IBL, DBL & AI

Inquiry-Based Learning, Design-Based Learning, and Artificial Intelligence

The conversations around inquiry based learning had me curious about how artificial intelligence could potentially help support the two methods of learning: inquiry-based and design-based.  I read three separate papers on the topic and came away with some major takeaways to reflect on. In the following blog post, I’m experimenting with a different approach to formatting. Each article is linked, with a subsequent reflection list, thereafter, the relevant research paper quote to back my reflection. I wanted to format it this way so that I can come back to it during my thesis and collect the information and citations.

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In this paper, the big takeaways for me were:

1. Intergroup communication and collaboration effectiveness are important for inquiry based learning, how can I enhance this in my AI course?
2. AI can help with teacher effectiveness (organizing inquiry activities)
3. Constructivism definition to use in my (thesis) paper / project with an emphasis on teacher reflection, ideally collaborative reflection
4. Shifts the focus from results to process
5. Inquiry based mind mapping = enhances students critical thinking skills and learning motivation
6. Teacher presence and guidance is fundamental

1. “When designing inquiry-based learning activities, teachers must deliberately select tasks that cannot be fully replaced by generative artificial intelligence (Hodges et al., 2023). Activities such as oral presentations, group collaborations, and hands-on practical tasks serve as prime examples of effective engagement. These types of activities require students not only to participate actively in practical exercises but also to develop essential teamwork and communication skills, which will help mitigate over-reliance on text generated by GAI.” (Xu, 2024, p. 16)
2. “The future direction of education will be focused on providing an inclusive and stimulating learning environment where every student can study successfully and their abilities can be nurtured and developed. Therefore, AI-driven inquiry teaching can be a valuable instructional approach that aids students in learning through efficient data analysis and algorithmic decision-making. This method also allows for more classroom time to be dedicated to higher-level learning activities, thereby facilitating continuous improvement in college students’ learning outcomes.” (Xie, 2023, p. 2)
3. Their paper also outlined a definition of constructivism theory that seems more accessible than others I’ve read, because it also talked about teacher’s reflecting. The usual definitions of how students acquire knowledge and information stayed true, but the addition of teachers also paying “attention to the changes in their own identity to become guides for students’ meaning construction instead of simply imparting what students have learned” was a new aspect that I hadn’t heard before or considered myself (Xie, 2023, p. 3). And yes, it’s true – teachers to a tremendous amount of reflecting, in the moment and on the fly, and in great depth. I recently blogged about a project I did with my students and how I was happy with the success of it, but at every step of the way I was reflecting on how I could have done it better, or how I will do it differently next time. They also suggested that collaborative teacher reflection is more impactful, a tool that I’ve been grateful to have more of this year with sharing a classroom with a teacher more experienced in providing adaptations in the classroom. Additionally, “Lotter [21] found that teachers need to reflect at different levels in the inquiry teaching mode, which can provide a more realistic learning environment to enhance students’ learning outcomes. Lin [22] investigated the influence of collaborative reflection on teachers’ inquiry teaching practices.” (Xie, 2023, p. 4)
4. “Gardner [5], an American psychologist, proposed the theory of multiple intelligences, theory which encompasses spatial intelligence, linguistic intelligence, and bodily kinesthetic skills. This theory emphasizes the abilities that learners need when encountering problems or creating works that exist independently. Therefore, this theory advocates various evaluation concepts to promote development through evaluation. It transcends the traditional testing-based evaluation orientation and shifts the focus from results to the procedural review of work.” (Xie, 2023, p. 3)
5. “Sari [14] found that students who utilize inquiry-based mind mapping exhibit differences in critical thinking ability and learning motivation. Furthermore, inquiry-based mind mapping tools have a significant impact on enhancing learners’ critical thinking skills and learning motivation. Aditomo [15] indicated that inquiry teaching is positively correlated with learners’ learning outcomes. However, in the absence of teacher guidance, it is negatively correlated with learners’ learning outcomes. This further proves that inquiry teaching must take into account the role of teachers, who should provide scientific and reasonable guidance in the inquiry learning process of learners.” (Xie, 2023, p. 4)

The authors also outlined four components of AI-Driven inquiry:

1. “Questioning
2. Evidence Acquisition
3. Explanation Focus
4. Evaluation Summary” (Xie, 2023, p. 1)

