As a developing scholar in the field of self-regulation, I anticipate that the innovations in methodology will greatly advance the field of cognitive and metacognitive research. The shifts in study design, data collection, and data analysis have meaningful implications for metacognitive/cognitive researchers. Technology has enabled the development of new data collection procedures that capture mental processes that were previously unobservable, such as the reading comprehension processes analyzed in Coiro’s study (2009). The development of data analysis tools (video-coding software, audio-coding software, computer-assisted coding) enables researchers to capture and quantize micro-processes that would have been previously too cumbersome to analyze. These advances in methodology allow cognitive researchers to map out external behaviors to mental processes (Coiro & Dobler, 2007).
Whereas previous research on metacognition has largely relied on self-reported measures, the development of technology may enable the study of metacognitive skills in action. The use of simulated environments (such as VR) may allow researchers a deeper look into metacognitive skills that activated when participants are engaged in an authentic experience which requires the use of self-regulation. Additionally, simulated environments can be outfitted with data-capture features that capture the range of processes (decision-making actions, eye-tracking movements, etc.) more comprehensively than naturalistic observations. These shifts in my field are evident in the growing number of self-regulation studies that are observing and capturing the self-regulatory processes in real-time through video and audio-capturing devices.
Kramarski, B., & Kohen, Z. (2017). Promoting preservice teachers’ dual self-regulation roles as learners and as teachers: effects of generic vs. specific prompts. Metacognition and Learning, 12(2), 157-191.
Michalsky, T. (2012). Shaping self‐regulation in science teachers’ professional growth: Inquiry skills. Science Education, 96(6), 1106-1133.
Hi Marissa – Your post made me reflect on how much technological shifts have impacted ALL domains within education and psychology. It was interesting to see how you reflected on the future of metacognitive/cognitive work in the new millennium. Similar to your work, the field of motivation can also benefit from new data collection procedures and data analysis strategies. For instance, in our lab the students have mostly shifted from using SPSS to using R because of the flexibility in the codes you can use and develop. You mentioned previous tools making the data we use today more cumbersome and we are experiencing similar constraints with SPSS. What type of specific tools do you envision you will be using to analyze your data in the near future?
Hi, Marissa.
Thank you for sharing your observations about new methodologies for studying cognition and metacognition. Your post reminded me of a fascinating presentation about VR in education, which I saw a couple weeks ago at the conference of the Society for Information Technology and Teacher Education. I think you might really enjoy this conference in the future: http://site.aace.org/conf/
Your post might have been stronger if it had cited the Mishra, Koehler & Greenhow chapter from the new Handbook of Educational Psychology (2015), which was mentioned in the prompt. I do appreciate the other research you cited in your authoritative post.
I look forward to reading your research in this area in the future.
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