Tag: extending the discussion

Week 10 – Extending the Discussion: New Literacies

A.M. Ternullo

Extending the Discussion – Week 11 New Literacies

Technology has shaped and reshaped the way people interact with and create information. Up until the late 1990s, information was gate-kept by publishers. People had to be bona fide experts who paid their dues in the formal education process. Scholars published works on politics, health, science, etc. Conspiracy theories were relegated to cheap tabloids found at check out counters. There was limited information available, as the experts could only supply so much information at one time. But the internet changed that (Leu et al., 2012). Especially in the wake of Web 2.0 technologies of the early 2000s and 2010s – blogs, wikis, Facebook, and Twitter – changed the ways users created and interacted with content. Anyone could post anything. In 2008, I was a newly minted college instructor and would warn my students not to use Wikipedia. I’d set up assignments where I would have them look up things on Wikipedia and then edit the pages to feature outlandish nonsense to prove it couldn’t be trusted – because what would twinklestar099 know about literature of the Cold War that Richard Slotkin didn’t know better? We were wary of authority of sources in the early days of Web 2.0 because those of us teaching and working had grown up with card catalogues and library collections that could only be used on campus, even if the catalogue was now digitized on the computer. There were processes in place to make sure disseminated information was as accurate and well composed as was possible (most of the time).

Teaching literacy in writing classes used to be the difference between an encyclopedia, a trade journal, a scholarly peer-reviewed source, and the difference between .com and .edu sources. But once Web 2.0 emerged – more was demanded. Yi (2021) get at this in his definition of AI competency. As the technologies we have become more complex, so do the means of critical thinking and reflection of the tool. And then to add to that, people have to be cognizant of how the information they find and the tools they use to find it shape them and their possible futures. We have to simultaneously evaluate the material we get, plus the source of the material, and it’s future effect on us, our culture, and our opportunities (Leander et al, 2020; Yi, 2021). Generative AI has the capacity to shape our world more than any Wikipedia article ever did. At some point, the AI is going to become indistinguishable from reality and people are going to have to be critical observers and critical participants in their world. Leu et al. (2012) articulated that the youth will drive the change and the way language happens. But in the past, language change and social change were driven by youth in a social context where fact checking was always going to be possible; I’m not sure that with AI that will be the same. Not to mention that algorithms shape what we see online and there is not a single Internet or ChatGPT or TikTok we encounter (Leander et al, 2020). Every single thing we do online is shaped by our specific interactions with the Internet. Knobel et al. (2014) discuss the ways people work to collaborate to create knowledge, and de-centralize knowledge making, but don’t talk about the pitfalls. We’re living them in 2023. Anyone can post anything online. People give credibility to the person with the camera or the blog post, I think, because we’re still stuck with the old gate-keeping mentality of we can trust published things because their published. Being published used to mean an entire vetting process of credentials, veracity of claims, research validation – now anyone with a smartphone and opinion can post anything. We have witnessed what happens when arm chair experts dominate the discourse an so many important topics with a sharp intensity in this last five years, especially. And if people do not learn to approach digital texts, digital searches, and the technologies that facilitate our access to that information with a critical eye – especially with all generative AI can do – there are problems on the horizon we cannot even articulate today.

References:

Knobel, M., & Lankshear, C. (2014). Studying new literacies. Journal of Adolescent & Adult Literacy, 57(9), 1-5.

Leu, D. J., & Forzani, E. (2012). New literacies in a Web 2.0, 3.0, 4.0, …∞ world. Research in the Schools, 19(1), 75-81.

Leander, K. M., & Burriss, S. K. (2020). Critical literacy for a posthuman world: When people read, and become, with machines. British Journal of Educational Technology, 51(4), 1262-1276.

