Posts Tagged ‘Quizlet’

Digital flashcard systems like Memrise and Quizlet remain among the most popular language learning apps. Their focus is on the deliberate learning of vocabulary, an approach described by Paul Nation (Nation, 2005) as ‘one of the least efficient ways of developing learners’ vocabulary knowledge but nonetheless […] an important part of a well-balanced vocabulary programme’. The deliberate teaching of vocabulary also features prominently in most platform-based language courses.

For both vocabulary apps and bigger courses, the lexical items need to be organised into sets for the purposes of both presentation and practice. A common way of doing this, especially at lower levels, is to group the items into semantic clusters (sets with a classifying superordinate, like body part, and a collection of example hyponyms, like arm, leg, head, chest, etc.).

The problem, as Keith Folse puts it, is that such clusters ‘are not only unhelpful, they actually hinder vocabulary retention’ (Folse, 2004: 52). Evidence for this claim may be found in Higa (1963), Tinkham (1993, 1997), Waring (1997), Erten & Tekin (2008) and Barcroft (2015), to cite just some of the more well-known studies. The results, says Folse, ‘are clear and, I think, very conclusive’. The explanation that is usually given draws on interference theory: semantic similarity may lead to confusion (e.g. when learners mix up days of the week, colour words or adjectives to describe personality).

It appears, then, to be long past time to get rid of semantic clusters in language teaching. Well … not so fast. First of all, although most of the research sides with Folse, not all of it does. Nakata and Suzuki (2019) in their survey of more recent research found that results were more mixed. They found one study which suggested that there was no significant difference in learning outcomes between presenting words in semantic clusters and semantically unrelated groups (Ishii, 2015). And they found four studies (Hashemi & Gowdasiaei, 2005; Hoshino, 2010; Schneider, Healy, & Bourne, 1998, 2002) where semantic clusters had a positive effect on learning.

Nakata and Suzuki (2019) offer three reasons why semantic clustering might facilitate vocabulary learning: it (1) ‘reflects how vocabulary is stored in the mental lexicon, (2) introduces desirable difficulty, and (3) leads to extra attention, effort, or engagement from learners’. Finkbeiner and Nicol (2003) make a similar point: ‘although learning semantically related words appears to take longer, it is possible that words learned under these conditions are learned better for the purpose of actual language use (e.g., the retrieval of vocabulary during production and comprehension). That is, the very difficulty associated with learning the new labels may make them easier to process once they are learned’. Both pairs of researcher cited in this paragraph conclude that semantic clusters are best avoided, but their discussion of the possible benefits of this clustering is a recognition that the research (for reasons which I will come on to) cannot lead to categorical conclusions.

The problem, as so often with pedagogical research, is the gap between research conditions and real-world classrooms. Before looking at this in a little more detail, one relatively uncontentious observation can be made. Even those scholars who advise against semantic clustering (e.g. Papathanasiou, 2009), acknowledge that the situation is complicated by other factors, especially the level of proficiency of the learner and whether or not one or more of the hyponyms are known to the learner. At higher levels (when it is more likely that one or more of the hyponyms are already, even partially, known), semantic clustering is not a problem. I would add that, on the whole at higher levels, the deliberate learning of vocabulary is even less efficient than at lower levels and should be an increasingly small part of a well-balanced vocabulary programme.

So, why is there a problem drawing practical conclusions from the research? In order to have any scientific validity at all, researchers need to control a large number of variable. They need, for example, to be sure that learners do not already know any of the items that are being presented. The only practical way of doing this is to present sets of invented words, and this is what most of the research does (Sarioğlu, 2018). These artificial words solve one problem, but create others, the most significant of which is item difficulty. Many factors impact on item difficulty, and these include word frequency (obviously a problem with invented words), word length, pronounceability and the familiarity and length of the corresponding item in L1. None of the studies which support the abandonment of semantic clusters have controlled all of these variables (Nakata and Suzuki, 2019). Indeed, it would be practically impossible to do so. Learning pseudo-words is a very different proposition to learning real words, which a learner may subsequently encounter or want to use.

