Text-based writing of low-skilled postsecondary students: relation to comprehension, self-efficacy and teacher judgments

Perin, Dolores; Lauterbach, Mark D.; Raufman, Julia; Kalamkarian, Hoori Santikian

doi:10.1007/s11145-016-9706-0

Cited by 25 publications

(11 citation statements)

References 57 publications

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“…Likewise, the inclusion of revising in the state test may have resulted in better alignment with the nature of the AWE intervention. Considering this improved alignment and considering the direct effects of AWE on self-efficacy and the relationship between self-efficacy and writing performance (Pajares, 2003; Pajares & Johnson, 1996; Perin, Lauterbach, Raufman, & Kalamkarian, 2017), including performance on state literacy assessments (Bruning et al., 2013), may explain why there were no effects of composing condition on the researcher-administered writing prompt but there were effects on the state test.…”

Section: Discussionmentioning

confidence: 99%

Automated Writing Evaluation and Feedback: Multiple Metrics of Efficacy

Wilson

Roscoe

2019

Journal of Educational Computing Research

106

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The present study extended research on the effectiveness of automated writing evaluation (AWE) systems. Sixth graders were randomly assigned by classroom to an AWE condition that used Project Essay Grade Writing ( n = 56) or a word-processing condition that used Google Docs ( n = 58). Effectiveness was evaluated using multiple metrics: writing self-efficacy, holistic writing quality, performance on a state English language arts test, and teachers' perceptions of AWE's social validity. Path analyses showed that after controlling for pretest measures, composing condition had no effect on holistic writing quality, but students in the AWE condition had more positive writing self-efficacy and better performance on the state English language arts test. Posttest writing self-efficacy partially mediated the effect of composing condition on state test performance. Teachers reported positive perceptions of AWE's social validity. Results emphasize the importance of using multiple metrics and considering both contextual factors and AWE implementation methods when evaluating AWE effectiveness.

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Section: Discussionmentioning

confidence: 99%

Automated Writing Evaluation and Feedback: Multiple Metrics of Efficacy

Wilson

Roscoe

2019

Journal of Educational Computing Research

106

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“…Empirical evidence supports the conclusion that summarization strategies are effective for different types of learners, including native speakers (Britt & Sommer, 2004;Leopold, Sumfleth, & Leutner, 2013;Trabasso & Bouchard, 2002;Westby, Culatta, Lawrence, & Hall-Kenyon, 2010), language learners (Baleghizadeh & Babapur, 2011;Chiu, 2015;Oded & Walters, 2001;Shokrpour, Sadeghi, & Seddigh, 2013), students with learning disabilities (Jitendra, Cole, Hoppes, & Wilson, 1998;Jitendra, Hoppes, & Xin, 2000;Rogevich & Perin, 2008), and students with low literacy skills Perin, Lauterbach, Raufman, & Kalamkarian, 2016). Moreover, summarization is more efficient and effective in improving student learning than are other formats of assessment, such as short-answer comprehension questions (Carroll, 2008;Shokrpour et al, 2013), argument essay writing (Gil, Bråten, Vidal-Abarca, & Strømsø, 2010), multiple-choice questions, and fill-in-the-blank questions (Mok & Chan, 2016).…”

Section: Related Literature Summary Writingmentioning

confidence: 71%

Computerized summary scoring: crowdsourcing-based latent semantic analysis

Cai

Graesser

2017

Behav Res

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In this study we developed and evaluated a crowdsourcing-based latent semantic analysis (LSA) approach to computerized summary scoring (CSS). LSA is a frequently used mathematical component in CSS, where LSA similarity represents the extent to which the to-be-graded target summary is similar to a model summary or a set of exemplar summaries. Researchers have proposed different formulations of the model summary in previous studies, such as pregraded summaries, expert-generated summaries, or source texts. The former two methods, however, require substantial human time, effort, and costs in order to either grade or generate summaries. Using source texts does not require human effort, but it also does not predict human summary scores well. With human summary scores as the gold standard, in this study we evaluated the crowdsourcing LSA method by comparing it with seven other LSA methods that used sets of summaries from different sources (either experts or crowdsourced) of differing quality, along with source texts. Results showed that crowdsourcing LSA predicted human summary scores as well as expert-good and crowdsourcing-good summaries, and better than the other methods. A series of analyses with different numbers of crowdsourcing summaries demonstrated that the number (from 10 to 100) did not significantly affect performance. These findings imply that crowdsourcing LSA is a promising approach to CSS, because it saves human effort in generating the model summary while still yielding comparable performance. This approach to small-scale CSS provides a practical solution for instructors in courses, and also advances research on automated assessments in which student responses are expected to semantically converge on subject matter content.

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“…The purpose of this research paper is to investigate the correlation between reading comprehension skills level and composition writing performance of low intermediate-level EFL underachievers participating in a strategic reading instructional program. Writing skill depends on a complex interweaving cognitive, linguistic and affective processes since the writer needs to rapidly retrieve knowledge from long term memory, manage working memory and attention, express ideas cohesively in verbal form and think clearly about topics (Kellogg & Whiteford, 2009 as cited by Perin, Lauterbach, Raufman & Kalamkarian, 2016) and to be a competent writer, learners need to form coherent sentences with correct spelling, capitalization, adequate semantic and syntactic structure to convey their intended meaning to the reader. On the other hand, reading comprehension necessitates the reader to retain and integrate information in short term memory and deploy higher-level text-processing skills such as drawing inferences to fill in gaps in understanding, making connections within sentences and relating information from different parts of the text to maintain both local cohesion and global coherence which in turn affects the reader's orthographic, morphological, lexical, syntactic, and discourse features (Berninger, 2000;Shanahan, 1984;Shanahan & Lomax, 1986 as cited by Shanahan, 2006).…”

Section: Literature Reviewmentioning

confidence: 99%

The Relationship Between EFL Underachievers’ Reading Comprehension Skills and their Writing Performance

العزیز¹,

الخبیری²,

امام³

2020

مجلة جامعة الفیوم للعلوم التربویة والنفسیة

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The present research paper is a correlation study that aimed at exploring the relationship between reading comprehension skills level and composition writing performance for EFL underachievers. The study sample was 80 low intermediate-level students at El Tawfik Preparatory school for girls in El Fayoum Governorate in their first semester of the academic year (2018/2019). The participants' age ranged between twelve and thirteen years old. The low achieving students were selected based on their scores in the reading comprehension and achievement pre-tests. The lowest 25% of them were considered underachievers. The measurement instruments were (1) a reading comprehension skills test (the post-test version, Form B) and (2) a composition writing task. The two instruments were prepared by the researcher. Pearson correlation coefficient between the two study variables was computed. Results indicated a statistically significant positive correlation between reading comprehension skills level and composition writing performance in EFL at (0.01) level. That is, the higher students' scores in reading comprehension skills, the higher their scores in EFL composition writing and vice versa. Practical implications of these findings are discussed.

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Text-based writing of low-skilled postsecondary students: relation to comprehension, self-efficacy and teacher judgments

Cited by 25 publications

References 57 publications

Automated Writing Evaluation and Feedback: Multiple Metrics of Efficacy

Automated Writing Evaluation and Feedback: Multiple Metrics of Efficacy

Computerized summary scoring: crowdsourcing-based latent semantic analysis

The Relationship Between EFL Underachievers’ Reading Comprehension Skills and their Writing Performance

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