Archive for the ‘apps’ Category

Screenshot_2016-04-29-09-48-05I call Lern Deutsch a vocabulary app, although it’s more of a game than anything else. Developed by the Goethe Institute, the free app was probably designed primarily as a marketing tool rather than a serious attempt to develop an educational language app. It’s available for speakers of Arabic, English, Spanish, Italian, French, Italian, Portuguese and Russian. It’s aimed at A1 learners.

Users of the app create an avatar and roam around a virtual city, learning new vocabulary and practising situational language. They can interact in language challenges with other players. As they explore, they earn Goethe coins, collect accessories for their avatars and progress up a leader board.Screenshot_2016-04-29-09-50-12

As they explore the virtual city, populated by other avatars, they find objects that can be clicked on to add to their vocabulary list. They hear a recording of an example sentence containing the target word, with the word gapped and three multiple choice possibilities. They are then required to type the missing word (see the image below). After collecting a certain number of words, they complete exercises which include the following task types:

  • Jumbled sentences
  • Audio recording of individual words and multiple choice selection
  • Gapped sentences with multiple choice answers
  • Dictation
  • Example sentences containing target item and multiple choice pictures
  • Typing sentences which are buried in a string of random letters

Screenshot_2016-05-02-14-23-07Screenshot_2016-05-02-14-26-13

Screenshot_2016-05-02-14-27-21Screenshot_2016-05-02-14-31-49

 

 

 

 

 

 

 

 

 

The developers have focused their attention on providing variety: engagement and ‘fun’ override other considerations. But how does the app stand up as a language learning tool? Surprisingly, for something developed by the Goethe Institute, it’s less than impressive.

The words that you collect as you navigate the virtual city are all nouns (Hotel, Auto, Mann, Banane, etc), but some (e.g. Sehenswurdigkeit) seem out of level. Any app that uses illustrations as the basic means of conveying meaning runs into problems when it moves away from concrete nouns, but a diet of nouns only (as here) is of necessarily limited value. Other parts of speech are introduced via the example sentences, but no help with meaning is provided so when you come across the word for ‘egg’, for example, your example sentence is ‘Ich möchte das Frühstück mit Ei.’ It’s all very well embedding the target vocabulary in example sentences that have a functional value, but example sentences are only of value if they are understandable: the app badly needs a look-up function for the surrounding language.

The practice exercises are varied, too, but they also vary in their level of difficulty. It makes sense to do receptive / recognition tasks before productive ones, but there is no evidence that I could see of pedagogical considerations of this kind. Neither does there seem to be any spaced repetition at work: the app is driven by the needs of the game design rather than any learning principles.

It’s unclear to me who the app is for. The functional language that is presented is adult: the situations are adult situations (buying a bed, booking a hotel room, ordering a beer). However, the graphic design and the gamification features are juvenile (adding a pirate patch to your avatar, for example).

The lack of attention to the business of learning is especially striking in the English of the English language version that I used. The number of examples of dodgy English that I came across do not inspire confidence.

  • Quite alright! You win your first Goethe coin.
  • What sightseeings do you spot in the city center and the train station?
  • Have a picknick in the park. You now have a picnic in the park with the musician.
  • You still search for your teacher. Whom do you meet in the park? What do they work?

 

All in all, it’s an interesting example of a gamified approach to language, and other app developers may find ideas here that they could do something with. It’s of less interest, though, to anyone who wants to learn a bit of German.

Having spent a lot of time recently looking at vocabulary apps, I decided to put together a Christmas wish list of the features of my ideal vocabulary app. The list is not exhaustive and I’ve given more attention to some features than others. What (apart from testing) have I missed out?

1             Spaced repetition

Since the point of a vocabulary app is to help learners memorise vocabulary items, it is hard to imagine a decent system that does not incorporate spaced repetition. Spaced repetition algorithms offer one well-researched way of improving the brain’s ‘forgetting curve’. These algorithms come in different shapes and sizes, and I am not technically competent to judge which is the most efficient. However, as Peter Ellis Jones, the developer of a flashcard system called CardFlash, points out, efficiency is only one half of the rote memorisation problem. If you are not motivated to learn, the cleverness of the algorithm is moot. Fundamentally, learning software needs to be fun, rewarding, and give a solid sense of progression.

2             Quantity, balance and timing of new and ‘old’ items

A spaced repetition algorithm determines the optimum interval between repetitions, but further algorithms will be needed to determine when and with what frequency new items will be added to the deck. Once a system knows how many items a learner needs to learn and the time in which they have to do it, it is possible to determine the timing and frequency of the presentation of new items. But the system cannot know in advance how well an individual learner will learn the items (for any individual, some items will be more readily learnable than others) nor the extent to which learners will live up to their own positive expectations of time spent on-app. As most users of flashcard systems know, it is easy to fall behind, feel swamped and, ultimately, give up. An intelligent system needs to be able to respond to individual variables in order to ensure that the learning load is realistic.

3             Task variety

A standard flashcard system which simply asks learners to indicate whether they ‘know’ a target item before they flip over the card rapidly becomes extremely boring. A system which tests this knowledge soon becomes equally dull. There needs to be a variety of ways in which learners interact with an app, both for reasons of motivation and learning efficiency. It may be the case that, for an individual user, certain task types lead to more rapid gains in learning. An intelligent, adaptive system should be able to capture this information and modify the selection of task types.

Most younger learners and some adult learners will respond well to the inclusion of games within the range of task types. Examples of such games include the puzzles developed by Oliver Rose in his Phrase Maze app to accompany Quizlet practice.Phrase Maze 1Phrase Maze 2

4             Generative use

Memory researchers have long known about the ‘Generation Effect’ (see for example this piece of research from the Journal of Verbal Learning and Learning Behavior, 1978). Items are better learnt when the learner has to generate, in some (even small) way, the target item, rather than simply reading it. In vocabulary learning, this could be, for example, typing in the target word or, more simply, inserting some missing letters. Systems which incorporate task types that require generative use are likely to result in greater learning gains than simple, static flashcards with target items on one side and definitions or translations on the other.

