Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success

Chen, Yu; Jensen, Scott A.; Albert, Leslie Jordan; Gupta, Sambhav; Lee, Terri

doi:10.1007/s10796-022-10291-4

Cited by 149 publications

(106 citation statements)

References 63 publications

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“…Chatbots can be used to answer student questions, provide explanations, and give feedback on student work, which can help to increase student engagement and motivation in the learning process. One of the main benefits of using chatbots in a flipped learning context is the ability to provide personalized support for students (Chang et al, 2022;Chen et al, 2022). Another benefit of using chatbots in a flipped learning context is the ability to facilitate group discussions and collaborations.…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, chatbots can help create a more flexible learning environment, allowing students to learn at their own pace and in their way. With a chatbot, students can learn topics as deeply as they choose and always access support when needed (Chen et al, 2022). This helps facilitate a more comprehensive understanding of the studied topics, leading to excellent knowledge retention.…”

Section: Step Descriptionmentioning

confidence: 99%

“…The use of chatbots in the context of flipped learning presents promising opportunities for enhancing student engagement and improving learning outcomes, despite the potential challenges that come with it. Although the existing literature on chatbots in education has primarily focused on their use in traditional classroom settings, integrating chatbots with flipped learning has received little attention from scholars (Chen et al, 2022;Jeon, 2021). To bridge this gap, the present study provides a theoretical framework that illuminates how chatbots can support flipped learning principles and enhance student engagement and learning outcomes.…”

Section: Introductionmentioning

confidence: 98%

“…However, using chatbots in education is challenging (Huang et al, 2022;Hwang & Chang, 2021;Kuhail et al, 2022;Okonkwo & Ade-Ibijola, 2021;Tsivitanidou & Ioannou, 2020;Wollny et al, 2021;Yang & Evans, 2019). One of the main challenges is the ethical and privacy concerns related to using chatbots in education (Chen et al, 2022). The study also examines these challenges and suggests ways to address them in a flipped learning context.…”

Section: Introductionmentioning

confidence: 99%

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Chatbots and Flipped Learning: Enhancing Student Engagement and Learning Outcomes through Personalised Support and Collaboration

Baskara

2023

IJORER Int. J. Recent Educ. Res.

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Objective: This paper explored the relationship between chatbots and flipped learning in an educational setting. It also identifies the benefits and drawbacks of using chatbots in a flipped learning context and the ethical and privacy concerns related to their use. Method: The study utilized a theoretical analysis approach, which included a comprehensive review of relevant literature from Scopus and World of Science databases. The data collected from the literature review was analyzed using a qualitative approach. Results: The study found that chatbots can potentially enhance student engagement and learning outcomes in a flipped learning context by providing personalized support, facilitating group discussions and collaborations, providing feedback and assessment on student work, supporting self-directed learning, and enhancing student engagement and motivation. However, using chatbots in a flipped learning context also raises ethical and privacy concerns, including data privacy, data security, and student anonymity. Novelty: Contributes to the existing research on using chatbots in education by providing insights into the potential benefits and drawbacks of using chatbots in a flipped learning context. The study highlights the importance of considering the ethical and privacy concerns and the future potential of chatbots in a flipped learning context and proposes future research directions.

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Section: Resultsmentioning

confidence: 99%

Section: Step Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Chatbots and Flipped Learning: Enhancing Student Engagement and Learning Outcomes through Personalised Support and Collaboration

Baskara

2023

IJORER Int. J. Recent Educ. Res.

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“…Another interesting, yet theoretically underdeveloped application of AI is the use of AI-powered chatbots in the context of education and the experiences of students who use them. Chen et al, (2023) make the case that chatbots theory-building efforts and theory-driven designs in SRS research and practice.…”

Section: The Special Issuementioning

confidence: 99%

Artificial Intelligence (AI) and Information Systems: Perspectives to Responsible AI

et al. 2022

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example the responsible design (Dennehy et al., 2021) and governance (Mäntymäki et al., 2022b) of AI systems. While organisations are increasingly investing in ethical AI and Responsible AI (RAI) (Zimmer et al., 2022), recent reports suggest that this comes at a cost and may lead to burnout in responsible-AI teams (Heikkilä, 2022). Thus, it is critical to consider how we educate about RAI (Grøder et al., 2022) and rethink our traditional learning designs (Pappas & Giannakos, 2021), as this can influence end-users' perceptions towards AI applications (Schmager et al., 2023) as well as how future employees approach the design and implementation of AI applications (Rakova et al., 2021;Vassilakopoulou et al., 2022).The use of algorithmic decision-making and decisionsupport processes, particularly AI is becoming increasingly pervasive in the public sector, also in high-risk application areas such as healthcare, traffic, and finance (European Commission, 2020). Against this backdrop, there is growing concern over the ethical use and safety of AI, fuelled by reports of ungoverned military applications (Butcher and Beridze, 2019; Dignum, 2020), privacy violations attributed to facial recognition technologies used by the police (Rezende, 2022), unwanted biases exhibited by AI applications used by courts (Imai et al., 2020), and racial biases in clinical algorithms (Vyas et al. 2020). The opacity and lack of explainability frequently attributed to AI systems makes evaluating the trustworthiness of algorithmic decisions challenging even for technical experts, let alone the public. Together with the algorithm-propelled proliferation of misinformation, hate speech and polarising content on social media platforms, there is a high risk for erosion of trust in algorithmic systems used by the public sector (Janssen et al., 2020). Ensuring that people can trust in the algorithmic processes is essential not only for reaping the potential benefits from AI (Dignum, 2020) but also for fostering trust and resilience at a societal level.AI researchers and practitioners have expressed their fears about AI systems being developed that are Denis Dennehy

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Plagiarism in AI Empowered World

Steponenaite

Barakat

2023

Lecture Notes in Computer Science

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The use of Artificial Intelligence (AI) has revolutionized many aspects of education and research, but it has also introduced new challenges, including the problem of students using AI to create assignments that cannot be detected by plagiarism checkers. The proliferation of AI tools that can generate original-sounding text has made it easier for students to pass off the work of others as their own, making it more difficult for educators to identify and prevent plagiarism. This paper identifies the problem of plagiarism in the AI empowered world by comparing ChatGPT written assignments for biology and computer science. We have tested the plagiarism of those assignments in freely available tools online as well as in trusted and widely used Turnitin. We show that although the original ChatGPT written assignments sometimes result in relatively high plagiarism level, adding just one additional step of paraphrasing the work with free AI tools online significantly reduces the detected plagiarism with similarity levels laying within the acceptable range. This suggests that educational facilities should rethink of how they are assessing students' knowledge.

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Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success

Cited by 149 publications

References 63 publications

Chatbots and Flipped Learning: Enhancing Student Engagement and Learning Outcomes through Personalised Support and Collaboration

Chatbots and Flipped Learning: Enhancing Student Engagement and Learning Outcomes through Personalised Support and Collaboration

Artificial Intelligence (AI) and Information Systems: Perspectives to Responsible AI

Plagiarism in AI Empowered World

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