Yi, Y. (2021). Establishing the concept of AI literacy: Focusing on competence and purpose. JAHR, 12(2), 353-368. https://doi.org/10.21860/j.12.2.8

Week 8 – Extending the Discussion

A.M. Ternullo

Extending the Discussion – Week 8

Online learning environments are difficult because they’re asynchronous. In face to face classrooms, I could always tell where my students were in terms of understanding and could very easily course correct. I built rapport very easily through bad jokes and being able to show my humanity to my students regularly. In online classes – I’m a block of text, and maybe sometimes a quick video or a voice file. It’s a very different type of interaction with students. But a key piece of success is students feeling like their teacher is present. Richardson (2003) pointed out that students who felt their instructor was present in the class felt like they learned more. Hratsinski (2009) pointed out that having someone around with a higher level knowledge than the learner increases learning. It’s difficult to be present as a block of text and it’s so easy to stifle a discussion as the instructor if you encroach on it too soon.

Online classrooms need a level of instructor interaction, however. They cannot just be left for students to engage with each other or with content and/or technology as a means of feedback. Hrtatsinski (2009) cited there are three types of interaction in a classroom: learner to learner, learner to content, and learner to instructor. When I observe and evaluate any classroom environment, I look for all of these interactions. When I build my own classroom environments, I strategically and intentionally build in all of these pieces. I would also add there needs to be clear interaction between the instructor and the content to model disciplinary thinking for a student. All three interactions need to be present for an online classroom to function well (Abrami et al., 2011). Learners cannot be left to engage only with other learners and the content – only reaching out to the instructor piecemeal for clarification and expect to leave with a well-rounded learning experience. Instructors need to set up learner to learner engagements that have a specific end goal and participate in that interaction at key points to provide timely feedback. As Jensen et al. (2023) argued, feedback while students are in process of an assignment at a useful point can lead to substantive learning. If there is no feedback from the instructor, the learner can be uncertain about their interactions with peers or content leading to correct understanding. The instructor also needs to challenge student ideas at a time when they’re developing, as that is when that feedback is more likely, in my opinion, to be able to help shape approaches and ideas.

References

Abrami, P. C., Bernard, R. M., Bures, E. M., Borokhovski, E., & Tamim, R. M. (2011). Interaction in distance education and online learning: using evidence and theory to improve practice. Journal of Computing in Higher Education, 23, 82-103.

Hrastinski, S. (2009). A theory of online learning as online participation. Computers & Education, 52(1), 78–82.

Jensen, L. X., Bearman, M., & Boud, D. (2023). Characteristics of productive feedback encounters in online learning. Teaching in Higher Education, 1-15. https://doi.org/10.1080/13562517.2023.2213168

Richardson, J. C., & Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 71-88.

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 6 – Extending the Discussion

A.M. Ternullo

Extending the Conversation

While reading Kay (2012) literature review, one thing that stood out to me was the underlying idea that using video in the classroom – especially streaming video that an instructor could create on their own or students could create – really challenges the role of the instructor. Kay’s literature review found there were multiple reasons students use videos: improve learning, preparing for class, self-checking understanding, obtaining a global overview of chapters, taking better notes and to improve face-to-face quality of classes. Kay also pointed out that there as a concern (maybe a fear) among instructors that videoing lectures or PowerPoint lectures would mean students won’t come to class. And Kay’s literature review uncovered that students were as likely to come to class as not when a video lecture was posted, but if it was a PowerPoint lecture, then students would not be as willing to come to class.

Prior to the emergence of the science of learning in the 1980s, the common model of education was one where knowledge was transferred from instructor to student, creating a dynamic where the instructor has all the power, and for students to get what they need, they had to be physically present (Nathan et al., 2022). Educational technology allows a shift in where, when, and how students access information. This also displaces the power dynamic that has been put in place, especially in the context of direct learning environments. Videos allow students to have some more ownership and control over their learning experiences. They’re not quite ready to give up on face-to-face interactions, as evidenced by the fact that brick and mortar education still exists in 2023, and students chose to return to that space after the COVID-19 pandemic’s long pause of face-to-face learning.

