Educational chatbots for project-based learning: investigating learning outcomes for a team-based design course

Artificial Intelligence (AI)-driven dental education: Exploring the role of chatbots in a clinical learning environment

STATEMENT OF PROBLEM

Despite their widespread use in various educational contexts, the integration of chatbots into dental clinical education has not been thoroughly investigated. The noted discrepancy signifies a lack of understanding of how chatbots could enhance the personalized and interactive learning experiences of predoctoral dental students.

PURPOSE

The purpose of this study was to evaluate the awareness and perceptions of artificial intelligence (AI) technology, interaction experiences, and concerns about a custom-developed chatbot (CB) intervention in the clinical education of predoctoral dental students at the University of Illinois Chicago, College of Dentistry (UIC-COD) compared with the traditional Blackboard (BB) online platform.

MATERIAL AND METHODS

Eligible participants (n=86) providing verbal consent were allocated via the random block method into BB (n=43) and CB (n=43) groups and asked to engage with their designated platforms for 10 to 15 minutes by focusing on clinical inquiries in a predoctoral implant clinic and supported by a list of 35 typical questions. After the interaction, participants responded on a 5-point Likert scale to a 19-item survey probing AI awareness, platform engagement, and technological concerns. Survey data were anonymized and analyzed using descriptive, inferential statistics and nonparametric Mann-Whitney U tests to compare interventions. The Bonferroni correction for multiple comparisons was performed (α=.0045).

RESULTS

Neither the BB or CB group showed any difference in their awareness and perception of AI technology. The CB group demonstrated improved timeliness (P<.001), more interaction (P<.001), reduced faculty workload (P=.001), enhanced receptiveness (P=.002), and less anxiety (P<.001) and was more satisfied (P<.001) when compared with the BB group. However, concerns regarding the potential for incorrect information (P=.003) were more pronounced in the CB group.

CONCLUSIONS

The integration of chatbot technology into dental clinical education significantly enhanced learning and student engagement, highlighting the potential for future technological enrichment of the educational landscape.

Implementing the Bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies

Since the fourth industrial revolution, intelligent software and applications that attempt to mimic human behavior have become increasingly common. The chatbot is an example of an artificial intelligence-based computer program that simulates human behavior by having a conversation and interacting with users using natural language. The implementation of chatbot technology in the educational context is still in its nascent stage, and further investigation into measuring its effectiveness in supporting learning and teaching processes is required, particularly in the context of higher education. Thus, this study presents the design and implementation of a task-oriented chatbot, that is embedded into the WhatsApp application, called Bashayer. It aims at supporting postgraduate students' motivation and learning strategies in Saudi Arabia. A quasi-experimental design with a single-subject experimental approach was adopted with a sample of 60 Saudi postgraduate students. The descriptive analysis of the collected data showed promising results of postgraduate students utilized the Bashayer chatbot system. Participants in the experimental group that used Bashayer were more motivated to learn than those in the control group. Participants also practiced more cognitive and metacognitive learning strategies while utilizing the chatbot compared to the control group. The results of this study are encouraging for the development of chatbot systems similar to Bashayer to support postgraduate students' successful learning. These results contribute to bridging the research gap and adding to the literature on chatbots use in postgraduate educational contexts.

Educational Psychology Aspects of Learning with Chatbots without Artificial Intelligence: Suggestions for Designers

Chatbots without artificial intelligence can play the role of practical and easy-to-implement learning objects in e-learning environments, allowing a reduction in social or psychological isolation. This research, with a sample of 79 students, explores the principles that need to be followed in designing this kind of chatbot in education in order to ensure an acceptable outcome for students. Research has shown that students interacting with a chatbot without artificial intelligence expect similar psychological and communicative responses to those of a live human, project the characteristics of the chatbot from the dialogue, and are taken aback when the chatbot does not understand or cannot help them sufficiently. The study is based on a design through research approach, in which students in information studies and library science interacted with a specific chatbot focused on information retrieval, and recorded their experiences and feelings in an online questionnaire. The study intends to find principles for the design of chatbots without artificial intelligence so that students feel comfortable interacting with them.

