Tag: conceptual framework

Extending the Discussion, Week 7 – TPACK/TPAC

A.M. Ternullo

Mishra et al. (2006) presented a framework that to me makes sense. When I started working as a trainer for technology in 2008/2009, I didn’t know that this was a theory – but the idea that we would train teachers on specific technologies, like Blackboard or YouTube or whatever the software-du-jour was made no sense to me. I always pushed back on this idea that if you know how to use the software, then you can teach your students to use it. None of the training I received to train others ever focused on a pedagogical underpinning of why the technology should be implemented. And this of course, led to a lot of resistance from instructors to adopt and adapt technology into their classroom. The biggest pedagogical reason that was offered is that it would help students get jobs; and that idea was at odds with the purpose of a college education, which was to learn to think and become well-rounded so you could would, but not be trained for a job.

            TPACK centers the instructor in the conversation, and in turn, the instructors are supposed to center the students so they can deliver the best content using the most reasonable technology to get the job done. In a lot of the work and discourse around technology, students are centered – educators want to know about their perceptions, their learning, their motivation, etc. as it’s influenced by technology. This discourse has also dominated my professional academic career. We are always measuring how X effects student learning – but rarely do we stop to ask how X effects teaching. So, TPACK re-centers this idea in powerful ways.

            For my additional article on the topic this week, I read about TPACK and Generative AI (Mishra et al. 2023). This article attempts to re-center the discourse around generative AI from: How to do we stop students from cheating? to How do we create learning spaces that leverage this technology that is not going away? How do we adapt teaching to the changing educational landscape? And again, the instructor’s work is re-centered.

            Education is cognitive work. Educators strive to help their students build their own content knowledge in areas so they can adapt it to their future needs. TPACK provides a way for instructors to be intentional about the use of technology in their classroom to maximize benefits for their students. One thing that I found compelling in Mishra et al. (2023) is the idea that if educators are intentional about the deployment of Generative AI into learning spaces, they don’t need to police student use – which is a futile effort anyway, since AI detection software is unreliable. TPACK provides a lens for intentionality that I really find valuable as a student, instructor, and administrator when it comes to technology implementation.  

References

Mishra, P., & Koehler, M.J. (2006). Technological pedagogical content knowledge: A framework for integrating technology in teacher knowledge. Teachers College Record, 108(6), 1017-1054.

Week 7 Annotation – TPACK in the age of ChatGPT and generative AI.

A.M. Ternullo

Mishra et al. (2023) apply the TPACK framework to ChatGPT to illustrate the framework is relevant to generative AI. Mirsha situate their argument the significance of the TPACK framework in educational technology and the daily work of teachers. Mishra et al. also point out that TPACK has fallen into the canon of educational technology research, and that it’s not engaged with intellectually. Rather education students learn it as part of another theory to memorize. They seek to make TPACK relevant again and encourage educators to questions of generative AI through the lens of this framework. Mirsha et al. provide an overview of the state of generative AI in education pointing out the pitfalls and benefits of using AI in the classroom, while ultimately coming to the conclusion that the educational space is forever changed because it is not a human only space any longer. Generative AI will require that new pedagogies are created to support learning that is inclusive of generative AI. Through the lense of TPACK, educators will have to think beyond the current moment to the long-term ramifications of generative AI in the classroom to assess student learning and prepare them for jobs in a world we cannot yet fully envision. Mishra et al. also point out that assessment will have to change to accommodate the ways learning will change as a result of human/machine partnerships in learning.

While Mishra et al. provide a robust overview of the current state of the TPACK framework in educational literature, they do fall into a pitfall of separating the elements of TPACK apart in order to explain the framework rather than analyzing ChatGPT holistically (Saubern et al., 2020). Mirsha et al. provide relevancy for application of the TPACK framework and try to provide some examples for how teachers can use generative AI in their classrooms to stimulate learning in new ways. These examples are cursory and only show how the focus on the discussion over academic dishonesty is the wrong place to situation the conversation in education around generative AI. Ultimately, the paper is very well organized. The literature review pulls from relevant TPACK literature, always choosing to cite the seminal work over discussions of the seminal work. The framework does not appear to be mischaracterized, but the separation of the parts does not allow for the creative dynamic between knowledge, pedagogy and technology Mishra et al. pointed out in their literature review to be fully explored in their own assessment of how TPACK can apply to generative AI in the classroom – which is also interesting because Mishra is one of the architects of TPACK.

