Writing pal: Feasibility of an intelligent writing strategy tutor in the high school classroom.

Roscoe, Rod D.; McNamara, Danielle S.

doi:10.1037/a0032340

Cited by 106 publications

(57 citation statements)

References 47 publications

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“…Moreover, asynchronous interaction among students through expository or persuasive writing may also be considered an opportunity for communication (Drew, Olinghouse, Faggella‐Luby, & Welsh, ). Because communicative abilities are widely regarded as critical for future school and career success across a number of domains of learning (e.g., Beaufort, ; Roscoe & McNamara, ), opportunities to practice and develop such abilities were considered indicators of deeper learning here.…”

Section: Review Of Relevant Scholarship: Construct Specificationmentioning

confidence: 99%

Development and calibration of the student opportunities for deeper learning instrument

Dumas

Dong

2019

Psychology in the Schools

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This article describes the development and calibration of the student opportunities for deeper learning instrument (SODLI). The SODLI is designed to measure the amount of learning opportunities intended to support higher‐order thinking that students are exposed to through student self‐report, and is expected to be widely useful in psychological research in schools. Here, the psychometric functioning of the SODLI is investigated in a relatively large sample of U.S. high‐school students (N = 963). Using multidimensional item‐response theory methods, a nine‐factor correlated model is determined to fit the data best, and to produce reliable estimates of SODLI dimensions. The SODLI is also shown to exhibit scalar‐invariant measurement properties across sex, race/ethnicity, and language‐background groups, although latent mean differences on some of the SODLI dimensions across those groups were identified.

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Section: Review Of Relevant Scholarship: Construct Specificationmentioning

confidence: 99%

Development and calibration of the student opportunities for deeper learning instrument

Dumas

Dong

2019

Psychology in the Schools

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“…According to research, AEA scoring tends to be accurate. Some AEA systems have become embedded within automated writing evaluation systems that assign scores and give feedback on errors, and may include instructional scaffolding and learning management tools (Roscoe and McNamara, 2013).…”

Section: Semantic Technologies Are Helping With the Challengementioning

confidence: 99%

Using Semantic Technologies for Formative Assessment and Scoring in Large Courses and MOOCs

Lancho¹,

Hernández²,

Paniagua³

et al. 2018

Journal of Interactive Media in Education

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Formative assessment and personalised feedback are commonly recognised as key factors both for improving students' performance and increasing their motivation and engagement (Gibbs and Simpson, 2005). Currently, in large and massive open online courses (MOOCs), technological solutions to give feedback are often limited to quizzes of different kinds. At present, one of our challenges is to provide feedback for open-ended questions through semantic technologies in a sustainable way.To face such a challenge, our academic team decided to use a test based on latent semantic analysis (LSA) and chose an automatic assessment tool named G-Rubric. G-Rubric was developed by researchers at the Developmental and Educational Psychology Department of UNED (Spanish national distance education university). By using G-Rubric, automated formative and iterative feedback was provided to students for different types of open-ended questions (70-800 words). This feedback allowed students to improve their answers and writing skills, thus contributing both to a better grasp of concepts and to the building of knowledge.In this paper, we present the promising results of our first experiences with UNED business degree students along three academic courses (2014-15, 2015-16 and 2016-17). These experiences show to what extent assessment software such as G-Rubric is mature enough to be used with students. It offers them enriched and personalised feedback that proved entirely satisfactory. Furthermore, G-Rubric could help to deal with the problems related to manual grading, even though our final goal is not to replace tutors by semantic tools, but to give support to tutors who are grading assignments.

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“…A third system, Writing-Pal (W-Pal), was designed to tutor writing skills relevant to argument essays (McNamara et al 2012). Writing-Pal features automated essay assessment that gives students feedback on their writing skills (Roscoe and McNamara 2013).…”

Section: Reading Comprehension Strategy Tutoringmentioning

confidence: 99%

AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring

Nye

Graesser

2014

Int J Artif Intell Educ

173

107

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AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages of natural language tutoring are presented. Next, we review three central themes in AutoTutor's development: human-inspired tutoring strategies, pedagogical agents, and technologies that support natural-language tutoring. Research on early versions of AutoTutor documented the impact on deep learning by co-constructed explanations, feedback, conversational scaffolding, and subject matter content. Systems that evolved from AutoTutor added additional components that have been evaluated with respect to learning and motivation. The latter findings include the effectiveness of deep reasoning questions for tutoring multiple domains, of adapting to the affect of low-knowledge learners, of content over surface features such as voices and persona of animated agents, and of alternative tutoring strategies such as collaborative lecturing and vicarious tutoring demonstrations. The paper also considers advances in pedagogical agent roles (such as trialogs) and in tutoring technologies, such semantic processing and tutoring delivery platforms. This paper summarizes and integrates significant findings produced by studies using AutoTutor and related systems.

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Writing pal: Feasibility of an intelligent writing strategy tutor in the high school classroom.

Cited by 106 publications

References 47 publications

Development and calibration of the student opportunities for deeper learning instrument

Development and calibration of the student opportunities for deeper learning instrument

Using Semantic Technologies for Formative Assessment and Scoring in Large Courses and MOOCs

AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring

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