Assessing Writing最新文献

How writing prompts influence analytic trait scores: A differential feature functioning analysis for English language learners 写作提示如何影响分析特质得分：英语学习者的差异特征功能分析

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-26 DOI: 10.1016/j.asw.2026.101018

İdil Sayın , Hacer Hande Uysal

This study examines whether analytic writing traits function equivalently across diverse thematic prompt categories for English language learners (ELLs). We utilized the ELLIPSE Corpus, which contains 6482 essays written by ELLs in response to 44 prompts during standardized annual testing in the United States. These essays were organized into six thematic prompt categories. To estimate the students’ underlying writing ability, we employed a unidimensional Item Response Theory (IRT) model. Subsequently, we conducted Differential Feature Functioning (DFF) analysis using a step-by-step ordinal logistic regression framework based on IRT. DFF analysis revealed that while Vocabulary and Grammar show statistically detectable category-related variation, effect sizes were negligible, indicating no practical impact on score interpretation. A more focused, category-by-category DFF analysis identified minor DFF in Cohesion, Vocabulary, and Grammar across the Education, Personal Development, and Society and Social Life categories, yet effects remained practically negligible. Diagnostic plots further confirmed the stability of trait functioning across prompt categories. Comprehensive sensitivity analyses supported the robustness of these findings. These results support the fairness and comparability of analytic trait-based scoring for ELL writing assessments. The study contributes to equitable writing assessment practice by offering evidence-based guidance for fair prompt design, targeted rater training, and rubric refinement.

本研究考察了分析性写作特征在不同主题提示类别中对英语学习者的作用是否相同。我们使用ELLIPSE语料库，其中包含由ELLs根据美国标准化年度测试中的44个提示撰写的6482篇文章。这些文章被组织成六个主题提示类别。为了评估学生的潜在写作能力，我们采用了一维项目反应理论（IRT）模型。随后，我们使用基于IRT的逐步有序逻辑回归框架进行了差分特征功能（DFF）分析。DFF分析显示，虽然词汇和语法表现出统计上可检测的类别相关变化，但效应大小可以忽略不计，表明对分数解释没有实际影响。一项更有针对性的逐类DFF分析发现，在教育、个人发展、社会和社会生活类别中，衔接、词汇和语法方面的DFF较小，但影响实际上仍然可以忽略不计。诊断图进一步证实了提示类别间性状功能的稳定性。综合敏感性分析支持这些发现的稳健性。这些结果支持了基于分析性特质的英语写作评分的公平性和可比性。该研究为公平的写作评估实践提供了基于证据的指导，包括公平的提示设计、有针对性的评分员培训和题型改进。

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引用次数: 0

Associations of adolescents’ argumentative writing scores and growth when evaluated by different human raters and artificial intelligence models 不同人类评分者和人工智能模型评估青少年议论文写作分数与成长的关系

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-23 DOI: 10.1016/j.asw.2026.101015

Deborah K. Reed , Sterett Mercer

Having accurate and timely information on students’ argumentative writing skills is necessary to foster their improvement. Therefore, this study explored the associations among two different human rater types (researchers and teachers) and four different artificial intelligence (AI) models when using an analytic rubric to score eighth and ninth graders' argumentative writing gathered at two time points. Results revealed that, at each time point, AI models and teacher raters generally assigned higher scores than researchers. There tended to be moderate agreement of AI model scores with researcher scores that generally exceeded the agreement of teacher scores with researchers. However, there also tended to be greater agreement among the scores from AI models compared to the agreement of AI scores with either human rater type. There were some differences by writing trait and by AI model, suggesting ChatGPT-4o scores had the strongest association with researcher scores particularly for the task and development traits. When examining growth over time, the teacher and researcher scores demonstrated positive growth, whereas the AI scores generally suggested students declined. Again, the AI models had more concordance to each other than to human estimations of growth, but there was slightly more agreement in the estimates when comparing researchers to AI than to teachers. Implications for data use and interpretation are discussed.

