Tutoring writing spelling skills within a web-based platform for children

Abstract

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.

Full text

LONG PAPER
Tutoring writing spelling skills within a web-based platform
for children
Markus Ebner
1
•Konstanze Edtstadler
2
•Martin Ebner
3
Published online: 5 July 2017
The Author(s) 2017. This article is an open access publication
Abstract 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 dic-
tionary. 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 occur-
red. 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.
Keywords German spelling acquisition Technology-
enhanced learning Learning analytics Educational media
1 Introduction
This article presents the workflow and the interface design
of a prototype in the field of German orthography with an
approach on learning analytics (LA). German orthography
is known to be relatively difficult to acquire and master,
especially for primary-school pupils—as the Austrian
national survey in 2015 showed [2]. 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. Teachers and researchers are benefiting from
the application, since it supports the decision-making
process and provides them with possible educational
interventions [4,5] supported by the offered training
database.
&Markus Ebner
markus.ebner@tugraz.at
1
Institute of Interactive Systems and Data Science, Graz
University of Technology, Inffeldgasse 16c, 8010 Graz,
Austria
2
Institute of Professionalization in Early Childhood and
Primary Teacher Education, University College of Teacher
Education Styria, Hasnerplatz 12, 8010 Graz, Austria
3
Educational Technology, Graz University of Technology,
Mu
¨nzgrabenstraße 35A/I, 8010 Graz, Austria
1
IDeRBlog, acronym of German: Individuell Differenziert
Rechtschreiben mit Blogs, which means translated literally to
English: ‘‘Individually differentiated spelling with blogs’’, available
online: http://iderblog.eu/ (German language only, Accessed 11
November 2016).
123
Univ Access Inf Soc (2018) 17:305–323
https://doi.org/10.1007/s10209-017-0564-6
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The data produced in the field of education are used by
various kinds of institutions worldwide [6]. This kind of
interaction leaves traces, with the result that learner beha-
viour can be analysed [7]. The students’ interactions with
the learning platform are also captured for analysis in order
to gain further understanding, knowledge, and insight into
a learner’s learning process [8]. 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].
1.1 Outline
The next section is concerned with teaching and learning
German orthography. It examines the theoretical back-
ground, modern approaches, and the use of digital media
for writing, spelling, and publishing. The subsequent sec-
tions address the design and workflow of the platform, its
prospects for self-learning, and the process of interface
design. The fifth section presents preliminary results from
the first three months of usage from our partner schools.
The last section will focus on discussion and conclusion
and provide the reader with an outlook.
2 Related work
2.1 Teaching and learning German orthography
If a continuum of orthographies is constructed, where
shallow orthographies are located on the one side (e.g.
Turkish, Serbian) and deep orthographies on the other (e.g.
English, French), then German orthography can be found
more or less in the middle. The reason for this position is
that there is quite a clear relationship between phonemes
and the graphemes in German [11]. This means that the
phonemes, the smallest unit of the speech that marks a
difference in meaning, e.g. the phonemes (‘‘sounds’’—no-
tated with//)/h/and/m/, such as in the English terms
\house[vs. \mouse[or the German terms \Haus[vs.
\Maus[are strongly related to a certain grapheme (‘‘let-
ter’’ notated with\[). Following this example it would be
the link between/h/and \H,h[and/m/and \M,m[. The
application of the correspondences between phonemes and
graphemes in order to convert spoken language into written
language and vice versa is crucial for alphabetic writing
systems and therefore also for German orthography [11].
Understanding and applying these correspondences is also
crucial for the acquisition of reading and spelling. As soon
as pupils understand these correspondences they are able to
apply an alphabetic strategy: this means that they can
analyse all phonemes of spoken words and apply the basic
correspondences between phonemes and graphemes in
order to write them. This is a major developmental step,
although it does not necessarily lead to orthographically
correct spelling in German orthography. For example, the
pupils hear the word/hut/(hat) and spell it correctly as
\Hut[. Anyway, applying the alphabetic strategy for
spelling the word/bilt/(picture) by considering the basic
correspondences/b/–[\b[,/i/–[\i[, /l/–[\l[, /t/–[
\t[would lead to the incorrect spelling \*bilt[.
The reason for this is the morphological principle [11]:
it supports the identification of a given morpheme and
consequently the identification of its meaning by spelling it
the same way even if the pronunciation is (slightly) dif-
ferent. For example, the word \Bild[(picture) is spelled
with \d[although pronounced as/t/because it is pro-
nounced as/d/in the plural form \Bilder[. Consequently,
this morpheme is spelled the same in all possible mor-
phologically complex words as \
Bild[, e.g. \abbilden[
‘‘to represent’’, \bebildert[‘‘illustrated’’, \bildhaft[
‘‘pictographic’’, \bildlich[‘‘figurative’’, \Bildchen[
‘‘small picture’’, etc.
The morphological principle, which is especially
important for a morphologically rich language such as
German, can be subsumed under the orthographic strategy
[12]. In the German language and orthography it is
appropriate to distinguish an orthographic, a morphological
and a crossword strategy as in May [13]. The conceptual-
ization of these three strategies—besides the basic alpha-
betic strategy—considers the complexity and
systematology of German orthography. However, the
notion of an ‘‘orthographic’’ strategy is still problematic as
an orthographic strategy can serve as the umbrella term for
all possible strategies concerning spelling. According to
Nerius’ [11] theory of German orthography, a lexical and
syntactic principle also exists. A peculiarity of German
orthography is the use of capital letters within sentences,
which is a feature of the lexical principle according to
