Quizlet: what the students think – a qualitative data analysis

254

Quizlet: what the students

think – a qualitative data analysis

Bruce Lander

Abstract. The immediate area of interest in this study is the primary building

block of all foreign languages: vocabulary acquisition. Due to recent updates and

innovations in educational software, foreign language educators now have a huge

supply of ever improving tools to help enhance, transform and completely modify

learning. Despite this surge in interest of recent times, there is very little physical

evidence that indicates an overall sign of approval from learners. This empirical

study used the now well-known digital ashcard tool Quizlet to help a large group

of lower intermediate students to improve their vocabulary and ultimately raise

their English comprehension levels at a medium sized private university in Japan.

They were encouraged to use the said tool throughout the duration of the year-long

course and were asked for their feedback about it in the nal class. This study

helps to reinvigorate the notion that technology can and does help the modern

day language learner and can be approved in a positive manner by the majority

stakeholder; the student.

Keywords: Quizlet, digital ashcards, blended learning, qualitative data analysis.

1. Introduction

This paper will provide empirical evidence of what students think about using

Quizlet. This tool was rst released in 2007 and provided a contemporary alternative

to traditional, paper ashcards. Quizlet has since undergone considerable changes

and now provides near perfect text-to-speech pronunciation of words entered, has

an in-built dictionary, and allows users to add visual aids in the form of all jpeg

or gif les publicly available on ickr (ickr.com). These functions provide users

with a tool far superior to their analogue paper ashcard counterparts. There are

1. Matsuyama University, Matsuyama, Japan; bruce.w[email protected]

How to cite this article: Lander, B. (2016). Quizlet: what the students think – a qualitative data analysis. In S. Papadima-

Sophocleous, L. Bradley & S. Thouësny (Eds), CALL communities and culture – short papers from EUROCALL 2016

(pp. 254-259). Research-publishing.net. https://doi.org/10.14705/rpnet.2016.eurocall2016.571

255

Quizlet: what the students think – a qualitative data analysis

now several competitors. However, the widespread use of Quizlet with its clever,

interactive interface remains in language learning.

Many emerging educational software programmes are now providing links to

Quizlet and its user-friendly interface thanks to its increasing popularity the past

two years in Japan and abroad. Ashcroft and Imrie (2014) gave a practical account

of Quizlet and its full functionality at that time. They focused their account of

Quizlet on the Puentedura’s (2013) Substitution Augmentation Modication

Redenition (SAMR) model. Although their account provided a highly practical

outlook on the various functions available, it did not provide any factual data to

disclose its approval with students. Barr (2016) classied users of Quizlet into

three types, non-users who only use in class, visual and kinesthetic users. However,

no evidence was given on student opinion on the tool.

This begs the following questions: (1) what do students think of Quizlet and

its digital ashcard format?; (2) do they prefer it to more traditional methods

of learning vocabulary?; and perhaps more importantly, (3) is it effective? This

study will introduce two sets of qualitative data obtained over a two-year time

span in a test-based English language class and aims to answer these three

questions.

2. Method

Quizlet was introduced to two sets of lower intermediate students in an

introductory Test Of English for International Communication (TOEIC) course

at a university in Japan. The rst set comprised of 450 students varying in age

and gender from ages 19-21 years old. This group was instructed from April

2013 to January 2014 over the course of two 15-week semesters. The second set

comprised of a smaller group of 380 students from April 2014 to January 2015,

bringing the total sample size of this study to 830 subjects. No student within

this group had any prior experience with Quizlet or any other digital ashcard

tool to date.

Although Quizlet was not the entire focus of this course, it played a large part in

the internal and external running of the class. Each student within both groups

was required to create their own word list in class and to review words out of

class. All classes were conducted in computer classrooms with one computer per

student. Students were encouraged and expected to review words autonomously at

home either by computer or through the freely available smartphone application.

256

Bruce Lander

All lists were accessible by members of each class, creating a profoundly

collaborative nature of learning.

In the nal class of the second term, students were required to answer two simple

questions. The rst question involved students giving their opinion in a 6-point

Likert scale format, (1=strongly disagree, 2=disagree, 3=somewhat disagree,

4=somewhat agree, 5=agree, 6=strongly agree) on the following construct: “I think

smartphone apps can be effective for learning English” (Construct 1).

Students were also asked to give their opinion on Quizlet through the following

question: “Do you think Quizlet is a useful learning tool? If so why?” (Question 1).

Both the construct and the question

were conducted online using surveymonkey.