掌握学生议论文写作技能的准确和及时的信息对于促进他们的进步是必要的。因此，本研究探讨了两种不同的人类评判员类型（研究人员和教师）和四种不同的人工智能（AI）模型在使用分析标题对八年级和九年级学生在两个时间点收集的议论文写作进行评分时的关联。结果显示，在每个时间点，人工智能模型和教师评分者通常比研究人员给出更高的分数。人工智能模型得分与研究者得分有中等程度的一致性，通常超过教师得分与研究者得分的一致性。然而，与人工智能得分与任何一种人类评分类型的一致性相比，人工智能模型的得分之间也往往存在更大的一致性。写作特征和人工智能模型之间存在一些差异，这表明chatgpt - 40得分与研究人员得分的相关性最强，特别是在任务和发展特征方面。随着时间的推移，教师和研究人员的分数显示出正增长，而人工智能分数通常表明学生下降。同样，人工智能模型之间的一致性比人类对增长的估计要高，但在将研究人员与人工智能进行比较时，估计的一致性略高于将教师与人工智能进行比较。讨论了对数据使用和解释的影响。

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引用次数: 0

From spelling to content: The influence of spelling quality on text assessment 从拼写到内容：拼写质量对课文评价的影响

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-21 DOI: 10.1016/j.asw.2026.101014

Frederike Strahl , Jörg Kilian , Jens Möller

Background

Text assessments by different teachers can lack objectivity, with some text characteristics influencing the evaluation of others.

Aims

This research explored the halo effect of spelling quality on first language text assessment and investigated whether a prompt could reduce this effect.

Samples

Study 1 involved 134 pre-service teachers and 83 in-service teachers. Study 2 included 130 in-service teachers, who were divided into three groups.

Methods

In Study 1, participants assessed six student texts with varying overall and spelling quality on a holistic, content, style, and linguistic accuracy scale. Study 2 replicated Study 1, but additionally involved two prompting groups, emphasizing independent assessments of text characteristics.

Results

In both studies, texts with better spelling quality received higher ratings on spelling independent and spelling dependent scales, demonstrating successful manipulation and halo effects of spelling quality on content and style assessments. Study 2 showed robust halo effects in first language assessment, even after prompting.

Conclusion

The studies showed halo effects of spelling quality in text assessment, which remained stable even when prompted to reduce them. Future research should test more detailed interventions to reduce halo effects in text assessment.

不同教师对文本的评价可能缺乏客观性，某些文本特征会影响对他人的评价。目的本研究探讨拼写质量对母语文本评估的光环效应，并探讨提示是否可以降低这种效应。研究1涉及134名职前教师和83名在职教师。研究2包括130名在职教师，他们被分为三组。在研究1中，参与者从整体、内容、风格和语言准确性等方面评估了六篇整体和拼写质量不同的学生课文。研究2重复了研究1，但增加了两个提示组，强调文本特征的独立评估。结果在两项研究中，拼写质量越高的文本在拼写独立和拼写依赖量表上得分越高，这表明拼写质量对内容和风格评估的成功操纵和光环效应。研究2显示，即使在提示之后，在第一语言评估中也存在强大的光环效应。结论研究表明，在文本评估中存在拼写质量的光环效应，即使提示降低光环效应，光环效应仍保持稳定。未来的研究应该测试更详细的干预措施，以减少文本评估中的光环效应。

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引用次数: 0

Conceptual, rhetorical and linguistic transformations: Assessing L2 literature review writing using simulated tasks 概念、修辞和语言转换：用模拟任务评估第二语言文献综述写作

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-20 DOI: 10.1016/j.asw.2026.101013