5             Receptive and productive practice

The most basic digital flashcard systems require learners to understand a target item, or to generate it from a definition or translation prompt. Valuable as this may be, it won’t help learners much to use these items productively, since these systems focus exclusively on meaning. In order to do this, information must be provided about collocation, colligation, register, etc and these aspects of word knowledge will need to be focused on within the range of task types. At the same time, most vocabulary apps that I have seen focus primarily on the written word. Although any good system will offer an audio recording of the target item, and many will offer the learner the option of recording themselves, learners are invariably asked to type in their answers, rather than say them. For the latter, speech recognition technology will be needed. Ideally, too, an intelligent system will compare learner recordings with the audio models and provide feedback in such a way that the learner is guided towards a closer reproduction of the model.

6             Scaffolding and feedback

feebuMost flashcard systems are basically low-stakes, practice self-testing. Research (see, for example, Dunlosky et al’s metastudy ‘Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology’) suggests that, as a learning strategy, practice testing has high utility – indeed, of higher utility than other strategies like keyword mnemonics or highlighting. However, an element of tutoring is likely to enhance practice testing, and, for this, scaffolding and feedback will be needed. If, for example, a learner is unable to produce a correct answer, they will probably benefit from being guided towards it through hints, in the same way as a teacher would elicit in a classroom. Likewise, feedback on why an answer is wrong (as opposed to simply being told that you are wrong), followed by encouragement to try again, is likely to enhance learning. Such feedback might, for example, point out that there is perhaps a spelling problem in the learner’s attempted answer, that the attempted answer is in the wrong part of speech, or that it is semantically close to the correct answer but does not collocate with other words in the text. The incorporation of intelligent feedback of this kind will require a number of NLP tools, since it will never be possible for a human item-writer to anticipate all the possible incorrect answers. A current example of intelligent feedback of this kind can be found in the Oxford English Vocabulary Trainer app.

7             Content

At the very least, a decent vocabulary app will need good definitions and translations (how many different languages?), and these will need to be tagged to the senses of the target items. These will need to be supplemented with all the other information that you find in a good learner’s dictionary: syntactic patterns, collocations, cognates, an indication of frequency, etc. The only way of getting this kind of high-quality content is by paying to license it from a company with expertise in lexicography. It doesn’t come cheap.

There will also need to be example sentences, both to illustrate meaning / use and for deployment in tasks. Dictionary databases can provide some of these, but they cannot be relied on as a source. This is because the example sentences in dictionaries have been selected and edited to accompany the other information provided in the dictionary, and not as items in practice exercises, which have rather different requirements. Once more, the solution doesn’t come cheap: experienced item writers will be needed.

Dictionaries describe and illustrate how words are typically used. But examples of typical usage tend to be as dull as they are forgettable. Learning is likely to be enhanced if examples are cognitively salient: weird examples with odd collocations, for example. Another thing for the item writers to think about.

A further challenge for an app which is not level-specific is that both the definitions and example sentences need to be level-specific. An A1 / A2 learner will need the kind of content that is found in, say, the Oxford Essential dictionary; B2 learners and above will need content from, say, the OALD.

8             Artwork and design

My wordbook2It’s easy enough to find artwork or photos of concrete nouns, but try to find or commission a pair of pictures that differentiate, for example, the adjectives ‘wild’ and ‘dangerous’ … What kind of pictures might illustrate simple verbs like ‘learn’ or ‘remember’? Will such illustrations be clear enough when squeezed into a part of a phone screen? Animations or very short video clips might provide a solution in some cases, but these are more expensive to produce and video files are much heavier.

With a few notable exceptions, such as the British Councils’s MyWordBook 2, design in vocabulary apps has been largely forgotten.

9             Importable and personalisable lists

Many learners will want to use a vocabulary app in association with other course material (e.g. coursebooks). Teachers, however, will inevitably want to edit these lists, deleting some items, adding others. Learners will want to do the same. This is a huge headache for app designers. If new items are going to be added to word lists, how will the definitions, example sentences and illustrations be generated? Will the database contain audio recordings of these words? How will these items be added to the practice tasks (if these include task types that go beyond simple double-sided flashcards)? NLP tools are not yet good enough to trawl a large corpus in order to select (and possibly edit) sentences that illustrate the right meaning and which are appropriate for interactive practice exercises. We can personalise the speed of learning and even the types of learning tasks, so long as the target language is predetermined. But as soon as we allow for personalisation of content, we run into difficulties.

10          Gamification

Maintaining motivation to use a vocabulary app is not easy. Gamification may help. Measuring progress against objectives will be a start. Stars and badges and leaderboards may help some users. Rewards may help others. But gamification features need to be built into the heart of the system, into the design and selection of tasks, rather than simply tacked on as an afterthought. They need to be trialled and tweaked, so analytics will be needed.

11          Teacher support

Although the use of vocabulary flashcards is beginning to catch on with English language teachers, teachers need help with ways to incorporate them in the work they do with their students. What can teachers do in class to encourage use of the app? In what ways does app use require teachers to change their approach to vocabulary work in the classroom? Reporting functions can help teachers know about the progress their students are making and provide very detailed information about words that are causing problems. But, as anyone involved in platform-based course materials knows, teachers need a lot of help.

12          And, of course, …

Apps need to be usable with different operating systems. Ideally, they should be (partially) usable offline. Loading times need to be short. They need to be easy and intuitive to use.

It’s unlikely that I’ll be seeing a vocabulary app with all of these features any time soon. Or, possibly, ever. The cost of developing something that could do all this would be extremely high, and there is no indication that there is a market that would be ready to pay the sort of prices that would be needed to cover the costs of development and turn a profit. We need to bear in mind, too, the fact that vocabulary apps can only ever assist in the initial acquisition of vocabulary: apps alone can’t solve the vocabulary learning problem (despite the silly claims of some app developers). The need for meaningful communicative use, extensive reading and listening, will not go away because a learner has been using an app. So, how far can we go in developing better and better vocabulary apps before users decide that a cheap / free app, with all its shortcomings, is actually good enough?

I posted a follow up to this post in October 2016.

