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Many pupils struggle with the acquisition of the German orthography. In order to meet this struggle a web based platform for German speaking countries is currently developed. This platform aims to motivate pupils aged 8 to 12 to improve their writing and spelling competences. In this platform pupils can write texts in the form of blog entries concerning everyday events or special topics. Since the core of this platform consists of an intelligent dictionary focussing on different categories of misspellings, students can improve their own spelling skills by trying to correct their mistakes according to the feedback of the system. Teachers are informed about specific orthographic problems of a particular student by getting a qualitative analysis of the misspellings from this intelligent dictionary. The article focuses on the development of the intelligent dictionary, details concerning the requirements, the categorization and the used wordlist. Further, necessary information on German orthography, spelling competence in general and the platform itself is given. By implementing methods of learning analytics it is expected to gain deeper insight into the process of spelling acquisition and thus serves as a basis to develop better materials on the long run.
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eLearning
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45
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eLearning Papers ISSN: 1887-1542 www.openeducationeuropa.eu/en/elearning_papers
n.º 45 November 2015
Authors
Konstanze, Edtstadler
konstanze.edtstadler@kphvie.
ac.at
University College of Teacher
Education Vienna/Krems,
Researcher
Vienna / Krems, Austria
Markus, Ebner
markus.ebner@tugraz.at
Institute of Information
Systems and Computer
Media, Graz University of
Technology, Researcher
Graz, Austria
Martin, Ebner
martin.ebner@tugraz.at
Department Educational
Technology, Graz University
of Technology, Head of
Department
Graz, Austria
Improved German Spelling Acquisition through
Learning Analytics
Many pupils struggle with the acquision of the German orthography. In order to
meet this struggle a web based plaorm for German speaking countries is currently
developed. This plaorm aims to movate pupils aged 8 to 12 to improve their wring
and spelling competences. In this plaorm pupils can write texts in the form of blog
entries concerning everyday events or special topics. Since the core of this plaorm
consists of an intelligent diconary focussing on dierent categories of misspellings,
students can improve their own spelling skills by trying to correct their mistakes
according to the feedback of the system. Teachers are informed about specic
orthographic problems of a parcular student by geng a qualitave analysis of the
misspellings from this intelligent diconary. The arcle focuses on the development
of the intelligent diconary, details concerning the requirements, the categorizaon
and the used wordlist. Further, necessary informaon on German orthography, spelling
competence in general and the plaorm itself is given. By implemenng methods
of learning analycs it is expected to gain deeper insight into the process of spelling
acquision and thus serves as a basis to develop beer materials in the long run.
1. Introduction
This arcle is concerned with a learning analycs approach in the eld of German orthography.
Due to the increasing internet usage in the eld of educaon, the amount of data that is
produced is rising daily. This data is shared between various kinds of instuons around
the globe (Piety, 2013). Furthermore, the heavy use of the Internet generates enormous
data about learners’ behavior and leaves traces of every interacon (Duval, 2010). Thus,
interacon between students and a learning plaorm can be captured and used for later
analysis in order to gain an insight into a learners’ learning process (Khalil & Ebner, 2015).
This can then be used for early detecon of learning issues and enables teachers to acvely
intervene accordingly in order to solve such issues eecvely (Siemens et al., 2011; Greller
& Drachsler, 2012).
German orthography is known to be quite dicult to master. People from dierent social
classes, of dierent ages and with varying degrees of educaon, struggle with spelling words
correctly. However, the importance of correct spelling for social acceptance is quite high. It
aects primary-school pupils’ as well as a university students’ everyday life inside and outside
German orthography,
learning analytics, qualitative
analysis of misspellings,
categorization, Technology
Enhanced Learning
Tags
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schooling. Sll, instrucons in German orthography are oen
unsystemac and not parcularly aracve for children.
The development of the IDERBLOG-Plaorm1 aims to solve
such problems by combining technology enhanced learning
and learning analycs with the acquision of German
orthography (Ebner et al., 2015a). The plaorm should serve
as an aracve and movang innovaon for children to
acquire German orthography appropriately and more easily.
It has also advantages for teachers and researchers, as the
applicaon of learning analycs supports them in their decision
making process by providing them with an overview of possible
educaonal intervenons (Ebner et al., 2015b).
Outline
The next secon gives a short overview of the German
orthography as well as orthographic competence and
learning analycs. The following secon is concerned with the
development of the informaon system of the plaorm, its
interface design process and the planned workow. The two
succeeding secons focus on to the intelligent diconary and
the feedback system. The arcle aims to give an overview of the
categories, the requirements and the process of categorizaon
of the intelligent diconary.
2. Related work
German Orthography
German orthography uses an alphabec wring system.
Alphabec wring systems are characterised by mirroring the
phonemic structure of the spoken language to the wrien
language, which leads to the assumpon that words are spelled
as they sound (cf. Katz & Frost, 1992, p. 149).
This phonological principle is applied to a varying degree of
consistency in dierent languages. It leads to a connuum
of orthographies ranging from transparent to opaque ones
with a huge impact on spelling instrucon and acquision. In
transparent orthographies like Serbian, Turkish or Italian each
phoneme (notated consecuvely with / /) is represented by one
leer or more precisely – grapheme (notated consecuvely
with < >). Therefore, the assumpon to spell a word as it is heard
is quite true in these orthographies. In opaque orthographies
like English or French “there is a pronounced discrepancy
1 IDERBLOG-Plaorm, available online: hp://iderblog.eu/ (German language
only, last visited October 9, 2015)
between pronunciaon and orthography” (Klees, 1989, p.
137). Consequently, learners are confronted with unreliable
correspondences since in the case of English for example
“the alphabet contains just 26 leers yet these correspond to
44 phonemes associated with 102 funconal spelling units.
(Snowling, 1989, p. 1). The German orthography can be found
in the middle between transparent and opaque orthographies.
Following Nerius (2007) it consists of two basic principles, the
phonological and the semanc principle. Part of the phonological
principle are the phoneme-grapheme-correspondences (PGC),
which are mostly not in a 1:1 relaonship, e.g. /a:/ can be <a>
in <Wal> whale, <aa> in <Saal> hall or <ah> in <kahl> bald (cf.