Haiying Feng , Lawrence Jun Zhang , Kexin Li

This research addresses a critical gap in assessing literature review (LR) writing among L2 learner writers in terms of knowledge transformation. By integrating three strands of literature—genre analysis, source-based writing, and discourse synthesis—this study develops a framework that conceptualizes knowledge transformation along three dimensions: conceptual, rhetorical, and linguistic. It examines transforming performance of 125 Chinese students across bachelor, master, and doctoral levels through two simulated LR writing tasks, and explores the influence of factors including language proficiency and prior genre knowledge on their performance. Furthermore, it reveals the intricate interacting relationship among six transforming indicators (i.e., content units included, accuracy of information representation, extent of source integration, academic critiques and niche construction, verbatim copying, and lexico-grammatical errors). The results of textual and statistical analysis offer pedagogical implications, including enhancing compare-and-contrast practice, cultivating awareness of niche construction, and reducing L2 writers’ cognitive load in linguistic transformation.

本研究解决了从知识转化角度评估二语学习者的文献综述写作的一个关键空白。通过整合文学流派分析、基于来源的写作和话语合成这三条线索，本研究开发了一个框架，该框架将知识转换概念化，并沿着三个维度进行：概念、修辞和语言。通过两个模拟LR写作任务，研究了125名中国学生在本科、硕士和博士阶段的转化表现，并探讨了语言熟练程度和先前的体裁知识等因素对他们表现的影响。此外，它还揭示了六个转化指标（即内容单元包含、信息表示的准确性、来源整合程度、学术评论和生态位构建、逐字复制和词汇语法错误）之间错综复杂的相互关系。文本分析和统计分析的结果提供了教学启示，包括加强比较对比练习，培养小生境建构意识，减少二语作者在语言转换中的认知负荷。

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引用次数: 0

Extracting interpretable writing traits from a large language model 从大型语言模型中提取可解释的写作特征

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-01 DOI: 10.1016/j.asw.2025.101011

Paul Deane, Andrew Hoang

Large language models (LLMs) are increasingly used to support automated writing evaluation (AWE), both for purposes of scoring and feedback. However, LLMs present challenges to interpretability, making it hard to evaluate the construct validity of scoring and feedback models. BIOT (best interpretable orthogonal transformations) is a new method of analysis that makes dimensions of an embedding interpretable by aligning them with external predictors. It was originally developed to improve the interpretability of multidimensional scaling models. However, This paper shows that BIOT can be used to align LLM embeddings with an interpretable writing trait model developed using multidimensional analysis of classical NLP features to measure latent dimensions of writing style and writing quality. This makes it possible to determine whether an AWE model built using an LLM is aligned with known (and construct-relevant) dimensions of textual variation, supporting construct validity. Specifically, we examine the alignment between the hidden layers of deBERTA, a small LLM that has been shown to be useful for a variety of natural language processing applications, and a writing trait model developed through factor analysis of classical features used in existing AWE models. Specific dimensions of transformed deBERTA layers are strongly correlated with these classical factors. When the transformation matrix derived using BIOT is applied to token vectors, it is also possible to visualize which tokens in the original text contributed to high or low scores on a specific dimension.

大型语言模型（llm）越来越多地用于支持自动写作评估（AWE），既用于评分，也用于反馈。然而，llm对可解释性提出了挑战，使得评估评分和反馈模型的构造有效性变得困难。最佳可解释正交变换（BIOT）是一种新的分析方法，通过将嵌入的维度与外部预测因子对齐，使其可解释。它最初是为了提高多维尺度模型的可解释性而开发的。然而，本文表明，BIOT可以用来将LLM嵌入与一个可解释的写作特征模型结合起来，该模型使用经典NLP特征的多维分析来测量写作风格和写作质量的潜在维度。这使得确定使用LLM构建的AWE模型是否与文本变化的已知（和结构相关）维度一致成为可能，从而支持结构的有效性。具体来说，我们检查了deBERTA的隐藏层之间的一致性，deBERTA是一个小型的LLM，已被证明对各种自然语言处理应用程序有用，以及通过对现有AWE模型中使用的经典特征进行因子分析而开发的写作特征模型。变换后的deBERTA层的具体尺寸与这些经典因素密切相关。当使用BIOT导出的变换矩阵应用于标记向量时，还可以可视化原始文本中的哪些标记导致特定维度上的高分或低分。