VocApp – a review

Posted: October 28, 2015 in apps
Tags: , , ,

Go to an app store and you’ll find a number of unrelated products called VocApp. One of them, from a Polish-based outfit, has the https://vocapp.com/ url. From over 30 products in the catalogue, I selected the free ‘Top 1000 English Words’: this is, after all, the showcase app which will show you how fast and easy you can learn with us (sic). VocApp Founder, Marcin Młodzki, writes that learning languages and mobile devices are my two greatest passions. Unfortunately there wasn’t any language app on the market which satisfied me in 100% (or even in 70%…). Anki, Babel, DuoLingo, Memorize, Quizlet – each of them has some serious disadvantages. So I decided to create my own app. Prof. Ewa Lajer-Burchardt of Harvard University says it’s undoubtedly one of the best flashcard applications for learning foreign languages on the educational market. This is presumably the eminent Ewa Lajer-Burcharth, a Polish art historian and author of Necklines: The Art of Jacques-Louis David After the Terror. So, how does the app stand up? Will users raise their understanding up to 83%? I was impatient to find out.common english wordsIt’s a flashcard system with spaced repetition. This particular app has target items and audio recordings on one side of the flashcard, definitions in English, along with illustrations, on the other. It is, the makers say, multisensory. Users are then given two self-evaluation options.

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And that, I’m afraid, is about all there is to say. Apart, that is, from the content. Many of the definitions have been culled from Wiktionary, not perhaps the best source of definitions for A1 / A2 learners. Others appear to have been made up in-house. Here is an opportunity to raise your own understanding by up to 83%. Look at the VocApp definitions below and see if you can guess what the target word is (answers below[i]).

1 a piece of a whole

2 a) a kind of box b) a formal word for a situation

3 something people do every day e.g. from 10 o’clock to 4 o’clock to get money

4 a group of people who deal with politics and who give new rules

5 when we are born our life begins, when we die our life comes to an end.

6 an object

7 a) where the cars drive b) a method of doing something

8 The place where we live, not only the Earth, everything which exists; ‘world’ is a general world

9 a location of something

10 a) 24 hours b) when the sun is up, not night

Sorry, Marcin. I’m afraid your app didn’t satisfy me in 100% (or even in 70%…).

[i] Answers: 1 part 2 case 3 work 4 government 5 life 6 thing 7 way 8 world 9 place 10 day

MosaLingua  (with the obligatory capital letter in the middle) is a vocabulary app, available for iOS and Android. There are packages for a number of languages and English variations include general English, business English, vocabulary for TOEFL and vocabulary for TOEIC. The company follows the freemium model, with free ‘Lite’ versions and fuller content selling for €4.99. I tried the ‘Lite’ general English app, opting for French as my first language. Since the app is translation-based, you need to have one of the language pairings that are on offer (the other languages are currently Italian, Spanish, Portuguese and German).Mosalingua

The app I looked at is basically a phrase book with spaced repetition. Even though this particular app was general English, it appeared to be geared towards the casual business traveller. It uses the same algorithm as Anki, and users are taken through a sequence of (1) listening to an audio recording of the target item (word or phrase) along with the possibility of comparing a recording of yourself with the recording provided, (2) standard bilingual flashcard practice, (3) a practice stage where you are given the word or phrase in your own language and you have to unscramble words or letters to form the equivalent in English, and (4) a self-evaluation stage where users select from one of four options (“review”, “hard”, “good”, “perfect”) where the choice made will influence the re-presentation of the item within the spaced repetition.

In addition to these words and phrases, there are a number of dialogues where you (1) listen to the dialogue (‘without worrying about understanding everything’), (2) are re-exposed to the dialogue with English subtitles, (3) see it again with subtitles in your own language, (4) practise it with standard flashcards.

The developers seem to be proud of their Mosa Learning Method®: they’ve registered this as a trademark. At its heart is spaced repetition. This is supplemented by what they refer to as ‘Active Recall’, the notion that things are better memorised if the learner has to make some sort of cognitive effort, however minimal, in recalling the target items. The principle is, at least to me, unquestionable, but the realisation (unjumbling words or letters) becomes rather repetitive and, ultimately, tedious. Then, there is what they call ‘metacognition’. Again, this is informed by research, even if the realisation (self-evaluation of learning difficulty into four levels) is extremely limited. Then there is the Pareto principle  – the 80-20 rule. I couldn’t understand the explanation of what this has to do with the trademarked method. Here’s the MosaLingua explanation  – figure it out for yourself:

Did you know that the 100 most common words in English account for half of the written corpus?

Evidently, you shouldn’t quit after learning only 100 words. Instead, you should concentrate on the most frequently used words and you’ll make spectacular progress. What’s more, globish (global English) has shown that it’s possible to express yourself using only 1500 well-chosen words (which would take less than 3 months with only 10 minutes per day with MosaLingua). Once you’ve acquired this base, MosaLingua proposes specialized vocabulary suited to your needs (the application has over 3000 words).

Finally, there’s some stuff about motivation and learner psychology. This boils down to That’s why we offer free learning help via email, presenting the Web’s best resources, as well as tips through bonus material or the learning community on the MosaLingua blog. We’ll give you all the tools you need to develop your own personalized learning method that is adapted to your needs. Some of these tips are not at all bad, but there’s precious little in the way of gamification or other forms of easy motivation.

In short, it’s all reasonably respectable, despite the predilection for sciency language in the marketing blurb. But what really differentiates this product from Anki, as the founder, Samuel Michelot, points out is the content. Mosalingua has lists of vocabulary and phrases that were created by professors. The word ‘professors’ set my alarm bells ringing, and I wasn’t overly reassured when all I could find out about these ‘professors’ was the information about the MosaLingua team .professors

Despite what some people  claim, content is, actually, rather important when it comes to language learning. I’ll leave you with some examples of MosaLingua content (one dialogue and a selection of words / phrases organised by level) and you can make up your own mind.

Dialogue

Hi there, have a seat. What seems to be the problem?

I haven’t been feeling well since this morning. I have a very bad headache and I feel sick.

Do you feel tired? Have you had cold sweats?

Yes, I’m very tired and have had cold sweats. I have been feeling like that since this morning.

Have you been out in the sun?

Yes, this morning I was at the beach with my friends for a couple hours.

OK, it’s nothing serious. It’s just a bad case of sunstroke. You must drink lots of water and rest. I’ll prescribe you something for the headache and some after sun lotion.

Great, thank you, doctor. Bye.

You’re welcome. Bye.

