It has been a while since my last report. I spent the past couple of years looking into the neural network of attention and how it is related to the perisylvian cortex and limbic system when processing another language. It is a follow-up, or rather prequel, to my book “Language Learning and the Brain” (Cambridge University Press, 2017).
I am excited to report that a series of experiments are to commence in the second half of 2021 researching attention and processing using technology in second language acquisition. The experiments are run using a Virtual Reality learning platform developed by the Victoria based start-up Infusion Edutainment. The experiments will investigate the effectiveness of each tool, the platform features, as well as how attention is sustained over longer periods of time.
Preliminary results will be reported later this year on this blog and in person at the next CALICO conference in 2022.
In this post entry, we are interested in the analysis of the students’ interactions on Twitter. The interactions between the peers, between the lecturer and the students, or between the students and the TA, and the students’ interactions with the subscriptions change in Fall 2016, Spring 2017, Fall 2018 and in Spring 2018. We would like to compare the references of that category and identify the trigger of those variations.
Source image: pixabay
In Fall 2016, there are 219 references in the node interaction with the lecturer, 100 in Spring 2017, 135 in Fall 2018, and 70 references in Spring 2018. It appears here that the references in Fall are higher than those in Spring. It has also occurred to us that the lecturer’s engagement was higher than in the following years. Actually, the students were constantly answering questions about the course material. This assumption must nevertheless be backed up by the information about the node theme.
There are 94 references in the node interactions with peers in Fall 2016, 87 in Spring 2017, 439 references in Fall 2018, and 86 references in Spring 2018. In this case, the references are also higher in Fall. But it is even higher in Fall 2018. It will be interesting to understand what reasons could have possibly triggered that result. In Fall 2018, the lecturer was not involved in the Twitter activity. Moreover, in the same semester, more than 40 students are taking the French course. The high level of interactions between them may indicate the convenience to interact with peers, and probably a motivation originating from the non-participation of the lecturer on Twitter.
In Fall 2016, the node interactions with TA has 16 references node in Spring 2017. In Fall 2018, 204 references in that node and 164 in Spring 2018. The numbers are lower in Fall 2016, which breaks the trends we were trying to build.
In Fall 2016 and 2018, the interactions with subscriptions are low. 23 references in 2016 against 15 in 2018. In Spring, only one interaction with the subscriptions is counted. Those numbers also show that the student does not really interact with subscriptions. It also reveals that the interactions between peers were higher when the professor was not interacting.
As a research assistant, I have been involved in Dr Caws’ project for approximately a year now. As a student in literature, I can assert that I was playing out of my comfort zone. My roles in her research were split between my tasks as a research assistant and a teaching assistant.
Image reference: pixabay
As a RA*, I have basically been collecting and coding data collected from Twitter using Nvivo. The coding comprehends 3 main parts. Firstly, I am coding the students’ interaction with their peers, their teacher and the TAs. Secondly, I was also coding their production, and thirdly the themes. The popularity of certain categories varies from one year to another.
When I was a TA in Fall 2018, I interacted with the students on Twitter. We were mostly encouraging them to produce data using the new vocabulary learned in their French class. Our conversations revolved around what they learned in the French class with their teacher.
Image refence : pixabay
Thanks to this research, I have discovered the possibility to use social media to learn a new language by following and interacting with pages in French. Nevertheless, the students’ motivation drop after each term since their interactions ceased.
During this research, I am also learning to recognize the common mistakes of English-speaking people who are learning French.
*RA= Research assistant
TA= teaching assistant
Here is the long overdue post on the grammar project, I have carried out in the lab for the past three years. I think the last post was four years ago when the pilot study had been completed.
The grammar project had students come to the lab and practice prepositions. Students were intermediate learners of German at an A2 proficiency level. Each student had six sessions in the lab, one per week. Each week each student read a fairy-tale and then practiced comprehension by either using a multiple-choice format (MC) or a fill-in-the blanks format (FiB). These formats represent what in cognitive psychology is referred to as “maintenance rehearsal” (MC) and “elaborate rehearsal” (FiB). A pre-test and two post-tests were carried out, one in the FiB and one in the MC format. The study was repeated for reasons of validity.
All in all, the data of 47 Intermediate German language learners has been analyzed by compiling the data in two groups (MC and FiB) and using inferential statistics as well as a log that tracked every klick (MC) and word typed (FiB) of every learner. Results showed that the learners in both groups improved their scores in the post-tests compared to the pre-test. The MC group took less time to do so. According to the log, the time, the MC group practiced was about half of what the FiB group needed. Furthermore, the MC group improved the number of correct answers by the third practice session while the FiB group needed at least four practice sessions. However, the FiB activity outperformed the learners using the MC activity in both tests, although differences were only significant in the test using the FiB format.
What do we learn from this? If my students ask me how to practice prepositions, I ask them how much time they have to practice. The MC activity type should assist them to improve their knowledge of prepositions in a relatively short period of time. Using the FiB activity type, they need to put in more time and effort to see some improved results. However, they will likely improve their knowledge of prepositions more than with the MC activity.
This week I have been working on using NVivo to code the language used by UVic French students in a peer tutoring relationship with French students in Brazil. Under the direction of Dr. Catherine Caws, I have sorted their transcribed discussions into the categories of “language”, “instrument” and “task”. Through these categories, certain qualitative trends have become more evident, such as the type of metalanguage used by UVic students while helping the Brazilians, the strategies that they use, and the sorts of tools that they use for searching and correcting language errors. Below is a diagram illustrating a frequent word in that category of “instrument” and the contexts in which it was employed.
After identifying the vocabulary associated with each category, diagrams like this, as well as the frequency of their occurrences can be easily generated. This coding helps us to see from the context of their own dialogue, what technology these second language learners use as support.