Learning strategies in interpreting text: From comprehension to illustration

Learning strategies can be described as behaviours and thoughts a learner engages in during learning that are aimed at gaining knowledge. Learners are, to use Mayer’s (1996) constructivist definition, ‘sense makers’. We can therefore position this to mean that, if learners are sense makers, then learning strategies are essentially cognitive processes used when learners are striving to make sense out of newly presented material. This paper intends to demonstrate that such thoughts and behaviours can be made explicit and that students can co-ordinate the basic cognitive processes of selecting, organising and integrating. I will discuss two learning strategies which were developed during three cycles of an action research enquiry with a group of illustration students. While each cycle had its own particular structure and aims, the main task, that of illustrating a passage of expository text into an illustration was a constant factor. The first learning strategy involved assisting students develop ‘macropropositions’—personal understandings of the gist or essence of a text (Louwerse and Graesser, 2006; Armbruster, Anderson and Ostertag, 1987; Van Dijk & Kintsch, 1983). The second learning strategy used a form of induction categorised as analogical reasoning (Holyoak, 2005; Sloman and Lagnado, 2005). Both strategies were combined to illustrate the expository text extract. The data suggests that design students benefit from a structured approach to learning, where thinking processes and approaches can be identified and accessible for other learning situations. The research methodology is based on semi-structured interviews, questionnaires, developmental design (including student notes) and final design output. All student names used are pseudonyms. The text extract from ‘Through the Magic Door’ an essay Sir Arthur Conan Doyle, (1907) has been included as it provides context to analysis outcomes, student comments and design outputs. Keywords: Action Research; Illustration; Macrostructures; Analogical Reasoning; Learning Strategies</p

Web-based Cooperative Learning, Learning Styles, And Student's Learning Outcomes

This study was aimed to examine the effect of the instructional learning strategy (webbased STAD-type cooperative and text-based STAD-type cooperative learning strategies) and learning styles towards student learning achievement. This quasi-experimental study used a non-equivalent control group version of the factorial design. The subjects were the first-semester undergraduate students of Information Systems at STIKOM Surabaya. Sixty-nine (69) students were involved, 34 of whom were the subjects of the experimental group and 35 were the subjects of the control group. The collected data were statistically analyzed by using the two-way analysis of variance technique (ANOVA) with the significance level of 0.05. The findings of this research indicate that there was a significant difference in learning achievement, for the General Management course, between groups of students taught with the web-based STAD-type cooperative learning strategies and those taught with the text-based STAD-type cooperative learning strategies. Based on the findings, the researcher suggests lecturers to implement the STAD-type cooperative learning strategies, and use the web-based and text-based strategies simultaneously (complementarily) in the form of blended learning

Learners’ use of communication strategies in text-based and video-based synchronous computer-mediated communication environments: opportunities for language learning

This study investigates the different learning opportunities enabled by text-based and video-based synchronous computer-mediated communication (SCMC) from an interactionist perspective. Six Chinese-speaking learners of English and six English-speaking learners of Chinese were paired up as tandem (reciprocal) learning dyads. Each dyad participated in four kinds of interactions, namely, English text-based SCMC, Chinese text-based SCMC, English video-based SCMC and Chinese video-based SCMC. Their use of communication strategies (CSs) were analyzed along with an after-task questionnaire and with stimulated reflection to explore systematically and comprehensively the differences between text-based and video-based SCMC. In addition to the main role of qualitative analysis, the quantitative analysis was undertaken to provide an overview of the relative frequencies of the occurrence of the different strategies and to understand their distribution in the different conditions. A MANOVA was applied to understand to what extent the differences are likely to have occurred by chance. The results showed that learners used CSs differently in text-based and video-based SCMC and indicated different learning opportunities provided by these two modes of SCMC. While text-based SCMC appears to have greater potential for learning target-like language forms, video-based SCMC seems particularly effective for fluency development as well as pronunciation improvement

Opening the black box of students’ text-learning processes: A process mining perspective