While instructors may record, create, or curate video content for their students to consume, that still places them in a different role in the learning context. I see an underlying fear in the ways video can shift a dynamic – if there is a video lecture, then it can be reused indefinitely, in perpetuity. For example, Concordia University was assigning a dead professor a course, using his recorded lecture materials, while being led by a living professor and two TAs. There are some ethical concerns that come up. McCllelan et al. (2022) also point out that video lectures mean students can over inflate their learning because the instructor is not there to immediately guide understanding. The role of the professor even shifts away from “guide on the side”. I’m not sure really what it looks like. But I am interested in the question of how video lectures – active or passive in the student experience – can reshape the power dynamic of the instructor and the student in a learning context. What happens to learning when the instructor is potentially perceived as more passive in the learning experience than in student-centered learning?

References:

McClellan, D., Chastain, R. J., & DeCaro, M. S. (2023). Enhancing learning from online video lectures: The impact of embedded learning prompts in an undergraduate physics lesson. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-023-09379-w

Nathan, M. J., & Sawyer, R. K. (2022). Foundations of the learning sciences. Cambridge University Press. https://doi.org/10.1017/9781108888295.004

Tangermann, V. (n.d.). A university is using a dead professor to teach an online class: “I just found out the prof for this online course I’m taking died in 2019.” The Byte. https://futurism.com/the-byte/university-dead-professor-teach-online-class

Week 5 Extension Discussion – Overview of Educational Hypermedia Research

A.M. Ternullo

Extension Discussion – Week 5 – Overview of Educational Hypermedia Research

In our guided reading, we were asked to think about researchable ideas from the Kuiper et al. (2005) article. In short summary, the article explores the new-in-2005 concerns about K-12 students being able to use the Internet in their learning and whether the Internet requires specific skill of students. In 2023, these questions are still relevant.

In the article, Kuiper et al. (2005) make reference to a research study where students were being taught explicitly that when they click on a hyperlink, they also need to interact with it deeply. In 2023, in the college setting where I teach, the assumption is that kids are going to come into the classroom with a fully formed understanding of how to interact with the Internet. The myth of the digital native, coined by Prensky (2001) persists in higher education to the detriment of learners and teachers. Prenksy’s theory was that those who grew up with technology – digital natives– would have an innate sense of how use technology, unlike digital immigrants, who came to technology later. The assumption carries over to educational spaces where it can be easy to assume that just because students grew up with technology, they will automatically know how to apply that technology to a variety of learning contexts. An innate skill to apply technology to learning does not exist.

Enyon (2020) explored the harm of the persistent nature of the digital native myth. The myth itself presents a generational divide (which Enyon notes, the literature does not support) and leads to a very hands-off approach in adults teaching children to use technology. Now, this may be different as so-called elder millennials, the original digital natives per Prensky’s theory, are taking spaces as educators in classrooms. Millennials were assumed to be native to technology because it was ubiquitous as they grew. As an elder millennial, I know that I had to learn technology and how to apply it on my own. There was no one to teach me because the divide Enyon pointed out was ever-present in my educational experiences. I had no guidance when it came to encountering hypertext for the first time, for example. The closest I ever got to “online training” was in grad school when a research librarian taught us Boolean searches in the time before Google was ubiquitous and natural language searches were a thing.

The research opportunities in this area come from looking at how learner relationship to technology is established, nurtured, and supported. The skills an Internet user needed in 2005 are also vastly different from the skills an Internet user needs in 2023.

The Web has become a different place. In the early days of the Internet, people in general were leery of it. I remember being explicitly told by high school English teachers and college professors that I could not trust everything I found online. But in 2023, “the Internet” has become an all-encompassing resource. “I read it online” becomes the only needed – or maybe even differently in 2023, “I saw it on TikTok.”  It seems that the old traditions of authorial authority (from the days of publishing when author work had to be vetted for credibility among other things before it was published) has transplanted online. If it’s published online, it must be credible, right? I see this a lot with Internet users who don’t understand that the vetting process for publishing online is to hit “submit” on a website. There are no more checks and balances. The Internet democratizes access to information, and it also allows anyone with Internet access to become a content creator. Search engine algorithms have also become very siloed. People get return results based on what they like to see, which means they confront ideas less and less that challenge their worldviews (Pariser, 2011) Not to mention the dawn of Chat GPT, which manufactures source information to appear credible and returns results based on user inputs.