Meinhold & Stock, 2007, p. 122). Part of the semanc principle is,
according to Nerius (2007, p. 89 ), the morphological principle
- among the lexical, the syntacc and the textual one. This
principle is responsible for spelling one morpheme in the same
way in all words in which it occurs. This oen leads to a conict
with the phoneme-grapheme-correspondences: e.g. spelling the
word dog, in German pronounced as /hunt/, following the PGC
would lead to the misspelling (usually indicated with an asterisk)
<*Hunt>. It has to be spelled <Hund> because of the plural form
/hundə/ dogs. The spelling <Hund> with a <d> is kept the same
in all words, like <Hündin> female dog or <Hundeschlien> dog
sled. The spelling of the orthographically challenging ‘Umlaut
(= vowel mutaon spelled as ä/äu) in morphologically complex
words is also due to the morphological principle (e.g. <Hände>
hands, not <*Hende>).
These principles and their value for German orthography
highly aect the didacc approach of teaching – especially in
higher classes and addional trainings. In general, the spelling
instrucon at the beginning of literacy acquision is clearly
phoneme based (cf. Landerl & Thaler, 2006). This is the reason
why children are able to write (new) words relying on their
knowledge of pronunciaon soon aer geng to know the
PGC. Words wrien in this way can also be read, but they are
oen not orthographically correct (e.g. <*falipt> for <verliebt>
in love). Especially for children who are not speaking the
standard German variety, the inuence of the spoken language
is evident in their spelling. Due to other sub-principles of the
semanc basic principle further orthographic challenges are
for example:
Nouns must be spelled with capital leers – a feature that
can only be found in the German orthography (cf. Valn,
1989, p. 119). It leads to many mistakes – even in texts of
well-educated adults.
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Homophone words are somemes, but not always, spelled
dierently (e.g. /li:t/ as <Lied> song or <Lid> eyelid, but /
notə/ as <Note> for mark and note) (cf. Nerius, 2007, 167).
Compounds are usually spelled compound (e.g. <Teetasse>
tea cup). Depending on the meaning of a combinaon of
words, it must be spelled separately or compound (e.g.
<Schweinebraten> roast pork or <Schweine braten> – to
fry pork) (cf. Fuhrhop, 2011, p. 107).
Spelling Competence
Especially in the German speaking world correct spelling is
considered very presgious, but students consider spelling
instrucons oen as boring and formal (cf. Küel, 2007, p.
418f). Addionally, teachers oen do not pay aenon to the
systemac principles that stand behind the spelling of certain
words. This oen leads to the assumpon, that it is not possible
to teach German orthography systemacally (cf. Fröhler, 2002).
In contrast to other areas of language learning, there is hardly
space to argue about the correct or incorrect spelling of a
word. This orthographical sness can probably serve as an
explanaon for its importance.
It is important to understand that the spelling competence of
a person does not only include the knowledge of the correct
spelling of a given word and knowing the rules of orthography.
It also includes being sensive to misspelled words, knowing
how to correct them, using spelling aids and applying strategies
(cf. Sommer Stumpenhorst, 2012; Naumann, 2008). Concerning
instrucon, it is not enough to simply oer dierent online or
oine exercises. “Children or student’s need purposeful reading
and wring in a broad range of situaons, in an environment
that values risk-taking. They will develop spelling competence
as they implement their knowledge of the spelling system,
receive feedback and rene their hypotheses.” (Government
of South Australia, 2011, p. 6). Furthermore, children should
be encouraged to think about and reect language in order
to become aware of the structure of words (cf. e.g. Tsesmeli
& Seymour, 2006). Due to the dierent principles of German
Orthography, metalinguisc awareness must be established
beyond phonological awareness (cf. e.g. Naumann, 2008). For
example, children must be encouraged to see the morphological
link between singular and plural form (e.g. <Hälse> because of
<Hals> necks, <Rind> because of <Rinder> cows).
Learning Analytics
The eld of Learning Analycs tries to consider the learning
process as a whole in its full complexity. According to Baker et al.
(2012) and Neuhold (2013) it is important to keep feedback and
its visual representaon as simple as possible to avoid confusion
and unreasonable interpretaon on the side of the stakeholders.
Campbell et al. (2007) provide a model for the analysis process
in ve steps: capture, report, predict, act and rene. Clow
(2012) used these ve steps as a basis for his learning analycs
cycle. This iterave process consists of four main components:
learners, data, metrics/analycs and intervenon (Clow, 2012).
To get an overview about the whole process Khalil & Ebner
(2015) added stakeholders to the cycle. Nevertheless, the main
idea of Learning Analycs is to provide and process a learners’
data in an appropriate way in order to facilitate teachers to
react and (if necessary) to intervene. For instance, Taraghi et al.
(2015a) introduced an analycal approach to model a learner’s
prole according to their answering behavior. Moreover, the
analysis of dierent error types can lead to ndings that help to
enhance the learning process as a whole (Taraghi et al., 2015b).
3. Information system
The plaorm (informaon system) for the project is
currently under development and yet not available for public
presentaon. Nevertheless, this secon will provide basic
design ideas to ensure good age-appropriate interface design
and usability (Ebner et al., 2015a). In the second secon the
planned workow of the analysis will be outlined.
Writing by using the Computer
Since developing wring skills and acquiring orthographic
competence is important and wring with computers is
aracve for children, the IDERBLOG-Plaorm combines these
components. The aim is not to replace handwring by typing on
keyboards, but to take advantage of the digital age. “For some
people with major handwring problems, personal computers
are a boon.” (Høien & Lundberg, 2000, p. 68)
A further advantage of wring on a computer is, to train the
ability to correct texts. Since correcons are made within a digital
text, correcons do not leave traces in contrast to a handwrien
text. Consequently, a text can be edited several mes unl it
becomes publishable. Furthermore, the IDERBLOG-Plaorm
is “providing relevant reasons and audiences for wring”
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(Government of South Australia, 2011, p. 8) as children can
publish their texts. Therefore, it is expected that the movaon
to formulate a text and to revise it several mes is possibly
higher in contrast to typical essay wring in a classroom where
the addressee is almost only the teacher.
