Interactional coherence in asynchronous learning networks: A rhetorical approach

The main purpose of the study is to determine the effect of asynchronous learning to academic performance and students’ motivation towards Science. It is necessary since motivation serves as a foundation for better understanding of science concepts in an asynchronous setting. The respondents are 201 grade 11 students of Iligan Computer Institute (ICI) who are enrolled during the Academic Year 2020-2021. The ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model was used in the study for the development of asynchronous lesson on Genetic Engineering with Google Classroom as the online platform. The research utilized SMTSL (Students Motivation Towards Science Learning) questionnaire developed by Tuan, et al. (2005) composed of 35 questions encompassing six (6) domains of motivation namely, self-efficacy, active learning strategies, science learning value, performance goal, achievement goal and learning environment stimulation. Quantitative data together with qualitative analysis showed that students are moderately motivated towards science learning in an asynchronous environment. The highest identified domain is science learning value indicating that students find the relevance of science with daily life which makes them motivated to learn science even in a remote learning environment where there is no direct contact and supervision. In contrast, self-efficacy and performance goal are the least domains suggesting that students are least concerned with their own ability to perform well in science learning tasks and they do not compete with other students and get attention from the teacher. Using the researcher-made achievement test and performance task to measure their academic performance, 80% of the students belong to approaching proficiency, proficient and advanced groups showing that students did well in science in an asynchronous learning environment. Moreover, students’ motivation was significantly correlated with science academic performance so science academic performance can be used as indirect evidence of students’ motivation. Based on these findings, it is recommended that curriculum experts and educators consider factors of motivation in revisiting the science curriculum in an asynchronous environment.

Women are under-represented in technology-intensive fields. Arguments abound on the question are there true gender differences. Some see the Internet as the great equalizer. Some studies have shown the gender gap to be narrowing in certain online activities. Distance education often uses discussion forum postings as one of the common learning activities. This research reports on a study with doctoral level students in both a technology intensive class and a more people-oriented class. The directionality of forum discussion postings were examined from both a within gender perspective and a cross gender perspective. The findings did show that the postings in this Asynchronous Learning Environment (ALN) were gender-neutral. In addition, two different configurations were examined: a free-form posting and a structured posting. These configurations were examined from a gender perspective and no difference was found. Lastly, the nature of the program of study was examined in regards to level of interactivity related to gender. Again, there were no significant differences found. This research did demonstrate that an ALN can be perceived as a gender-neutral environment.

Recent events have focused more attention on online learning including strategies for overcoming feelings of disconnection and isolation in an asynchronous environment. The purpose of this action research was to understand communication and collaboration in asynchronous learning environments to improve the implementation of instructional practices using communities of practice, a generative theoretical framework. Twelve educators participating in asynchronous courses were interviewed using action research methodology to understand their experiences learning online. Findings of this study identified lack of communication that may lead to feelings of disconnection and isolation among students. Subsequently, action steps were created intended to increase communication and collaboration in asynchronous learning environments. This action steps' evaluation indicated students may better connect and better develop meaningful relationships with increased communication and collaboration opportunities using a Communities of Practice (CoP) model. Additionally, teachers' professional development using this model situates individual and collective learning in the important work of facilitating growth and development for a community of teachers. --Author's abstract

The present study investigated (1) the impact of cognitive styles on learner performance in well-structured and ill-structured learning, and (2) scaffolding as a cognitive tool to improve learners' cognitive abilities, especially field dependent (FD) learners' ability to thrive in an ill-structured learning environment. Two experiments were conducted with 116 college students recruited from a large research I university in the west of the United States. Experiment 1 ( n = 42) employed the group learning strategy to match learners' cognitive styles in asynchronous online learning. The results showed that the style matching strategy failed to yield expected gains in ill-structured asynchronous learning for FD learners. Different from the style-matching strategy, experiment 2 ( n = 74) used a scaffolding model proposed by Cazden (1988) to improve FD learners' cognitive abilities in asynchronous online learning. Results indicated that focusing on learners' cognitive abilities proved to be more effective than style-matching strategy for FD learners in both ill-structured and well-structured asynchronous online learning. Implications of the findings were discussed with suggestions for future research.