Nerius [11], whereas other authors (e.g. [14]) assign it to
the syntactic principle. This peculiarity causes a lot of
problems in the acquisition process. Although most of the
spellings that require the use of a capital letter within a
sentence can be explained by the lexical principle of Nerius
[11] due to their part-of-speech classification (e.g. concrete
nouns such as \Haus[‘‘house’’ and abstract nouns such as
\Gu
¨te[‘‘benignity’’), others can be better explained by
the syntactic principle. It is especially challenging to spell
words correctly using capital letters because the position
within a sentence requires it, whereas this part of speech is
usually spelled with non-capital letters. For example, the
preposition \fu
¨r[‘‘for’’ needs to be spelled with a capital
letter in the phrase \das Fu
¨r und Wider[‘‘pros and cons’’.
306 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Grammatical knowledge is necessary in order to obey this
rule. May’s [13] crossword strategy covers these aspects of
German orthography, among others.
In contrast to (former) approaches, which focus on the
memorization of the correct spelling of words, new
approaches to teaching and learning German orthography
follow a concept that enables the learners to gain ‘‘cogni-
tive clarity’’. This means that the learner becomes aware of
the structure of words [14] and obtains insight into the
language [15]. Models dealing with the spelling compe-
tence of words take into account the automated spelling of
words as well as meta-linguistic control systems [16].
Consequently, developing orthographic competence can be
summed up by the combination and interaction of several
aspects of knowledge, such as declarative knowledge,
procedural knowledge, knowledge of problem solving, and
metacognitive knowledge [14]. Following Mu
¨ller [14]a
good way of developing orthographic competence is to
investigate language and orthography—most usefully in
dialogue form.
Until now, this approach to teaching and learning Ger-
man orthography can only be applied by teachers in the
classroom or by tutors in tutoring lessons. Everybody who
has worked with children acquiring orthography knows the
following phenomenon: a child writes a text, and when
asked to review it and to find (possible) mistakes the child
does not find (all) the mistakes. But when the child is given
a hint for discovering a mistake and/or is provided with
feedback in order to correct it, he/she recognizes the mis-
take and corrects it. Insight into the language and orthog-
raphy as well as metalinguistic awareness is raised by this
means. Although this approach is an effective method for
the learner, this 1:1 tuition can hardly be implemented
within a classroom setting and parents probably do not
have the necessary knowledge for providing it at home.
Consequently, there is the need to develop a digital
system, which considers these aspects to make it available
for as many pupils as possible. The intelligent dictionary of
the web-based platform IDeRBlog tries to implement this
approach of teaching and learning German orthography
with the help of learning analytics methods for the first
time.
2.2 Writing, spelling, and digital media
Computers, tablets, and other mobile devices are highly
attractive for children. Surprisingly, there are almost no
elaborated concepts for integrating German language
learning and digital media in the area of text writing and
spelling. A great deal of discussion and public debate is
dedicated to the question of whether writing with the
keyboard instead of handwriting is harmful to children. In
consensus with Berndt & Thelen [17], however,
questioning the use of digital media in education is point-
less, since digital media determine our lives and the aim
should be to gain expertise in using them. Two contrasting
positions can currently be identified concerning this issue:
One position favours handwriting for pupils. A survey
conducted in Germany revealed that 59.1% of the inter-
viewed mothers and 91.6% of the interviewed teachers
think that learning to write by hand is ‘‘very important’’ (cf.
[18]). The other position acknowledges the advantages of
text produced with digital media. Frederking [19] high-
lights two advantages of using computers for text produc-
tion: on the one hand, the didactic principle ‘‘writing is re-
writing’’ can easily be put into practice; on the other hand,
the correction of (spelling) mistakes can easily be made.
Abraham [20] states that the potential of writing aids such
as spelling correction, syntax check and automatic word
completion is not considered in didactic settings. More-
over, he criticizes that the programming of these writing
aids is merely based on the standard language, which
hinders young users from applying them.
Although using word processing programs and other
digital work environments and using the aids on offer are
initial steps, these are not sufficient in themselves. The
need for developing didactic concepts that make use of the
advantages of digital media in text writing, such as how the
IDeRBlog-Project does it, is a dictate of teaching and
learning languages in the twenty-first century. Without
much doubt, offering human–computer interaction tools
that help improve learning in a specific domain, such as
writing and spelling, will increase the acceptance of the use
of digital media in learning environments. It is essential
that they dispose additional value for teachers and students.
Furthermore, due to technical developments and the
availability of digital media at any time, holding on to
traditional approaches generates a gap between everyday
life and formal educational environments. For example, it
will be difficult to make a child look up a word in a printed
dictionary when online dictionaries are available. Apart
from that online dictionaries often provide more specific
information (e.g. declination of the searched noun, a list of
phrases with this word, etc.) than printed ones. The future
challenge of teaching will be how to make adequate use of
online dictionaries and autocorrection systems.
Although teaching and learning of spelling will change
due to digital environments, spelling competence will
undoubtedly always be important and probably even gain
importance, as the core function of orthography is to
facilitate reading. 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
Univ Access Inf Soc (2018) 17:305–323 307
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