Concerning the training of orthographic skills, the IDERBLOG-
Plaorm oers an intelligent diconary, which does not only
count the number of mistakes in a text, but also categorizes
the mistakes in dierent orthographic areas. In contrast to the
work of Thelen (2010), that analyses misspellings in German
orthography, we do not only focus on beginning spellers but
also on more advanced learners. One of the most important
features of the intelligent diconary is that it oers feedback
and hints for the correcon of a mistake. Addionally, the
plaorm oers a number of exercises that are connected and
categorised according to spelling mistakes and therefore meet
the need of pracce in a specic area of spelling.
Interface Design
The plaorm is generally designed for children the primary
school (age 8 to 12) with the focus on a graphically appealing
and age-appropriate web interface (Liebal et al., 2011). For
this purpose, a graphic designer created dras that have been
examined and rated by students from dierent schools. The
designs that were favoured by the majority were then, in a
second step, developed further and aerwards integrated into
the plaorm.
Another important part of the plaorm is usability. We had to
ensure that the students can reach the most important parts of
the plaorm in less than ve clicks. This convenient accessibility
in combinaon with aracve gures should ensure high
movaon in fullling the task of wring texts. In ongoing
usability tests (Holzinger et al., 2005) we connue to improve
the concept step by step.
Workow of the Platform
The students, as shown in Figure 1, can write their texts on the
provided plaorm. First the text will be analysed orthographically
by the intelligent diconary (which will be described in the
next secon). Proper feedback will be provided to the student,
based on error type and category. The student has the choice
to either try to correct the wrong words or to hand-in the text
directly to the teacher. This intermediate step encourages the
experse of independent correcon (Bartnitzky et al., 2010).
Aer the submission, the teacher should inspect the text for
further correcons and/or improvements. Notes can be made
and delivered with the nal correcon to the student. Aer this
step the text can be published in the class blog of the school (if
appropriate).
Figure 1: Workow of the plaorm
The methods of learning analycs will be used for further
analysis of the texts (Siemens, 2012). The results will be
provided to students, teachers and parents in an appropriate
way. Further, an overview of the frequency of mistakes and
possible systemacally made errors is oered. In the long run
changes in a students’ performance will be measured (Schön et
al., 2012).
Training database
The plaorm will include an addional training database, as
shown in Figure 1, with selected online exercises and oine
work sheets. This database will aid teachers and students
to nd appropriate exercises to improve the performance in
problemac areas (as a consequence of the learning analycs
analyses). The exercises and work sheets are congruently
ordered in categories and sub-categories for easier selecon.
4. The intelligent dictionary
Categorization of mistakes
A word can be either orthographically right – in case the spelling
of a given word exists in a list of correctly spelled word, called
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diconary, or wrong – in case it does not exist. In science,
mistakes are analyzed in dierent categories depending on the
purpose of the study: e.g. for the English language Broc et al.
(2013) categorise spelling errors of people with specic language
impairments in phonologically acceptable vs. unacceptable. Flor
& Futagi (2012) focus on non-word misspellings in the context of
spell checker. In school oen a quantave approach is applied,
which means counng the number of misspelled words. In
addion to the correct-wrong dichotomy there are some other
ways in the categorisaon of incorrectly spelled words that lead
to a greater insight into the orthographic competence.
One way is to count the number of correctly wrien graphemes
of a given word: This helps to analyse the progress of extremely
weak or very young spellers (cf. May, 2010). For example, the
spelling for /V/e/r/k/äu/f/e/r seller in *F/e/r/k/eu/f/a contains
only 4 out of 8 correct graphemes in contrast to */V/e/r/k/
eu/f/e/r with 7 out of 8 correct graphemes. Although both
wring aempts are wrong, the second one is much beer.
This grapheme-based approach is a rather detailed and me
consuming way of correcng. Therefore, it is generally only
applied in a standardized spelling test called “Hamburger
Schreibprobe” (May, 2010) which provides pre-dened
templates for the quite small amount of words used in the test.
Another way of categorizing incorrectly spelled words is to dene
the type of mistake(s) and to collect the various frequencies
for the given categories in order to idenfy the orthographic
areas that need to be worked on (cf. e.g. Naumann, 2008, p.
139; Thomé & Thomé, 2014). The determinaon and the
assessment of these categories vary and are highly depending
on the purpose. The applied systems range from unpublished
templates developed by teachers to published and buyable
ones. For example, sciencally based and evaluated templates
for texts can be found in the “Oldenburger Fehleranalyse”
(OLFA) (Thomé & Thomé, 2014) and those specically meant
for the qualitave analysis of standardized tests can be found in
the “Aachener Förderdiagnossche Rechtschreibfehleranalyse”
(AFRA) (Herné & Naumann, 2002). When using the OLFA (Thomé
& Thomé 2014) the teacher has to collect texts containing
a certain amount of mistakes. Each mistake of a word has to
be analysed and categorized in one of the 35 categories (e.g.
lower case leer instead of upper case leer, upper case leer
instead of lower case leer, omission of a vowel, addion of
a vowel, etc.) that are described in detail in an accompanying
manual. Since the dierent categories are related to the stages
of spelling development the teacher gets to know the level of
spelling competence of a student.
In all described cases above, the me consuming analysis of
misspellings must be done by the teacher personally. This
requires eort to get familiar with the theory of German
orthography and the (applied) way of analysing the mistakes.
From our experiences, a detailed analysis is made only by highly
specialised people in rare cases. Since a clear qualitave analysis
of misspellings is the basis for a good and target oriented
intervenon, the IDERBLOG-Project aims to conduct the
analysis in large part automacally in order to support teachers
and consequently foster the spelling acquision process for
children.
