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Vetting AI Tools for Academic Use (Vetting AI Series #3)

Explore the TPACK framework's role in AI integration, examining how thoughtful selection of AI tools can enhance pedagogy, content, and technology synergy in the academic setting.

Welcome back, fellow academics!

In our third, and final, post in our Vetting AI Series, we’ll learn about vetting artificial intelligence (AI) tools. Vetting AI tools for use in academic research, teaching, and learning is similar to the process of selecting technology tools.

Let’s start off with the video, "Vetting AI Tools for Academic Use." (Length 2:54)

When looking to adapt teaching practices, it is important to include AI tools thoughtfully and intentionally in the curriculum (Stanford University Center for Teaching and Learning, 2023). The TPACK framework for technology integration is helpful when considering the selection of technology tools for teaching and learning (Koehler & Mishra, 2009). The TPACK framework aims to help understand the complex interplay between three core components of teacher knowledge: content (the subject matter to be taught), pedagogy (the methods and processes of teaching and learning), and technology (the tools and digital resources that can be used in teaching and learning). The TPACK framework suggests that in order to successfully integrate technology, it requires creative, context-specific methods, rather than a one-size fits all approach (Koehler & Mishra, 2009). A similar approach can also be applied to selecting AI tools for integration into teaching, learning, and research.

Visual representation of described TPACK Framework

Figure 1. The TPACK Framework Adapted from Koehler & Mishra, 2009

The above graphic outlines the TPACK framework for integrating technology in education. It includes:

  • Content Knowledge (CK): Understanding the subject matter to be taught.
  • Pedagogical Knowledge (PK): Knowledge of teaching methods and processes.
  • Technological Knowledge (TK): Awareness of digital tools and resources.
  • Pedagogical Content Knowledge (PCK): Combining pedagogy with content.
  • Technological Content Knowledge (TCK): Merging technology with content.
  • Technological Pedagogical Knowledge (TPK): Integrating technology with teaching methods.
  • Technological Pedagogical Content Knowledge (TPACK): The intersection of all three areas, representing the optimal approach for teaching with technology.

Fact-checking AI also requires critical thinking, assessing the facts' accuracy, and understanding the biases and viewpoints embedded in the responses, similar to evaluating and peer-reviewing written works. Though AI models do not have their own opinions, they are trained on datasets filled with human biases and viewpoints, which can influence their outputs. Therefore, it's important to recognize that AI responses may not be neutral and can reflect biases in their training data, necessitating a thoughtful consideration of the underlying viewpoints and potential biases in their answers (University of Maryland, n.d.). Vetting AI can help combat the spread of misinformation (Lin, 2023), assist researchers in discovering new knowledge, and help individuals understand scientific evidence (Vladika & Matthes, 2023).

Content Knowledge (CK): The subject matter to be taught.

When selecting the subject matter to be taught, instructors must identify the subject matter needs and determine the specific content areas where AI tools could enhance understanding or engagement. For example, in a reading research course, AI could generate creative writing prompts or assist in analyzing texts. Aligning AI with goals is another key component to effective integration, by ensuring that the selected AI tools are aligned with the curriculum's goals, helping students meet the learning objectives for the course. Institutions and instructors should integrate discussions on the ethical use of AI and the importance of digital literacy into the curriculum as well (Fowler, 2023). Privacy issues, especially regarding AI tools like ChatGPT that store user information, underscore the necessity for careful use in sensitive academic contexts (Ahmad et al., 2023). This is crucial for preparing students to critically evaluate AI tools and their outputs. Faculty should also cultivate learning environments where academic integrity and is valued (Fowler, 2023).

Pedagogical Knowledge (PK): The methods and processes of teaching and learning.

Defining education outcomes is a logical next step when integrating technology tools into teaching and learning (Koehler & Mishra, 2009). When developing AI-infused assignments, instructors should consider encouraging critical thinking (Stanford University Center for Teaching and Learning, 2023). Instructors should consider how AI tools can support pedagogical strategies that promote critical thinking, collaboration, and personalized learning. For example, AI-driven analytics embedded in learning management systems can provide insights into learning patterns, allowing for more targeted teaching approaches.

Another important aspect of technology integration is the element of student engagement and interaction, a key component of instructional design (Koehler & Mishra, 2009). Online courses should include various forms of engagement relating to the learner (eg. learner to content engagement, learner to instructor engagement, learner to learner engagement) (Martin & Bollinger, 2018). When students aren’t properly engaged in the learning process or content, it leads to many problems, especially student success in the course (Goad et. al., 2021). Selecting AI tools that enhance interaction between students and content, students and instructors, and among students themselves. Tools that support active learning, such as AI-based simulations or interactive Q&A bots, could be effective options.

Vetting AI tools is also important because it requires a deeper examination of the challenges and risks involved, as well as the insufficient linkage to theoretical and educational frameworks (Zawacki-Richter et al., 2019). Instructors should explore innovative ways to integrate AI that enhance pedagogical approaches. For instance, using AI to create dynamic, adaptive learning experiences that tailor content to the learner's pace and understanding. AI has the potential to influence academic integrity and has prompted recent shifts in teaching methods (Fowler, 2023). It is essential to carefully evaluate AI technologies to ensure they align with educational goals, ethical standards, and pedagogical practices (Slimi & Carballido, 2023).

Technological Knowledge (TK): The tools and digital resources that can be used in teaching and learning.

Next, it is essential to assess the efficiency, accessibility, and usability of the technology tool (Koehler & Mishra, 2009). Evaluating AI tools for their usability, accessibility, and alignment with existing platforms (i.e., learning platforms, learning management systems, existing integrated technology tools, etc.) will aid in the integration process. The selected AI tools should be user-friendly and accessible to all students. It is also important to understand the selected technology’s capabilities and limitations (Koehler & Mishra, 2009). Instructors should gain a thorough understanding of what the selected AI tool can do, how reliable and accurate it is, and its specific limitations. It is helpful to select tools that are transparent about the data sources and learning algorithms. When developing AI-informed assignments and integrating AI tools into learning activities, it is important for instructors to help students understand the functionality, limitations, and ethical use of the AI tools (Stanford University Center for Teaching and Learning, 2023).

Intersection of CK, PK, and TK (TPACK)

When selecting technology tools for integration, it is important to understand the intersections of content, pedagogy, and technology in the TPACK framework (Koehler & Mishra, 2009). Instructors should explore AI tools that sit at the intersection of content, pedagogy, and technology. For example, an AI tool that can adapt its content delivery based on students' understanding (CK), supports collaborative learning assignments (PK), and integrates seamlessly into the digital classroom environment (TK) would be the most ideal AI tool.

Continuous Evaluation and Adaptation

As educators, monitoring and assessment are second nature. Continuously monitoring and evaluating the effectiveness of technology tools in alignment with learning outcomes and adjusting integration strategies as needed is key for successful integration (Koehler & Mishra, 2009). Instructors can also solicit feedback from students, colleagues, and peers (Koehler & Mishra, 2009). This feedback can be used to understand the impact of AI tools on learning, and can aim to develop a community of practice among academics.  It is also important to stay up to date and current with technology trends, especially as new AI tools are continuously developed. Instructors should engage in ongoing professional development to stay informed about new technologies, pedagogical strategies, and content developments (Koehler & Mishra, 2009). Continuing education and professional development  are common practices among educators and academics. This continued training will help to establish the integration of technology and AI tools remains relevant and effective.

Prior to integrating AI, make sure to use the IT Purchase Request process to ensure the tool you want to use is secure.

Resources to Learn More:

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