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引用次数: 0

Assessing the effects of explicit coherence instruction on EFL students’ integrated writing performance 评估显性连贯教学对英语学生综合写作成绩的影响

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-01 DOI: 10.1016/j.asw.2026.101019

Xi Li , Mo Chen

As a key attribute of effective writing, coherence remains challenging to teach in language classrooms, with traditional writing instruction frequently overlooking coherence in favor of discrete, rule-based features. This mixed-methods study investigates the effectiveness of explicit coherence instruction on English-as-a-Foreign-Language (EFL) students’ performance on integrated writing tasks. The study employed a controlled experimental design with 64 upper-intermediate-level undergraduate students at a Chinese university, drawing on Hasan’s Cohesive Harmony theory as the theoretical framework. Half of the participants (n = 32) in the experimental group received explicit instruction on coherence with a focus on cohesive chains and cohesive devices in integrated writing, while the control group (n = 32) received standard paraphrasing instruction. Quantitative analysis revealed that the experimental group showed significant improvements in coherence scores and multiple cohesive chain measures. Qualitative discourse analysis of six students’ writing samples from the experimental group demonstrated varying levels of improvement in writing coherence, with high-performing students showing better use of identity chains and pronoun references. The findings revealed that explicit instruction on coherence significantly improved students’ performance in creating coherent integrated writing, particularly through the development of cohesive chains and appropriate use of cohesive devices. This study underscores the pedagogical value of teaching coherence to enhance writing quality and provides concrete strategies for developing more effective teaching approaches for integrated writing tasks in EFL contexts.

作为有效写作的一个关键属性，连贯在语言课堂教学中仍然具有挑战性，传统的写作教学经常忽视连贯，而倾向于离散的、基于规则的特征。本研究旨在探讨显性连贯教学对英语作为外语学生完成综合写作任务的影响。本研究采用对照实验设计，以国内某高校64名中上水平本科生为研究对象，以哈桑的内聚和谐理论为理论框架。实验组中一半的参与者（n = 32）接受了关于连贯的明确指导，重点是连贯链和综合写作中的衔接手段，而对照组（n = 32）接受了标准的释义指导。定量分析显示，实验组在连贯性评分和多项内聚链测量方面均有显著改善。对实验组六名学生写作样本的定性语篇分析表明，他们在写作连贯性方面有不同程度的提高，表现优异的学生在身份链和代词引用方面表现得更好。研究结果表明，连贯的明确指导显著提高了学生在连贯综合写作方面的表现，特别是通过发展连贯链和适当使用连贯手段。本研究强调了连贯教学对提高写作质量的教学价值，并为开发更有效的英语综合写作教学方法提供了具体的策略。

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引用次数: 0

Volume 67 editorial 第67卷社论

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-01 DOI: 10.1016/j.asw.2026.101016

Martin East , David Slomp

引用次数: 0

Is it beneficial to strive for perfection in writing?: Exploring the relationship between perfectionism, motivational regulation, and second language (L2) writing performance 在写作中力求完美有益吗？研究完美主义、动机调节与第二语言写作表现之间的关系

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2026-01-01 DOI: 10.1016/j.asw.2025.101012

Li Dong

Perfectionism, a personality trait characterized by the pursuit of flawlessness and high personal standards, and motivational regulation, the strategies through which individuals manage their motivational states, have received limited attention in second language (L2) writing. Framed within social cognitive theory, this study examines how two dimensions of perfectionism—perfectionistic strivings and perfectionistic concerns—relate to writing performance (syntactic complexity, accuracy, lexical complexity, and fluency) and how motivational regulation sub-strategies (interest enhancement, self-talk, and emotional control) mediate these relationships. Data from 689 university students in China were analyzed using questionnaires and argumentative writing samples. Results indicated that perfectionistic strivings positively predicted syntactic complexity, accuracy, and lexical complexity, while perfectionistic concerns negatively predicted these dimensions; neither dimension significantly affected fluency. Crucially, motivational regulation sub-strategies partially mediated the relations between perfectionism and writing performance. These findings underscore the importance of distinguishing perfectionism dimensions and targeting motivational regulation strategies to improve L2 writing. Implications for instruction and directions for future longitudinal research are discussed.