The current study uncovers secondary school students’ actual use of text-learning strategies during an individual learning task by means of a concurrent self-reported thinking aloud procedure. Think-aloud data of 51 participants with different learner profiles, distinguished based on a retrospective self-report questionnaire (i.e., 15 integrated strategy users, 15 information organizers, 10 mental learners, and 11 limited strategy users), were analysed by means of educational process mining. Both the frequency of students’ strategy use, as well as the temporal patterns between these strategies were studied. The process mining results clearly demonstrated differences between students with different learner profiles with respect to the frequency of their applied strategies, as well as concerning the sequences wherein strategies were applied throughout the course of students’ text-learning process. The added value of combining both retrospective and concurrent self-report measures of students’ strategies as well as conducting process mining analysis is discussed

Diffusion Adaptation Strategies for Distributed Estimation over Gaussian Markov Random Fields

The aim of this paper is to propose diffusion strategies for distributed estimation over adaptive networks, assuming the presence of spatially correlated measurements distributed according to a Gaussian Markov random field (GMRF) model. The proposed methods incorporate prior information about the statistical dependency among observations, while at the same time processing data in real-time and in a fully decentralized manner. A detailed mean-square analysis is carried out in order to prove stability and evaluate the steady-state performance of the proposed strategies. Finally, we also illustrate how the proposed techniques can be easily extended in order to incorporate thresholding operators for sparsity recovery applications. Numerical results show the potential advantages of using such techniques for distributed learning in adaptive networks deployed over GMRF.Comment: Submitted to IEEE Transactions on Signal Processing. arXiv admin note: text overlap with arXiv:1206.309

Adversarial Attack and Defense on Graph Data: A Survey

Deep neural networks (DNNs) have been widely applied to various applications including image classification, text generation, audio recognition, and graph data analysis. However, recent studies have shown that DNNs are vulnerable to adversarial attacks. Though there are several works studying adversarial attack and defense strategies on domains such as images and natural language processing, it is still difficult to directly transfer the learned knowledge to graph structure data due to its representation challenges. Given the importance of graph analysis, an increasing number of works start to analyze the robustness of machine learning models on graph data. Nevertheless, current studies considering adversarial behaviors on graph data usually focus on specific types of attacks with certain assumptions. In addition, each work proposes its own mathematical formulation which makes the comparison among different methods difficult. Therefore, in this paper, we aim to survey existing adversarial learning strategies on graph data and first provide a unified formulation for adversarial learning on graph data which covers most adversarial learning studies on graph. Moreover, we also compare different attacks and defenses on graph data and discuss their corresponding contributions and limitations. In this work, we systemically organize the considered works based on the features of each topic. This survey not only serves as a reference for the research community, but also brings a clear image researchers outside this research domain. Besides, we also create an online resource and keep updating the relevant papers during the last two years. More details of the comparisons of various studies based on this survey are open-sourced at https://github.com/YingtongDou/graph-adversarial-learning-literature.Comment: In submission to Journal. For more open-source and up-to-date information, please check our Github repository: https://github.com/YingtongDou/graph-adversarial-learning-literatur

THE CORRELATION BETWEEN SELF-REGULATED LEARNING STRATEGIES AND READING COMPREHENSION

Self-regulation is one of the motivational factors influencing the students’ learning process. It helps the students to accomplish the learning goals by formulating the thoughts and action to support the learning process. The aims of this study were to find out (1) the students Self-Regulated Learning (SRL) strategies at the eleventh graders of SMA Arinda Palembang, and (2) whether there was or not any significant correlation between SRL and reading comprehension of narrative text. The population and sample of this study was the students of eleventh grade of SMA Arinda Palembang. The total of sample was 46 students selected by using non-random sampling technique. Self-regulated learning (SRL) strategies questionnaire and reading comprehension test were administered as the instruments of study and they were distributed to the students to gather the data. In analyzing the data, correlation analysis was used. Based on the statistical analysis, it was found that the correlation coefficient or the r-value (0.631) was higher than r-table (0.245). Then, the level probability (p) significant (sig.2-tailed) was 0.000. it means that p-value (0.000) was lower than 0.05. it can be concluded that there was high significant correlation between the students’ self-regulated learning strategies and reading comprehension in narrative text. Keywords: Self-regulated learning strategies, reading comprehensio

Estudio de algunas variables que afectan la comprensión de textos de física

The problem about the comprehension of Physics Texts by students of the First Courses at University is the axis of analysis in this paper. Our intention is to know the learning strategies that our university students use to comprehend a scientific text. We studied the cognitive activities of the students when reading the text and the relationship between them through a global coefficient of comprehension. The results obtained let us assert that it is convenient to teach adequate strategies for the comprehension of physics texts