Requirements for analysis
The categories of the qualitave analysis for the intelligent
diconary need to full some requirements on scienc,
technical and praccal basis. In order to full all these
requirements, the system of categories is established on
dierent hierarchical levels from ne to coarse grained. This
has the advantage, that the system stays exible as each level
is mainly dedicated to a specic purpose. We had to take into
account that many dierent words belong to one category
of mistakes. In order to provide a detailed analysis, we split
a category into specic phenomena (see table 1). Based on
those we have a proper ne-grained level for the applicaon
of learning analycs. However, those phenomena on such a
detailed level are not suitable for a general feedback. Therefore,
the phenomena of this specic level are merged in order to
retrieve a qualitave analysis for the teacher with a manageable
amount of categories and in order to be linked to the database
containing appropriate orthographic exercises. It also needs to
be taken into account that the naming of the categories that
are visible for the teachers and/or children, are sciencally
correct but sll easy to understand and consistent with the
established terms used in school environment, which are not
always consistent with the scienc terminology.
Method
In order to establish the dierent categories, a literature survey
was conducted and well-known approaches for qualitave
analysis for misspellings within the German orthography
were evaluated (cf. Edtstadler, in press). At the same me, 55
short texts of 3rd grade students from Germany and a limited
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number of longer texts of 5th and 7th graders from Austria were
collected. In a next step a dra of categories was developed
based on the ndings of our research of relevant literature as
well as by using, as a starng point, established categories of
exisng analysis methods such as OLFA and AFRA. This dra
was rearranged, modied and extended in order to meet the
requirements of the intelligent diconary. It was especially
challenging to construct the categories in a way that the
descripon of the phenomena ts in with the possibilies of
programming misspellings as well as with the categories for
the teachers and the database with the exercises. Addionally,
specic misspellings due to the existence of dierent German
variees are considered.
The usability and suitability of the dra’s categories were further
checked by assigning one mistake encountered in the above
menoned texts from dierent regions of the German speaking
area to a phenomenon, for which a feedback can be given.
Also, phenomena of mistakes that were not found in the quite
small amount of texts’ (menoned above), but are theorecally
possible and/or by experience encountered in students’ texts
were added: For example, in the texts an inected form shows
that the ‘Umlaut’ is substuted by <e> (<*fengt> he/she/it
catches instead of <fängt> because of <fangen> to catch),
therefore, the substuon in plural forms (<Apfel - Äpfel>
apple - apples), derivaons (<Glanz – glänzend> shine - shiny),
and comparisons (<warm - wärmer> warm -warmer) were also
added.
General Description of the Categories
The categories are established on a linguisc and orthographic
basis, also by regarding previous ndings of the theory of German
Orthography (e.g. Nerius, 2007). Consequently, the system (see
table 1) is divided in two parts: On the one hand, the system
contains the parts that are invisible for the user where the
scienc and theorecal basis can be found. This is necessary
for the descripon of the phenomena and consequently for
programming the possibly misspelled words. The visible parts,
on the other hand, appear in the qualitave analysis for the
teacher, serve for the selecon of exercises from the training
database and appear in the feedback the writer gets in case a
word is not spelled correctly.
Since this system is quite complex, the described system is
shown in table 1. The orthographic area of ‘Umlaut’ serves as
an example.
Linguistic level
(not visible)
Ortho-graphic
area
(not visible)
description/
rule based
phenomenon
(not visible)
Category for
the teacher
(visible)
Category of
spelling
exercise
(visible)
Sub-category of
spelling
exercise
(visible)
Example of a
misspelled word
Feedback for
the writer
Morpho-logical
level
Um-laut Inflection of
nouns: e/eu for
ä/äu
Umlaut
derivable
Morpho-logical
hints
Derivation apples: not
<*Epfel> but
<Äpfel> because
of <Apfel> apple
Think, if there
exists a base
form with a.
Morpho-logical
level
Um-laut Inflection of
verbs: e/eu for
ä/äu
Umlaut
derivable
Morpho-logical
hints
Derivation he/she/it catches
er/sie/es not
<*fengt> but
<fängt> because
of <fang-en> to
catch
Think, if there
exists a base
form with a.
Morpho-logical
level
Um-laut Comparison of
adjectives: e/eu
for ä/äu
Umlaut
derivable
Morpho-logical
hints
Derivation warmer: not
<*wermer>
but <wärmer>
because of
<warm> warm
Think, if there
exists a base
form with a.
Morpho-logical
level
Um-laut Word formation
/ derivation: e/
eu for ä/äu
Umlaut
derivable
Morpho-logical
hints
Derivation shiny: not
<*glenzend>
but <glänzend>
because of
<Glanz> shine
Think, if there
exists a base
form with a.
Table 1: Example of the system of the intelligent diconary in the orthographic area of ‘Umlaut’
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Starng from four linguisc levels phonological,
morphological, lexical and syntacc – the categories are further
divided into orthographic areas. The phonological, the lexical
and the syntacc level consist of three orthographic areas.
The morphological level that is used for giving insight to the
complex system (cf. partly Nerius, 2007, p. 158) contains ve
orthographic areas, including ‘Umlaut’ (see table 1), which are
essenal for spelling words correctly:
1. Morpheme constancy: lexical and grammacal morphemes
are spelled the same way in compounding, derivaon and
inecon, even when the sound cannot be heard (e.g.,
<Ohrring> earring, <Weihnachten> Christmas because of
<weihen> hallow, <stehen> not <*stehn> because of the
sux –en, <Verkäufer> seller because of the prex ver-).
2. Morphological hints for using capital leers: the use of
capital leers for nouns is quite dicult and depending
on the syntax, but because of certain suxes, derivaons
can easily be idened as nouns that must be wrien with
capital leers, e.g. <*belohnung> gracaon because of
the sux –ung.
3. Morphological hints for not using capital leers: there
are also some suxes that indicate that a given word is
not wrien with a capital leer, although morpho-syntax
can change the word class, e.g. <*Furchtbar> horrible is
correctly spelled <furchtbar> because of the sux –bar,
but it is spelled with capital leers in the phrase <etwas
Furchtbares> something horrible whereas the use of
the same word form as an adjecve requires the use of
lower case, e.g. <ein furchtbares Gewier> a horrible
thunderstorm.
