This doctoral consortium paper investigates the design and implementation of a chatbot/smart assistant system for Massive Open Online Courses (MOOCs) in Technology-Enhanced Learning (TEL). The research question focuses on improving the efectiveness and user experience of a smart assistant in supporting learners during their learning journey. By addressing significant issues in TEL, such as learner engagement, information overload, and personalized support, this paper proposes a novel approach to improve learner support especially in MOOCs. The paper provides an overview of the current state of the problem domain. Preliminary ideas, the proposed approach, and the obtained results are discussed, highlighting the unique contribution of the PhD project. The applied research methodology is outlined, focusing on empirical investigation and the iterative design process. The proposed solution aims to provide a more interactive and personalized learning experience that difers from existing approaches by incorporating adaptive features, social interaction, and personalized recommendations. Through this work, the thesis project aims to advance the field of TEL by providing a more efective and engaging learning environment for MOOC participants.
icant strides in recent years, with Massive Open OnTechnology-enhanced learning (TEL) has made signif- individual needs, preferences, and learning progress. To provide a comprehensive understanding of the probline Courses (MOOCs) becoming a popular and acces- lem domain, this paper reviews the current state of knowlquestions, the paper aims to contribute to ongoing ef- ers and the information they need, provide a sense of sible form of online education. However, despite their widespread use, learners in MOOCs often face challenges such as lack of engagement, information overload, and the need for individualized support. To address these issues, the integration of chatbots has gained attention as a promising solution.
In this doctoral consortium work, the focus is on the design and implementation of a smart assistant system for MOOCs in the TEL domain. The primary research question revolves around (1) enhancing learner support and accessibility in MOOCs with the help of a smart assistant and (2) improving the efectiveness and user experience of the smart assistant to better support learners during their learning journey. By framing these research forts to optimize the learner support provided by MOOC platforms. There are significant problems in the TEL ifeld that hinder learners’ educational experiences. These problems include the overwhelming amount of course content, dificulty finding relevant information, and a lack of personalized guidance. The proposed research project ence on Technology Enhanced Learning Responsive and Sustainable Proceedings of the Doctoral Consortium of the 18th European Confer- in the MOOC context. CEUR htp:/ceur-ws.org ISN1613-073
CEUR © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License aims to address these problems by designing and implementing a smart assistant that is responsive to learners’ edge, including the status of existing solutions. The PhD project uses an applied research methodology that focuses on an iterative design process and empirical research. Through user testing and feedback collection, the efectiveness of the system and the user experience are evaluated and iteratively refined.
lution by leveraging natural language processing and machine learning techniques. These chatbots can serve as virtual learning companions that provide personalized assistance, answer questions, and ofer timely support.
course progress updates, content searches, and recommendations, chatbots can bridge the gap between learnpersonalized support, and encourage active engagement.
search project aims to contribute to the TEL field by developing a chatbot/smart assistant specifically for MOOCs.
face issues such as high participation rates, overwhelming amounts of information, and delayed responses, which limit their efectiveness in providing timely and In the area of TEL, several significant issues have been individualized support. [3] identified that pose challenges to learners in the context Another approach is the availability of course menof MOOCs. These challenges relate to the lack of person- tors or facilitators who can accompany learners on their alized support, limited access to course information, and learning journey [4] [5]. Mentors provide individualized the lack of interactive learning tools. support, provide feedback, and address learners’ ques
Personalized support is a critical aspect of efective tions and concerns. While mentors can provide valuable learning experiences. In traditional face-to-face courses, assistance, their availability may be limited due to the learners have the opportunity to interact with instructors large number of learners in MOOCs. In addition, reand classmates, receive individualized feedback, and ask sponse times can vary, which afects the immediacy of for clarification when needed. However, in MOOCs, it support. is often dificult to provide individualized support due In terms of accessibility, MOOC platforms typically to the large number of learners and the asynchronous provide course materials in a variety of formats, such nature of the courses. Learners may find it dificult to as video lectures, readings, and assessments. Still, learnifnd tailored support for their specific needs, leading to a ers may have dificulty finding certain information in decrease in engagement and motivation. [1] the courses, such as prerequisites, assessment details, or
Another problem lies in the limited access to course additional resources. Navigating course content and acinformation. MOOC platforms typically provide course cessing relevant information can be time-consuming and descriptions and syllabi, but learners may have dificulty frustrating, hindering learner progress and engagement. ifnding specific details such as prerequisites, course materials, or assessment methods. The lack of easily accessible 4. Proposed Approach and and comprehensive information about courses makes it dificult for learners to make informed decisions about Preliminary Findings their learning goals and progress.
