A fuzzy-based approach for classifying students' emotional states in online collaborative work

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Emotion awareness is becoming a key aspect in collaborative work at academia, enterprises and organizations that use collaborative group work in their activity. Due to pervasiveness of ICT's, most of collaboration can be performed through communication media channels such as discussion forums, social networks, etc. The emotive state of the users while they carry out their activity such as collaborative learning at Universities or project work at enterprises and organizations influences very much their performance and can actually determine the final learning or project outcome. Therefore, monitoring the users' emotive states and using that information for providing feedback and scaffolding is crucial. To this end, automated analysis over data collected from communication channels is a useful source. In this paper, we propose an approach to process such collected data in order to classify and assess emotional states of involved users and provide them feedback accordingly to their emotive states. In order to achieve this, a fuzzy approach is used to build the emotive classification system, which is fed with data from ANEW dictionary, whose words are bound to emotional weights and these, in turn, are used to map Fuzzy sets in our proposal. The proposed fuzzy-based system has been evaluated using real data from collaborative learning courses in an academic context.Peer ReviewedPostprint (author's final draft

Sentiment analysis in MOOCs: a case study

Proceeding of: 2018 IEEE Global Engineering Education Conference (EDUCON2018), 17-20 April, 2018, Santa Cruz de Tenerife, Canary Islands, Spain.Forum messages in MOOCs (Massive Open Online Courses) are the most important source of information about the social interactions happening in these courses. Forum messages can be analyzed to detect patterns and learners' behaviors. Particularly, sentiment analysis (e.g., classification in positive and negative messages) can be used as a first step for identifying complex emotions, such as excitement, frustration or boredom. The aim of this work is to compare different machine learning algorithms for sentiment analysis, using a real case study to check how the results can provide information about learners' emotions or patterns in the MOOC. Both supervised and unsupervised (lexicon-based) algorithms were used for the sentiment analysis. The best approaches found were Random Forest and one lexicon based method, which used dictionaries of words. The analysis of the case study also showed an evolution of the positivity over time with the best moment at the beginning of the course and the worst near the deadlines of peer-review assessments.This work has been co-funded by the Madrid Regional Government, through the eMadrid Excellence Network (S2013/ICE-2715), by the European Commission through Erasmus+ projects MOOC-Maker (561533-EPP-1-2015-1-ESEPPKA2-CBHE-JP), SHEILA (562080-EPP-1-2015-1-BEEPPKA3-PI-FORWARD), and LALA (586120-EPP-1-2017-1-ES-EPPKA2-CBHE-JP), and by the Spanish Ministry of Economy and Competitiveness, projects SNOLA (TIN2015-71669-REDT), RESET (TIN2014-53199-C3-1-R) and Smartlet (TIN2017-85179-C3-1-R). The latter is financed by the State Research Agency in Spain (AEI) and the European Regional Development Fund (FEDER). It has also been supported by the Spanish Ministry of Education, Culture and Sport, under a FPU fellowship (FPU016/00526).Publicad

FROM LANGUAGE TO LITERACY: STRUCTURAL FEATURES OF ACQUIRED LANGUAGES FACILITATING ENGLISH MORPHOLOGICAL AWARENESS

Morphological awareness is a crucial metalinguistic skill, specifically for English Language Learners (ELLs). Since languages differ widely in degree of orthographic opacity, degree of morphological fusion, and degree of morphological synthesis, this thesis sought to evaluate the impact of the structural features of other languages upon ELLs’ levels of English morphological awareness. Additionally, the study investigated the relationship between morphological awareness and perceived levels of literacy and oracy proficiency. Multilingual individuals responded to an online survey containing a morphological awareness task and a language history questionnaire. Each language represented in the sample was coded according to its structural features. Subsequently, the relationship between the features and morphological awareness was analyzed. Morphological awareness was impacted by a confluence of all three structural features. Knowledge of languages with higher degrees of morphological synthesis or higher degrees of orthographic opacity was found to predict higher levels of morphological awareness. Additionally, perceived English literacy proficiency explained a larger degree of the variance in English morphological awareness than perceived English oracy proficiency, though both were statistically significant. The findings indicate the acquisition of English may be impacted by familiarity with other languages and by perceptions of English proficienc

Detecting Aggressiveness in Tweets: A Hybrid Model for Detecting Cyberbullying in the Spanish Language