4. ‘Umlaut’: Because of phoneme-grapheme correspondences,
especially in the area of Austria, the ‘Umlaut’ is oen
incorrectly wrien as <e>, e.g. <*glenzend> instead of
<glänzend> shiny, since the ‘Umlaut’ needs to be applied
because of the base morpheme <Glanz> shine (for details,
see table 1).
5. Terminal devoicing: In German a word is pronounced
with a devoiced obstruent at the end of the word, but
spelled with the voiced variant of the phoneme-grapheme
correspondences (e.g. /hunt/, but spelled as <Hund> dog
because of the wordform /hunde/ whereas <Brot> bread is
spelled as <Brot> because of /bro:t – bro:tə/).
Each orthographic area is associated with a wide range of
phenomena. These phenomena are formed in a way that they
can funcon as a rule for programming the possible mistakes
(see table 1). The number of phenomena is depending on the
given orthographic area and can be expanded and reduced,
based on evidence. The following example will help to show the
variety in the number and the characteriscs of phenomena:
In the orthographic area of morpheme constancy the
category derivaonal suxes (for the analysis for the teacher)
summarises the phenomenon of misspelling suxes such as –ig
(e.g. <lusg> funny) (wrien in dierent ways depending on the
spoken German variety as –ich <*lusch>, -isch <*lussch>, -ik
<*lusk>), and the phenomenon of spelling the sux –lich as
<*-lig> as well as further phenomena describing the misspelling
of other derivaonal suxes.
As menoned above, it is important to work with a manageable
amount of categories when oering the qualitave analysis for
the teacher. Therefore, the currently 110 phenomena are linked
with 34 categories of the qualitave analysis for the teacher.
In the example in table 1, the four dened phenomena for
misspelling the ‘Umlaut’ are summed up in one category that
tells the teacher that within a certain amount of mistakes the
‘Umlaut’ was derivable, but incorrectly spelled with the wrong
grapheme.
The categories of the qualitave analysis are then connected
with and/or mirrored in the labels of the orthographic exercises
available on the plaorm. For an easier orientaon they are
divided in categories and sub-categories of exercises. However,
the labelling of the exercises is in some cases more coarsely
grained than the category of the qualitave analysis itself (e.g.
the category upper case instead of lower case and the category
lower case instead of upper case are labelled as upper and
lower case exercises, since a lot of exercises pracce both at
the same me). This is due to the fact, that in the rst step only
already exisng exercises are available on the plaorm, but in
the progress of the project specic exercises will be developed.
The phenomena also funcon as the starng point for the
feedback of the intelligent diconary, which will be described
more in detail below.
5. Feedback from the Intelligent Dictionary
All of the categories and phenomena form the basis for the
analysis and applicaon of the intelligent diconary, which is
the core of the plaorm. The idea is that a child, who misspells
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a word, does not only get the feedback that the word is spelled
incorrectly, but also gets a hint for correcng it. The given
feedback is connected with the phenomenon. In order to keep
a straighorward number of feedbacks the same feedback will
be given – whenever possible - for more than one phenomenon
within an orthographic area. It is formulated in a way that forces
the child to think about the spelling and further encourages
the development and applicaon of spelling strategies.
Therefore, no direct commands (e.g. “use <ä> instead of <e>”)
for correcng the word are included in the feedbacks. The
correcon will only be successful if the child reects on the hint
in combinaon with the misspelled word. This approach stands
in contrast to the usual word-correcon process where either
the misspelled word is marked or the correct word needs to
be selected from a variety of oered words. In both cases the
correcon will probably not lead to a deeper understanding of
correct orthography.
Klicpera et al. (2003, p. 255) menon that in order to acquire
correct spelling, it is important to oer exercises that allow the
autonomous correcon in a movang context. Experienced
teachers and trainers for dyslexic children know that poor
spellers have problems in idenfying their mistakes in a text.
But as soon as a hint for correcng the word is given, they oen
know how to spell it correctly. This is a successful, but a me and
energy consuming way of improving orthographic competence.
In order to avoid exhauson, the intelligent diconary gives this
feedback instead of a teacher, which also has the advantage
that the intelligent diconary can and will repeat the feedback
several mes. In case a child spells <*Epfel> instead of <*Äpfel>
apples the intelligent diconary provides the feedback “Think
if there exists a base form with “a”?”, the same feedback will
be given in case the child writes <*fengt> instead of <fängt> to
catch or <*glenzend> instead of <glänzend> shiny. There is no
strict applicaon of a syntacc paern for the feedback since
the wording of the feedback is chosen rather on a didacc than
on a formal basis.
Wordlist of the intelligent dictionary
Since this intelligent diconary so far, is designated to funcon
as a rst prototype, only a selecon of words funcons as the
basis for programming the diconary. For the rst prototype
we had to choose around 1000 words. Generally such a
selecon of words would be based on the frequency of the
CELEX (1995) database – although this would propose some
problems (cf. Brysbaert et al., 2011). Selecng words only based
on frequency in general without considering the frequency of
words in children´s language is especially problemac for the
development of an applicaon aimed at children. Also the fact
that the selected words should be prone to be misspelled had to
be considered (for a discussion see Risel, 2008).
In order to meet these requirements, the word list for the
prototype of the intelligent diconary is based on the basic
vocabulary of three German Federal States (Bavaria, Hamburg,
Berlin-Brandenburg). In the next step it was checked, whether
in these basic vocabularies the 100 most frequently misspelled
words of 4th graders (compiled and made available by Tacke,
2008) are included. Words that do not appear in any form in one
of these three basic vocabularies were included (e.g. <kommt>
comes was not included since <kommen> to come is a word of
the basic vocabulary, but <ziemlich> quite was included since
it does not appear in one of the basic vocabularies). At the
end, the word list for the prototype of the intelligent diconary
ended up containing around 1100 words.
