Learning Literature Research Articles

The Construction of the Value System of English Language and Literature Courses Based on the Deep Learning Model

With the rapid development of artificial intelligence, big data and other modern technologies, the intelligence of education has become the trend of modern education reform, and the deep learning model, as a representative of the application of artificial intelligence in the field of education, has a natural connection with the construction of the value system of English language and literature courses. This paper analyzes the feasibility and significance of the application of deep learning model in English language and literature from the characteristics of deep learning model, and constructs the value system of English language and literature based on it, aiming to provide more choices for English majors and improve their interest and enthusiasm in learning English language and literature.

Graph-guided Bayesian matrix completion for ocean sound speed field reconstruction.

Reconstructing ocean sound speed field (SSF) from limited and noisy measurements/estimates is crucial for many ocean acoustic applications, including underwater tomography, target localization/tracking, and communications. Classical reconstruction methods include deterministic approaches (e.g., spline interpolation) and geostatistical methods (e.g., kriging). They exhibit a strong link to linear regression and Gaussian process regression in machine learning (ML) literature, by uniformly viewing them as supervised regression models that learn the mapping from the geographical locations to the sound speed outputs. From a unified ML perspective, theoretical analysis indicates that classical reconstruction methods have several drawbacks, such as the sensitivity to noises and high computational cost. To overcome these drawbacks, inspired by the recent thriving development of graph machine learning, we introduce graph-guided Bayesian low-rank matrix completions (LRMCs) for fine-scale and accurate ocean SSF reconstruction. In particular, a more general graph-guided LRMC model is proposed that encompasses the state-of-the-art one as a special case. The proposed model and the associated inference algorithm simultaneously exploit the global (low-rankness) and local (graph structure) information of ocean sound speed data, thus striking an outstanding balance of reconstruction accuracy and computational complexity. Numerical results using real-life ocean SSF data have demonstrated the encouraging performances of the proposed approaches.

“The Last Time” by Guillermo Martinez: Latin American boom and its assessment after 60 years

The article attempts to trace the general dynamics of the development of Latin American literature before and after the Latin American boom through the prism of Guillermo Martinez’s recently published novel “The Last Time” (2022). Well learned Latin-American literature of “boom” in some sense eclipses the following generations. The purpose of the article is to show the general picture of the development of Latin American literature before and after, to comprehend the processes taking place in Spanish American literature over the past 60 years and to summarize them. The recent novel by argentine writer Guillermo Martinez “The last time” represents some kind of farewell, an attempt of looking to the “golden generation” from long distance and appreciate it in the terms of postmodern poetic. From the Martinez’s point of view the writers of boom were conspirators, and there books were passwords. These conspirations and passwords could ne comprehended as confirmation of their specific reality described throw unique code, precisely mythopoetic. The article deals with the story of search for Latin-American identity and the way towards mythopoetic, witch is analyzed as connected with archaic mentality and archaic categories of myth and magic. The following generations of Latin-American writers gradually returned to plain reality of human world: magic realism turns into naked and dirty. Simultaneously the tradition of Borges and Cortazar brings the literature of continent into the configuration of western postmodern.

An Experimental Study of Dimension Reduction Methods on Machine Learning Algorithms with Applications to Psychometrics

Developing interpretable machine learning models has become an increasingly important issue. One way in which data scientists have been able to develop interpretable models has been to use dimension reduction techniques. In this paper, we examine several dimension reduction techniques including two recent approaches developed in the network psychometrics literature called exploratory graph analysis (EGA) and unique variable analysis (UVA). We compared EGA and UVA with two other dimension reduction techniques common in the machine learning literature (principal component analysis and independent component analysis) as well as no reduction in the variables. We show that EGA and UVA perform as well as the other reduction techniques or no reduction. Consistent with previous literature, we show that dimension reduction can decrease, increase, or provide the same accuracy as no reduction of variables. Our tentative results find that dimension reduction tends to lead to better performance when used for classification tasks.

Analysis of Interpolating Regression Models and the Double Descent Phenomenon

A regression model with more parameters than data points in the training data is overparametrized and has the capability to interpolate the training data. Based on the classical bias-variance tradeoff expressions, It is commonly assumed that models which interpolate noisy training data are poor to generalize. In some cases, this is not true. The best models obtained are overparametrized and the testing error exhibits the double descent behavior as the model order increases. In this contribution, we provide some analysis to explain the double descent phenomenon, first reported in the machine learning literature. We focus on interpolating models derived from the minimum norm solution to the classical least-squares problem and also briefly discuss model fitting using ridge regression. We derive a result based on the behavior of the smallest singular value of the regression matrix that explains the peak location and the double descent shape of the testing error as a function of model order.