[3,21] will always be crucial. The consideration of these
aspects of spelling competence is fundamental for the
applied approach in the IDeRBlog-Project.
2.3 Spelling, text writing, and publishing
As mentioned previously, spelling must not be seen isolated
from other aspects of language skills but as one aspect of text
writing. The results of Reichhardt [22], who analysed spel-
ling competence and text-writing competence in German-
speaking 3rd graders, show that there is little correlation
between those two competencies. Consequently, the writers
of good texts are not necessarily good spellers and vice versa
[22]. In the context of spelling competence when writing
texts there is also empirical evidence from Austria [2]. A
survey of various competencies in the German language,
such as reading, text writing, spelling, language awareness,
and listening, was conducted in 2015 with 76,552 Austrian
4th graders. It shows that 27% of the children tested have
problems using correct language in terms of spelling and
grammar when writing a text. This means that they are, for
example, not able to consider basic phenomena of German
orthography, to spell frequently used words correctly and/or
to apply correct grammar.
In accordance with Reichhardt [22] both spelling com-
petence and text-writing competence need to be improved.
The reason for this conflation is that a higher spelling com-
petence relieves the working memory in order to have greater
capacities to focus on the complex task of text writing.
Nevertheless, spelling should not be trained in isolation.
Unfortunately, this seems to be a common approach as can be
traced in the large quantity of online and offline spelling
exercises that are available—most of which are based on the
behaviourist concept. Mann [23] already claimed that the
communicative aspect plays a vital role in teaching and
learning spelling and that this communicative aspect can be
realized by publishing texts. Twenty-five years later, the
requirement she recommended can easily be fulfilled. Most
children have access to the Internet, which provides them with
many possibilities for publishing content—known or
unknown by teachers and parents. There is thus an urgent need
to provide web-based platforms, where pupils can publish
texts in a guided way with added didactic value. Additionally,
Frederking [24] states that web-based systems are ideal for
implementing modern didactic approaches in literacy classes.
To our knowledge, there are currently only two web-
based platforms in the German-speaking countries for
publishing texts, namely youtype
2
and myMoment.
3
It
should be noted, however, that they are altogether different
from the IDeRBlog-Platform.
Both platforms are developed and hosted in Switzerland.
Following the description on the platform itself and the
article of Schneider [25] the development of the platform
myMoment started in 2005. It is described as a platform
where children from grade 1 to grade 5 can write and
immediately publish texts without being corrected by
teachers. Consequently, the only correction feature avail-
able is that other users can rate the published texts and can
report inappropriate behaviour. Furthermore, children need
to decide to which genre the published text should belong
(e.g. funny stories, fantasy, or poems). All published texts
can be read without being registered. A registration is only
necessary for writing, publishing, and commenting. The
platform youtype focuses more at the integration of mul-
timedia as users can also add pictures, videos, and audio
(cf. [26]). The users are older than the users of myMoment
as the target group are pupils from 5th grade.
4
The users
can create an avatar for themselves and publish their cre-
ations under specific categories, e.g. news, short stories,
stars, etc., which can be viewed without registration;
however, it is necessary to be registered in order to make
comments. These two platforms seem to focus more on the
process of publishing and media education, whereas the
IDeRBlog-Platform combines publishing and media edu-
cation to spelling acquisition by applying learning
analytics.
2.4 Learning analytics
LA focuses on ‘‘the measurement, collection, analysis and
reporting of data about learners and their contexts, for
purposes of understanding and optimizing learning and the
environments in which it occurs’’ [27]. According to
Campell [28], an analysis process has five steps: capture,
report, predict, act, and refine. Clow [29] used these five
steps as a basis for his iterative learning analytics cycle
which states that the loop should be closed. Khalil and
Ebner [8] added stakeholders to the cycle according to their
visions and missions. In addition, they highlight some of
the ethical issues of LA and proposed an anonymization
framework to preserve the privacy of students [30]. The
learners’ data have to be processed in a specific mode in
order to conduct scientific analysis and support teachers
and students with the adaption of their teaching and
learning approach [31]. As part of the previous frame-
works, an adequate visualization has to be applied to pre-
sent the feedback as simple and informative as possible to
the stakeholders [32,33]. Furthermore, analytical
2
Available online: http://www.youtype.ch (Accessed 13 November
2016).
3
Available online: http://www.mymoment.ch (Accessed 11
November 11 2016).
4
Available online: http://edu-imedias.ch/module/ (Accessed 11
November 2016).
308 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

