
Verified
Journal Article
Open access
LMLaura Mendoza
Laura Mendoza
SLSari Lindblom-Ylänne
Sari Lindblom-Ylänne
TLTuula Lehtonen
Tuula Lehtonen
HHHeidi Hyytinen
Heidi Hyytinen