Take, for example, the days of the week. It’s quite common for learners to muddle up Tuesday and Thursday. The reason for this is not just semantic similarity (Tuesday and Monday are less frequently confused). They are also very similar in terms of both spelling and pronunciation. They are ‘synforms’ (see Laufer, 2009), which, like semantic clusters, can hinder learning of new items. But, now imagine a French-speaking learner of Spanish studying the days of the week. It is much less likely that martes and jueves will be muddled, because of their similarity to the French words mardi and jeudi. There would appear to be no good reason not to teach the complete set of days of the week to a learner like this. All other things being equal, it is probably a good idea to avoid semantic clusters, but all other things are very rarely equal.

Again, in an attempt to control for variables, researchers typically present the target items in isolation (in bilingual pairings). But, again, the real world does not normally conform to this condition. Leo Sellivan (2014) suggests that semantic clusters (e.g. colours) are taught as part of collocations. He gives the examples of red dress, green grass and black coffee, and points out that the alliterative patterns can serve as mnemonic devices which will facilitate learning. The suggestion is, I think, a very good one, but, more generally, it’s worth noting that the presentation of lexical items in both digital flashcards and platform courses is rarely context-free. Contexts will inevitably impact on learning and may well obviate the risks of semantic clustering.

Finally, this kind of research typically gives participants very restricted time to memorize the target words (Sarioğlu, 2018) and they are tested in very controlled recall tasks. In the case of language platform courses, practice of target items is usually spread out over a much longer period of time, with a variety of exposure opportunities (in controlled practice tasks, exposure in texts, personalisation tasks, revision exercises, etc.) both within and across learning units. In this light, it is not unreasonable to argue that laboratory-type research offers only limited insights into what should happen in the real world of language learning and teaching. The choice of learning items, the way they are presented and practised, and the variety of activities in the well-balanced vocabulary programme are probably all more significant than the question of whether items are organised into semantic clusters.

Although semantic clusters are quite common in language learning materials, much more common are thematic clusters (i.e. groups of words which are topically related, but include a variety of parts of speech (see below). Researchers, it seems, have no problem with this way of organising lexical sets. By way of conclusion, here’s an extract from a recent book:

‘Introducing new words together that are similar in meaning (synonyms), such as scared and frightened, or forms (synforms), like contain and maintain, can be confusing, and students are less likely to remember them. This problem is known as ‘interference’. One way to avoid this is to choose words that are around the same theme, but which include a mix of different parts of speech. For example, if you want to focus on vocabulary to talk about feelings, instead of picking lots of adjectives (happy, sad, angry, scared, frightened, nervous, etc.) include some verbs (feel, enjoy, complain) and some nouns (fun, feelings, nerves). This also encourages students to use a variety of structures with the vocabulary.’ (Hughes, et al., 2015: 25)

 

References

Barcroft, J. 2015. Lexical Input Processing and Vocabulary Learning. Amsterdam: John Benjamins

Erten, I.H., & Tekin, M. 2008. Effects on vocabulary acquisition of presenting new words in semantic sets versus semantically-unrelated sets. System, 36 (3), 407-422

Finkbeiner, M. & Nicol, J. 2003. Semantic category effects in second language word learning. Applied Psycholinguistics 24 (2003), 369–383

Folse, K. S. 2004. Vocabulary Myths. Ann Arbor: University of Michigan Press

Hashemi, M.R., & Gowdasiaei, F. 2005. An attribute-treatment interaction study: Lexical-set versus semantically-unrelated vocabulary instruction. RELC Journal, 36 (3), 341-361

Higa, M. 1963. Interference effects of intralist word relationships in verbal learning. Journal of Verbal Learning and Verbal Behavior, 2, 170-175

Hoshino, Y. 2010. The categorical facilitation effects on L2 vocabulary learning in a classroom setting. RELC Journal, 41, 301–312

Hughes, S. H., Mauchline, F. & Moore, J. 2019. ETpedia Vocabulary. Shoreham-by-Sea: Pavilion Publishing and Media

Ishii, T. 2015. Semantic connection or visual connection: Investigating the true source of confusion. Language Teaching Research, 19, 712–722

Laufer, B. 2009. The concept of ‘synforms’ (similar lexical forms) in vocabulary acquisition. Language and Education, 2 (2): 113 – 132

Nakata, T. & Suzuki, Y. 2019. Effects Of Massing And Spacing On The Learning Of Semantically Related And Unrelated Words. Studies in Second Language Acquisition 41 (2), 287 – 311

Nation, P. 2005. Teaching Vocabulary. Asian EFL Journal. http://www.asian-efl-journal.com/sept_05_pn.pdf

