Benefits and Barriers of Chatbot Use in Education Technology and the Curriculum: Summer 2023

This innovative approach to mobile learning has been positively received by both students and teachers. For example, Chen et al. (2020) highlighted the effectiveness of AICs for Chinese vocabulary learning by comparing chatbot-based tutoring with traditional classroom settings. The study reported positive user feedback on the chatbot’s ease of use, usefulness, and enjoyment, as measured by the Technology Acceptance Model (TAM).

• They should avoid sharing sensitive personal information and refrain from using the model to extract or manipulate personal data without proper consent.
• Quantitative data obtained were analysed using the IBM® SPSS® Statistics software 27.
• However, according to Pan et al. (2020), there is a positive relationship between creativity and the need for cognition as it also reflects individual innovation behavior.
• The study mentioned in (Mendez et al., 2020) conducted two focus groups to evaluate the efficacy of chatbot used for academic advising.
• Thanks to these advances, the incorporation of chatbots into language learning applications has been on the rise in recent years (Fryer et al., 2020; Godwin-Jones, 2022; Kohnke, 2023).

As mentioned previously, the goal can be purely administrative (Chocarro et al., 2021) or pedagogical (Sandoval, 2018). By addressing these challenges, we believe that chatbots can become effective educational tools capable of supporting learners with informative feedback. Therefore, looking at our results and the challenges presented, we conclude, “No, we are not there yet! ” – There is still much to be done in terms of research on chatbots in education. Still, development in this area seems to have just begun to gain momentum and we expect to see new insights in the coming years.

Products and services

This research shows that English teachers are enthusiastic about generative AI tools and want to learn how to use them, but want more support and guidance. The following recommendations for increased technology adoption are based on the current perceptions of chatbots in education. Therefore, it was hypothesized that using ECs could improve learning outcomes, and a quasi-experimental design comparing EC and traditional (CT) groups were facilitated, as suggested by Wang et al. (2021), to answer the following research questions. Henceforth, encouraging participation (Tamayo et al., (2020); Verleger & Pembridge, 2019) and disclosure (Brandtzaeg & Følstad, 2018; Ischen et al., 2020; Wang et al., 2021) of personal aspects that were not possible in a traditional classroom or face to face interaction. Conversely, it may provide an opportunity to promote mental health (Dekker et al., 2020) as it can be reflected as a ‘safe’ environment to make mistakes and learn (Winkler & Söllner, 2018).

The basic concepts of digital transformation still apply and in many ways are more relevant than ever. Our campuses continue to look to technology to help advance our missions, streamline operations, and provide critical insights and services for our students. We engage in conversations across the institution to help shape the culture, and we continually assess and redefine the roles, skills, and jobs needed from our workforces for success. True transformations are occurring across our campus communities, as evidenced by the examples in the EDUCAUSE Dx Journey. Let students use GenAI tools to develop their critical thinking and digital literacy. One example of this for secondary or adult learners is to give them a debate topic, and ask them to collect different arguments or opinions from their classmates, a GenAI chatbot, and other resources on the internet.

Technology

The widespread adoption of chatbots and their increasing accessibility has sparked contrasting reactions across different sectors, leading to considerable confusion in the field of education. Among educators and learners, there is a notable trend—while learners are excited about chatbot integration, educators’ perceptions are particularly critical. However, this situation presents a unique opportunity, accompanied by unprecedented challenges.

For (Goal 5), we want to extend the work of (Winkler and Soellner, 2018) and (Pérez et al., 2020) regarding Application Clusters (AC) and map applications by further investigating specific learning domains in which chatbots have been studied. Addressing these gaps in the existing literature would significantly benefit the field of education. Firstly, further research on the impacts of integrating chatbots can shed light on their benefits of chatbots in education long-term sustainability and how their advantages persist over time. This knowledge is crucial for educators and policymakers to make informed decisions about the continued integration of chatbots into educational systems. Secondly, understanding how different student characteristics interact with chatbot technology can help tailor educational interventions to individual needs, potentially optimizing the learning experience.

Article Access Statistics

Here, the MCQ Bot is an example that is designed to introduce students to transformative learning (W. Huang et al., 2019). From this, it can be seen that Learning is the most frequently used role of the examined publications (49%), followed by Assisting (20%) and Mentoring (15%). It should be noted that pedagogical roles were not identified for all the publications examined. The purpose of this work was to conduct a systematic review of the educational chatbots to understand their fields of applications, platforms, interaction styles, design principles, empirical evidence, and limitations. The surveyed articles used different types of empirical evaluation to assess the effectiveness of chatbots in educational settings.