Jihanne Dumo, University of Northern British Columbia
@JihanneDumo
Participants completing a study online cannot clarify their understanding of the task with an experimenter, possibly leading to reduced data quality. The absence of an experimenter can be particularly detrimental to the data quality for designs that involve complex cognitive tasks and multiple testing sessions. However, the insurgence of video conferencing technology now permits live interaction between a participant and an experimenter, facilitating task comprehensiveness and possibly improving data quality of online studies. The purpose of the current study was to determine how the delivery of task instructions impacts data quality in an online cognitive study.
In a between-subjects design, participants completed two testing sessions in either the Zoom condition where an experimenter delivered instructions or in a written instruction condition (no experimenter). Each participant completed two cognitive tasks (spatial n‑back and Remote Associates Test) along with surveys. Data quality was assessed through attention checks, comprehension quizzes, task performance, and survey test-retest reliability. Data collection was recently completed, and results will be presented at the conference. As an integrated service provider with its graphical user interface, helpful support team, and online community, Gorilla has allowed us to create and run our first online study in less than a year.
Full Transcript:
Jihanne:
Awesome. Well, thank you so much for inviting me to give this talk. And I’m just going to say hi to everybody. I’m Jihanne, And today I’ll be talking about the impact of different modes of instruction delivery on data quality in an online multi-session cognitive study.
Jihanne:
So, as I’m sure we’re all familiar with, there is a gold standard in the lab where we can control for many aspects of testing, such as the environment and the equipment use, which helps reduce noise. Another important aspect of the lab is that an experimenter can be present to guide the participant through the study. And in online experiments, we lose control of a lot of those elements. So there are many extraneous variables that may influence the data collected. And that includes the participants being unable to clarify their understanding of the instructions. And this factor is critical to experiments in our lab, which uses complex cognitive tasks and multi-session designs, wherein in each participant is worth a lot of data. So variable comprehension in study elements can lead to reduced data quality.
Jihanne:
Instructions in online studies are commonly in written format, and there have been studies that directly address instruction delivery and experimenter presence in online settings, but they are quite sparse. They mostly compared face-to-face versus online studies, and there have been mixed findings. Some of them comparable results while others have found more varied performance online.
Jihanne:
So from those studies, along with the rest of our lit review, we found that the lack of supervision online can lead to noisier data due to two factors related to experimenter presence. And that includes the implicit expectations imparted by the experimenter that help maintain the participants attention, as well as the experimenter’s role in ensuring that the participants understand the instructions of the study.
Jihanne:
So with this in mind, along with the ubiquity of Zoom during the pandemic, as evidenced by the previous talks as well with Teams, we set out to test video conferencing technology as a tool that can be used in online research to translate aspects of the lab environment.s
Jihanne:
So specifically, we wanted to see how different modes of instruction delivery, comparing Zoom versus written instructions, impact the data quality in surveys and cognitive tasks, the comprehension of instructions, the data quality within multi-session design, as well as the participants’ experience. And with that be predicted that the Zoom condition would lead to better data quality, compared to the written condition only, as it translates elements of the lab.
Jihanne:
So from attending the conference last year, we were introduced to Gorilla, which we used for our study. We had two testing days. We also had two cognitive tasks, which was in line with the interests of our lab, and was deemed a bit harder than some of the previous tasks that have been replicated online. So we chose this spatial n‑back task and the Remote Associates Test. We also had three surveys, and we had comprehension quizzes for the task and survey instructions.
Jihanne:
So we recruited undergrads through SONA, which is our departmental recruitment platform. All the participants, regardless of the condition, had to sign up for time slots. So there is a recruitment option in Gorilla to connect with SONA, but we wanted to control the time that participants completed the study, so we won’t have written participants completing the experiment at odd hours, and with our participants randomly assigned to either written or Zoom condition. And they were tested twice one week apart, and the tasks were counterbalanced, and the survey order was randomized.
Jihanne:
So one testing session started with participants giving consent, and setting up their device and their environment according to the instructions provided. Then they were quizzed on the task instructions before completing the task. The same format was followed for all three surveys. And then they answered the subjective experience survey, followed by the demographic questionnaire on the first day, and they were debriefed on the second day.