Level 1: could you help me, I would like a …, I need to …, I don’t know, it’s okay, I (don’t) agree, do you speak English, to drink, to sleep, bank, I’m going to call the police

Level 2: I’m French, cheers, can you please repeat that, excuse me how can I get to …, map, turn left, corner, far (from), distance, thief, can you tell me where I can find …

Level 3: what does … mean, I’m learning English, excuse my English, famous, there, here, until, block, from, to turn, street corner, bar, nightclub, I have to be at the airport tomorrow morning

Level 4: OK, I’m thirty (years old), I love this country, how do you say …, what is it, it’s a bit like …, it’s a sort of …, it’s as small / big as …, is it far, where are we, where are we going, welcome, thanks but I can’t, how long have you been here, is this your first trip to England, take care, district / neighbourhood, in front (of)

Level 5: of course, can I ask you a question, you speak very well, I can’t find the way, David this is Julia, we meet at last, I would love to, where do you want to go, maybe another day, I’ll miss you, leave me alone, don’t touch me, what’s you email

Level 6: I’m here on a business trip, I came with some friends, where are the nightclubs, I feel like going to a bar, I can pick you up at your house, let’s go to see a movie, we had a lot of fun, come again, thanks for the invitation

Photo 01-07-2015 16 23 47Flovoco is a vocabulary app developed by ELTjam. This review was written by Mike Harrison and first appeared on his blog. After the review, I’ve added a response by Jo Sayers (of ELTjam). Many thanks to Mike for allowing me to repost his review, and thanks to Jo for allowing me to repost his comment.

I first became aware of this mobile application around July 2014, when ELTjam first posted about their product development. There was a fair amount of heat – the Edtech-meets-ELT specialists Nick Robinson, Laurie Harrison, Tim Gifford, and newbie at the time Jo Sayers, pitched us their product-in-waiting. A year or so later, I saw a presentation at IATEFL in Manchester where Jo talked about reviewing educational and ELT apps. And so to this review of an ELTjam ELT app.

This review follows a model presented by Jo, reviewing the app across four categories: pedagogy and methodology; instructional design; user experience; cost and access.

The version of the app I’m reviewing is 1.0 in the Apple AppStore, and I’m working on an iPhone 5S.

Note – the app is only available in Spanish and English at the moment.

Initial impressions

But first, it is almost impossible to comment on an app without some ‘at first glance’ context, so here it is. I initially thought that ELTjam’s marketing was a little audacious – creating a landing page for an app that didn’t exist – but following conversations recently I now realise this is fairly common practice, and a good way to generate leads for email lists and such. I do still balk a little at the audacity of fanfare around the app (more on that to come under ‘pedagogy and methodology’). On opening the app for the first time, I was impressed by how slick it looked and felt (and more on that under ‘user experience’!) – I have to hold my hands up and say that I have yet to be blown away by an educational app, whether designed for ELT or more general educational fields. Let’s see whether this will change.

untitledhimPedagogy and methodology

★★☆☆☆

The overarching principle behind Flovoco is that words are important. And that in order to get better at using a language, the best thing to do is bump up what you know about the most common words in that language. So far , so good. Flovoco aims to help learners learn more about words by presenting them with a number of activities focusing on different information about a given word – its meaning, pronunciation, how it might be used in a phrase, and then again with words deemed to be confusing. These different areas are named as Translation, Listening, Usage, and Confused Words – and they are presented as ‘levels’, Translation being the first (easiest?) level and Confused Words being the fourth level (and most difficult of the four?). This all seems fairly logical.

But then it all starts to go a bit wrong. In the Translation activity, words are presented with possible matches that aren’t even the same part of speech. Alright, wrong answers are clearly marked with a red light and wrong buzzer sound – but this is behaviourism at best. At worst this may actually confuse learners. Not to mention that this only works by looking at a single meaning of a word – so there won’t be many colloquial meanings and translations included here.

Photo 30-06-2015 18 32 10 eggsThe Listening level does the same thing. Words that are presented alongside each other are completely different. Sometimes phrases are presented, but the audio only comprises of one word in the phrase. For example, you might see ‘pay for something’ but only hear ‘play’. There may be less potential for confusion among words here, but having such a mismatch between the audio and text may be more problematic.

The next two levels are essentially the same – gap fills featuring the words that are being studied. Level three, Usage, again often presents possible answers that are completely different parts of speech. Confused Words is more of the same, but this time the words presented in the three answer slots are potentially easily confused – this seems to be focusing mainly on spelling and/or pronunciation.

Overall, pedagogically Flovoco has a noble aim – looking at the different things it’s useful to know about a word – but in practice it’s a bit confused. Methodologically, the structure of feedback is very behaviouristic. Didn’t we leave Skinner behind a while back?

Instructional design

★★☆☆☆

Admittedly I’m getting my head around the jargon of app development here, but I can’t see this. There isn’t any adaptivity (is that a word) built in to the app. You just work your way up the levels, aiming to get all 500 words into the Your Word Collection at the top level. Nothing adapts down if I keep getting a word wrong – there’s no help other than hoping that I’ll see the red ‘wrong’ button highlight enough times to learn. If I’m racing through the words, there isn’t any extension to what can be done with the words. Maybe there is space for some kind of freer practice, perhaps based around the community of language learners that ELTjam probably hope to cultivate with the app.

Photo 01-07-2015 16 43 09 word collectionPhoto 22-04-2015 08 01 36 372Photo 01-07-2015 16 42 56 profilePhoto 01-07-2015 16 43 05 usage

User experience

★★★☆☆

It looks pretty. It’s fairly easy to tap-and-go in getting started working with the app. There aren’t too many (any?) instructions, so it does rather rely on learners using the app to work things out by trial and error. The user Profile screen is relatively clean and looks straigtforward. But I haven’t worked out exactly how the Daily Word Goal works (maybe because I don’t use the app regularly) and navigating the Profile screens is a little laggy.

There is a playful feel to the app, from the Flovoco logo font to the coloured circles and stars representing the different levels. If they wanted to make learning words look like a game, that’s the impression you get.

Cost and access

Free. Spanish and English only. iOS only (the website says an Android version is in the works).

Technical requirements (iOS):

Category: Education

Updated: Feb 25, 2015

Version: 1.1.4

Size: 21.1 MB

Compatibility: Requires iOS 7.1 or later. Compatible with iPhone, iPad, and iPod touch. This app is optimized for iPhone 5.

Not yet available on Google Play.