Since German has a rich morphology and texts are not merely
made of words that are listed in a diconary, it is necessary
to list all the possible word forms of a given word in order to
construct all possible misspellings for the intelligent diconary
in a next step. The collecon of all possible word forms of a
given word (or to be precise of a lemma) is based on the CELEX
(1995) database. This incorporaon of all word forms enlarged
the wordlist to over 7500 orthographically correct words. In
German the variaon in the number of word forms for a given
lemma is quite high as is proven by the following examples:
For the adjecve <ähnlich> similar the CELEX (1995)
database has 17 word forms (<ähnlich, ähnliche, ähnlichen,
ähnlicher, ähnlichem, ähnliches, ähnlichst, ähnlichste,
ähnlichsten, ähnlichster, ähnlichstem, ähnlichstes,
ähnlichere, ähnlicheren, ähnlicherer, ähnlicherem,
ähnlicheres>) including inecon for singular, plural, the
dierent cases and comparison.
For the regular verb <arbeiten> to work 10 word forms
can be found in the CELEX (1995) database in summary,
whereas for the irregular verb <beginnen> to begin exactly
24.
For the noun <Beispiel> example exist only four word forms.
For preposions no other word form can be found since
they cannot be modied.
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For these 7500 word forms of this wordlist all possible mistakes
for a given category are constructed and connected with the
feedback. For instance, for the orthographic area of ‘Umlaut
all words containing an <ä> in the wordlist must be searched
for. To consider the dierent phenomena where substung
<ä> for <e> is a mistake due to the morphological principle,
the search is done separately for verbs (e.g. <*fengt> instead
of <fängt> he/she/it catches), nouns (e.g. <Epfel> instead of
<Äpfel> apples), adjecves (e.g. <*kelter> instead of <kälter>
colder) and derivaons (e.g. <glenzend> instead of <glänzend>
shiny). But, since the ‘Umlaut in the word <ähnlich> and its
substuon with the incorrect <e> does not qualify for the
morphological level it must not be included in this category but
has to be added in another appropriate category with according
feedback.
6. Conclusion
In this arcle we introduced a plaorm that aims to movate
children to improve their spelling skills by wring and publishing
texts. In this plaorm an intelligent diconary is integrated and
based on the presented system of categories, the intelligent
diconary gives feedback in order to enable children to
correct mistakes with the help of this feedback. The plaorm
also provides a qualitave analysis for teachers, who can use
the results in order to help pupils with the improvement of
word spelling. Concerning learning analycs, the occurred
misspellings can also be used for an in depth analysis.
The development of the plaorm and the intelligent diconary
is sll under construcon and changes are sll possible. There
are sll issues such as the idencaon of several mistakes in
one word that will most certainly lead to further discussion
in the future. However, we are posive that this combinaon
and the interdisciplinary work of the IDERBLOG-Project will in
future movate more children from grade 3 on to write texts
and to improve their spelling competence. Further, we can
support teachers by providing analysis and material for the
improvement of spelling. The acve applicaon of the methods
of learning analycs in this area of language learning will help us
to understand the process of spelling acquision in more detail.
It is expected that this unique combinaon in one plaorm has a
posive impact on didacc approaches, educaon and science.
7. Acknowledgements
This research project is supported by the European Commission
Erasmus+ program in the framework of the project IDERBLOG.
For more informaon about the IDERBLOG-Project and its
project partners: Hugo Adolph2 , Chrisan Aspalter3 , Susanne
Biermeier4 , Sandra Ernst5 , Sonja Gabriel 6, Gabriele Goor5
Michael Gros2, Mike Cormann5, Anneliese Huppertz5, Kathrin
Irma4, Susanne March3, Nina Steinhauer2, Behnam Taraghi
7 and Marianne Ullmann3, please visit our homepage hp://
iderblog.eu/ (German language only).
2 LPM Saarland, Beethovenstraße 26, 66125 Saarbrücken, Germany
3 University of Teacher Educaon Vienna, IBS/DiZeTIK, Grenzackerstraße 18,
1100 Vienna, Austria - Europe
4 Albert-Weisgerber School St. Ingbert, Robert-Koch-Straße 4, 66386 St. Ingbert,
Germany
5 School of Raeren, Hauptstraße 45, 4730 Raeren, Belgium
6 University College of Teacher Educaon Vienna/Krems, Mayerweckstraße 1,
1210 Vienna, Austria - Europe
7 Graz University of Technology, Department Educaonal Technology,
Münzgrabenstraße 35a, 8010 Graz, Austria - Europe
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15
In-depth
eLearning
Papers
45
eLearning Papers ISSN: 1887-1542 www.openeducationeuropa.eu/en/elearning_papers
n.º 45 November 2015
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ISSN: 1887-1542
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... The platform, IDeR-Blog, 1 which is described in Sect. 3, aims to address this issue by combining technology-enhanced learning (TEL) and LA [3,4]. The platform, which is currently in its testing stage with our partners, serves as a motivating innovation for children to acquire German orthography more easily. ...
... This information can be used for early detection of learning issues and enables teachers to actively intervene [9,10]. The platform IDeR-Blog will use this information in order to enhance the acquisition of German orthography, since problems in the field of German orthography affect both primary-school pupils and university students in everyday life [3]. ...
... The reason for this is that publishing texts on the Internet are becoming easier and consequently more and more people are potential readers of a text. Aspects of this such as being sensitive to misspelled words, knowing how to correct them, using spelling aids and applying strategies to prevent spelling errors in the long run [3,21] will always be crucial. The consideration of these aspects of spelling competence is fundamental for the applied approach in the IDeRBlog-Project. ...
Article
Full-text available
According to the NMC Horizon Report (Johnson et al. in Horizon Report Europe: 2014 Schools Edition, Publications Office of the European Union, The New Media Consortium, Luxembourg, Austin, 2014 [1]), data-driven learning in combination with emerging academic areas such as learning analytics has the potential to tailor students’ education to their needs (Johnson et al. 2014 [1]). Focusing on this aim, this article presents a web-based (training) platform for German-speaking users aged 8–12.Our objective is to support primary-school pupils—especially those who struggle with the acquisition of the German orthography—with an innovative tool to improve their writing and spelling competencies. On this platform, which is free of charge, they can write and publish texts supported by a special feature, called the intelligent dictionary. It gives automatic feedback for correcting mistakes that occurred in the course of fulfilling a meaningful writing task. Consequently, pupils can focus on writing texts and are able to correct texts on their own before publishing them. Additionally, they gain deeper insights in German orthography. Exercises will be recommended for further training based on the spelling mistakes that occurred. This article covers the background to German orthography and its teaching and learning as well as details concerning the requirements for the platform and the user interface design. Further, combined with learning analytics we expect to gain deeper insight into the process of spelling acquisition which will support optimizing our exercises and providing better materials in the long run.
