A5070644242- Online Learning and Analytics
- Intelligent Tutoring Systems and Adaptive Learning
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Advanced Text Analysis Techniques
- Teaching and Learning Programming
- Learning Styles and Cognitive Differences
- Innovative Teaching and Learning Methods
- E-Learning and Knowledge Management
- Educational Innovations and Technology
- Online and Blended Learning
- Health and Lifestyle Studies
- Natural Language Processing Techniques
- AI in Service Interactions
- Aging, Health, and Disability
- Educational methodologies and cognitive development
- Stress and Burnout Research
- Educational Technology and Assessment
- Educational Outcomes and Influences
- Artificial Intelligence in Games
- Emotion and Mood Recognition
Universidad Autónoma de Occidente
2020
Division of Undergraduate Education
2019
Instituto Tecnológico de Culiacán
2014-2018
Tecnológico Nacional de México
2017-2018
Universidad de Occidente
2015-2017
Universidad Autónoma del Estado de México
2014
National Training Service
2014
Purpose This paper proposes an integrated method for predicting the value of a garment’s trendy attributes in upcoming fashion season. Design/methodology/approach The paper’s methodology includes web crawling and data scraping from online social network Pinterest to collect opinions on garment attributes. Machine learning models are then employed classify users as trustworthy based their opinions. Subsequently, comments analyzed identify trending approach offers valuable insights designers...
Abstract In this paper, we present the development of an opinion‐mining module. The module consisted creating emotion tagged dataset opinions; implementing opinion mining that processes sentences about computer programming, predicting or recognizing their polarity (positive/negative) and type (frustrated, bored, excited, engagement, neutral); integrating previous in intelligent learning environment. We evaluated corpus, accuracy text polarity, recognition. results with respect to are...
This paper presents an implementation of Sentiment Analysis module that works in Affective Intelligent Tutoring System. Later, we show the results evaluating this and some experiments made with students. We consider main contribution work is module, system will be able to analyze student's feedback using sentiment analysis techniques provide useful information course administrators teachers for improving teaching material.
We present Java Sensei, an Intelligent Learning Environment (ILE) for learning programming. The ILE is formed by affective tutoring system working in a Web environment. was implemented under different methodologies like problem-solving the pedagogical module, knowledge space expert and overlays student module. main contribution of this work integration cognitive information behavior graph which used agent to show emotion empathy student.
In this paper we present the creation process of a corpus phrases (opinions) related to learning computer programming. Opinions (textual phrases) are categorized in different emotions such as frustration, boring, excitement, and engagement. The results shows that 851 opinions (754 Positives 97 Negatives), there was neutral, excited engaged emotional tendency which indicates must include resources induce students write negative comments. We tested with set machine classifiers where classifier...
Despair generates personal devaluation, which can lead to states of greaterdepression. The aim was describe experiences despair in a sample 224 Mexican youths both genders aged 26 on average. A questionnaire nine reagents validated by expert judges used. results show that women have experienced it more frequently. Lack hope participants is evidenced the following areas: academic, occupational, economic, emotional, personal, accident / illness. With regard causes, attribute internal factors...
Learning-centered emotions unlike basic emerge during deep learning activities and they have an important relation to cognitive processes of students.In this paper we present the creation process a corpus phrases (opinions) related computer programming.Opinions (textual phrases), are categorized in different such as frustrated, bored, neutral, excited, engaged.The main contribution work is sentences Spanish that can be used analyze text dialogs order detect student's improve teaching...
Resumen.En este artículo se presenta un ambiente inteligente de aprendizaje con manejo afectivo para Java llamado Sensei.El sistema está diseñado ayudar a los estudiantes programación reforzar distintas áreas del conocimiento sobre Java.El evalúa aspectos como el estado cognitivo y estudiante tomar las estrategias intervención que realizara agente pedagógico, así realiza procesos adaptabilidad por medio recomendaciones.El pedagógico realizó una perspectiva Example-Tracing afectivo.
We present a descriptive statistical study about an Intelligent Learning Environment for learning Java programming and the student's results. Sensei is (ILE) built around affective tutoring system working in web-based environment. The ILE was implemented under different methodologies like problem solving pedagogical module, knowledge space expert overlays student module.
Resumen.En este trabajo se presenta el desarrollo de un clasificador frases relacionadas con aprendizaje en ámbito programación computadoras para realizar análisis sentimientos sistemas educativos inteligentes.El ofrece como servicio web que recibe texto español y regresa resultado una emoción centrada aprendizaje.El fue entrenado corpus expresadas por estudiantes al acceder a diversos objetos creó mediante Sistema Evaluación Recursos Educativos (SERE) encarga recolectar textuales escritas...
El sistema evalúa aspectos cognitivos y afectivos del estudiante mediante una red neuronal utiliza un experto difuso para decidir el siguiente ejercicio que deberá resolver estudiante, lo posibilita aprendizaje personalizado.