approaches to model a learner’s profile based on their
answering behaviour and the analysis of different error
types can lead to findings that help to enhance the whole
learning process [34,35].
3 The platform
3.1 The concept
The platform IDeRBlog tries to combine the development
of writing skills, the acquisition of orthographic compe-
tence, and the use of modern means of communication
and digital instruments [3]. The aim is not to replace
handwriting with typing on a keyboard, but rather to take
advantage of the digital age: on the one hand, a text
written on the platform can be published as a blog entry
in a private, class, or school blog. Thereby, the platform
is ‘‘providing relevant reasons and audiences for writing’’
[36]. On the other hand, the text is first analysed auto-
matically for spelling mistakes and can consequently be
edited several times. It is expected that the motivation to
formulate a text and to revise it many times is higher with
the prospect of publishing it, compared to typical essay
writing in a classroom [3].
The analysis is conducted by the core of the platform,
the intelligent dictionary, which also serves as the basis
for training orthographic skills. The only prerequisite is
that children have acquired the alphabetic principle of
German orthography. This means that the children should
apply at least the basic correspondences between pho-
nemes and graphemes. The deeper understanding of other
strategies, e.g. the morphological strategy, is supported by
the intelligent dictionary. It categorizes mistakes in order
to offer specific feedback and hints for correcting the
misspelled words. In doing so, the children should be
encouraged to reflect and think about the language in
order to become aware of the word structure [37]and
consider these insights in their spelling.
Based on the mistakes it also provides a qualitative
analysis of orthographic problems for teachers. Addition-
ally, these categories of mistakes are connected with a
number of exercises in the training database [3]. With all
these offered features, the platform meets several demands
for a spelling learning software as formulated by Berndt
and Thelen [17].
The platform for the project is currently in the testing
phase with our partner schools and interested third-party
schools. The official rollout to the public will start in
summer term 2017. The current workflow and the general
concept to ensure age-appropriate usability and interface
design [4] will be described briefly in the following
sections.
3.2 Design
It is a web-based application with state-of-the-art technol-
ogy such as HTML5, responsive web design, and web
services. The application server is implemented with the
GRAILS
5
web application framework version 3.x for Java
platforms with Apache Tomcat 7
6
and handles the com-
munication from students and the teachers. Figure 1shows
the IDeRBlog system, which can be used after prior reg-
istration with a separate user management system.
GRAILS is based on Groovy
7
and uses different estab-
lished frameworks such as Spring
8
and Hibernate
9
to
operate. The database server uses MySQL
10
for the
advantage of high on-demand scalability and performance
as well as the possibility to optimize the query load on the
server. To ensure a clean and manageable project the
model view controller (MVC) pattern is used [38].
The texts submitted by the student are first analysed
automatically for spelling mistakes. The conventional
system of dividing the text into sentences and further into
tokens is used for this. After the part-of-speech tagging
[39] the tokens, if identified by the intelligent dictionary,
are assigned to categories. Based on this information the
intelligent dictionary will provide age-appropriate feed-
back, according to the detected spelling mistake in con-
nection with its phenomenon. Further spelling mistakes are
handled by our support spellchecker Language Tools [38].
3.3 Intelligent dictionary and feedback
The main idea behind the intelligent dictionary is providing
hints for appropriate corrections whenever a spelling mis-
take is made. This is in contrast with conventional auto-
correction systems, which only provide the information
that something is wrong and/or immediately provide the
correct word. The intelligent feedback system considers the
requirement for the acquisition of orthography to offer
exercises and hints that allow the autonomous and mainly
strategy-based correction in a motivating context [40].
Additionally, several aspects of the German orthography
system [e.g. 11] and its modern approaches in teaching and
5
GRAILS, available online: https://grails.org/ (Accessed 10 Febru-
ary 2017).
6
Apache Tomcat, available online: http://tomcat.apache.org/ (Ac-
cessed 10 February 2017).
7
Groovy Language, available online: http://www.groovy-lang.org/
(Accessed 10 February 2017).
8
Spring Framework, available online: http://projects.spring.io/
spring-framework/ (Accessed 10 February 2017).
9
Hibernate Framework, available online: http://hibernate.org/ (Ac-
cessed 10 February 2017).
10
MySQL database, available online: https://www.mysql.com (Ac-
cessed 10 February 2017).
Univ Access Inf Soc (2018) 17:305–323 309
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