You can get the iOS version from here: https://itunes.apple.com/us/app/flovoco/id915793649?mt=8

Overall score:

★★½☆☆

This app certainly got people talking when ELTjam first posted about it, and there is the intent to do something different in the world of ELT apps. But from what I see so far, putting it into practice leaves a fair amount to be desired. Further thought needs to be made about plausible distractors, the focus on the word level meaning may need to be expanded to make this truly different, and sorting out some kind of support/challenge for more and less able learners is something I think is quite key.

Flovoco a go? There is some potential for this app to be really good. But sorry Flovoco, at the moment it’s a no from me.

The response from Jo Sayers:

Hi Mike,

Firstly, thanks very much for writing a review; we really appreciate the feedback and reviews like this will help us as we build Flovoco to a state where both learners and industry professionals can clearly see the value it delivers. This is still our v1.0, as you point out, and so there are many things that we had to do in a way that was good enough to ship it, but necessarily not as finalised as we’d want it to be in an ideal world. The hope was that we would test some key assumptions with this version and learn things that will help us to build it out in a direction that sees it add real value to learners.

The review matches well with a lot of what we have already identified as the strengths and weaknesses of the app and we’re really happy that there are enough positive things in this early version that it already gets 2.5 out of 5. There are a few comments in the review that I wanted to respond to though:

The behaviourist approach. Our intention with the app is not to offer a complete language learning solution, rather to offer a way of quickly acquiring key vocabulary that will act as a foundation for other language development. We feel that lexical acquisition is an area that lends itself well to a more systematic (behaviourist?) approach, and also helps to achieve the flow state that we were aiming for.

Multiple senses. We made a decision to focus only on the primary senses of the words in this version to avoid the complexity of having to demonstrate what is a second or other sense of a word that they’ve encountered before. What you’re actually pushing through the levels in the app is a single sense of a word, rather than a word itself.

The distractors. The distractors for levels 1 and 2 were chosen automatically by an algorithm. I’m not sure I agree that they should all be the same part of speech. This would actually have been very straightforward for us to achieve programmatically, but we felt that it wasn’t any more pedagogically sound than mixing parts of speech. In level 2, the algorithm choosing the distractors selected words with the same initial letter and as close to the same total number of letters as possible, but as the distractors are chosen only from the 500 words in the initial pool this reduced their effectiveness. We have a plan for the next version which should make the selection much more effective. What we wanted to test here, ultimately, was that the algorithm approach worked and didn’t interfere with the learner’s ability to complete the activities.

Levels 3 and 4 being the same. Level 3 focuses on collocation by keeping the target word in the sentence (in bold) and removing a collocate; the distractors are, where possible, similar words that don’t collocate with the target word. Level 4 initially aimed to focus on derived forms of the target word and in this case the target itself is removed and other words which are similar to it act as distractors. As a lot of the words at A1 don’t have strong and obvious collocates and many don’t have derived and inflected forms this was more challenging than it would be at higher levels with fewer functional words and lower frequency content.

Instructional design. Yes, there is no adaptivity. But if you get words wrong they move to the level below, and if you get them right they move up to the next level. In terms of the feedback, the word list on the results page gives a bit of additional information about the words that you have seen. We have plans to incorporate in some community aspects to the product too. However, our plan is not to build that up within ELTjam. As I have discussed in this post for a product website, we have made a shift away from offering this directly to consumers, and now see this as an opportunity to work with publishers and offer the product to their learners through partnerships with them. The B2C version acts as a way of gaining market validation.

Daily word goal. Yes, there are bugs in this which affect the calendar and the lag you mentioned. A new version was built out last month and we should be able to ship the updated version soon.

I hope that helps to put a few of the things you noted into context. It’s also worth pointing out that during the first two months of the app being out and promoted (we are no longer promoting this version as we have learned the things we hoped to) the average session length was over 9 minutes; way more than average in most industries and even more than the average for music apps, according to this data. We also had around 8% of sessions that were over 30 minutes long. So there were a core group of people who were incredibly motivated to use the app. And given that very little is done to incentivise returning to the app (no push notifications, leaderboards, 2 player games etc.) we were really pleased to see that around 8% of learners came back for an 8th visit. So, while there are definitely things to improve, the core offering resonates with learners in what is clearly a very busy and highly competitive marketplace.

Thanks again for the review, it would be really interesting to see what your thoughts are on future iterations. Looking forward to chatting it over next time we meet.

Cheers,
Jo

FluentU, busuu, Bliu Bliu … what is it with all the ‘u’s? Hong-Kong based FluentU used to be called FluentFlix, but they changed their name a while back. The service for English learners is relatively new. Before that, they focused on Chinese, where the competition is much less fierce.

At the core of FluentU is a collection of short YouTube videos, which are sorted into 6 levels and grouped into 7 topic categories. The videos are accompanied by transcriptions. As learners watch a video, they can click on any word in the transcript. This will temporarily freeze the video and show a pop-up which offers a definition of the word, information about part of speech, a couple of examples of this word in other sentences, and more example sentences of the word from other videos that are linked on FluentU. These can, in turn, be clicked on to bring up a video collage of these sentences. Learners can click on an ‘Add to Vocab’ button, which will add the word to personalised vocabulary lists. These are later studied through spaced repetition.

FluentU describes its approach in the following terms: FluentU selects the best authentic video content from the web, and provides the scaffolding and support necessary to bring that authentic content within reach for your students. It seems appropriate, therefore, to look first at the nature of that content. At the moment, there appear to be just under 1,000 clips which are allocated to levels as follows:

Newbie 123 Intermediate 294 Advanced 111
Elementary 138 Upper Int 274 Native 40

It has to be assumed that the amount of content will continue to grow, but, for the time being, it’s not unreasonable to say that there isn’t a lot there. I looked at the Upper Intermediate level where the shortest was 32 seconds long, the longest 4 minutes 34 seconds, but most were between 1 and 2 minutes. That means that there is the equivalent of about 400 minutes (say, 7 hours) for this level.

The actual amount that anyone would want to watch / study can be seen to be significantly less when the topics are considered. These break down as follows:

Arts & entertainment 105 Everyday life 60 Science & tech 17
Business 34 Health & lifestyle 28
Culture 29 Politics & society 6

The screenshots below give an idea of the videos on offer:

menu1menu2

I may be a little difficult, but there wasn’t much here that appealed. Forget the movie trailers for crap movies, for a start. Forget the low level business stuff, too. ‘The History of New Year’s Resolutions’ looked promising, but turned out to be a Wikipedia style piece. FluentU certainly doesn’t have the eye for interesting, original video content of someone like Jamie Keddie or Kieran Donaghy.

