The purpose of the research was to identify whether the English language e-classes that are automated and delivered through the Smart Sender platform influence the students’ attendance and procrastination rates, their motivation, time management skills, cognitive processing speed, and satisfaction. The study used qualitative and quantitative methods to monitor students’ attendance and procrastination rates, motivation and engagement, time management skills, thinking speed, and satisfaction. The questionnaire on learning motivation, engagement, and competence, the time management skills test, the mental speed test, and the course satisfaction questionnaire were used to collect data. The focus group discussion questionnaire was used to obtain verbal feedback for the participants. The Smart Sender platform proved effective as an instructional tool for teaching the English Language to students majoring in Philology, International Business, and Law. The automated delivery of the English language e-classes was effective in addressing the issues of dropouts and procrastination in distance learning through automation of the lesson delivery based on the ‘push’ factor. It increased students’ motivation, improves time management skills, and satisfaction. The quantitative findings showed that the students experienced a positive change in attendance, motivation and learning engagement, time management skills, and thinking speed due to the intervention. The students perceived the automated delivery-based approach to language teaching positively. They reported that the delivery approach content met the participants’ expectations and needs. Focus group discussion revealed that the intervention changed their learning behaviour and strategies which were considered the improvements of the quality learning outcomes.

This study sought to investigate the current state of innovative teaching research and identify emerging themes and trends in the field from 2013 to 2023. The Scopus database was searched for the term “innovative teaching,” resulting in 1005 documents. After manual screening, 903 articles were exported in the BibTeX format for further processing in Bibliometrix using three bibliometric analysis types: network analysis, science mapping, and performance analysis. Performance analysis revealed bursts in publication output in 2015 and 2021, with a moderate boost in 2018. Ten top-cited journal papers were identified. The citation rates were low between 2019 and 2021, but there has been an upturn since 2022. The top keywords included simulation and nursing education, and there was a shift in research topics from broad educational concepts to more specific approaches, such as e-learning. Innovative teaching has been predominantly investigated in higher education, particularly in nursing education, with themes like “teaching/learning strategies” suggesting an emphasis on enhancing teaching practices not just through technology infusion. This study can aid educators and researchers in staying current with innovative teaching developments and inform their teaching practices.

The central focus of this study is exploring the potential of Artificial Intelligence (AI) Chatbots in enhancing digital dialogue for students. The study investigates the key attributes of Chatbots that can contribute to the feasibility of facilitating digital dialogue to improve students' communication skills through discussions and dialogues. The study employed a descriptive method using a questionnaire to gather the perspectives of 35 educational experts on the use of AI Chatbots in digital dialogue skills. This study revealed that using AI Chatbots plays a crucial role in enhancing digital dialogue skills and can be effectively integrated into instructional practices to facilitate meaningful dialogue among students. Finally, the study recommends that educational technology specialists leverage new technologies, such as Al Chatbots to help improve student performance and facilitate digital dialogue in education.