This study investigates the (re)creation of rhetorical structure, a crucial aspect of coherence that plays an important part in establishing functional equivalence in translation. While considerable amount of research is available on certain aspects of coherence, little attention has been devoted to the translation of rhetorical structure, despite its acknowledged significance in discourse processing (Hatim and Mason 1990, Mann et al. 1992, Nord 1997, Tirkkonen-Condit 2002). Based on Rhetorical Structure Theory (Mann and Thompson 1986), this study aims to generate initial hypotheses regarding the (re)creation of rhetorical structure in Hungarian-English news translation and demonstrate the interplay between rhetorical and discourse structure, with a view to highlighting the significance of rhetoric in producing functionally adequate translations. Findings indicate that while no statistically significant shifts occur in the quantity of relational propositions in source texts and translations, considerable shifts may be identified in the quality and position of certain relational propositions . These shifts affect the rhetorical as well as generic structure of the target text and thus exert a very subtle influence on the way it is interpreted by the reader.

Rhetorical Structure Theory (RST) is a theory of text structure that is being extended to serve as a theoretical basis for computational text planning. Text structures in RST are hierarchic, built on small patterns called schemas. The schemas which compose the structural hierarchy of a text describe the functions of the parts rather than their form characteristics. Relations between text parts, comparable to conjunctive relations, are a prominent part of RST’s definitional machinery. Recent work has put RST onto a new definitional basis. This paper details the current status of descriptive RST, along with efforts to create a constructive version for use as a basis for programming a text planner.

Learning in asynchronous online environments has gained importance over the last several decades, and educational environment shifts from the COVID-19 pandemic appear to have increased this need. Science educators and students need information about which approaches work in the asynchronous environment where informal feedback tends to be reduced, compared to other teaching modalities. In this study, we asynchronously implemented a learning module across 5 institutions that guided students (N = 199) from prescriptive data analysis through guided inquiry and eventually to open inquiry. The module focuses on the science behind climate change. Students work with the same authentic data sets used by professional scientists to examine geologic history and causes of climate change. By analyzing contemporary atmospheric carbon dioxide and temperature data and then using the 800,000-year record available from the Vostok ice core proxy record of atmospheric properties, students identify the causes of climate change and discover the unprecedented nature of recent atmospheric changes. Using a pre/post-module assessment, we demonstrate improvement in students’ understanding of climate change processes and statistical methods used to analyze data. However, there was no evidence that the module develops students’ scientific reasoning about the relationship between causation and correlation. Students maintained that correlation is not causation, even when a robust causal mechanism (i.e., the greenhouse effect) explains the link between atmospheric carbon dioxide and temperature. Finally, our analysis indicated that generally, anxiety about climate change was reduced during the module, such that students become less anxious about the climate change the more they learn about it. However, science-denying students experienced much higher anxiety about climate change than students who accepted the scientific consensus about climate change. Climate science-dissenting students were so few in this study that a statistical comparison was not possible, but this intriguing finding warrants further investigation of the role of anxiety in science denial. Mainly, this study demonstrates how asynchronous online learning environments can indeed support the achievement of learning objectives related to conducting authentic science, such as increasing understanding of climate change and statistical concepts, all while not provoking anxiety about climate change.

The existing discourse parsing systems make use of different theories to put at the basis of processes of building discourse trees. Many of them use Recall, Precision and F-measure to compare discourse tree structures. These measures can be used only on topologically identical structures. However, there are known cases when two different tree structures of the same text can express the same discourse interpretation, or something very similar. In these cases Precision, Recall and F-measures are not so conclusive. In this paper, we propose three new scores for comparing discourse trees. These scores take into consideration more and more constraints. As basic elements of building the discourse structure we use those embraced by two discourse theories: Rhetorical Structure Theory (RST) and Veins Theory, both using binary trees augmented with nuclearity notation. We will ignore the second notation used in RST – the name of relations. The first score takes into account the coverage of inner nodes. The second score complements the first score with the nuclearity of the relation. The third score computes Precisions, Recall and F-measures on the vein expressions of the elementary discourse units. We show that these measures reveal comparable scores there where the differences in structure are not doubled by differences in interpretation.Keywordsdiscourse parserRhetorical Structure TheoryVeins Theoryevaluationdiscourse tree structure

This paper discusses the planning of multisentential text by computer. In order to construct coherent paragraphs, we have been using relations from Rhetorical Structure Theory (RST) operationalized as plans. The paper first describes, in some detail, the current method of planning a paragraph using operationalized RST relation/plans. It then makes two points that illustrate why RST relation/plans are an ideal tool for planning paragraphs. First, these relation/plans can be shown to combine the best features of paragraph-sized schemas and clause-sized planning rules under a top-down planning regime in a way which affords much flexibility to the user. Second, RST relation/plans can support both standard top-down planning and open-ended conversation-like behavior; a small difference in treatment gives rise to either paradigm.