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In this paper, the big takeaways for me were:

1. GAI can help make the learning process highly personalized, catering to the learner
2. Students benefit from timely and effective feedback as they go through the process
3. They provided good suggestions on how to keep the soft skills sharp through the process of inquiry based learning

1. “GAI significantly enriches the variety of learning resources available to students, addressing the diverse educational needs of different individuals by employing sophisticated algorithms to generate highly personalized learning content. At the forefront of its capabilities, GAI possesses the ability to meticulously analyze each student’s learning history alongside their personal preferences, thus enabling the customization of personalized learning paths and content tailored specifically for them.” (Xu, 2024, p. 14)
2. “Within inquiry-based learning, the provision of timely and effective feedback is crucial for facilitating students’ growth and development. GAI is capable of conducting a thorough analysis of students’ learning processes and outcomes, offering personalized evaluations that cater to individual learning experiences.” (Xu, 2024, p. 15) This real-time feedback mechanism not only fosters an environment conducive to student reflection and self-regulation but also empowers teachers with timely insights into students’ learning statuses, allowing them to provide more effective support tailored to students’ evolving educational needs.” (Xu, 2024, p. 15)
3. “When designing inquiry-based learning activities, teachers must deliberately select tasks that cannot be fully replaced by generative artificial intelligence (Hodges et al., 2023). Activities such as oral presentations, group collaborations, and hands-on practical tasks serve as prime examples of effective engagement. These types of activities require students not only to participate actively in practical exercises but also to develop essential teamwork and communication skills, which will help mitigate over-reliance on text generated by GAI.” (Xu, 2024, p. 16)

Photo by Hal Gatewood on Unsplash

1. Design thinking is a skill teachers need more practice at, it’s not effectively being done, nor is there adequate research examining this.
2. This paper outlined an effective use of AI (in a well-established study with quantitative data) that I would like to explore with my future AI Course. They used AI in the process of creating a digital story. They reiterated the effect use of structured frameworks throughout the lessons to help guide students through the process with clarity.
3. Teacher guidance, again, needs to be specific and step-by-step
4. AI can help facilitate reflective thinking and student self-efficacy

1. “Tsai and Chai (2012) explained this situation with tertiary barriers. The learning process is not static; it is dynamic and constantly changing. Therefore, teachers need to have design thinking skills to transform this variable nature of the learning process (Tsai & Chai, 2012; Yildiz Durak et  al., 2023). Overcoming tertiary barriers significantly facilitates the effective use of technology in education.” (Saritepeci and Yildiz Durak, 2024, p. 25176)
2. “Participants were tasked with developing a digital story in a design-based process. In the context of experimental treatment, participants were systematically encouraged to use Chat GPT and Midjourney as guidance tools in the digital story development process.” (Saritepeci and Yildiz Durak, 2024, p. 25179)
3. “The students created the stories within the steps of the instruction presented by the instructor in collaboration with ChatGPT.” (Saritepeci and Yildiz Durak, 2024, p. 25182)
4. “In support of this, we have evidence that incorporating AI in various forms in educational processes has essential outcomes for reflective thinking. Indeed, Liu et al. (2023) reported that an intervention involving incorporating AI into the learning process as a feedback tool to support reflective thinking in foreign language teaching resulted in remarkable improvements in learning outcomes and student self-efficacy.” (Saritepeci and Yildiz Durak, 2024, p. 25193)

Works Cited:

Saritepeci, M., & Yildiz Durak, H. (2024). Effectiveness of artificial intelligence integration in design-based learning on design thinking mindset, creative and reflective thinking skills: An experimental study. Education and Information Technologies, 29(18), 25175–25209. https://doi.org/10.1007/s10639-024-12829-2

Xie, X. (2023). Influence of AI-driven Inquiry Teaching on Learning Outcomes. International Journal of Emerging Technologies in Learning (iJET), 18(23), Article 23. https://doi.org/10.3991/ijet.v18i23.45473

Xu, Y. (2024). Generative Artificial Intelligence Empowering Inquiry-Based Learning: Strategy and Challenges. Journal of Educational Research and Policies, 6(9), 14–18. https://doi.org/10.53469/jerp.2024.06(09).04

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