learning—as described in Sect. 2—are considered in the
development. In short, the feedback for correcting a mis-
take is formulated in such a way that the learner must think
about the spelling [3].
The following example illustrated in Fig. 2shows how
the feedback works.
Figure 2shows the sentence ‘‘Mein Pfert Rannte ganz
shnell im Gallop’’ which means ‘‘My horse galloped
very fast’’ (literally translated: ‘‘My horse ran very fast
in gallop’’). In this sentence four orthographic mistakes
can be found (\*Pfert[instead of \Pferd[,\*Rannte[
instead of \rannte[,\*shnell[instead of \schnell[and
\*Gallop[instead of \Galopp[). The three mistakes,
marked in red, are mistakes that are categorized. Con-
sequently, the intelligent dictionary can provide a
specific feedback.
The mistake \*Pfert[instead of \Pferd[shows that
the phoneme–grapheme–correspondences are applied
correctly (alphabetic strategy), though it is spelled
incorrectly due to the morphological principle. Conse-
quently, the user gets the feedback ‘‘Extend the word
and deduce the spelling’’. The word can be extended, for
example, by forming the plural. On adding the plural
suffix, the word changes from a word with one syllable
to a word with two syllables and the devoiced consonant
is voiced. This strategy should enable the child to choose
the correct grapheme.
The mistake ‘‘Rannte’’ does not consider the syntactic
principle, as the verb is written with a capital letter. The
feedback ‘‘Think about the part of speech and deduce the
spelling’’ should thus be a sufficient hint to make the child
correct the mistakes. Children are usually familiar with the
rule that nouns are spelled with a capital letter and other
words are not.
In the case of the ‘‘shnell’’ mistake, users are prompted
to have a closer look at the graphemes as the \c[in the
grapheme \sch[is missing. This mistake is located at the
level of phoneme–grapheme–correspondences. As one
phoneme is represented by a complex grapheme with three
letters, omissions can occur.
The feedback is kept short and simple. It can be assumed
that some users cannot make use of the hint given for
correcting the word, because they do not understand the
intention of the feedback. The platform offers additional
courses for pupils in order to guarantee that children can
benefit from the feedback independent of the teaching
approach chosen by the teacher and their state of knowl-
edge when starting to use the platform. These courses
explain for example the background knowledge required
for the feedback in order to understand the feedback:
‘‘Extend the word and deduce the spelling’’, it is necessary
to know how a word can be extended and what is meant by
deducing the spelling. This is explained by the online
course with the child appropriate title ‘‘d-t g-k p-b’’.
11
The mistake marked in yellow is not yet categorized
in the intelligent dictionary. As a result the feedback
says only: ‘‘possible mistake found’’. This feedback is
provided because, in addition to the categorized mistakes
in our intelligent dictionary, a grammar and spell
checker support proofreading. This is necessary because
the intelligent dictionary cannot cover all spelling mis-
takes due to the infinite number of all possible words
and possible mistakes. Nevertheless, users should not
have the impression that a word is correct just because it
is not categorized yet.
Additionally, the feedback for the spelling mistakes is
linked to the categories of the qualitative analysis for
teachers. In that way teachers can retrieve a qualitative
analysis based on mistakes that occurred, before and after the
feedback was given. Consequently, requirements for quali-
tative analysis of misspellings are considered [3,42].
3.4 General workflow for text creation
and correction
A student, as shown in Fig. 3, can write her/his text in the
writing area provided (1). First, the text will be analysed
orthographically by the intelligent dictionary (2) [3]. Proper
feedback, based on the spelling mistake and error category,
will be provided to the student. Then he/she has the choice
either to try correcting the text (3) as often as he/she wants or
to submit the text directly (4). This intermediate step
encourages pupils to correct spelling mistakes in an inde-
pendent and self-reflexive way [43]. After submission, the
teacher receives a notification (5) and reviews the text for
further correction and/or improvements as well as personal
notes to the student (6). The result and report are then
delivered back to the students for review (7) or, if necessary,
the teacher can hand the text back to the student with further
instructions for corrections (7a). The student then repeats the
correction process (step 1–4) and resubmits the text. After
this step the text may be published in the blogs provided
subject to permission from the student (8). Based on the
recommendations made by the system, the student can
choose between different online and offline exercises (9)
and/or do the exercises suggested by the teacher (10).
3.5 Student’s workflow
Figure 4shows the detailed workflow of a student. After
the login, an overview over all submitted texts will be
11
Available online: http://typo3.lpm.uni-sb.de/iderblog/fuer-erwach
sene/schuelerkurse/rhythmisches-verlaengern/kurs-dt-gk-pb-am-wor
tende/ (Accessed 11 November 2016).
310 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

provided together with the feedback given by the teacher
as well as further information and hints for possible self-
study exercises, provided by the training database. Fur-
ther, the student will be informed if a previously sub-
mitted text needs further improvement, suggested by the
teacher. The process of text creation/rewriting is outlined
in Fig. 4as well. The process is designed to be as
simple as possible in order to ensure an easy usability,
and the platform can be started directly with a single
click after the login button.
Fig. 1 Architecture [38]
Fig. 2 Example sentence with
4 feedbacks [41]
Univ Access Inf Soc (2018) 17:305–323 311
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