Students today need to be trained to be critical of information and resources they encounter online. The Internet is a great repository of information, but not all information is created equal, or should be held as having the same value or veracity. The notion that students need specific skills still holds true and is still an area of valid research. This is an area of research I am personally very interested in.  

References

Kuiper, E., Volman, M., & Terwel, J. (2005). The web as an information resource in k–12 education: Strategies for supporting students in searching and processing information. Review of Educational Research, 75(3), 285-328. https://doi.org/10.3102/00346543075003285

Eynon, R. (2020).  “The myth of the digital native: Why it persists and the harm it inflicts”, in Burns, T. and F. Gottschalk (eds.), Education in the Digital Age: Healthy and Happy Children, OECD Publishing, Paris, https://doi.org/10.1787/2dac420b-en.

Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. penguin UK.

Prensky, M. (2001). Digital natives, digital immigrants, part 1. On the Horizon, 9(5), 1-6. https://doi.org/10.1108/10748120110424816

Extending the Discussion – Week 4: Educational Research Methods

A.M. Ternullo

Extending the Discussion –   Week 4 Educational Research Methods

Early discourse in educational technology research were focused on the difference between quantitative, experimental research and qualitative, descriptive research. Quantitative research designs are privileged in that discussion as though they illuminate generalizable truths, while qualitative methods may be viewed as illuminating specific, local truths. The discourse has since shifted to adopting mixed-methods approaches so the right tool can be employed for the research task at hand (Cobb, 2003; Foster, 2023; Jacobsen et al., 2023). Design-based research seems to be emerging in the discourse as a top contender for “gold standard” status of research in educational technology.

Design-based research does not privilege one qualitative or quantitative study. Rather, the process of research, the question posed, and the desired outcome of the research should shape and determine what processes are applied to gain an understanding (Jacobsen et al., 2023; Sandoval, 2014). Research is an iterative process – and when a researcher starts out looking at a topic, the questions asked are not fully formed and shaped because information is gathered during the research process (Jacobsen et al., 2023). Since the question evolves based on the phase and researcher’s knowledge, the methodologies employed may also need to evolve as the study progresses (Jacobsen et al., 2023). Cobb (2002) pointed out that a “primary goal for a design experiment is to improve the initial design by testing and revising conjectures as informed by ongoing analysis …” (p. 11.) Even though Cobb is speaking specifically to student learning, this goal underscores the iterative process of specifically educational research that may be overlooked in strictly quantitative or qualitative research designs, where the questions do not evolve much during the process.

Jacobsen et al. (2023) analyzed two student dissertations to illustrate the iterative process of design-based approaches in educational research. The methods to achieve understanding aren’t as important as having an open mind for this iterative process. The goal of methodological alignment should be to make sure that the questions asked by researchers can be “operationalized at each phase” of the process and are “precise” so the questions can be answered proficiently by the research (p.5). Qualitative methods should be applied when the question calls for it, just as quantitative methods should. Results from all aspects of investigation should be analyzed, compared and contrasted, and synthesized to make meaning.

The most compelling aspect of design research for me so far is that it breaks down silos of scientific vs. non-scientific, qualitative vs. quantitative, and hard vs. soft science. It opens up the discourse to focus not on how educational researchers approach questions, but what questions we are asking and what value those answers will have on the field of educational technology.

References

Cobb, P., Confrey, J., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9-13.

Foster, C. (2023). Methodological pragmatism in educational research: From qualitative-quantitative to exploratory-confirmatory distinctions. International Journal of Research & Method in Education, 1-16. https://doi.org/10.1080/1743727x.2023.2210063

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

Sandoval, W. (2013). Conjecture mapping: An approach to systematic educational design research. Journal of the Learning Sciences, 23(1), 18-36. https://doi.org/10.1080/10508406.2013.778204