Papathanasiou, E. 2009. An investigation of two ways of presenting vocabulary. ELT Journal 63 (4), 313 – 322

Sarioğlu, M. 2018. A Matter of Controversy: Teaching New L2 Words in Semantic Sets or Unrelated Sets. Journal of Higher Education and Science Vol 8 / 1: 172 – 183

Schneider, V. I., Healy, A. F., & Bourne, L. E. 1998. Contextual interference effects in foreign language vocabulary acquisition and retention. In Healy, A. F. & Bourne, L. E. (Eds.), Foreign language learning: Psycholinguistic studies on training and retention (pp. 77–90). Mahwah, NJ: Erlbaum

Schneider, V. I., Healy, A. F., & Bourne, L. E. 2002. What is learned under difficult conditions is hard to forget: Contextual interference effects in foreign vocabulary acquisition, retention, and transfer. Journal of Memory and Language, 46, 419–440

Sellivan, L. 2014. Horizontal alternatives to vertical lists. Blog post: http://leoxicon.blogspot.com/2014/03/horizontal-alternatives-to-vertical.html

Tinkham, T. 1993. The effect of semantic clustering on the learning of second language vocabulary. System 21 (3), 371-380.

Tinkham, T. 1997. The effects of semantic and thematic clustering on the learning of a second language vocabulary. Second Language Research, 13 (2),138-163

Waring, R. 1997. The negative effects of learning words in semantic sets: a replication. System, 25 (2), 261 – 274

I have been putting in a lot of time studying German vocabulary with Memrise lately, but this is not a review of the Memrise app. For that, I recommend you read Marek Kiczkowiak’s second post on this app. Like me, he’s largely positive, although I am less enthusiastic about Memrise’s USP, the use of mnemonics. It’s not that mnemonics don’t work – there’s a lot of evidence that they do: it’s just that there is little or no evidence that they’re worth the investment of time.

Time … as I say, I have been putting in the hours. Every day, for over a month, averaging a couple of hours a day, it’s enough to get me very near the top of the leader board (which I keep a very close eye on) and it means that I am doing more work than 99% of other users. And, yes, my German is improving.

Putting in the time is the sine qua non of any language learning and a well-designed app must motivate users to do this. Relevant content will be crucial, as will satisfactory design, both visual and interactive. But here I’d like to focus on the two other key elements: task design / variety and gamification.

Memrise offers a limited range of task types: presentation cards (with word, phrase or sentence with translation and audio recording), multiple choice (target item with four choices), unscrambling letters or words, and dictation (see below).

Screenshot_2016-05-24-08-10-42Screenshot_2016-05-24-08-10-57Screenshot_2016-05-24-08-11-24Screenshot_2016-05-24-08-11-45Screenshot_2016-05-24-08-12-51Screenshot_2016-05-24-08-13-44

As Marek writes, it does get a bit repetitive after a while (although less so than thumbing through a pack of cardboard flashcards). The real problem, though, is that there are only so many things an app designer can do with standard flashcards, if they are to contribute to learning. True, there could be a few more game-like tasks (as with Quizlet), races against the clock as you pop word balloons or something of the sort, but, while these might, just might, help with motivation, these games rarely, if ever, contribute much to learning.

What’s more, you’ll get fed up with the games sooner or later if you’re putting in serious study hours. Even if Memrise were to double the number of activity types, I’d have got bored with them by now, in the same way I got bored with the Quizlet games. Bear in mind, too, that I’ve only done a month: I have at least another two months to go before I finish the level I’m working on. There’s another issue with ‘fun’ activities / games which I’ll come on to later.

The options for task variety in vocabulary / memory apps are therefore limited. Let’s look at gamification. Memrise has leader boards (weekly, monthly, ‘all time’), streak badges, daily goals, email reminders and (in the laptop and premium versions) a variety of graphs that allow you to analyse your study patterns. Your degree of mastery of learning items is represented by a growing flower that grows leaves, flowers and withers. None of this is especially original or different from similar apps.

Screenshot_2016-05-24-19-17-14The trouble with all of this is that it can only work for a certain time and, for some people, never. There’s always going to be someone like me who can put in a couple of hours a day more than you can. Or someone, in my case, like ‘Nguyenduyha’, who must be doing about four hours a day, and who, I know, is out of my league. I can’t compete and the realisation slowly dawns that my life would be immeasurably sadder if I tried to.