Action Learning Literature Review

Action Learning Literature Review

Private Multi-Winner Voting for Machine Learning

Private multi-winner voting is the task of revealing k-hot binary vectors satisfying a bounded differential privacy (DP) guarantee. This task has been understudied in machine learning literature despite its prevalence in many domains such as healthcare. We propose three new DP multi-winner mechanisms: Binary, Tau, and Powerset voting. Binary voting operates independently per label through composition. Tau voting bounds votes optimally in their L2 norm for tight data-independent guarantees. Powerset voting operates over the entire binary vector by viewing the possible outcomes as a power set. Our theoretical and empirical analysis shows that Binary voting can be a competitive mechanism on many tasks unless there are strong correlations between labels, in which case Powerset voting outperforms it. We use our mechanisms to enable privacy-preserving multi-label learning in the central setting by extending the canonical single-label technique: PATE. We find that our techniques outperform current state-of-the-art approaches on large, real-world healthcare data and standard multi-label benchmarks. We further enable multi-label confidential and private collaborative (CaPC) learning and show that model performance can be significantly improved in the multi-site setting.

A Comparative Study of Learner Satisfaction in Synchronous and Asynchronous Online Courses Among Japanese EFL Learners

This article reports on a mixed method study that investigated the differences in Japanese EFL (English as a foreign language) learners’ satisfaction toward two different online teaching formats incorporated in universities during the COVID-19 situation: synchronous online courses (n = 324) and asynchronous on-demand courses (n = 323). Applying the items of the previously developed online satisfaction scale in the literature of online learning to EFL learning contexts, this study examined learner satisfaction from three main factors, engaged learning, agency, and assessment, as a quantitative inquiry. According to the Mann-Whitney U test, there were significantly higher results of engaged learning and assessment in synchronous online courses than in asynchronous ondemand courses, indicating a higher level of learner satisfaction in synchronous online courses. In addition, based on the qualitative textmining analysis of learner comments on their perceptions of the online courses they had taken, findings suggest that synchronous online courses accounted for higher percentages of positive comments compared to those in the asynchronous on-demand courses. This study shows that synchronous online teaching ensured higher satisfaction among Japanese EFL learners than asynchronous on-demand courses.

Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices

In this paper we assess how intra-day electricity prices can improve the prediction of zonal day-ahead wholesale electricity prices in Italy. We consider linear autoregressive models with exogenous variables (ARX) with and without interactions among predictors, and non-parametric models taken from the machine learning literature. In particular, we implement Random Forests and support vector machines, which should automatically capture the relevant interactions among predictors. Given the large number of predictors, ARX models are also estimated using LASSO regularization, which improves predictions when regressors are many and selects the important variables. In addition to zonal intra-day prices, among the predictors we include also the official demand forecasts and wind generation expectations. Our results show that the prediction performance of the simple ARX model is mostly superior to those of machine learning models. The analysis of the relevance of exogenous variables, using variable importance measures, reveals that intra-day market information successfully contributes to the forecasting performance, although the impact differs among the estimated models.

Multi-view multi-label learning with high-order label correlation

Multi-label learning deals with a kind of problem that the given samples areassociated with multiple labels simultaneously. Recently, multi-label learning has become a populartopic in the literatures of machine learning and has attracted lots of researches. In this paper, we propose a new multi-view multi-label learning method by considering the label correlation, which is called ELSMML. Based on the high-order strategy, we construct a crafted label correlation matrix to describe the relationships among labels. We further utilize multi-view learning and dimension reduction to exploit the high-level latent semantic label information and the latent feature information, so as to build a classifier in the low dimensional space. In addition, we apply manifold regularization terms to make the data samples in the low dimensional space have the same intrinsic structure as the original data. After that, we put forward the accelerated proximal gradient method to optimize the ELSMML model and obtain thepredictive classifier. Besides, we conduct convergence analysis and computational complexity analysis for ELSMML method. In the experiments, the ELSMML method can achieve better performance on the evaluation metrics compared with other baselines.

Nilai Sosial dan Nilai Moral dalam Novel Bukan Pasar Malam Karya Pramoedya Ananta Toer serta Relevansinya dengan Pembelajaran Bahasa dan Sastra di SMA