In recent years, the use of social networks has increased exponentially, which has led to a significant increase in cyberbullying. Currently, in the field of Computer Science, research has been made on how to detect aggressiveness in texts, which is a prelude to detecting cyberbullying. In this field, the main work has been done for English language texts, mainly using Machine Learning (ML) approaches, Lexicon approaches to a lesser extent, and very few works using hybrid approaches. In these, Lexicons and Machine Learning algorithms are used, such as counting the number of bad words in a sentence using a Lexicon of bad words, which serves as an input feature for classification algorithms. This research aims at contributing towards detecting aggressiveness in Spanish language texts by creating different models that combine the Lexicons and ML approach. Twenty-two models that combine techniques and algorithms from both approaches are proposed, and for their application, certain hyperparameters are adjusted in the training datasets of the corpora, to obtain the best results in the test datasets. Three Spanish language corpora are used in the evaluation: Chilean, Mexican, and Chilean-Mexican corpora. The results indicate that hybrid models obtain the best results in the 3 corpora, over implemented models that do not use Lexicons. This shows that by mixing approaches, aggressiveness detection improves. Finally, a web application is developed that gives applicability to each model by classifying tweets, allowing evaluating the performance of models with external corpus and receiving feedback on the prediction of each one for future research. In addition, an API is available that can be integrated into technological tools for parental control, online plugins for writing analysis in social networks, and educational tools, among others

The identification of improvement strategies in continuous assessment using sentiment analysis in the Operational Research course

[EN] The University aims is to graduate professionals with high levels of competence to impact society positively. In consequence, the institutions apply different educational strategies to focus on improving the curricular competences until mastery the whole competences topics. An alternative highly applied is continuous assessment, which is a form of educational examination that evaluates the progress of a student throughout a prescribed course. A critical course in the engineer formation is Operational Research; this course focuses on scientific management supported by mathematical models such as decision theory, stochastic scenarios, simulation, mathematical optimization etcetera. This work aim is to diagnose the continuous assessment strategy apply to Industrial and System engineer students enrolled in Operational Research course, to do that, this research carries out a sentiment analysis which is a text classification tool that analyses an incoming message (in this case a perception essay) and indicates whether the underlying sentiment is positive, negative or neutral. Furthermore, the Techniques applied to group the emotions of anger, anticipations, disgust, fear, joy, negative, positive, sadness, surprise, and trust. Taking into account the initial results, the authors highlight alternatives such as the flipped classroom, gamification as educational strategies to implement in futures courses looking to improving the continuous assessment positive perception.Talero-Sarmiento, L.; Durán-Peña, J.; Salcedo-Rugeles, K.; Garcia-Franco, S.; SALCEDO (2020). The identification of improvement strategies in continuous assessment using sentiment analysis in the Operational Research course. Editorial Universitat Politècnica de València. 389-397. https://doi.org/10.4995/INN2019.2019.10246OCS38939

Creative activities linked to lexical approach to improve reading skill for english language learning of students in the "Natalia Jarrin" high school 2020 - 2021

To produce creative activities linked to the lexical approach to improve reading skills for English language learning of students in the “Natalia Jarrín” high school 2020 – 2021.El desarrollo de habilidades lectoras y hábitos lectores siempre se ha convertido en un reto para las personas que se desempeñan en la educación ya que la lectura es la base del conocimiento para muchas áreas. Cuando las personas aprenden un segundo idioma, también quieren un espacio significativo para la lectura. Por tal motivo, el objetivo principal de esta investigación es producir actividades creativas vinculadas al enfoque léxico para mejorar las habilidades lectoras en el aprendizaje del idioma inglés de los estudiantes de la Unidad Educativa “Natalia Jarrín” 2020 - 2021. Se desarrolla las estrategias creativas para mejorar la lectura en estudiantes de segundo año de secundaria, que pueden ser bien aplicados a otros años e incluso adaptados a diferentes niveles de escolaridad. La base de la propuesta es el conocimiento de: ¿Cuál es el aporte del enfoque léxico en las destrezas lectoras para el aprendizaje del idioma inglés?, ¿Cómo se desarrolla la lectura en las actividades de clase?, ¿Se considera el enfoque léxico en las actividades del currículo?, y ¿Qué actividades con el enfoque léxico se han aplicado en el aula para el desarrollo de la lectura?. Estas cuatro preguntas han brindado información confiable necesaria para la construcción de estrategias de lectura con enfoque léxico. La investigación destaca estudios internacionales, regionales y locales sobre este enfoque; algunos principios y reflexiones. Además, características relevantes sobre las habilidades lectoras. Las estrategias están desarrolladas para niveles principiantes, intermedios y avanzados en el proceso de enseñanza y aprendizaje. Esta teoría contribuye positivamente a la adecuada comprensión del inglés como segunda lengua.Maestrí

Analysis of lexical acquisition in foreign languages through video games

Softwares as video games allow a virtual interaction with characters and environments which belong to the proper system, and these programs in turn need of an electronic device for its execution. Eguía argues (2012), video games promote a constructivist experience, which is defined as the foundation of an idea through students’ participation in didactical processes. Piaget Explains (1969) the process of knowledge is inherent in human reasoning, more specifically since childhood. The absorption of insight works from the first stages of children by means of experiences, which give them a meaning or a symbol to an action. For instance, take the hand of an adult express a way of conduction to the child. This philosophy of knowledge obtained by own experiences and discoveries is well-known as constructivism. Video games works as entertainment systems, but also could be a good instrument to develop different skills. As Sedeño interprets (2010), video games foment reflection and strategic thinking and these help to stimulate levels of mental agility.PregradoProfesional en Lenguas ModernasLenguas Moderna