Integrating Technology in Online Learning Based on Computer-Mediated Communication Artificial Intelligence to Improve Students’ Achievement

The growing percentage of fully online classes has highlighted the necessity to explore Computer-Mediated Communication Artificial Intelligence (CMC AI) in English language class. This study aimed to investigate students’ achievement and perceptions in English grammar class. It used a mix-method approach. The participants of the study were the undergraduate students of the English Education Department. The result of the pre-test mean score was 69.07, while the post-test mean score was 80.26. Asymp. Sig. (2-tailed) in Test Statistics of Wilcoxon Signed Ranks Test shows 0.000, which is lower than 0.05. Therefore, there was a significant improvement difference of the scores of the students before and after being taught by using CMC AI. The interview and questionnaire data showed students' overall positive perceptions toward the use of CMC AI within the English grammar class. The students mentioned their positive perceptions that CMC AI can improve autonomous and fun learning. It can also be used anytime and anywhere as a private tutor and partner, challenging and enhancing resources in learning English language

Using Chatbots as AI Conversational Partners in Language Learning

Recent advances in Artificial Intelligence (AI) and machine learning have paved the way for the increasing adoption of chatbots in language learning. Research published to date has mostly focused on chatbot accuracy and chatbot–human communication from students’ or in-service teachers’ perspectives. This study aims to examine the knowledge, level of satisfaction and perceptions concerning the integration of conversational AI in language learning among future educators. In this mixed method research based on convenience sampling, 176 undergraduates from two educational settings, Spain (n = 115) and Poland (n = 61), interacted autonomously with three conversational agents (Replika, Kuki, Wysa) over a four-week period. A learning module about Artificial Intelligence and language learning was specifically designed for this research, including an ad hoc model named the Chatbot–Human Interaction Satisfaction Model (CHISM), which was used by teacher candidates to evaluate different linguistic and technological features of the three conversational agents. Quantitative and qualitative data were gathered through a pre-post-survey based on the CHISM and the TAM2 (technology acceptance) models and a template analysis (TA), and analyzed through IBM SPSS 22 and QDA Miner software. The analysis yielded positive results regarding perceptions concerning the integration of conversational agents in language learning, particularly in relation to perceived ease of use (PeU) and attitudes (AT), but the scores for behavioral intention (BI) were more moderate. The findings also unveiled some gender-related differences regarding participants’ satisfaction with chatbot design and topics of interaction.This study is part of a larger research project, [The application of AI and chatbots to language learning], financed by the Instituto de Ciencias de la Educacion at the Univesity of Alicante (Reference number: 5498)

The application of chatbot as an L2 writing practice tool

This study investigates the effect of chatbot-based writing practices on second language learners’ writing performance and perceptions of using the chatbot in L2 writing practices. A total of 75 Korean elementary school students were randomly allocated to two groups. While the control group received traditional teacher-led writing instruction, the experimental group used a chatbot for individual writing practices for 15 weeks. The chatbot was developed using Google’s Dialogflow machine-learning AI platform by encoding expressions from an elementary school English textbook. A pretest was carried out prior to the experiment to examine the initial writing performance, and a posttest was carried out 15 weeks later with a different writing topic. The participants in the experimental group also responded to a short survey to report their perceptions and opinions about the chatbot. The results showed that the two groups generally showed a similar writing proficiency in the pretest scores, but the experimental group performed significantly better in the posttest than the control group, suggesting that the chatbot-based writing practice had a facilitating effect on their test performance. The participants of the experimental group also found the chatbot useful in improving their language skills and made them feel comfortable when learning a foreign language

Chatbot en redes sociales para solucionar problemas de soporte técnico de internet

El problema de la investigación será ¿En qué medida el chatbot mejorara la orientación en las soluciones de incidentes informáticos de servicios de internet?, que tiene por objetivo construir un sistema de chatbot para la orientación en las soluciones de incidentes informáticos de servicios de internet, y conocer el efecto que este tendrá en la orientación, satisfacción y conocimiento a los usuarios, brindando buen servicio de atención mostrando, soluciones mediante procedimientos detallados. El tipo de estudio es de tipo experimental aplicada y el diseño preexperimental

KritiaBot: herramienta para el desarrollo de chatbot de atención postoperatoria en oftalmología

Brinda una herramienta para la creación de chatbots para una afección oftalmológica, atendiendo las preguntas de los pacientes y mejorando la calidad de la atención postoperatoria. El éxito de una cirugía depende mucho de una adecuada atención postoperatoria, detectando y previniendo situaciones perjudiciales para el paciente, atendiendo oportunamente sus consultas. Por esta razón, los chatbots son cada vez más utilizados en el área médica, por ser agentes conversacionales que promueven la salud e impulsan un cambio de comportamiento. Para su validación, se incorporó un escenario de caso de uso, describiendo los inconvenientes del paciente y el posterior uso del sistema, identificando las ventajas obtenidas como resultado de esta interacción. Asimismo, se realizó un análisis comparativo entre las funciones de KritiaBot y los sistemas en el sector salud. Como resultado, se observó beneficios en la reducción de tiempos para la atención de las consultas de los pacientes y la disminución de los costos del seguimiento del estado de salud, por su disponibilidad 24/7. La comparativa realizada permitió ver que KritiaBot es un chatbot muy completo en este sector, pues cumple con las funcionalidades deseables, además de permitir crear chatbots de forma simple y rápida. Como conclusión, se puede entender que el contar con los servicios necesarios para garantizar una mejor calidad de vida es primordial. Por esta razón, un servicio óptimo de atención postoperatoria, con los medios necesarios para un seguimiento constante del estado de salud del paciente, permite hacer frente a posibles situaciones perjudiciales