完美主义是一种追求完美和高标准的人格特征，而动机调节是个体管理动机状态的策略，这两种人格特征在第二语言写作中受到的关注有限。在社会认知理论的框架下，本研究探讨了完美主义的两个维度——完美主义的努力和完美主义的关注——与写作表现（句法复杂性、准确性、词汇复杂性和流畅性）的关系，以及动机调节子策略（兴趣增强、自我对话和情绪控制）如何调节这些关系。通过问卷调查和议论文样本分析了689名中国大学生的数据。结果表明，完美主义努力正向预测句法复杂性、准确性和词汇复杂性，而完美主义关注负向预测句法复杂性、准确性和词汇复杂性；这两个维度对流利程度都没有显著影响。重要的是，动机调节子策略在完美主义与写作表现之间起到部分中介作用。这些发现强调了区分完美主义维度和有针对性的动机调节策略对提高二语写作的重要性。最后讨论了今后纵向研究的指导意义和方向。

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引用次数: 0

Unveiling the antecedents of feedback-seeking behavior in L2 writing: The impact of future L2 writing selves and emotions 揭示二语写作中反馈寻求行为的前因：未来二语写作自我和情绪的影响

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2025-12-17 DOI: 10.1016/j.asw.2025.101009

Jia Li , Lawrence Jun Zhang

While existing research on second or foreign (L2) feedback has predominantly focused on the effectiveness of various feedback practices and their impacts on writing performance, limited attention has been devoted to learners’ proactive role in seeking feedback, and how this important yet underexplored construct correlates with conative and affective variables remains insufficiently examined. To help fill that void, we sought to explore the concept of feedback-seeking behavior and its antecedents in L2 writing by examining the correlations with future L2 writing selves and emotions, particularly unpacking the mediating effect of emotions in the emotion-driven chain of “motivation→emotion→increased or decreased behavior” among 225 undergraduate English major students. Structural equation modeling unveiled that ideal and ought-to L2 writing selves directly and significantly influenced emotions, and emotions impacted the two dimensions of feedback-seeking behavior significantly. More importantly, ideal L2 writing self indirectly influenced feedback monitoring and feedback inquiry through the mediation of writing enjoyment. Nevertheless, writing boredom exercised no significant mediating effect on future L2 selves and feedback-seeking behavior. These findings reinforced the learner-centered perspective that positions students as proactive agents and provide some notable implications for L2 writing instruction to advance our understanding of teacher feedback.

虽然现有的关于第二语言或外语反馈的研究主要集中在各种反馈实践的有效性及其对写作表现的影响上，但对学习者在寻求反馈方面的积极作用的关注有限，以及这一重要但未被充分探索的结构与意蕴和情感变量之间的关系仍未得到充分研究。为了填补这一空白，本研究通过对225名英语专业本科生的调查，探讨了反馈寻求行为的概念及其在二语写作中的前因，研究了反馈寻求行为与未来二语写作自我和情绪之间的关系，特别是揭示了情绪在“动机→情绪→行为增加或减少”的情绪驱动链中的中介作用。结构方程模型揭示了理想自我和二语写作自我对情绪的直接显著影响，情绪对反馈寻求行为的两个维度均有显著影响。更重要的是，理想的二语写作自我通过写作享受的中介间接影响反馈监控和反馈查询。然而，写作无聊对未来二语自我和反馈寻求行为没有显著的中介作用。这些发现强化了以学习者为中心的观点，将学生定位为积极主动的主体，并为第二语言写作教学提供了一些显著的启示，以促进我们对教师反馈的理解。

