A multi-measure approach for lexical diversity in writing assessments: Considerations in measurement and timing

Woods, Kelly; Hashimoto, Brett; Brown, Earl Kjar

doi:10.1016/j.asw.2022.100688

Cited by 4 publications

(3 citation statements)

References 38 publications

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“…An independent t-test showed a significant mean score difference between the two groups, indicating that students who had additional time for writing tasks achieved higher performance. This result corroborates the hypothesis and resembles the findings from prior research (see Biola, 1982;Hale, 1992;Lee, et al, 2021;Margolis, et al, 2020;Powers and Fowles, 1996;Pusey and Butler, 2024;Woods, et al, 2023). The similar finding was also shown in the research by Mardiana, et al (2023) that was conducted in an Indonesian higher education setting.…”

Section: Resultssupporting

confidence: 91%

“…Because students' resilience in time-pressured environments is involved as construct irrelevant factor, the factual state of academic writing skill was challenged by the discrepancy in scores impacted by time-related factors (Wu & Erlam, 2016). Thus, in order to address the problems, current research on extended time allocation were conducted (see Lee, et al, 2021;Margolis, et al, 2020;Pusey and Butler, 2024;Woods, et al, 2023) but the findings were diverse.…”

Section: Introductionmentioning

confidence: 99%

“…Studies such as those by Biola (1982), Hale (1992), Knoch and Elder (2010), Lee, et al (2021), Powers and Fowles (1996), Bisriyah (2022), Pusey and Butler (2024), and Woods, et al (2023), have highlighted the significance of time allocation in writing tasks, with parts of the findings suggesting that longer time duration often lead to higher quality compositions. Similar research by Khunder and Harwood (2015) and Wu and Erlam (2016) even found that students' writing score on task achievement were significantly higher when tested without time restriction although other linguistic features were not significantly different.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the impact of time allocation on students’ writing performance: A quantitative study

Ramadhani

2024

Journal of English Language Teaching and Learning

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Many educational institutions have been conducting writing assessments to measure students’ ability in writing, yet little is known about whether time restriction and learning strategies are contributing factors to students’ performance. In Indonesian educational institutions, writing assessments serve as a means to measure students’ proficiency in articulating thoughts in the target language, providing teachers with insights into their linguistic ability. The objective of this study is to determine whether allocating extra time for timed academic essays will substantially enhance the quality of students' writing. Additionally, this study seeks to uncover the correlation between students' L2 learning strategies and their writing performance. This study used a quantitative design. The main instruments were questionnaires and writing tests collected at two parallel classes of a private university in Indonesia, comprising of 50 students in total as the study participants. The quantitative methods used independent t-tests and Spearman’s rho correlation to analyze the data. The result showed that time limit had a significant effect on writing performance (t(34.6)= 3.185, p= .003). Another result indicated minimal to no correlation between writing scores and autonomous learning practices. In conclusion, this study offers valuable and practical implications in the writing assessment industry that there should be a re-evaluation in the administration of writing assessment in educational institutions in Indonesia that truly reflects students’ writing ability.

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Section: Resultssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exploring the impact of time allocation on students’ writing performance: A quantitative study

Ramadhani

2024

Journal of English Language Teaching and Learning

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Mediating effects of NLP-based parameters on the readability of crowdsourced wikipedia articles

Setia,

Chhabra,

Arjun Verma

et al. 2024

Appl Intell

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In this era of information and communication technology, a large population relies on the Internet to gather information. One of the most popular information sources on the Internet is Wikipedia. Wikipedia is a free encyclopedia that provides a wide range of information to its users. However, there have been concerns about the readability of information on Wikipedia time and again. The readability of the text is defined as the ease of understanding the underlying text. Past studies have analyzed the readability of Wikipedia articles with the help of conventional readability metrics, such as the Flesch-Kincaid readability score and the Automatic Readability Index (ARI). Such metrics only consider the surface-level parameters, such as the number of words, sentences, and paragraphs in the text, to quantify the readability. However, the readability of the text must also take into account the quality of the text. In this study, we consider many new NLP-based parameters capturing the quality of the text, such as lexical diversity, semantic diversity, lexical complexity, and semantic complexity and analyze their impact on the readability of Wikipedia articles using artificial neural networks. Besides NLP parameters, the crowdsourced parameters also affect the readability, and therefore, we also analyze the impact of crowdsourced parameters and observe that the crowdsourced parameters not only influence the readability scores but also affect the NLP parameters of the text. Additionally, we investigate the mediating effect of NLP parameters that connect the crowdsourced parameters to the readability of the text. The results show that the impact of crowdsourced parameters on readability is partially due to the profound effect of NLP-based parameters.

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Use of lexical features in high-stakes tests: Evidence from the perspectives of complexity, accuracy and fluency

Qian

2023

Assessing Writing

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A multi-measure approach for lexical diversity in writing assessments: Considerations in measurement and timing

Cited by 4 publications

References 38 publications

Exploring the impact of time allocation on students’ writing performance: A quantitative study

Exploring the impact of time allocation on students’ writing performance: A quantitative study

Mediating effects of NLP-based parameters on the readability of crowdsourced wikipedia articles

Use of lexical features in high-stakes tests: Evidence from the perspectives of complexity, accuracy and fluency

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