But, perhaps, the underwhelming content is of less importance than what you do with it. After all, if you’re really interested in content, you can just go to YouTube and struggle through the transcriptions on your own. The transcripts can be downloaded as pdfs, which, strangely are marked with a FluentU copyright notice.copyright FluentU doesn’t need to own the copyright of the videos, because they just provide links, but claiming copyright for someone else’s script seemed questionable to me. Anyway, the only real reason to be on this site is to learn some vocabulary. How well does it perform?

fluentu1

Level is self-selected. It wasn’t entirely clear how videos had been allocated to level, but I didn’t find any major discrepancies between FluentU’s allocation and my own, intuitive grading of the content. Clicking on words in the transcript, the look-up / dictionary function wasn’t too bad, compared to some competing products I have looked at. The system could deal with some chunks and phrases (e.g. at your service, figure out) and the definitions were appropriate to the way these had been used in context. The accuracy was far from consistent, though. Some definitions were harder than the word they were explaining (e.g. telephone = an instrument used to call someone) and some were plain silly (e.g. the definition of I is me).

have_been_definitionSome chunks were not recognised, so definitions were amusingly wonky. Come out, get through and have been were all wrong. For the phrase talk her into it, the program didn’t recognise the phrasal verb, and offered me communicate using speech for talk, and to the condition, state or form of for into.

For many words, there are pictures to help you with the meaning, but you wonder about some of them, e.g. the picture of someone clutching a suitcase to illustrate the meaning of of, or a woman holding up a finger and thumb to illustrate the meaning of what (as a pronoun).what_definition

The example sentences don’t seem to be graded in any way and are not always useful. The example sentences for of, for example, are The pages of the book are ripped, the lemurs of Madagascar and what time of day are you free. Since the definition is given as belonging to, there seems to be a problem with, at least, the last of these examples!

With the example sentence that link you to other video examples of this word being used, I found that it took a long time to load … and it really wasn’t worth waiting for.

After a catalogue of problems like this, you might wonder how I can say that this function wasn’t too bad, but I’ve seen a lot worse. It was, at least, mostly accurate.

Moving away from the ‘Watch’ options, I explored the ‘Learn’ section. Bearing in mind that I had described myself as ‘Upper Intermediate’, I was surprised to be offered the following words for study: Good morning, may, help, think, so. This then took me to the following screen:great job

I was getting increasingly confused. After watching another video, I could practise some of the words I had highlighted, but, again, I wasn’t sure quite what was going on. There was a task that asked me to ‘pick the correct translation’, but this was, in fact a multiple choice dictation task.translation task

Next, I was asked to study the meaning of the word in, followed by an unhelpful gap-fill task:gap fill

Confused? I was. I decided to look for something a little more straightforward, and clicked on a menu of vocabulary flash cards that I could import. These included sets based on copyright material from both CUP and OUP, and I wondered what these publishers might think of their property being used in this way.flashcards

FluentU claims  that it is based on the following principles:

  1. Individualized scaffolding: FluentU makes language learning easy by teaching new words with vocabulary students already know.
  2. Mastery Learning: FluentU sets students up for success by making sure they master the basics before moving on to more advanced topics.
  3. Gamification: FluentU incorporates the latest game design mechanics to make learning fun and engaging.
  4. Personalization: Each student’s FluentU experience is unlike anyone else’s. Video clips, examples, and quizzes are picked to match their vocabulary and interests.

The ‘individualized scaffolding’ is no more than common sense, dressed up in sciency-sounding language. The reference to ‘Mastery Learning’ is opaque, to say the least, with some confusion between language features and topic. The gamification is rudimentary, and the personalization is pretty limited. It doesn’t come cheap, either.

price table

In the words of its founder and CEO, self-declared ‘visionary’ Claudio Santori, Bliu Bliu is ‘the only company in the world that teaches languages we don’t even know’. This claim, which was made during a pitch  for funding in October 2014, tells us a lot about the Bliu Bliu approach. It assumes that there exists a system by which all languages can be learnt / taught, and the particular features of any given language are not of any great importance. It’s questionable, to say the least, and Santori fails to inspire confidence when he says, in the same pitch, ‘you join Bliu Bliu, you use it, we make something magical, and after a few weeks you can understand the language’.

The basic idea behind Bliu Bliu is that a language is learnt by using it (e.g. by reading or listening to texts), but that the texts need to be selected so that you know the great majority of words within them. The technological challenge, therefore, is to find (online) texts that contain the vocabulary that is appropriate for you. After that, Santori explains , ‘you progress, you input more words and you will get more text that you can understand. Hours and hours of conversations you can fully understand and listen. Not just stupid exercise from stupid grammar book. Real conversation. And in all of them you know 100% of the words. […] So basically you will have the same opportunity that a kid has when learning his native language. Listen hours and hours of native language being naturally spoken at you…at a level he/she can understand plus some challenge, everyday some more challenge, until he can pick up words very very fast’ (sic).

test4

On entering the site, you are invited to take a test. In this, you are shown a series of words and asked to say if you find them ‘easy’ or ‘difficult’. There were 12 words in total, and each time I clicked ‘easy’. The system then tells you how many words it thinks you know, and offers you one or more words to click on. Here are the words I was presented with and, to the right, the number of words that Bliu Blu thinks I know, after clicking ‘easy’ on the preceding word.

hello 4145
teenager 5960
soap, grape 7863
receipt, washing, skateboard 9638
motorway, tram, luggage, footballer, weekday 11061

test7

Finally, I was asked about my knowledge of other languages. I said that my French was advanced and that my Spanish and German were intermediate. On the basis of this answer, I was now told that Bliu Bliu thinks that I know 11,073 words.

Eight of the words in the test are starred in the Macmillan dictionaries, meaning they are within the most frequent 7,500 words in English. Of the other four, skateboard, footballer and tram are very international words. The last, weekday, is a readily understandable compound made up of two extremely high frequency words. How could Bliu Bliu know, with such uncanny precision, that I know 11,073 words from a test like this? I decided to try the test for French. Again, I clicked ‘easy’ for each of the twelve words that was offered. This time, I was offered a very different set of words, with low frequency items like polynôme, toponymie, diaspora, vectoriel (all of which are cognate with English words), along with the rather surprising vichy (which should have had a capital letter, as it is a proper noun). Despite finding all these words easy, I was mortified to be told that I only knew 6546 words in French.