In addition, the lack of interactive learning tools in MOOCs can hinder learner engagement and active participation. While these courses often ofer video lectures, quizzes, assignments, and sometimes even podcasts the interactive elements are limited, and learners may miss opportunities for hands-on exercises, collaborative activities, or immediate feedback. This lack of interactivity can hinder the development of critical thinking skills, problem-solving, and a deeper understanding of course content.
The proposed approach focuses on the development of an intelligent assistant specifically tailored for MOOCs to improve learner support and accessibility. The chatbot initially enabled free communication, allowing users to interact with the system in a natural way. However, based on valuable user feedback, the chatbot was further improved by integrating buttons to facilitate user engagement and solve the common problem of users not knowing what to ask or how to start.
Key features of the chatbot include quick access to FAQs related to the MOOC platform, general information about MOOCs such as cost and duration, and instructions 3. Current Knowledge and on how to get started. Learners can also inquire about Existing Solutions their course progress and download their certificates, if applicable. In addition, the chatbot has a keyword-based The current state of knowledge in technology-enhanced content search function that allows learners to easily find learning highlights several existing solutions that have specific course materials or information within a course. been developed to address the challenges faced by learn- In addition, an external recommender-system has been ers in MOOCs. These solutions aim to provide support, integrated into the chatbot, allowing it to suggest relevant increase accessibility, and improve the overall learning courses based on learners’ preferences and interests. In experience. the example conversation shown in 1, the chatbot helps
One common approach is the use of discussion fo- a user change her name and also performs this action for
rums or online communities within MOOC platforms the user.
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User testing is conducted to evaluate the performance and usability of the chatbot. Learners are invited to interact with the chatbot, and their feedback is collected through surveys and observation. Thematic analysis methods is used to analyze the data and gain insights into the efectiveness of the chatbot and areas for improvement.
Based on the feedback received, iterative improvements will be made to improve the functionality of the chatbot and the user experience. During this iterative development process, user suggestions and issues are considered to ensure that the chatbot efectively meets the needs of learners. The iterative nature of the methodology allows for continuous refinement and optimization of the chatbot’s features.
Throughout the research process, the focus is on maintaining a user-centered approach. Learner perspectives and feedback are prioritized to ensure that the design and features of the chatbot aligned with their expectations and requirements.
The research methodology also involves collaboration with MOOC platform providers and experts in the field of TEL. Their expertise and insights contribute to the development and evaluation of the chatbot and ensure that it is in line with current trends and best practices in the TEL field.
The applied research methodology in this project enables the systematic development, evaluation, and improvement of the smart assistant.
