In online discussion, reflection can help learners actively participate in discussions and interact with others, and for this purpose, dashboards have been used with other media. Online discussion learning helps learners to understand discussion topic...
In online discussion, reflection can help learners actively participate in discussions and interact with others, and for this purpose, dashboards have been used with other media. Online discussion learning helps learners to understand discussion topics in depth, to think critically about the topics through interactions with other learners, and to have appropriate communication attitudes and abilities. Effective discussion learning requires learners to actively participate in discussion and interact with other learners, and for this purpose, it is necessary to reflect on discussion learning. To help learners effectively reflect on their discussion, data from the online discussion can be visualized in the form of a dashboard. Dashboards can help learners reflect on their learning processes and results by easily looking back on them. In addition, reflection prompts and interactions with instructors or learners have been used together to help learners reflect through dashboards.
However, the media previously used for dashboard-based reflection has several limitations. First, when reflecting with reflection prompts, learners are not adaptively provided with feedback when they have difficulty in reflection. In order for reflection to affect discussion, the quality of reflection is important, so it is necessary to provide help for learners to reflect effectively. In addition, learners have emotional problems of reflecting on their shortcomings in the process of reflection, but it is difficult to provide help for the emotional problems when reflecting with reflection prompts, and it is rather burdensome to reveal their shortcomings when reflecting with others. A Chatbot can supplement the limitations of existing media in that it can provide adaptive support to learners' answers and relieve learners' emotional burden by empathizing with learners as a conversation partner.
Therefore, the goal of this study is to create a dashboard-based reflection chatbot that may assist students in actively reflecting while providing cognitive and emotional help to learners. The research questions of this study are as follows. First, what are the design principles and development guidelines of the chatbot for dashboard-based reflection in online discussions? Second, what are the structure and functions of the developed chatbot? Third, what are learners’ perceptions of the chatbot?
To anwer the research questions, the design and development research methodology Type 1 was used. In the analysis stage, the literature review and need analysis of learners were conducted, which revealed the problems of existing media for dashboard-based reflection and the ways a chatbot can supplement them. Based on the results of the analysis, the design principles and development guidelines of the chatbot for promoting dashboard-based reflection in online discussion were derived, and the internal validity of the principles was ensured by three experts. Then, the scenario for the chatbot was designed and a dashboard-based reflection chatbot was finally developed. The developed chatbot was evaluated by five learners in the first usability test, followed by revisions. The second usability test is then conducted, which is different from the first one in that it was conducted in the context of the actual online discussion class. Four learners participated in the test and their perceptions of the chatbot were collected through usability test questionnaires and individual in-depth interviews.
As a result of the study, the design principles and development guidelines of the reflection chatbot were derived, the chatbot was developed, and the learner's perception of the chatbot was also confirmed. First, the design principles of a chatbot for dashboard-based reflection are largely composed of three design principles: adaptive feedback, social presence, and learner initiatives, and 10 detailed design principles in them. The principle of adaptive feedback was based on the chatbot’s characteristic that can give adaptive support to learners' chat contrary to prompt-based documents. The detailed design principle of the adaptive feedback principle consists of providing feedback to learners at each stage of reflection to understand the dashboard's important meaning, to recognize their strengths and weaknesses during the discussion, and to set and accomplish learning goals the subsequent discussion. The principle of social presence is to allow learners to feel intimacy in conversations with a chatbot so that they can be more engaged in reflection. The characteristics of a chatbot are connected to social presence so that learners could regard a chatbot as an interlocutor and have intimacy with it. Lastly, the principle of learner initiative is the principle that a chatbot provides help, but learners should take the initiative in reflection. To prevent situations in which learners unilaterally follow the prescription of the chatbot, the chatbot first requires the learner to answer reflection questions and provides help only when it is necessary. It also allows learners to recognize the need for reflection and work with a motive for reflection. After developing the design principle, development guidelines were derived to indicate how to develop the chatbot for dashboard-based reflection.
The developed chatbot helps learners reflect on their discussion based on three dashboards, and set and implement goals for the next discussion. the chatbot operates following the reflection model based on Kolb's reflection model : ‘checking dashboard – thinking over learning experience – setting goal – executing goal’. And the stages are linked to the reflection criteria of three dashboards(discussion participation dashboard, participation time dashboard, and interaction network dashboard). Using the chatbot, Learners can check their dashboards and evaluate their learning through the criteria presented by the chatbot or the criteria they decide by themselves. The chatbot’s evaluation of learners’ learning is also presented after the learners’ evaluation, and learners compare their evaluation with that of the chatbot and make a final evaluation. The chatbot provides questions adaptive to learners’ evaluation for their discussions to let them think about their learning in detail. After the learners answer the questions, they set goals for the next discussion based on the reflection of prior stages. The chatbot recommends appropriate goals to help learners set goals and provides adaptive question prompts to elaborate on the goals. After setting the goals, the learner goes through a process of practicing the goal in the next discussion. The chatbot aids learners to accomplish their goals by allowing learners to identify and modify goals at any time and adaptively providing reminders according to learners' goals. When learners use the chatbot again after the discussion, the chatbot makes the learner reflect on whether they have achieved the goals they set and reflect it when setting the goal in the following reflection.
The response of learners who used the chatbot appears to be generally positive. The survey revealed that learners found the chatbot useful and convenient to use, and thus learners had a positive attitude toward the chatbot and were willing to continue using them in the future. The interview also revealed that learners thought that the features of the chatbot, such as dashboards, questions, reflection criteria, and conversation with the chatbot, had a positive effect on their reflection and that the chatbot allowed them to reflect on their learning through interaction unlike prompt-based reflection document, and conversation with the chatbot was not burdensome compared to a conversation with people. However, the effect of the chatbot should be examined in the long term and it should offer more adaptable feedback based on the learner's situation.
In conclusion, the implications of this study are as follows. First, this study is meaningful in that it constructed a dashboard-based reflection framework by closely connecting Kolb's reflection model and dashboard in online discussion. Second, this study also confirms the advantages and disadvantages of chatbot as a reflection medium in three aspects: adaptive feedback, learner initiative, and social presence. Finally, in terms of research methodology, the method used to make the chatbot in this study can also be effectively utilized when developing a chatbot following the Design Development Research Type 1 methodology. For need analysis, a method of observing and interviewing learners while letting them experience the learning activity that researchers want to investigate can be useful, and the Wizard of OZ methodology, which involves users interacting with chatbots while researchers pretend to be a chatbot, can also be used to confirm learners' perceptions of the chatbot scenario. Therefore, this study makes a theoretical contribution to reflection and a methodological contribution to chatbot development in an online discussion, while having practical implication by developing the actual chatbot.