3.6 Teacher’s workflow
Figure 5shows the workflow of the teacher. A separate
user manager is provided in order to offer teachers easy
registration and class/school administration. If a student
forgets his/her password a reset for the password is easy
to do.
The teacher area of the IDeRBlog system gives an
overview of all texts of the classes in which the teacher is
active. In the class overview the teacher will be informed
when new texts for correction are available. An overview
of mistakes that have occurred as well as suggested exer-
cises will be provided for the class and for individual
students. This information can then be used for early
detection of learning issues and enables teachers to
undertake a proper intervention [9,10].
Once a new text is available, the teacher can review the
text and correct it if necessary. Additionally, it is possible
to categorize errors which may not have been detected and
categorized by the intelligent dictionary. This ensures a
qualitative analysis of all the spelling mistakes in the text.
The intelligent dictionary will be extended as a result,
ensuring that the system will recognize and categorize the
error correctly in future submissions after a linguistic
expert reviewed the suggestions.
3.7 Training database
The platform provides a training database. The platform
contains online and offline exercises (currently 260 in
total). Online exercises exclusively developed for the
project are being added. The preselection of exercises helps
teachers to support students with the improvement of the
performance in problematic/challenging areas identified by
LA. These exercises and worksheets are ordered congru-
ently in categories and subcategories of spelling mistakes
to provide a better overview [3]. All exercise types are
available for free to both teachers and students [45]. Fig-
ure 6shows the overview of exercises for students. The
menu on the left offers ‘‘U
¨ben im Internet’’ (online exer-
cises), ‘‘U
¨ben mit Arbeitsbla¨ttern’’ (printable offline exer-
cises, e.g. worksheets), ‘‘Suche Online U
¨bungen’’ and
Fig. 3 General workflow of the text creating and reviewing process, based on [44]
312 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

‘‘ Suche Arbeitsbla¨ tter’’ (search forms for the online and
offline exercises) and ‘‘Rechtschreibkurse’’ (spelling
courses). After selecting something on the left, the student
can choose between subcategories to refine the search.
The training database offers existing exercises catego-
rized in a way that corresponds to the categories of the
qualitative analysis; it also includes online exercises exclu-
sively developed for the IDeRBlog-Platform. The advantage
of the exclusive exercise is that the used words are the same
as the categorized ones for the intelligent dictionary.
4 Interface design
The platform is designed for primary-school children, aged
8–12. The focus lies on a graphically appealing and age-
appropriate web interface [46]. As suggested in the NMC
Horizon Report [1], we reviewed the possibility of
including the pupils as co-designers in the process. A
graphic designer created drafts and colour schemes for the
project that have been examined and rated by students from
different schools and classes. The favoured design by the
majority has then been developed further and integrated
into the platform. The process is shown in Fig. 7.
In order to guarantee a good usability of the platform,
we had to ensure that students can reach the most important
parts of the platform in less than five clicks. This conve-
nient accessibility in combination with attractive fig-
ures should ensure high motivation in fulfilling the task of
writing texts. In ongoing usability tests [47] we continue to
improve the concept step by step [3].
In the next subsections, interesting areas are presented in
the form of screenshots from the testing system with a brief
description.
Fig. 4 Student’s workflow, based on [44]
Univ Access Inf Soc (2018) 17:305–323 313
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