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引用次数: 0

Beyond the page: A multimodal self-efficacy framework for assessing L2 digital-academic writing 网页之外：评估第二语言数字学术写作的多模态自我效能框架

IF 5.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Assessing Writing

Pub Date : 2025-12-13 DOI: 10.1016/j.asw.2025.101010

Ke Li , Ying Hong , Chen Hao

As academic writing becomes increasingly digital and multimodal, traditional assessments of L2 writing self-efficacy—centered exclusively on print-based, monomodal tasks—inadequately represent learners' confidence in contemporary composition practices. While existing self-efficacy instruments have advanced our understanding of writing beliefs, including recent multidimensional scales and emerging work on multimodal processes, no validated tool specifically measures L2 writers' perceived efficacy in performing integrated multimodal academic writing tasks. This gap is particularly consequential as EAP assessments increasingly require students to synthesize audio, visual, and textual sources within digitally mediated writing environments—demands that extend beyond the constructs captured by existing scales. This study introduces and validates the Multimodal Academic Writing Self-Efficacy Scale (MAWSE), designed to assess L2 writers' beliefs about their capabilities in four theoretically distinct dimensions: digital content comprehension (interpreting multimodal sources), multimodal discourse synthesis (integrating cross-modal information), genre and format navigation (adapting to multimodal conventions), and self-regulation across digital platforms (managing multimodal composing processes). Using a sequential mixed-methods design, we gathered data from 1063 EFL university students across three institutional contexts in China. Qualitative think-aloud protocols informed item development, while exploratory and confirmatory factor analyses established construct validity. Multi-group invariance testing confirmed measurement equivalence across key and non-key university groups, and structural equation modeling revealed that MAWSE scores significantly predicted performance on scenario-based academic writing tasks involving integrated multimodal sources (β = 0.41, p < .01). The findings offer a psychometrically robust, construct-relevant tool that extends existing self-efficacy frameworks into the multimodal domain, addressing an empirical gap while supporting more accurate and equitable assessment practices in digitally enriched EAP contexts. This research contributes to evolving scholarship by validating an instrument aligned with the realities of contemporary academic communication.

随着学术写作变得越来越数字化和多模式，传统的第二语言写作自我效能评估——仅仅以基于印刷的、单一模式的任务为中心——不足以代表学习者对当代写作实践的信心。虽然现有的自我效能工具已经提高了我们对写作信念的理解，包括最近的多维尺度和关于多模式过程的新兴工作，但没有经过验证的工具专门衡量第二语言作者在执行综合多模式学术写作任务时的感知效能。随着EAP评估越来越多地要求学生在数字媒介的写作环境中综合音频、视觉和文本资源，这一要求超出了现有量表所捕获的结构，这一差距尤其重要。本研究引入并验证了多模态学术写作自我效能量表（MAWSE），该量表旨在从四个理论上不同的维度评估二语作者对自己能力的信念：数字内容理解（解释多模态来源）、多模态话语合成（整合跨模态信息）、体裁和格式导航（适应多模态惯例）以及跨数字平台的自我调节（管理多模态写作过程）。采用顺序混合方法设计，我们收集了来自中国三个机构背景下的1063名英语大学学生的数据。定性的有声思考协议为项目开发提供了信息，而探索性和验证性因素分析建立了结构效度。多组不变性检验证实了重点大学组和非重点大学组之间的测量等效性，结构方程模型显示，MAWSE分数显著预测了涉及综合多模态来源的基于场景的学术写作任务的表现（β = 0.41, p <； .01）。研究结果提供了一种心理测量学上稳健的、与构建相关的工具，将现有的自我效能框架扩展到多模态领域，解决了经验差距，同时支持在数字化丰富的EAP背景下更准确、更公平的评估实践。这项研究通过验证一种符合当代学术交流现实的工具，为不断发展的学术做出了贡献。

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引用次数: 0