The purpose of this research is to: 1) is to find out the structure of the novel (characters, plot, and setting) that builds the storytelling in the novel Bukan Pasarmalam by Pramoedya Ananta Toer. 2) Is to know the social values contained in the novel Bukan Pasarmalam by Pramoedya Ananta Toer. 3) is to know the moral values in the novel Bukan Pasarmalam by Pramoedya Ananta Toer. 4) is to find out the relevance between the novel Bukan Pasarmalam and learning Indonesian language and literature in high school. This research method uses content analysis method, using a qualitative approach. With the method used, this study found the results that: 1) The structure of the novel Bukan Pasarmalam describes people's lives in Indonesia before and after independence. In this novel, Pramoedya describes the sadness, suffering and difficulties of the post-independence Indonesian people. 2) the findings and results of the analysis of this novel, it is known that the novel Bukan Pasarmalam contains social values through social interactions within the family and society. These values include: the value of affection, the value of compassion, the value of protection, the value of religiosity, the value of caring, the value of equality, the value of togetherness, the value of sincerity. 3) The moral values contained in the character I are in the form of behavior that most are worthy of being an example for everyone such as being responsible, patient, guarding one's tongue, and being religious. 4) The social values and moral values in the novel Bukan Pasarmalam can be relevant to the 2013 curriculum for Indonesian language and literature subjects in class XI high schools, there is material about analyzing the intrinsic and extrinsic elements of literary works, one of which is Indonesian novels which contain values cultural, social, moral, historical, and religious with basic competencies: identifying life values contained in a collection of short stories and analyzing messages from two fiction books (novels and poetry), while the learning materials: short stories, short story contents, values life, short story intrinsic elements, novel elements and reviews of novels.

The development and validation of the student's employability competences questionnaire (SECQ)

PurposeThis paper aims to measure the extent to which students possess the necessary competences of an employable graduate, the authors explored the development and validation of a questionnaire that measures employability competences of students in higher education through combining insights from higher education and workplace learning literature.Design/methodology/approachThe paper aims to develop and validate the questionnaire a systematic literature review and factor analyses were conducted. The authors applied the questionnaire to two different groups of students. First, to undergraduate students in an applied sciences program in Belgium (N = 935). The dataset was randomly divided into two subsets to conduct an exploratory and a confirmatory factor analysis. Next, another confirmatory factor analysis was done to cross-validate the factor structure found. For this, the questionnaire was offered to a group of undergraduate and graduate students at a university in The Netherlands (N = 995).FindingsThe results support a model of employability based on combined insights from higher education and workplace learning literature. The model consists of the following seven factors: social competences, e-literacy, efficacy beliefs, flexibility, healthy work–life balance, lifelong learning and oral and written communication.Originality/valueThe questionnaire can be utilized to screen students' employability profiles and examine the relationship between teaching practices and students’ employability competences.

The Role of Cyber Literature in Learning Indonesian Language and Literature in the Digital Era

The rapid development of technology makes a process of change in all aspects of life. Likewise in literary life, changes occur in works, critics, and literary readers. In essence, literature is a work that aims to convey information and become a medium of communication. Technological developments have an impact on the emergence of cyber literature that is developing in the mass media. This article describes the role of cyber literature in learning Indonesian language and literature in the digital era. The method used in this paper is descriptive qualitative with the type of qualitative research. The discussion in this article is (1) cyber literature, (2) the impact of cyber literature, and (3) the role of cyber literature in learning Indonesian language and literature.The result showed that The negative impact is the plagiarism of literary works. However, the positive impact of cyber literature is that it provides an opportunity to express ideas and creative writings.

The effectiveness of a first-year module presented as an accelerated learning programme to repeating students for subsequent learning

The use of an accelerated learning programme as an intervention to allow failing students to repeat a module in an accelerated format instead of having to redo a module over a semester or academic year has various academic, economic, and social benefits. Accelerated learning programmes are, however, often criticised in the literature for surface learning that may influence subsequent learning. Using a quantitative approach, this study statistically analysed the grades achieved by three distinct groups of students for a first-year financial accounting module and their subsequent second-year financial accounting module. The study found no statistical difference between students who repeated a module over the traditional academic period and those who repeated the module in an accelerated format. This study contributes to the limited research on accelerated learning programmes for repeating a module. The results provide empirical evidence that supports the questioning of the notion that accelerated learning programmes only lead to surface learning, and results are presented that advocate for the implementation of accelerated learning programmes as an effective mode for repeating students to follow to achieve academic success, given the various benefits.

Cooperative Learning of Italian Literature in the Post-Pandemic Era

The paper analyses how cooperative learning can be used in teaching literature, specifically 19th century Italian literature. It presents the results of group activities carried out in October 2022 by students from the Faculty of Letters of the “Babes-Bolyai” University of Cluj-Napoca, with specialisation in Italian A and B. These are students attending the Italian Literature II course, taught in Italian. The participants returned to university (face-to-face didactic activities) only in the spring of 2022, in the second semester of their first year of study at a university level. They spent more than one year of high school during the Covid-19 pandemic (with online school). After having carried out a cooperative activity in the practical course that focused on the study of Italian literature, in groups of 3-4 students, they were given an anonymous questionnaire to express their views on cooperative learning of foreign languages and literatures. The questionnaire contained 7 questions in which the teacher wanted to check whether the students found cooperative learning more effective than the classical methods of learning foreign languages and literatures in the post-pandemic period and how the cooperative activity stimulated their curiosity for Italian literature, especially for reading the novel studied during the practical course.