I needn’t have bothered with the test, anyway. Irrespective of level, you are offered vocabulary sets of high frequency words. Examples of sets I was offered included [the, be, of, and, to], [way, state, say, world, two], [may, man, hear, said, call] and [life, down, any, show, t]. Bliu Bliu then gives you a series of short texts that include the target words. You can click on any word you don’t know and you are given either a definition or a translation (I opted for French translations). There is no task beyond simply reading these texts. Putting aside for the moment the question of why I was being offered these particular words when my level is advanced, how does the software perform?

The vast majority of the texts are short quotes from brainyquote.com, and here is the first problem. Quotes tend to be pithy and often play with words: their comprehensibility is not always a function of the frequency of the words they contain. For the word ‘say’, for example, the texts included the Shakespearean quote It will have blood, they say; blood will have blood. For the word ‘world’, I was offered this line from Alexander Pope: The world forgetting, by the world forgot. Not, perhaps, the best way of learning a couple of very simple, high-frequency words. But this was the least of the problems.

The system operates on a word level. It doesn’t recognise phrases or chunks, or even phrasal verbs. So, a word like ‘down’ (in one of the lists above) is presented without consideration of its multiple senses. The first set of sentences I was asked to read for ‘down’ included: I never regretted what I turned down, You get old, you slow down, I’m Creole, and I’m down to earth, I never fall down. I always fight, I like seeing girls throw down and I don’t take criticism lying down. Not exactly the best way of getting to grips with the word ‘down’ if you don’t know it!

bliubliu2You may have noticed the inclusion of the word ‘t’ in one of the lists above. Here are the example sentences for practising this word: (1) Knock the ‘t’ off the ‘can’t’, (2) Sometimes reality T.V. can be stressful, (3) Argentina Debt Swap Won’t Avoid Default, (4) OK, I just don’t understand Nethanyahu, (5) Venezuela: Hell on Earth by Walter T Molano and (6) Work will win when wishy washy wishing won t. I paid €7.99 for one month of this!

The translation function is equally awful. With high frequency words with multiple meanings, you get a long list of possible translations, but no indication of which one is appropriate for the context you are looking at. With other words, it is sometimes, simply, wrong. For example, in the sentence, Heaven lent you a soul, Earth will lend a grave, the translation for ‘grave’ was only for the homonymous adjective. In the sentence There’s a bright spot in every dark cloud, the translation for ‘spot’ was only for verbs. And the translation for ‘but’ in We love but once, for once only are we perfectly equipped for loving was ‘mais’ (not at all what it means here!). The translation tool couldn’t handle the first ‘for’ in this sentence, either.

Bliu Bliu’s claim that Bliu Bliu knows you very well, every single word you know or don’t know is manifest nonsense and reveals a serious lack of understanding about what it means to know a word. However, as you spend more time on the system, a picture of your vocabulary knowledge is certainly built up. The texts that are offered begin to move away from the one-liners from brainyquote.com. As reading (or listening to recorded texts) is the only learning task that is offered, the intrinsic interest of the texts is crucial. Here, again, I was disappointed. Texts that I was offered were sourced from IEEE Spectrum (The World’s Largest Professional Association for the Advancement of Technology), infowars.com (the home of the #1 Internet News Show in the World), Latin America News and Analysis, the Google official blog (Meet 15 Finalists and Science in Action Winner for the 2013 GoogleScience Fair) MLB Trade Rumors (a clearinghouse for relevant, legitimate baseball rumors), and a long text entitled Robert Waldmann: Policy-Relevant Macro Is All in Samuelson and Solow (1960) from a blog called Brad DeLong’s Grasping Reality……with the Neural Network of a Moderately-Intelligent Cephalopod.

There is more curated content (selected from a menu which includes sections entitled ‘18+’ and ‘Controversial Jokes’). In these texts, words that the system thinks you won’t know (most of the proper nouns for example) are highlighted. And there is a small library of novels, again, where predicted unknown words are highlighted in pink. These include Dostoyevsky, Kafka, Oscar Wilde, Gogol, Conan Doyle, Joseph Conrad, Oblomov, H.P. Lovecraft, Joyce, and Poe. You can also upload your own texts if you wish.

But, by this stage, I’d had enough and I clicked on the button to cancel my subscription. I shouldn’t have been surprised when the system crashed and a message popped up saying the system had encountered an error.

Like so many ‘language learning’ start-ups, Bliu Bliu seems to know a little, but not a lot about language learning. The Bliu Bliu blog has a video of Stephen Krashen talking about comprehensible input (it is misleadingly captioned ‘Stephen Krashen on Bliu Bliu’) in which he says that we all learn languages the same way, and that is when we get comprehensible input in a low anxiety environment. Influential though it has been, Krashen’s hypothesis remains a hypothesis, and it is generally accepted now that comprehensible input may be necessary, but it is not sufficient for language learning to take place.

The hypothesis hinges, anyway, on a definition of what is meant by ‘comprehensible’ and no one has come close to defining what precisely this means. Bliu Bliu has falsely assumed that comprehensibility can be determined by self-reporting of word knowledge, and this assumption is made even more problematic by the confusion of words (as sequences of letters) with lexical items. Bliu Bliu takes no account of lexical grammar or collocation (fundamental to any real word knowledge).

The name ‘Bliu Bliu’ was inspired by an episode from ‘Friends’ where Joey tries and fails to speak French. In the episode, according to the ‘Friends’ wiki, ‘Phoebe helps Joey prepare for an audition by teaching him how to speak French. Joey does not progress well and just speaks gibberish, thinking he’s doing a great job. Phoebe explains to the director in French that Joey is her mentally disabled younger brother so he’ll take pity on Joey.’ Bliu Bliu was an unfortunately apt choice of name.

friends

Lingua.ly is an Israeli start-up which, in its own words, ‘is an innovative new learning solution that helps you learn a language from the open web’. Its platform ‘uses big-data paired with spaced repetition to help users bootstrap their way to fluency’. You can read more of this kind of adspeak at the Lingua.ly blog  or the Wikipedia entry  which seems to have been written by someone from the company.

