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2014 » Papers » Volume 1 » PAPER VS. SLIDES: DO THEY HAVE SIMILAR TEXTUAL TRAITS? 1. PAPER VS. SLIDES: DO THEY HAVE SIMILAR TEXTUAL TRAITS? Authors: Stavarache Larise, Trausan-Matu Stefan, Dascalu Mihai, Dessus Philippe Volume 1 | DOI: 10.12753/2066-026X-14-026 | Pages: 184-192 | Download PDF | Abstract
Abstract: Every e-learning teacher proposes presentation slides to learners who often stem from larger and more complex lecture notes. Delivering both these learning formats has become the cornerstone of every university e-learning course, and even MOOCs (Massive Open Online Courses) are often based on them. However, discrepancies between these formats in terms of complexity have not been quantitatively analyzed so far. This study aims at performing a detailed comparison between these modalities using variations of textual complexity metrics as background, ranging from surface, syntactic, morphological and semantic factors. The analyzed corpora are automatically extracted from MOOC materials and encompass multiple domains: history, politics, geography and culture, in order to induce diversity and to observe different inter-domain presentation characteristics. As an overview, there are high variations in terms of proportions (slides per lecture note page), underlying structures and individual word complexities. Although words on slides generally tend to be less complex than on lecture notes (nor too simple), the significant reduce of stop words and of connectors shifts the balance in terms of frequently used quantitative complexity factors. If the initial decrease in individual word complexities should denote a decrease in the perceived difficulty, the latter computational perspective determined by the elimination of irrelevant words that usually tend to be small in length, artificially increases the perceived complexity level. Moreover, the lower cohesion between bullet items from presentations, in contrast to adjacent sentences from the same paragraph extracted from lecture notes, negatively influences the overall variation of the complexity scores. In the end, we conclude by providing a set of required metrics for supporting teachers in the adaptation of their learning materials. | Keywords
Keywords: textual complexity; readability; MOOCs; discourse analysis. |
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