Having said that, I have tried to compete and the way to do so is by putting in the time on the ‘speed review’. This is the closest that Memrise comes to a game. One hundred items are flashed up with four multiple choices and these are against the clock. The quicker you are, the more points you get, and if you’re too slow, or you make a mistake, you lose a life. That’s how you gain lots of points with Memrise. The problem is that, at best, this task only promotes receptive knowledge of the items, which is not what I need by this stage. At worst, it serves no useful learning function at all because I have learnt ways of doing this well which do not really involve me processing meaning at all. As Marek says in his post (in reference to Quizlet), ‘I had the feeling that sometimes I was paying more attention to ‘winning’ the game and scoring points, rather than to the words on the screen.’ In my case, it is not just a feeling: it’s an absolute certainty.

desktop_dashboard

Sadly, the gamification is working against me. The more time I spend on the U-Bahn doing Memrise, the less time I spend reading the free German-language newspapers, the less time I spend eavesdropping on conversations. Two hours a day is all I have time for for my German study, and Memrise is eating it all up. I know that there are other, and better, ways of learning. In order to do what I know I should be doing, I need to ignore the gamification. For those, more reasonable, students, who can regularly do their fifteen minutes a day, day in – day out, the points and leader boards serve no real function at all.

Cheating at gamification, or gaming the system, is common in app-land. A few years ago, Memrise had to take down their leader board when they realised that cheating was taking place. There’s an inexorable logic to this: gamification is an attempt to motivate by rewarding through points, rather than the reward coming from the learning experience. The logic of the game overtakes itself. Is ‘Nguyenduyha’ cheating, or do they simply have nothing else to do all day? Am I cheating by finding time to do pointless ‘speed reviews’ that earn me lots of points?

For users like myself, then, gamification design needs to be a delicate balancing act. For others, it may be largely an irrelevance. I’ve been working recently on a general model of vocabulary app design that looks at two very different kinds of user. On the one hand, there are the self-motivated learners like myself or the millions of other who have chosen to use self-study apps. On the other, there are the millions of students in schools and colleges, studying English among other subjects, some of whom are now being told to use the vocabulary apps that are beginning to appear packaged with their coursebooks (or other learning material). We’ve never found entirely satisfactory ways of making these students do their homework, and the fact that this homework is now digital will change nothing (except, perhaps, in the very, very short term). The incorporation of games and gamification is unlikely to change much either: there will always be something more interesting and motivating (and unconnected with language learning) elsewhere.

Teachers and college principals may like the idea of gamification (without having really experienced it themselves) for their students. But more important for most of them is likely to be the teacher dashboard: the means by which they can check that their students are putting the time in. Likewise, they will see the utility of automated email reminders that a student is not working hard enough to meet their learning objectives, more and more regular tests that contribute to overall course evaluation, comparisons with college, regional or national benchmarks. Technology won’t solve the motivation issue, but it does offer efficient means of control.

It’s practically impossible to keep up to date with all the new language learning tools that appear, even with the help of curated lists like Nik Peachey’s Scoop.it! (which is one of the most useful I know of). The trouble with such lists is that they are invariably positive, but when you actually find the time to look at the product, you often wish you hadn’t. I decided to save time for people like me by occasionally writing short posts about things that you can safely forget about. This is the first.

Nik’s take on Vocabulist was this:

Nik_Peachey

It sounds useful,  but for anyone involved in language teaching or learning, there is, unfortunately, nothing remotely useful about this tool.

Here’s how it works:

Vocabulist is super easy to use!

Here’s how:

1.Upload a Word, PDF, or Text document. You could also copy and paste text.

2.Wait a minute. Feel free to check Facebook while Vocabulist does some thinking.

3.Select the words that you want, confirm spelling, and confirm the correct definition.

4.All Done! Now print it, export it, and study it.

To try it out, I copied and pasted the text above. This is what you get for the first two lines:

vocabulist

The definitions are taken from Merriam-Webster. You scroll down until you find the definition for the best fit, and you can then save the list as a pdf or export it to Quizlet.

export

For language learners, there are far too many definitions to choose from. For ‘super’, for example, there are 24 definitions and, because they are from Merriam-Webster, they are all harder than the word being defined.

The idea behind Vocabulist could be adapted for language learners if there was a selection of dictionary resources that users could choose from (a selection of good bilingual or semi-bilingual dictionaries and a good monolingual learner’s dictionary). But, as it stands, here’s an app you can forget.