5. Applied Research Methodology accessibility. The chatbot acts as a virtual learning companion, ofering personalized help, answering questions The applied research methodology follows a systematic and providing timely support throughout the learning and iterative process to develop and evaluate the smart process. By answering FAQs, updating course progress, assistant. searching for content, and providing recommendations,
The first phase of the research methodology included the chatbot bridges the gap between learners and the requirements gathering. Surveys and workshops were information they need, fostering a sense of personalized conducted to understand the needs, expectations, and support. problems of MOOC learners. This step helped identify In addition, the integration of the recommendation the specific functionalities and features that the chat- module enhances the chatbot’s ability to suggest relebot should include to support learners and efectively vant courses based on learners’ preferences and interests, improve accessibility. further increasing their learning experience and engage
Based on the collected requirements, the design and ment. This personalized recommendation feature condevelopment phase was started. The conversation flow tributes to a customized and meaningful learning journey of the chatbot was designed considering the natural lan- for MOOC learners. guage processing capabilities and the user-friendly in
In addition, the research project will explore future adoption of the chatbot. Future research should address ideas such as integrating a quiz module for review ques- these challenges and propose strategies to efectively tions and providing recommendations for further reading overcome them. material. These ideas aim to increase learner engagement, reinforce learning outcomes, and provide additional resources to support learner knowledge acquisition and 8. Conclusion application.
By developing and evaluating the intelligent assistant in a MOOC context, this research project adds to the existing body of knowledge in TEL. It provides insights into the design, implementation, and evaluation of intelligent chatbot systems to improve learner support and accessibility in online learning environments.
Overall, the proposed research project provides an effective and innovative solution to the challenges faced by MOOC learners. Through the use of chatbot technology, the project enhances learner support, promotes engagement, and provides personalized support, ultimately improving the overall learning experience and outcomes in the MOOC context.
By applying a systematic research methodology, including requirements gathering, design and development, user testing, and iterative improvements, preliminary results have demonstrated the chatbot’s efectiveness in answering learners’ questions and providing timely assistance. The integration of the recommendation module and future ideas such as integrating a quiz module and providing more reading recommendations are promising to improve learner engagement and the overall learning experience.
The contribution of this research project is to advance 7. Discussion the field of technology enhanced learning by developing an innovative solution that addresses the identified One key aspect is the efectiveness of the chatbot in terms problems in MOOCs. By providing personalized support, of learner support and accessibility. Preliminary results encouraging learner engagement, and improving acceshave shown that the chatbot provides quick and accu- sibility, the chatbot helps improve the overall learning rate answers to FAQs and ofers personalized support. experience for MOOC learners.
However, it is important to conduct further research to In terms of future work, several paths can be taken. evaluate the chatbot’s performance on a larger scale and First, further evaluation of the chatbot’s performance and gather more comprehensive user feedback. This would usability on a larger scale would provide more comprehelp refine the chatbot’s capabilities and ensure that it is hensive insights into its efectiveness and highlight areas responsive to the diverse needs of MOOC learners. for improvement. Examining the chatbot’s long-term
Another point is the impact of the chatbot on learner impact on learner motivation, self-eficacy, and learning engagement and motivation. By providing personalized outcomes would be valuable in evaluating its impact. support, access to course information, and interactive In addition, enhancing the capabilities of the chatbot features, the chatbot is expected to increase learner en- by integrating the quiz module and additional reading recgagement. However, it is critical to explore the long- ommendations would improve its functionality and proterm impact of using a chatbot in MOOCs and how it vide additional learning opportunities for MOOC learnafects learner motivation and persistence. Future studies ers. Evaluating the impact of these additions on learner could investigate the impact of the chatbot on learner engagement, retention, and reinforcement would conself-eficacy, satisfaction, and overall learning outcomes. tribute to ongoing research in this area.
In addition, the potential of integrating a quiz module In addition, overcoming the challenges of accessibility and providing recommendations for further reading ma- in terms of language barriers, technical limitations, and terial represents an exciting direction for future research. user acceptance would be critical to the successful use of Investigating the impact of quizzes on learner retention the chatbot in various educational contexts. and knowledge consolidation, as well as exploring the benefits of additional reading recommendations, could provide valuable insights for improving the learning ex- References perience in MOOCs.
Another important point to focus on are the limita- [1] D. Wong, A critical literature review on e-learning
tions and challenges of implementing a smart assistant limitations, Journal for the Advancement of Science
in a MOOC context. Factors such as language barriers, and Arts (2007).
technical limitations, and user acceptance need to be [