4.1 Student’s login view
After the login, the student can choose between 4 tasks, as
shown in Fig. 8:‘‘Einen Text schreiben’’ (starts the process
of writing a new text, as described in the previous section),
‘‘ Meine Texte ansehen’’ (overview over all saved and
submitted texts plus all texts corrected and returned by the
teacher), ‘‘Mein Blog’’ (accesses the private/class/school
blog system) and ‘‘zur Auswertung’’ (a benchmark of the
student based on the submitted texts and recommendations
for exercises is made here).
4.2 Student’s writing area
As described in Fig. 4and shown in Fig. 8, after the login,
the student can start the writing process with a single click.
Figure 9shows the first review stage with information
concerning wrongly written words (in this case two). Fur-
ther information on how to handle this error will be dis-
played by clicking on the highlighted word. With this
information, it should be possible for the student to correct
the word and submit the text for an additional review, if
necessary. This intermediate step facilitates independent
and self-reflexive corrections among pupils [43].
4.3 Teacher’s correction area
The teacher is informed after the student makes a final sub-
mission. He or she then has the opportunity to review the
different versions of contributions by a student (if there has
been more than one) in order to examine the independent
correction potential. Furthermore, as shown in Fig. 10, the
teacher is able to correct the text, add notes, and provide
feedback in order to make it ready for (optional) publication
on the blog. If the text needs further improvements, the
teacher can hand the text back to the student ‘‘Zuru¨ ckgeben’’ .
Based on the information presented in the text (e.g. too much
personal information about the family), the teacher can
choose to mark it as ‘‘do not blog’’. In this case, the text will
only be published in the student’s personal blog to which
only he/she has access to (no access for class, school, or
public). Additionally, errors which may not have been
detected and categorized by the intelligent dictionary can be
categorized in this step. Once the teacher has finished the
review, the student will be informed and can review the text
and take further actions, for example look at the online
courses or exercises recommended either by the teacher or
the system to improve his or her own writing ability.
Figure 10 in detail: the first text area presents the contri-
bution from the student (1). Errors are marked accordingly.
The second text area is for the teacher’s correction (2).
Feedback for the student can be given in area (3), internal
notes for the teacher in area (4). Information about the text
(number of sentences, words, spelling mistakes, etc.) is
shown in (5). Actions available to the teacher are also given:
‘‘continue later’’ (6), ‘‘give back to student’’ (7), ‘‘complete
the correction’’ (8), and ‘‘allow the text to be blogged’’ (9).
4.4 Class evaluation and exercise recommendation
Recommendations for exercises are based on a pupil’s
spelling mistakes or the mistakes of a whole class. Using
this information the teachers can detect problems in
specific orthographic areas.
As the example in Fig. 11 shows, the teacher gets an
overview of the problematic orthographic areas based on
the categories of the intelligent dictionary (‘‘Lehrerkate-
gorie’’). Furthermore, he/she can see which words are
misspelled and how often (‘‘Fehlerwo
¨rter (Vorkommen)’’/
‘‘Anzahl’’)). In order to provide the adequate exercises
links to selected online and print exercises come along with
the qualitative analysis for ensuring there is enough
material for practising on (‘‘U
¨bungen’’).
We also plan to take the progress pupils make into
account. After sufficient data are provided the user can
review his or her progress over the months, to see the
development concerning the average length of the text and
the spelling mistakes. We are currently discussing further
possibilities for teachers, students, and parents with our
partner schools.
5 Preliminary results
5.1 Usage statistics
The platform has been in use at our partner schools since
October 2016. In the period from October 2016 until
December 2016 the system has mainly been in use by
classes at our two partner schools. Usage dropped in
December 2016, due to the Christmas and the winter hol-
idays as can be seen in Fig. 12. Since mid-January 2017 we
have started to invite interested third-party schools to
participate by offering online courses, which has led to an
increase in usage.
In 2017 several training sessions designed for teachers
will be held in different cities of Austria and Germany during
the summer term. It is expected that these face-to-face
trainings will have a further positive effect on the usage.
5.2 Submitted texts
In the period from October 2016 until January 2017, 277
submissions from 258 students have been corrected by
teachers. By the end of January, 14 submissions were in
review process by teachers and 69 submissions are in the
314 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Fig. 5 Teacher’s workflow, based on [44]
Univ Access Inf Soc (2018) 17:305–323 315
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

queue to be reviewed. This makes a total of 360 submitted
texts on the system. Considering the relatively small
number of schools and classes involved and the short
period of usage the number of submitted texts is impres-
sive. It can be concluded that the acceptability level is
relatively high and oral reports of the partner schools
indicate that writing on the platform is indeed motivating
for the users.
5.3 Spelling errors
Before the partner schools and their pupils could start to
use the system, the intelligent dictionary needed to be put
through a final test. For this test we collected 60 essays
written by third-grade pupils in the project group. After
digitalization and anonymization, the texts and their mis-
takes were analysed by the prototype of the intelligent
dictionary. A total of 549 spelling mistakes were found in
these texts. Our intelligent dictionary responded to 95 of
these 549 spelling mistakes with appropriate feedback,
which means it provided 17.3% coverage for the total
spelling mistakes found in the 60 essays (for details see
[38]). As this first proof of concept is based on hand-
written texts which have been digitalized, we conducted a
further analysis based on texts written on the IDeRBlog-
Platform. These 429 texts are written by 149 students in
Fig. 6 Training exercise
overview for students
Fig. 7 Figure creation: first
prototypes (left) and final
figures on the webpage (right)
[44]
316 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