... The provided blog further gives reasons for writing because the pupils can publish their essays later on [6]. Therefore, we expect a higher motivation in formulating and revising a text in contrast to typical essay writing in a classroom [7]. ...
... "In contrast to other areas of language learning, there is hardly space to argue about the correct or incorrect spelling of a word. This orthographical stiffness can probably serve as an explanation for its importance" [7]. ...
... Unlike a conventional auto correction system the intelligent dictionary in general does not offer the correctly spelled word straightaway in order to serve didactic purposes: First, students have to give attention to the feedback and have to process it by applying it on the misspelled word. Second, this approach is based on a wider definition of spelling competence that does not only include a person´s knowledge of the correct spelling of given words and the rules of orthography, but also being sensitive to misspelled words, knowing how to correct them, and applying strategies to prevent spelling errors in a long run [7,14] Third, this system follows a modern approach of teaching and learning orthography, which considers the communicative aspect of writing (cf. e.g. ...
Conference Paper
Full-text available
German orthography is known to be quite difficult to master, especially for primary-school pupils in writing texts [cf. 1]. In order to support children with the acquisition of German orthography, we are developing a web-based platform for German-speaking users based on learning analytics techniques. Our goal is to motivate pupils age 8 to 12 to improve their spelling abilities by writing texts and by the possibility to publish them. Concerning spelling in combination with learning analytics the system provides - in case of an orthographic mistake - a specific feedback that encourages pupils to think about the spelling and to correct it. Based on occurred mistakes the teachers and the students are provided with a qualitative analysis of the mistakes. This analysis shows the problematic orthographic areas and gives suggestions for online and offline exercises as well as online courses that are explaining the orthographic phenomena. The aim of this article is to describe the architecture of the web-based system and a proof of concept by evaluating 60 essays. Furthermore, relevant background information is given in order to gain a better understanding in the complex interdisciplinary development.
... This article introduces the workflow and the interface design of a prototype development in the field of German orthography with a strong approach on LA. The platform, IDERBLOG 1 , which is described in section 3, aims to solve this issue by combining Technology Enhanced Learning (TEL) and LA with the acquisition of German or-thography [2,3]. The platform, which will be released in the course of 2016, will serve as a motivating innovation for children to acquire German orthography more easily. ...
... This information can then be used for early detection of learning issues and enables teachers to actively intervene [8,28]. The platform IDERBLOG will use this information in order to enhance the acquisition of German orthography, since problems in the field of German orthography affect primary school pupils' as well as university students' in everyday life situations [2]. ...
... Although the German orthography is much more transparent than the English one, where "the alphabet contains just 26 letters [which] correspond to 44 phonemes associated with 102 functional spelling units" [10], it is not as transparent as, for example, the Turkish one. The reason for unreliable correspondences lies in the missing 1:1 phoneme-grapheme-correspondences of the phonological principle, which is often caused by interfering principles of the semantic principle [2]. In contrast to the overall opinion, the majority of correct spellings can be systematically explained. ...
Conference Paper
Full-text available
Data-driven learning in combination with emerging academic areas such as Learning Analytics (LA) has the potential to tailor students’ education to their needs [1]. The aim of this article is to present a web-based training platform for primary school pupils who struggle with the acquisition of German orthography. Our objective is the improvement in their writing and spelling competences. The focus of this article is on the development of the platform and the details concerning the requirements and the design of the User Interface (UI). In combination with Learning Analytics, the platform is expected to provide deeper insight into the process of spelling acquisition. Furthermore, aspects of Learning Analytics will help to develop the platform, to improve the exercises and to provide better materials in the long run.
... The main idea is that the student gets a hint for correcting spelling mistake by providing specific feedback instead of only flagging a mistake and/or offering the correctly spelled word. In order to accomplish this task ( for details see Edtstadler et al., 2015), the misspelled words are categorized into different orthographic areas, which are assigned to phenomena and are linked with corresponding feedback for giving hints for correcting mistakes. This way a modern didactic approach to learning and teaching German orthography is implemented, which focus on cognitive clarity . ...
Article
Full-text available
Purpose – Due to the important role of orthography in society, the project called IDeRBlog presented in this paper created a web-based tool to motivate pupils to write text as well as to read and to comment on texts written by fellow students. In addition, IDeRBlog aims to improve student’s German orthography skills and supports teachers and parents with training materials for their students. The paper aims to discuss these issues. Design/methodology/approach – With the aid of learning analytics, the submitted text is analyzed and special feedback is given to the students so that they can try to correct the misspelled words themselves. The teachers as well as the parents are benefiting from the analysis and exercises suggested by the system. Findings – A recent study showed the efficiency of the system in form of an improvement of the students’ orthographic skills. Over a period of four months 70 percent of the students achieved a significant reduction of their spelling mistakes. Originality/value – IDeRBlog is an innovative approach to improving orthography skills combining blogging and new media with writing and practice.
... Storing numerous records of previous students' activities based on specific modules help researchers predict the prospective action, such as dropping out of a course or detecting students at-risk. Additionally, Learning Analytics is used in predicting performance and motivation (Edtstadler, Ebner & Ebner, 2015). Further forecasting about video watching on a course and relative activity in discussion forums is feasible to be investigated. ...
