By Mihai Dascălu
With the arrival and lengthening approval for computing device Supported Collaborative studying (CSCL) and e-learning applied sciences, the necessity of automatic review andof teacher/tutor support for the 2 tightly intertwined actions of comprehension of interpreting fabrics and of collaboration between friends has grown considerably. during this context, a polyphonic version of discourse derived from Bakhtin’s paintings as a paradigm is used for studying either normal texts and CSCL conversations in a special framework interested by various features of textual cohesion.
As specificity of our research, the individual learning viewpoint is targeted at the id of studying innovations and on offering a multi-dimensional textual complexity version, while the collaborative learning measurement is headquartered at the assessment of individuals’ involvement, in addition to on collaboration assessment.
Our strategy in accordance with complicated traditional Language Processing strategies offers a qualitative estimation of the training strategy and complements figuring out as a “mediator of studying” by means of delivering automatic suggestions to either beginners and lecturers or tutors. the most merits are its flexibility, extensibility and however specificity for masking a number of levels, ranging from studying school room fabrics, to discussing on particular issues in a collaborative demeanour and completing the suggestions loop through verbalizing metacognitive thoughts.
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Extra resources for Analyzing Discourse and Text Complexity for Learning and Collaborating: A Cognitive Approach Based on Natural Language Processing
2012). 2 Textual Complexity 19 2012a). In terms of text cleaning, ATOS is specific in contrast to other systems, as the user is not required to perform cleaning on the input text if its dimension is considerable; in this case, the complexity level emerges from the overall document. Degrees of Reading Power (DRP) Analyzer (Koslin et al. 1987; Zeno et al. 1995) uses a derivation of a Bormuth mean cloze readability formula (Bormuth 1969, 1966) based on three features: word length, sentence length and word familiarity (Nelson et al.
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