Jihanne:
So all written instructions were identical for all the participants. We tried to make the written instructions as comprehensive as possible. And in the Zoom condition, we as experimenters had our cameras and mikes on for the entire experiment, except when the participants were completing the task and surveys, to reduce their discomfort. But we were present for the entire duration of the session. We frequently asked if participants had any questions, and we also confirmed their understanding of the instructions.
Jihanne:
We also read the instructions to the participants, except for the survey instructions. And as for the participants, we asked that they keep their mic on for the entire session, but the use of cameras were optional to maximize their level of comfort, and most participants did have their cameras off.
Jihanne:
So we had several outcomes of interest, but today I’ll be presenting our preliminary results on the accuracy in the cognitive task, and performance in the task instruction quizzes.
Jihanne:
So the n‑back consisted of three conditions with different levels of difficulty. For the 1‑back participants pressed the space bar when the blue box appeared in the same place in the following trial. For the 2‑back, they responded when it appeared in the same place in the second following trial. And for the 3‑back they responded when it appeared in the same place as the third following trial.
Jihanne:
So the values presented here are logic values, and there was a significant main effect of n‑back, such that participants performed worse in the harder conditions. And this performance range was comparable to the previous literature of the task being implemented in the lab. There was no mean effect of instruction delivery. However, we did find that instruction delivery interacted with the type of n‑back, such that Zoom improved performance in the easier conditions, and worse in performance in the harder conditions.
Jihanne:
As for the Remote Associates Test, where participants were presented with three words, and they had to provide the fourth word that would link those three words, the overall performance of our online sample was considerably lower than what was reported in the literature of the task being implemented in the lab. But there was a mean effect of instruction delivery, wherein the Zoom participants performed better than the written participants. However, there was no difference in the comprehension quiz for either task, so it suggests that the difference in task performance was not driven by the difference in comprehension of instructions.
Jihanne:
And so our preliminary findings partially supported our hypothesis, when the Zoom condition improved task performance in the Remote Associates Test, but we do note that the overall performance was lower than what was previously found in the lab. The Zoom condition also improved performance in the easier n‑back conditions, but performance declined in the harder n‑back conditions. And instruction delivery did not seem to impact task comprehension.
Jihanne:
So it appears that improvement in data quality related to instruction delivery is contingent to the type of cognitive task that is implemented. And so for our next steps, we plan to complete our analysis on the rest of our outcomes of interest. We’re also interested in exploring the possible differences in computer parameters between conditions. So for example, we instructed participants to maximize their browsers, and you can confirm this using the data collected by Gorilla.
Jihanne:
And just a couple of points we learned from setting up our study is to not underestimate the time it takes for participants to set up for participants when using Zoom. And so spacing out participants is key. And also taking advantage of the features offered by the experimental platform to help maximize data quality. So for example in Gorilla, the randomization and branching nodes were very helpful for us.
Jihanne:
And a final note to keep in mind is that most cognitive and behavioral tasks have been validated in lab. So we must continue to ask how we can adequately translate these tasks online, and even consider designing tasks for online settings.
Jihanne:
And with that, I’d just like to thank my supervisor, Dr. Annie Duchesne and from our lab, Kiran and Emma, as well as our senior lab instructor, Julie. And also thank you to everyone here for listening to my presentation.
Speaker 2:
Thank you very much Jihanne. We have time for a question, if somebody would like to ask one in the Q&A, otherwise I’m going to ask my question. So we’ll need to type furiously.
Speaker 2:
Okay, I’m going to grab the opportunity to ask a question. I liked your point at the end there, like we’ve started with a model of, “This is how we do experiments in the lab,” and then we’ve taken that online. But there would really be a value in thinking, “I’m starting again. This is a different format.” If in-person testing had never been possible, what would online testing look like? It would probably look different. Would you care to expand on that for just a minute?
Jihanne:
Yeah, for sure. So, as I said in that point very succinctly, right, like most of the tasks that we’re seeing online have been validated in the lab. And it’s really hard to compare the lab with online. There are benefits to both, for sure, but for us to just take one thing and throw it in another setting, I feel like it’s not the fairest thing to do, in terms of making sure that we’re getting the same output from those tasks.
Speaker 2:
Thank you very, very much. So thank you, Jihanne.