Blended e-learning skeleton of conversation: improving formative assessment in undergraduate dissertation supervision

The supervision of undergraduate student dissertations is an area in need of research. Although some studies have already addressed this, these are primarily based on academic staff responses. This study contributes to knowledge by gathering the responses of students and focusing on formative electronic assessment. Data was collected using a student focus group and student questionnaire. The findings suggest that good supervisor-student communication is crucial to the supervision process and a number of students felt unhappy with this aspect. It is suggested that to improve the undergraduate student dissertation experience, a combination of face-to-face and electronic formative assessment is used. In addition, the Blended E-learning Skeleton of Conversation model provides a sound theoretical framework that could guide supervisors and students in the supervision process. This model is advocated for use in dissertation module design and in supervisor development

Text-based recall and extra-textual generations resulting from simplified and authentic texts

This study uses a moving windows self-paced reading task to assess text comprehension of beginning and intermediate-level simplified texts and authentic texts by L2 learners engaged in a text-retelling task. Linear mixed effects (LME) models revealed statistically significant main effects for reading proficiency and text level on the number of text-based propositions recalled: More proficient readers recalled more propositions. However, text level was a stronger predictor of propositional recall than reading proficiency. LME models also revealed main effects for language proficiency and text level on the number of extra-textual propositions produced. Text level, however, emerged as a stronger predictor than language proficiency. Post-hoc analyses indicated that there were more irrelevant elaborations for authentic texts and intermediate and authentic texts led to a greater number of relevant elaborations compared to beginning texts

Text readability and intuitive simplification: A comparison of readability formulas

Texts are routinely simplified for language learners with authors relying on a variety of approaches and materials to assist them in making the texts more comprehensible. Readability measures are one such tool that authors can use when evaluating text comprehensibility. This study compares the Coh-Metrix Second Language (L2) Reading Index, a readability formula based on psycholinguistic and cognitive models of reading, to traditional readability formulas on a large corpus of texts intuitively simplified for language learners. The goal of this study is to determine which formula best classifies text level (advanced, intermediate, beginner) with the prediction that text classification relates to the formulas’ capacity to measure text comprehensibility. The results demonstrate that the Coh-Metrix L2 Reading Index performs significantly better than traditional readability formulas, suggesting that the variables used in this index are more closely aligned to the intuitive text processing employed by authors when simplifying texts

What's so simple about simplified texts? A computational and psycholinguistic investigation of text comprehension and text processing

This study uses a moving windows self-paced reading task to assess both text comprehension and processing time of authentic texts and these same texts simplified to beginning and intermediate levels. Forty-eight second language learners each read 9 texts (3 different authentic, beginning, and intermediate level texts). Repeated measures ANOVAs reported linear effects of text type on reading time (normalized for text length) and true/false comprehension scores indicating that beginning level texts were processed faster and were more comprehensible than intermediate level and authentic texts. The linear effect of text type on comprehension remained significant within an ANCOVA controlling for language proficiency (i.e., TOEFL scores), reading proficiency (i.e., Gates-MacGinitie scores), and background knowledge, but not for reading time. Implications of these findings for materials design, reading pedagogy, and text processing and comprehension are discussed

Critical perspectives on writing analytics

Writing Analytics focuses on the measurement and analysis of written texts for the purpose of understanding writing processes and products, in their educational contexts, and improving the teaching and learning of writing. This workshop adopts a critical, holistic perspective in which the definition of "the system" and "success" is not restricted to IR metrics such as precision and recall, but recognizes the many wider issues that aid or obstruct analytics adoption in educational settings, such as theoretical and pedagogical grounding, usability, user experience, stakeholder design engagement, practitioner development, organizational infrastructure, policy and ethics

Ariel - Volume 10 Number 5

Executive Editors Madalyn Schaefgen David Reich Business Manager David Reich News Editors Medical College Edward Zurad CAHS John Guardiani World Mark Zwanger Features Editors Meg Trexler Jim O\u27Brien Editorials Editor Jeffrey Banyas Photography and Sports Editor Stuart Singer Commons Editor Brenda Peterso