Pandemic, a catalyst for change: Strategic planning for digital education in English secondary schools, before during and post Covid

AbstractFollowing lockdowns in 2020 owing to Covid‐19, schools needed to find a way to ensure the education of their pupils. In order to do this, they engaged in digital learning, to varying extents. Innovations emanated from all school staff including, for example, teachers, leaders and teaching assistants. Some were already innovating in this area and brought forward and implemented digital strategies, while others engaged with digital learning for the first time. While research is emerging about the effects of the pandemic restrictions on pupils and staff in relation to key issues such as mental health and educational attainment, very little is known about the impact on school leaders' strategic planning processes. To address this gap, this paper draws on a UK Research and Innovation funded study adopting a strategy as learning approach to report on 50 qualitative interviews with school leaders to examine digital strategy in English secondary schools, before, during and after July 2021, when restrictions were lifted in England. It draws on strategy as learning literature to evaluate if schools have changed their strategic planning for digital learning, as a direct response to having learned and innovated during the pandemic. The paper concludes that there is evidence that digital innovations during the pandemic have changed the ways in which leaders think about their digital strategy, thus supporting a strategy as learning approach. However it also concludes that although there is ample evidence that the pandemic has changed the way many schools view digital learning, for some schools, there remain persistent barriers to digital integration and planning. These emanate both from material and cultural considerations, as well as leader vision and belief in digital learning.

From the margins to the mainstream: The online learning rethink and its implications for enhancing student equity

From being largely at the margins of higher education for many years, online learning now finds itself in the mainstream. This paper offers a critique of the online learning literature both pre- and post-2020, looking at changes in response to this shift. Evidence tells us that online learning plays a significant role in enhancing student equity, widening higher education access and participation for many students who would have found it difficult, if not impossible, to attend university on campus. This includes students from government-identified equity backgrounds, as well as other student cohorts underrepresented at university, such as older working students, parents, and others with caring responsibilities, and those from families with no previous experience of university. The mainstreaming and normalising of online learning now presents an opportunity for universities to learn from both past and emerging evidence, to evaluate past practice and offer a more flexible learning experience that better meets the needs of an even wider range of students. Keeping online learning firmly in the mainstream, while taking an evidence-based approach to ensuring the quality of its design and delivery, has the potential to enhance student equity on a much broader scale. Implications for practice or policy: Improving the quality of online learning, using evidence-based research to design and deliver it more effectively, will enable more students to stay and succeed at university. Continuing to offer online study options for all students, that is, keeping it in the mainstream, will further enhance student equity. Mainstreaming online learning options as part of standard university practice will enable more students to benefit from the greater flexibility of both fully online and hybrid models.

Towards explainable community finding.

The online version contains supplementary material available at 10.1007/s41109-022-00515-6.

The Role of Literature in Learning the English Language

This research article focuses on how it works to teach both speaking domains and fundamental language abilities (how to read, how to listen, and how to speak) (i.e. and vocab, grammatical structure, and pronunciation of words). Since English is the only language in which all topics are taught, it is important to emphasize and utilize texts in English as a foreign learning language as well as the primary considerations for choosing appropriate literary texts. Additionally, there are advantages to teaching language skills through various literary genres (such as poetry, short fiction, drama, and novels), but there are also challenges faced by language teachers when it comes to teaching the English language, including fewer sources of preparation in this area in "TESL "and "TEFL" programs, the nonappearance of specific goals explaining the role of English literature in “ESL” and “EFL”, and English language professors no specific sources or background and training.

Learning of English Literature: ESL Pre-Service Teachers’ Perceptions and Challenges

Learning of literature, particularly in the ESL context, has been subjected to controversy and consensus. Its proponents argue that literature learning can be beneficial for learners because it provides valuable authentic material and fosters language enrichment, cultural awareness, and personal involvement. Its opponents, however, believe that literature brings its own sets of challenges such as language difficulty and cultural disconnection. As the learning of literature has a direct impact on the learners, it is important to understand how learners view the subject, and their experience in learning it. Such understandings can lead to better teaching and learning of literature in ESL classrooms. Hence, this paper attempts to discuss pre-service teachers’ perceptions of, and challenges in, learning literature in a public university in Malaysia. A questionnaire, consisting of multiple-choice items and open-ended questions, was distributed to respondents enrolled in a literature course at the university. Frequency count is used to calculate the response of each question in the single-option format while crosstabulations are used whenever the responses are to be compared with each other. In addition, the learners’ academic grades are analysed and cross tabulated with the items in the questionnaire. The findings show that the learners have positive perceptions of literature and admitted having enjoyed learning literature in the course due to several factors, including the role of the instructor. These findings have implications on how educators plan and teach literature courses, which will affect how ESL learners approach and learn literature.