<p>Early identification of relevant factors that influence students’ experiences is vitally important to the educational process since they play an important role in learning outcomes. The purpose of this study is to determine underlying constructs that predict high school students’ subjective experience and quality expectations during asynchronous and synchronous distance education activities, in a form of <em>quality of experience</em> (QoE). One hundred and fifty-eight students from different high schools participated in several asynchronous and synchronous learning sessions and provided relevant feedback with comparable opinions regarding different conditions. Structural equation modeling was used as an analytical procedure during data analysis which led to a QoE prediction model that identified relevant factors influencing students’ subjective QoE. The results demonstrated no significant difference related to students’ behavior and expectations during both distance education methods. Additionally, this study revealed that students’ QoE in any situation was mainly determined by motivational factors (intrinsic and extrinsic) and moderately influenced by ease of use during synchronous or quality of content during asynchronous activities. We also found moderate support between technical performance and students’ QoE in both learning environments. However, opposed to existing technology acceptance models that stress the importance of attitude towards use, high school students’ attitude failed to predict their QoE.</p>

In the U.S., only 38 of every 100 ninth graders enroll in college; of these 38, only 18 complete bachelors’ degrees within six years. Asynchronous learning networks (ALN)—asynchronous, highly interactive, instructor-led, resource-rich, cohort-based learning—can yield high success rates. Growing demand for online education and the expectation among higher education leaders that ALN learning outcomes will exceed face to face outcomes reflect belief in ALN’s power to engage learners. Sloan-C’s body of research confirms that ALN is especially suited for the anytime, anywhere, affordable access that is responsive to learners in a knowledge society. In fact, the original principles of ALN are the same principles that characterize ALN programs that have high student success rates. This paper includes vignettes from two- and four-year ALN programs that have used these principles to achieve high success rates.

ABSTRACTFor many health programmes, developing interprofessional education (IPE) has been a challenge. Evidence on the best method for design and implementation of IPE has been slow to emerge, with little research on how to best incorporate IPE in the asynchronous online learning environment. This leaves online programmes with no clear guidance when embarking upon an initiative to integrate IPE into the curriculum. One tool that can be effective at guiding the incorporation of IPE across all learning platforms is the Interprofessional Education Collaborative (IPEC) competencies. A project was designed to integrate the nationally defined IPEC competencies throughout an asynchronous, online baccalaureate nursing completion programme. A programme-wide review led to targeted revision of course and unit-level objectives, learning experiences, and assessments based on the IPEC framework. As a result of this effort, the programme curriculum now provides interprofessional learning activities across all courses. This report provides a method for using the IPEC competencies to incorporate IPE within various asynchronous learning assessments, assuring students learn about, with, and from other professions.

This paper examines paradigms used in online learning, with a specific emphasis on how to effectively employ asynchronous learning networks (ALN) for the delivery of online courses. Recent progress in ALNs is presented, methodologies for getting started in creating an ALN course given and relationships between traditional teaching and learning methods and ALN-based courses discussed. To illustrate a specific ALN model, the paper presents a case study about the creation of an online course. The prospects for online education and the challenges that face the ALN field are considered.

This paper examines the benefits of both the Rhetorical Representation and Vector Representation for Arabic text summarization. The Rhetorical Representation uses the Rhetorical Structure Theory (RST) for building the Rhetorical Structure Tree (RS-Tree) and extracts the most significant paragraphs as a summary. On the other hand, the Vector Representation uses a cosine similarity measure for ranking and extracting the most significant paragraphs as a summary. The framework evaluates both summaries using precision. Statistical results show that Rhetorical Representation is superior to Vector Representation. Moreover, the rhetorical summary keeps the text in context, without leading to lack of cohesion in which the anaphoric reference is not broken i.e. improving the ability of extracting the semantics behind the text.

The computerisation of clinical guidelines can greatly benefit from the automatic analysis of their content using Natural Language Processing techniques. Because of the central role played by specific deontic structures, known as recommendations, it is possible to tune the processing step towards the recognition of such expressions, which can be used to structure key sections of the document. In this paper, we extend previous work on the automatic identification of guidelines’ recommendations, by showing how Rhetorical Structure Theory can be used to characterise the actual contents of elementary recommendations. The emphasis on causality and time in RST proves a powerful complement to the recognition of deontic structures and supports the identification of relevant knowledge, in particular for the identification of conditional structures, which play an important role for the subsequent analysis of recommendations.Keywordsnatural language processingrhetorical structure theoryguidelines