Identifying Potential Gamification Elements for A New Chatbot for Families With Neurodevelopmental Disorders: User-Centered Design Approach

Background

Chatbots have been increasingly considered for applications in the health care field. However, it remains unclear how a chatbot can assist users with complex health needs, such as parents of children with neurodevelopmental disorders (NDDs) who need ongoing support. Often, this population must deal with complex and overwhelming health information, which can make parents less likely to use a software that may be very helpful. An approach to enhance user engagement is incorporating game elements in nongame contexts, known as gamification. Gamification needs to be tailored to users; however, there has been no previous assessment of gamification use in chatbots for NDDs.

Objective

We sought to examine how gamification elements are perceived and whether their implementation in chatbots will be well received among parents of children with NDDs. We have discussed some elements in detail as the initial step of the project.

Methods

We performed a narrative literature review of gamification elements, specifically those used in health and education. Among the elements identified in the literature, our health and social science experts in NDDs prioritized five elements for in-depth discussion: goal setting, customization, rewards, social networking, and unlockable content. We used a qualitative approach, which included focus groups and interviews with parents of children with NDDs (N=21), to assess the acceptability of the potential implementation of these elements in an NDD-focused chatbot. Parents were asked about their opinions on the 5 elements and to rate them. Video and audio recordings were transcribed and summarized for emerging themes, using deductive and inductive thematic approaches.

Results

From the responses obtained from 21 participants, we identified three main themes: parents of children with NDDs were familiar with and had positive experiences with gamification; a specific element (goal setting) was important to all parents, whereas others (customization, rewards, and unlockable content) received mixed opinions; and the social networking element received positive feedback, but concerns about information accuracy were raised.

Conclusions

We showed for the first time that parents of children with NDDs support gamification use in a chatbot for NDDs. Our study illustrates the need for a user-centered design in the medical domain and provides a foundation for researchers interested in developing chatbots for populations that are medically vulnerable. Future studies exploring wide range of gamification elements with large number of potential users are needed to understand the impact of gamification elements in enhancing knowledge mobilization.

Designing learning technology collaboratively: Analysis of a chatbot co-design

Collaborative design approaches have been increasingly adopted in the design of learning technologies since they contribute to develop pedagogically inclusive and appropriate learning designs. Despite the positive reception of collaborative design strategies in technology-enhanced learning, little attention has been dedicated to analyzing the challenges faced in design processes using a collaborative approach. In this paper, we disclose the collaborative design of a chatbot for self-regulated learning in higher education using an action research approach. We analyze the design process of EDUguia chatbot, which includes diverse evidence from questionnaires and workshops with students and lecturers, as well as intermediary design objects. Based on the qualitative analysis, we identify several challenges that are transversal to the co-design work, as well as specific to the design phases. We critically reflect on the strategies deployed to overcome these challenges and how they relate to decision-making processes, highlighting the need to make stakeholders' tacit knowledge explicit, cultivate trust-building and support democratic decision-making in technology design processes. We believe that the recommendations we present in this paper contribute to developing best practices in the collaborative design of chatbots for the self-regulation of learning, as well as learning technology in general.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10639-022-11162-w.

Mobile Learning Acceptance Post Pandemic: A Behavioural Shift among Engineering Undergraduates

Mobile learning has become an essential telematic tool to facilitate and compliment online teaching and learning during the pandemic. This study investigates the change of behaviour and acceptance of using mobile learning specifically for engineering undergraduates due to this shift. The data collected pre-Covid19 (n = 326) and post-pandemic (n = 349) indicated an inclination for utilizing laptops than smartphones, while Telegram prevails as a popular tool for communicating and sharing information within the learning community. Next, while video conferencing tools and online learning management systems utilization increased, educational games and reading behaviour via mobile devices declined. Concurrently, behavioural intention post-pandemic were found to reduce marginally as importance were also given towards establishing learning communities via social influence compared to perceived usefulness. The outcome of this study contributes to the limited body of literature on engineering education mobile learning acceptance, and recommendations are provided for further investigation to ensure continuous sustainable use.