Questions were written in Japanese and English. Data was analysed with a text-

mining tool called ‘Wordminer’, version 1.5 by Fujitsu.

3. Discussion and results

Table 1. Qualitative data obtained

Phase 1

(n=432)

Phase 2

(n=371)

Total Japanese characters 8,990 11,325

Average length of answer 20.8 30.5

Retrieved 676 1,029

Repeated 50 86

No. of clusters 7 9

Table 1 shows the volume of data obtained from both data collection phases.

Altogether, 803 students responded. Of this total there were 788 respondents who

answered in Japanese, while 15 answered in English. All English answers were

translated into Japanese. This gave an average length of almost 21 characters per

answer in Phase 1 and about 30 for Phase 2. Designed specically for Japanese,

Wordminer analyses repeatedly used phrases or text within a qualitative dataset. All

redundant phrases are omitted by this tool, giving researchers the choice to choose

between the number of repetitions in each dataset. This number was set at ve or

more for this study. Construct 1 and Question 1 above were compared and collated.

2. The author carried out a similar study to this one in 2014 (Lander, 2015). However, that study analysed a different, and

smaller set of data.

257

Quizlet: what the students think – a qualitative data analysis

Figure 1. Distribution graphs for phase 1 (Lander, 2015)

Figure 1 shows all 50 of the phrases that were repeated ve times or more on the

left and then in a more comprehendible manner on the right. Figure 2 shows all of

the 86 repeated phrases for Phase 2. The bold red numbers indicate the Likert-scale

choice subjects chose for Construct 1. The cluster number demonstrates the typical

pattern of text choice to describe Question 1.

Figure 2. Distribution graphs for Phase 2

These distribution graphs indicate that the majority of subjects in this study gave

positive comments. This point is demonstrated by the relative position of clusters

in the central zone, which is true of both gures, but accentuated in Figure 2. Three

3. Republished with kind permission from Emerald

258

Bruce Lander

student answers to Question 1 are highlighted below. All comments were translated

into English from their original for this paper.

“I think Quizlet is a very useful learning tool. With Quizlet we can upload

our own word list, review words and take tests as many times as we want.

It also provides us with the correct pronunciation of words which is very

helpful when having trouble reading” (Student 1).

“I think it is useful, it provides many more ways to learn words than

normal. Quizlet helps us to keep focused and not lose interest” (Student 2).

“No, I don’t. I think using a regular dictionary for learning new words is

more efcient” (Student 3).

Students 1 and 2 give a clear indication that Quizlet provided a novel and enjoyable

way to learn vocabulary. Critical comments although in the minority, were evident

as is revealed by the comment made by student 3. By analysing qualitative,

empirical data in this way, repeated words can be highlighted and easily identied.

Table 2 shows a selection of words and phrases that were repeated ve times or

more. It is again possible to draw further conclusions through closer observation of

the words obtained in this table.

Table 2. Repeated words and phrases obtained

Words, phrases No. of repetitions

Our own pace

Correct spelling

Pronunciation

Countless times

Simple and easy to use

Various ways

Test function

Effective

Simple and convenient

Not really

4. Conclusions

By using highlighted phrases and word items selected by a text-mining tool like

Wordminer, it is much easier to see overall opinion of a blended learning tool

such as Quizlet. Students in this study have shown a resounding approval of

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Quizlet: what the students think – a qualitative data analysis

digital ashcards, but clearly some students prefer more traditional methods of

learning vocabulary. Lander (2015) conducted a more detailed study to this one,

and discovered that test scores in students who extensively used Quizlet can be

boosted by 6% compared to those who did not. New additions to Quizlet and

further improvements from competitors are inevitable. It is our duty as educational

researchers to make use of such tools, to enhance and redene the way our students

learn vocabulary with technology such as this.

References

Ashcroft, R. J., & Imrie, A. C. (2014). Learning vocabulary with digital ashcards. In JALT2013

Conference Proceedings. Tokyo: JALT.

Barr, B. (2016). Checking the effectiveness of Quizlet® as a tool for vocabulary learning

(Doctoral dissertation). The Centre for ELF Journal, Tamagawa University, Tokyo.

Lander, B. (2015). Lesson study at the foreign language university level in Japan: blended

learning, raising awareness of technology in the classroom. International Journal for Lesson

and Learning Studies, 4(4), 362-382. https://doi.org/10.1108/IJLLS-02-2015-0007

Puentedura, R. R. (2013, May 29). SAMR: Moving from enhancement to transformation. http://

www.hippasus.com/rrpweblog/archives/000095.html

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