Article
Full-text available
Learning Analytics is an emerging field in the vast areas of Educational Technology and Technology Enhanced Learning (TEL). It provides tools and techniques that offer researchers the ability to analyze, study, and benchmark institutions, learners and teachers as well as online learning environments such as MOOCs. Massive Open Online Courses (MOOCs) are considered to be a very active and an innovative form of bringing educational content to a broad community. Due to the reasons of being free and accessible to the public, MOOCs attracted a large number of heterogeneous learners who differ in education level, gender, and age. However, there are pressing demands to adjust the quality of the hosted courses, as well as controlling the high dropout ratio and the lack of interaction. With the help of Learning Analytics, it is possible to contain such issues. In this publication, we discuss the principles of engaging Learning Analytics in MOOCs learning environments and review its potential and capabilities (the good), constraints (the bad), and fallacy analytics (the ugly) based on our experience in last years.
... Storing numerous records of previous students' activities based on specific modules help researchers predict the prospective action, such as dropping out of a course or detecting students at-risk. Additionally, Learning Analytics is used in predicting performance and motivation (Edtstadler, Ebner & Ebner, 2015). Further forecasting about video watching on a course and relative activity in discussion forums is feasible to be investigated. ...
Conference Paper
Full-text available
Learning Analytics is an emerging field in the vast areas of Educational Technology and Technology Enhanced Learning (TEL). It provides tools and techniques that offer researchers the ability to analyze, study, and benchmark institutions, learners and teachers as well as online learning environments such as MOOCs. Massive Open Online Courses (MOOCs) are considered to be a very active and an innovative form of bringing educational content to a broad community. Due to the reasons of being free and accessible to the public, MOOCs attracted a large number of heterogeneous learners who differ in education level, gender, and age. However, there are pressing demands to adjust the quality of the hosted courses, as well as controlling the high dropout ratio and the lack of interaction. With the help of Learning Analytics, it is possible to contain such issues. In this publication, we discuss the principles of engaging Learning Analytics in MOOCs learning environments and review its potential and capabilities (the good), constraints (the bad), and fallacy analytics (the ugly) based on our experience in last year's.
Conference Paper
Full-text available
Viele Jugendliche haben mit Lese- und Schreib-oder Rechtschreibproblemen zu kämpfen. Werden diese nicht erkannt und gefördert, wirkt sich das im Erwachsenenalter negativ aus [SMH08]. In diesem Beitrag beschreiben wir ein Informationssystem für den deutschsprachigen Raum, das sich derzeit im Aufbau befindet und mit Hilfe von Learning Analytics versucht personalisiertes Lernen zu fördern. Die Zielgruppe des Forschungsprojekts sind Kinder im Alter zwischen 8 und 12 Jahren. Schülerinnen und Schüler können Texte in Form von Blogeinträgen verfassen, welche automatisiert auf orthografische Fehler ausgewertet werden. Die qualitative Analyse wird mit Hilfe eines eigens dafür entwickelten Wörterbuches umgesetzt und den Lehrkräften zur Verfügung gestellt.
Conference Paper
Full-text available
Literature in the area of psychology and education provides domain knowledge to learning applications. This work detects the difficulty levels within a set of multiplication problems and analyses the dataset on different error types as described and determined in several pedagogical surveys and investigations. Our research sheds light to the impact of each error type in simple multiplication problems and the evolution of error rates for different error types in relation to the increasing problem-size.
Conference Paper
Full-text available
Within the evolution of technology in education, Learning Analytics has reserved its position as a robust technological field that promises to empower instructors and learners in different educational fields. The 2014 horizon report (Johnson et al., 2014), expects it to be adopted by educational institutions in the near future. However, the processes and phases as well as constraints are still not deeply debated. In this research study, the authors talk about the essence, objectives and methodologies of Learning Analytics and propose a first prototype life cycle that describes its entire process. Furthermore, the authors raise substantial questions related to challenges such as security, policy and ethics issues that limit the beneficial appliances of Learning Analytics processes.
Book
Even though Specific Reading Disability (Dyslexia) has been clinically recognized as a developmental learning disorder for nearly a hundred years. only within the past two decades it has become the subject of major experimental investigation. Because. by definition. dyslexic children are of average or superior intelligence. it is often suspected that some arcane feature of the written language is responsible for the inordinate difficulty experienced by these children in learning to read. The occasional claim that developmental dyslexia is virtually nonexistent in some languages coupled with the fact that languages differ in their writing systems has further rendered orthography a subject of serious investigation. The present Volume represents a collection of preliminary reports of investigations that explored the relationship between orthography and reading disabilities in different languages. Even though not explicitly stated. these reports are concerned with the question whether or not some orthographies are easier to learn to read and write than others. One dimension on which orthographies differ from each other is the kind of relationship they bear to pronunciation. The orthographies examined in this book range from the ones that have a simple one-to­ one grapheme-phoneme relationship to those which have a more complex relationship.
Article
Kinder gewinnen als eigene Nutzergruppe von Software und Websites immer mehr an Bedeutung. Allerdings sind die Unterschiede zwischen Kindern und Erwachsenen hinsichtlich ihrer kognitiven, motorischen, emotionalen und sozialen Entwicklung so beträchtlich, dass die bestehenden Erkenntnisse zur ergonomischen Gestaltung nicht unmittelbar auf Software und Websites für Kinder übertragen werden können. Um diese Lücke zu schließen, liefern Janine Liebal und Markus Exner, basierend auf umfangreichen analytischen und empirischen Untersuchungen, einen Katalog von 110 Gestaltungsempfehlungen sowie sinnvolle Tipps und Techniken zur Einbindung von Kindern als Informanten, Nutzer, Design-Partner und Tester in den Entwicklungsprozess von Software und Websites.
Chapter
In French, there is a pronounced discrepancy between pronunciation and orthography; some letters do not correspond to any sound (mute letters): on the other hand, the same sound may be represented by different letters (été, chanter, nez, et). Some words, although spelled the same, are differently pronounced. Furthermore, for the same words, in certain cases, the pronunciation differs according to the sounding of final consonant before the initial vowel sound of the next word (e.g., un homme, deshommes). Some words are pronounced and written the same way although their meaning are quite different because their etymology or chronological appearance are different.
Chapter
In German, the grapheme-phoneme relations are rather regular when compared to English. About 40 phonemes are represented by 85 graphemes each consisting of one, two, or three letters. Estimates of the amount of words that can be written phonologically vary from 50 to 75 per cent of the total number of words (Thome’, 1987).