Assessing Writing最新文献

Recently, researchers are paying increasing attention to the influence of second language (L2) writers’ personal beliefs on writing learning experiences and outcomes. Drawing on the Positive Psychology approach and from a gender difference perspective, this study investigates the relationships among two important motivational factors (i.e., growth mindsets and the ideal L2 writing self) and L2 writing enjoyment, as well as the impacts of these three positive mentalities on English writing performance with 679 12th grade high school students in mainland China. Independent sample t-tests results indicated that female students had significantly better English writing performance and higher levels of the three mentalities, although the effect sizes of the differences were small. Our multi-group structural equation model reported positive associations among the three mentalities for both male and female students. Growth mindsets were more influential for male students, whereas the ideal L2 writing self more influential for female students. In terms of the influence of the three mentalities on English writing performance, only the ideal L2 writing self was a significant predictor for female students. Pedagogical suggestions are provided based on the findings.

An array of pictorial supports (e.g., emojis, geometrical figures, animals) is often used in studies assessing young students’ writing motivation with Likert scales. However, although these images may influence the students’ responses, sufficient rationales for these choices are often absent from the studies. To the best of our knowledge, the present study is the first to investigate two different types of pictorial support (circles vs. faces) in Likert scales assessing first and third graders’ writing interest, self-concept, and spelling interest and self-efficacy. The samples consist of 2197 first graders (mean age 6.8 years) and 1740 third graders (mean age 8.4 years). Results show statistically significant differences among the scales indicating that when face-scales are used, first-graders skip motivation items more often, and students in both grades avoid the minimum values of the scale more often. Gender differences are also found indicating that when face-scales are used, boys in third grade avoid maximum values more often, and girls in both grades avoid the minimum values more often. These findings suggest that the use of circle-scales compared to face-scales seem more appropriate in scales measuring young students’ writing and spelling interest and self-beliefs.

This study addresses a critical need in large-scale L2 writing assessment by emphasizing the significance of tailoring assessments to specific teaching and learning contexts. Focusing on the CET-4 writing test in China, the research unfolded in two phases. In Phase I, an empirically-developed analytic rating scale designed for the CET-4 writing test was rigorously validated. Twenty-one raters used this scale to rate 30 essays, and Many-Facets Rasch Model (MFRM) analysis was performed on the rating data. The outcomes demonstrate the scale’s robustness in effectively differentiating examinees’ writing performance, ensuring consistency among raters, and mitigating rater variation at both individual and group level. Phase II extends the research scope by applying the validated scale to score 142 CET-4 writing scripts. Utilizing Hierarchical and K-Means cluster analyses, this phase unveils three distinct score profiles. These findings are significant for both the CET-4 writing test and other L2 large-scale writing assessment. Theoretically, this study introduces a perspective that aims to enhance our understanding of learners’ performance in large-scale L2 writing assessment. Methodologically, this study presents a framework that integrates the validation of the rating scale with the identification of distinct score clusters, thus aiming to provide a more detailed solution for tailoring assessments to specific learning contexts.

Given increased prevalence of automated writing evaluation (AWE) systems in classroom settings, more research is needed to explore the potential for bias in automated scores with respect to English language learners (ELLs). Thus, this research study investigated and compared the predictive validity of automated and human scoring methods for elementary-age English ELLs on a writing test designed for ELLs and a state writing test designed for the general population. This study focused on the MI Write AWE system and sampled 2829 students comprising ELLs and non-ELLs in Grades 3–5. Results of multilevel regression analyses and simple slopes estimation indicated that, for ELLs, the automated MI Write score had similar predictive validity to the human score for both writing tests. However, automated and human scores for ELLs were less closely related to the state writing test score than scores for non-ELL students. Findings suggest that MI Write’s automated scoring was not uniquely biased relative to human scoring but does reproduce the same biases evident with human scoring. Implications and directions for future research are discussed.

Picture description (PD) tasks are widely used in second language (L2) teaching, research, and assessment to elicit and/or evaluate L2 learners’ writing performance. However, there is little research on the effects of the characteristics of such tasks on L2 writing performance. This study aimed to examine the effects of task difficulty and learner variables on the linguistic characteristics of responses to the 2020 version of the Duolingo English Test (DET) PD writing tasks. The written responses of 1439 test takers from four first language (L1) backgrounds and at different levels of L2 proficiency to 335 DET PD tasks at two levels of difficulty were analyzed and compared in terms of measures of fluency, accuracy, and complexity using various computer programs. The findings indicated that task difficulty did not affect writing performance significantly; high-proficiency learners tended to perform better than did their low-proficiency counterparts; responses receiving higher scores tended to be longer and more accurate; and learner L1 was significantly associated with writing grades and linguistic features. The findings and their implications for the DET PD task and the DET validity argument are discussed.

Research into the contribution of multimodality to language learning is gaining momentum. While most studies pave the way for new understandings of language teaching and learning, there is an increasing demand for comprehensive assessment practices, particularly within higher education contexts. A few studies have emphasized the importance of reflecting on and establishing criteria for the assessment of multimodal literacy. This is necessary to understand students’ contributions in detail and to provide them with effective support in developing their multimodal skills. This study discusses the assessment of multimodal writing in English for Specific Purposes (ESP) contexts. It presents the design of an analytical tool for assessing multimodal texts and provided an example of its application. This tool covers assessment categories such as language use, content expression, interpersonal meaning, multimodality, and creativity and originality. As an example, we focus on the multimodal writing of a video game narrative, a genre that requires the integration of multiple modes of communication to convey meaning more effectively. Finally, this study offers pedagogical insights into the assessment of multimodal literacy in ESP.