All three facets of my academic identity – doctoral student, writing instructor, and administrator – are very interested in how Generative AI effects the classroom experience. This article opened my eyes to the reality that learning spaces are not human only learning spaces. While technology has always been at the center of my teaching practice, the technology was always mediating the learning. And now, the technology is participating in the learning (and in some ways, it’s a co-learning experience where the AI can learn from the learner, too). I’m very interested in this area as doctoral student. As a writing teacher, I want to teach my students to leverage generative AI so they can be proficient in using it as a tool to leverage their critical thinking to get better jobs. As an administrator, I want to understand the application of generative AI in the classroom to help faculty create learning spaces that don’t penalize and police students while they also navigate how to use generative AI as a learning tool in their own educational journey.

References

Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and generative AI. Journal of Digital Learning in Teacher Education, 39(4), 235-251. https://doi.org/10.1080/21532974.2023.2247480

Saubern, R., Henderson, M., Heinrich, E., & Redmond, P. (2020). TPACK–time to reboot?. Australasian Journal of Educational Technology, 36(3), 1-9.

Annotation – Educational design research: Grappling with methodological fit

A.M. Ternullo

Jacobsen et al. (2023) present a conceptual framework to assess methodological fit based on educational design research (EDR) — a term that includes all research approaches that enhance practice and advance scientific understanding. Jacobsen at al. situate the framework in the current discussion and debate of educational methodologies. Researchers seeking out theoretical or practical research must  identify problems worth study which are legitimate, researchable, and research-worthy in theoretical and/or practical terms.  

Jacobsen et al. further explore three orientations of EDR trajectories, which they define as research for interventions, research on interventions, and research through interventions. Research for interventions add to theoretical knowledge and design work. Research on interventions aims to provide information on an intervention’s characteristics. Research through interventions focuses on implementation processes of an intervention. These trajectories are usually combined and used for comparative analysis in EDR work. Jacobsen et al. use two recent dissertations to examine and illustrate the EDR trajectories they describe.

The discussion of the conceptual framework comes to a close through a discussion of why methodological fit is so challenging for researchers. Jacobsen et al. point out methodological fit depends on a variety of factors such as: the researcher’s research expertise in the area, expertise in methodologies, concerns of the researcher and other practical considerations. Four specific challenges to applying the correct methodological fit are identified: asking beginner level questions, focusing on state-of-art, rather than state of practice, insufficient measures for causal inferences, and absence of synthesis. Jacobsen et al. conclude the field of educational research needs more EDR examples to show how valuable this type of research can be.

Jacobsen et al.’s conceptual framework’s main strength comes first from the way the discussion is situated in the current discourse of methodological framework. The analysis of two dissertations to illustrate the concepts of the orientations of EDR trajectories was very strong. Elements of research design were shown at various stages of the dissertation process to illustrate and highlight the iterative nature of creating questions to shift focus of the orientation EDR trajectory. Jacobsen et al. also point out the pitfalls of this type of research for the novice researcher – which is what doctoral students are – and underscore the significance of support and mentorship from faculty if students pursue this avenue of research.

As a doctoral student knowing a dissertation is on the horizon, this conceptual framework is helpful thinking about potential topics and approaches. The most interesting sections of the article for me were the determinants of research-worthy problems and the orientations of EDR trajectories. This also connects back to Salomon & Perkins (2005) and the discussion of a concept of, with, and through technology, though this time focusing on specific intervention, which may or may not be technology. EDR is a complex, but rich way to analyze topics using mixed-methodologies that are brought to bear on a research topic as the research grows.

References

Jacobsen, M., & McKenney, S. (2023). Educational design research: Grappling with methodological fit. Educational Technology Research and Development. https://doi.org/10.1007/s11423-023-10282-5

Salomon, G., & Perkins, D. (2005). Do technologies make us smarter? Intellectual amplification with, of and through technology. In R. J. Sternberg, & D. D. Preiss (Eds). Intelligence and technology: The impact of tools on the nature and development of human abilities (pp. 71-86). Mahwah, NJ: Lawrence Erlbaum Associates.