How does it work? First of all, state the language you want to study (currently there are 10 available) and the language you already speak (currently there are 18 available). Then, there are three possible starting points: insert a word which you want to study, click on a word in any web text or click on a word in one of the suggested reading texts. This then brings up a bilingual dictionary entry which, depending on the word, will offer a number of parts of speech and a number of translated word senses. Click on the appropriate part of speech and the appropriate word sense, and the item will be added to your personal word list. Once you have a handful of words in your word list, you can begin practising these words. Here there are two options. The first is a spaced repetition flashcard system. It presents the target word and 8 different translations in your own language, and you have to click on the correct option. Like most flashcard apps, spaced repetition software determines when and how often you will be re-presented with the item.

The second option is to read an authentic web text which contains one or more of your target items. The company calls this ‘digital language immersion, a method of employing a virtual learning environment to simulate the language learning environment’. The app ‘relies on a number of applied linguistics principles, including the Natural Approach and Krashen’s Input Hypothesis’, according to the Wikipedia entry. Apparently, the more you use the app, the more it knows about you as a learner, and the better able it is to select texts that are appropriate for you. As you read these texts, of course, you can click on more words and add them to your word list.

I tried out Lingua.ly, logging on as a French speaker wanting to learn English, and clicking on words as the fancy took me. I soon had a selection of texts to read. Users are offered a topic menu which consisted of the following: arts, business, education, entertainment, food, weird, beginners, green, health, living, news, politics, psychology, religion, science, sports, style. The sources are varied and not at all bad – Christian Science Monitor, The Grauniad, Huffington Post, Time, for example –and there are many very recent articles. Some texts were interesting; others seemed very niche. I began clicking on more words that I thought would be interesting to explore and here my problems began.

I quickly discovered that the system could only deal with single words, so phrasal verbs were off limits. One text I looked at had the phrasal verb ‘ripping off’, and although I could get translations for ‘ripping’ and ‘off’, this was obviously not terribly helpful. Learners who don’t know the phrasal verb ‘ripped off’ do not necessarily know that it is a phrasal verb, so the translations offered for the two parts of the verb are worse than unhelpful; they are actually misleading. Proper nouns were also a problem, although some of the more common ones were recognised. But the system failed to recognise many proper nouns for what they were, and offered me translations of homonymous nouns. new_word_added_'ripping_off' With some words (e.g. ‘stablemate’), the dictionary offered only one translation (in this case, the literal translation), but not the translation (the much more common idiomatic one) that was needed in the context in which I came across the word. With others (e.g. ‘pertain’), I was offered a list of translations which included the one that was appropriate in the context, but, unfortunately, this is the French word ‘porter’, which has so many possible meanings that, if you genuinely didn’t know the word, you would be none the wiser.

Once you’ve clicked on an appropriate part of speech and translation (if you can find one), the dictionary look-up function offers both photos and example sentences. Here again there were problems. I’d clicked on the verb ‘pan’ which I’d encountered in the context of a critic panning a book they’d read. I was able to select an appropriate translation, but when I got to the photos, I was offered only multiple pictures of frying pans. There were no example sentences for my meaning of ‘pan’: instead, I was offered multiple sentences about cooking pans, and one about Peter Pan. In other cases, the example sentences were either unhelpful (e.g. the example for ‘deal’ was ‘I deal with that’) or bizarre (e.g. the example sentence for ‘deemed’ was ‘The boy deemed that he cheated in the examination’). For some words, there were no example sentences at all.

Primed in this way, I was intrigued to see how the system would deal with the phrase ‘heaving bosoms’ which came up in one text. ‘Heaving bosoms’ is an interesting case. It’s a strong collocation, and, statistically, ‘heaving bosoms’ plural are much more frequent than ‘a heaving bosom’ singular. ‘Heaving’, as an adjective, only really collocates with ‘bosoms’. You don’t find ‘heaving’ collocating with any of the synonyms for ‘bosoms’. The phrase is also heavily connoted, strongly associated with romance novels, and often used with humorous intent. Finally, there is also a problem of usage with ‘bosom’ / ‘bosoms’: men or women, one or two – all in all, it’s a tricky word.

Lingua.ly was no help at all. There was no dictionary entry for an adjectival ‘heaving’, and the translations for the verb ‘heave’ were amusing, but less than appropriate. As for ‘bosom’, there were appropriate translations (‘sein’ and ‘poitrine’), but absolutely no help with how the word is actually used. Example sentences, which are clearly not tagged to the translation which has been chosen, included ‘Or whether he shall die in the bosom of his family or neglected and despised in a foreign land’ and ‘Can a man take fire in his bosom, and his clothes not be burned?’

Lingua.ly has a number of problems. First off, its software hinges on a dictionary (it’s a Babylon dictionary) which can only deal with single words, is incomplete, and does not deal with collocation, connotation, style or register. As such, it can only be of limited value for receptive use, and of no value whatsoever for productive use. Secondly, the web corpus that it is using simply isn’t big enough. Thirdly, it doesn’t seem to have any Natural Language Processing tool which could enable it to deal with meanings in context. It can’t disambiguate words automatically. Such software does now exist, and Lingua.ly desperately needs it.

Unfortunately, there are other problems, too. The flashcard practice is very repetitive and soon becomes boring. With eight translations to choose from, you have to scroll down the page to see them all. But there’s a timer mechanism, and I frequently timed out before being able to select the correct translation (partly because words are presented with no context, so you have to remember the meaning which you clicked in an earlier study session). The texts do not seem to be graded for level. There is no indication of word frequency or word sense frequency. There is just one gamification element (a score card), but there is no indication of how scores are achieved. Last, but certainly not least, the system is buggy. My word list disappeared into the cloud earlier today, and has not been seen since.

I think it’s a pity that Lingua.ly is not better. The idea behind it is good – even if the references to Krashen are a little unfortunate. The company says that they have raised $800,000 in funding, but with their freemium model they’ll be desperately needing more, and they’ve gone to market too soon. One reviewer, Language Surfer,  wrote a withering review of Lingua.ly’s Arabic program (‘it will do more harm than good to the Arabic student’), and Brendan Wightman, commenting at eltjam,  called it ‘dull as dish water, […] still very crude, limited and replete with multiple flaws’. But, at least, it’s free.