Enhancing L2 learners’ lexical gains via Quizlet learning tool: the role of individual differences

Nguyen, Long Quoc; Le, Ha Van

doi:10.1007/s10639-023-11673-0

Cited by 8 publications

(7 citation statements)

References 43 publications

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“…Course designers and teachers need to be aware of this and develop test item plans that promote the appropriate depth of knowledge for high-frequency vocabulary. Additionally, pretests could be used to determine the extent to which a particular cohort already has receptive knowledge of particular word list (Sevigny & Ramonda, 2013), and then design supplemental exercises at the sentence translation and sentence writing level such as those demonstrated in Nguyen and Le (2023). Thus, midterm and final test designs for NGSL items could reasonably expect learners to demonstrate not only inflectional and derivational morpheme manipulation at the word level, but also common collocation knowledge through sentence translation for example, where complete phrases are expected in the gap.…”

Section: Ngsl Vocabulary Study System Survey Resultsmentioning

confidence: 99%

“…Most studies of vocabulary acquisition that involve Quizlet lack control groups and investigation of students’ prior vocabulary knowledge, and mainly investigate students’ perceptions of Quizlet. One study did in fact use a control group with a pretest-posttest design and semi-structured interviews to determine the effect of working memory and prior vocabulary knowledge had on retention of vocabulary learning via Quizlet with 68 Vietnamese undergraduate participants (Nguyen & Le, 2023). Results from the quasi-experimental and semi-structured interviews demonstrated that students who used Quizlet to review vocabulary significantly improved their ability to recall the L1 meanings of the target terms (Nguyen & Le, 2023).…”

Section: Literature Reviewmentioning

confidence: 99%

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High-Frequency Vocabulary: Moving From Recognition to Recall Level on Quizlet

Sevigny,

Mack,

Stilp

et al. 2024

Sage Open

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This study expands arguments calling for a more rigorous approach to high-frequency vocabulary list-based learning in EFL learning environments. Test and flashcard item designs were validated through quantitative (midterm and final test) and qualitative (survey) results to explore the impact of digital flashcards designed to build recall-level comprehension on both timed gap-fill and traditional multiple-choice posttests. Quizlet was chosen as the platform due to the affordance it provides teachers to create flashcard content and monitor practice. The results showed that multiple-choice, recognition-level test items result in a 20% overestimation of knowledge relative to gap-fill posttests. Additionally, a post-semester survey of 138 Japanese, pre-intermediate students of English showed a highly positive response to the recall-focused practice and testing system. The results demonstrate that for high-frequency L2 vocabulary, a paradigm shift from form-meaning recognition to form-meaning recall is an important direction for high-frequency vocabulary instruction and testing.

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Section: Ngsl Vocabulary Study System Survey Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

High-Frequency Vocabulary: Moving From Recognition to Recall Level on Quizlet

Sevigny,

Mack,

Stilp

et al. 2024

Sage Open

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“…Moreover, the practitioners are recommended to incorporate a swift FB feature (Hongsuchon et al, 2023; Liu & Hwang, 2023) in the OSPs to easily cope with the needs and demands of “OSPs” users. Finally, based on user feedback, practitioners can enhance the PE (Yang, 2023) of OSP users by adding features and functionality to OSPs.…”

Section: Discussionmentioning

confidence: 99%

Modeling the Consumers’ Flow Experience in E-commerce: The Integration of ECM and TAM with the Antecedents of Flow Experience

Ruangkanjanases,

Khan,

Sivarak

et al. 2024

Sage Open

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To achieve sustainable development of e-commerce and promote customers’ online shopping conduct, companies develop online shopping platforms to enhance customers’ online shopping behavior. The growing significance of technology in advertising has sparked intense interest in the worlds of education and business to create enjoyable experiences for online clients. Analyzing flow-related states is crucial for generating these experiences. Based on a combined theoretical framework comprising the antecedents of flow, the expectation confirmation model, and the technology acceptance model, this research examines how flow experiences influence the willingness to participate in online purchasing through online shopping platforms, with a focus on Chinese internet users of online shopping platforms. Three hundred internet clients were selected using the convenience sampling technique, and a survey methodology was employed to collect information from internet consumers. Findings from this study suggest that flow had a significant effect on continuous intention, perceived usefulness, and satisfaction. Furthermore, concerning flow’s antecedents, flow was significantly influenced by feedback, perceived enjoyment, and perceived vividness. Moreover, perceived usefulness and perceived ease of use were found to have substantial relationships with satisfaction and continuous intention. This research provides significant implications for research scholars and practitioners.

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“…The researcher investigated the impact of Artificial Intelligence on English Language achievement, L2 motivation and self-regulated learning and the outcomes depicted positive results in the experimental group. Other educators have employed means of technology in order to create virtual environments through which learners can actively engage in the language learning process in a facilitated way (Loncar et al, 2023;Nguyen & Le, 2023).…”

Section: Introductionmentioning

confidence: 99%

Pattern Recognition of EFL University Students’ Online Behaviors through Data Science: Any Investment on English Language Components or Skills?

Arabshahi,

Kafi,

Krummacker

et al. 2024

IJEFL

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Artificial intelligence (AI) has played a crucial role in many fields of study, and its merits and demerits have been investigated by related scholars. However, it seems a somewhat gray area when implementing AI in teaching and learning. This could be mainly because AI developers know little about learning varied sciences and they also lack pedagogical knowledge for implementing AI in teaching (Luckin & Cukurova, 2019). Therefore, the current research aimed at gathering data regarding the online behaviors of 21 Iranian EFL university students through installing an application on their mobile phones for a period of eight days. Afterwards, the collected data were analyzed through Data Science methods and varied patterns of behavior were recognized. The results exhibited that messaging and social media applications are two great parts of the students’ life. Also, there existed some common patterns regarding the applications students owned and the amount of time they spent on them. As a small case in point, the results of the study cannot be generalized; however, the outcomes highlight the proof that in an EFL context, serious steps need to be adopted by course designers and stakeholders in order to cultivate a greater and purposeful use of online learning applications, websites etc. among EFL university students so as to enhance the teaching-learning process. This gains prominence because any AI-mediated learning approach is believed to enhance students’ second/foreign language motivation as well as self-regulation in learning. AI is actually promising a revolution in the realm of language education.

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Enhancing L2 learners’ lexical gains via Quizlet learning tool: the role of individual differences

Cited by 8 publications

References 43 publications

High-Frequency Vocabulary: Moving From Recognition to Recall Level on Quizlet

High-Frequency Vocabulary: Moving From Recognition to Recall Level on Quizlet

Modeling the Consumers’ Flow Experience in E-commerce: The Integration of ECM and TAM with the Antecedents of Flow Experience

Pattern Recognition of EFL University Students’ Online Behaviors through Data Science: Any Investment on English Language Components or Skills?

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