grade 3, 4, 5, and 6 in the period between end of October
2016 and end of January 2017. In sum, these texts contain
22,139 words. The length of these texts varies and ranges
from short texts of one sentence only to long texts of 23
sentences. A total of 3170 spelling mistakes were found in
these texts, representing a spelling mistake rate of 14.32%.
In total, 726 of these mistakes could be categorized and our
intelligent dictionary provided appropriate feedback. The
other 2444 mistakes were recognized by our supporting
spellchecker Language Tool. Compared to the identifica-
tion rate of the first proof of concept (see [38]), which is
based on hand-written texts, the identification rate of this
analysis, based on the actual use of the platform, increased
from 17.30 to 22.90%.
In the context of the qualitative aspects in this analysis we
can see that one category covers almost half of all mistakes. In
total, 49.31% of the mistakes recognized by the intelligent
dictionary are mistakes of neglecting the use of capital letters,
e.g. \*hase[instead of \Hase[‘‘ r a b b i t’’ o r \*wasser[
instead of\Wasser[‘‘water’’. The other half of the mistakes
is covered by15 categories, ranging from 18.32%—in the case
of gemination, e.g.\*Brile[instead of\Brille[‘‘ g l a s s e s ’’ —
to 0.14%—in the case of spelling with one vowel instead of
two, e.g.\*par[instead of \paar[‘‘some’’.
Fig. 8 Student’s login view
Univ Access Inf Soc (2018) 17:305–323 317
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

This analysis shows, as already stated in [38], that it
cannot be expected that all mistakes will be recognized by
the system and this is especially true for mistakes disre-
garding the phoneme–grapheme–correspondences (e.g.
\*schemkt[instead of \schenkt[‘‘he/she/it donates’’)
since there is an infinite number of possible mistakes. A
further constraint affects the spelling of names or places
and the use of English or other foreign words (e.g.
\*Matsh[instead of\match[) that cannot be categorized
in advance.
5.4 Usability tests
Evaluations have been conducted with six teachers from
our partner schools and two teachers from other institu-
tions. We used the thinking aloud test method [48,49]to
check the usability of the platform from the teachers’
perspective. Before the testing, the teachers were inter-
viewed about their computer and Internet experience.
The tasked assigned included the creation of a class,
adding students to it, correcting a submitted text from the
student and administer the blog. The overall acceptance
and feedback was positive due to the fact that all the
teachers have competences in the field of computer and
Internet usage, which emerged in the interviews referred to.
Some minor usability problems concerning the naming of
buttons and teachers’ workflow have been detected and
fixed to provide good user experience for the teachers in
the future.
In the case of the students: as stated in the previous
chapter we included students from our partner schools in
the process of designing the platform to ensure a good
usability. Furthermore we ensured that the students can
start doing a task in less than 5 mouse clicks (e.g. it is
possible to start writing a text after 1 click and to continue
writing after 2 clicks). Our partner schools are providing
continuous feedback on usage, usability, and problems.
Most of the students are digital natives [50] with experi-
Fig. 9 Student’s writing area.
The first text field shows errors
and hints for correction. In the
second text field, the student is
able to correct his/her text. The
3 buttons below are: (1) save,
(2) check again, and (3) submit
to the teacher. The button below
these three is used to cancel the
process
318 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Fig. 10 Teacher’s correction
area
Univ Access Inf Soc (2018) 17:305–323 319
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Fig. 11 Example view of the
qualitative analysis of spelling
mistakes for teachers
Fig. 12 Weekly login statistics
320 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

ence in using computers and digital media. The platform is
easy to use and in general is self-explanatory. In some
cases the text creation process took a little longer, because
of inexperience with keyboards and/or inability to use the
ten-finger system, especially among younger students.
6 Discussion and outlook
This article presents the architecture of a newly developed
platform for children aged 8–12, with the goal of moti-
vating them to improve their spelling skills by writing and
publishing texts in a blog. Furthermore, it gives insight to
the first experiences collected due to the use of schools
and pupils in a classroom setting. The unique feature of
this platform is that during the text creation process,
students benefit from automatic feedback provided by the
intelligent dictionary. This feedback is based on cate-
gories with age-appropriate responses for mistakes. As
described in the previous section, the intelligent dic-
tionary is able to recognize almost 23% of the mistakes in
texts written by pupils from grades 3 to 6. This is a very
promising finding considering that this is a prototype and
furthermore the infinite number of words, word forms,
and the contingent potential mistakes. Furthermore, the
platform provides a qualitative analysis for teachers, who
can use the results to help the pupils to improve their
spelling. A training database provides teachers and stu-
dents with suitable exercises for supervised and unsu-
pervised learning. It is planned that LA will be used for
in-depth analysis [31] of the misspellings that occurred to
help understand the process of spelling acquisition in
detail. Subsequently, the results together with an overview
of mistakes that are possibly made on a systematic basis
will be presented to students, teachers, and parents in an
appropriate form. Over the long term, this will allow the
measurement of a student’s performance [51]. In order to
fulfil these expectations, pupils should use the system
more intensively. The platform offers a unique combina-
tion of writing, feedback on spelling mistakes, and text
publishing in a single application, which is likely to bring
a very positive impact for didactic approaches, education,
and science [3]. We expect to see increasing use of the
platform—especially after the training for teachers’ in
summer term 2017—and as a consequence more data will
be produced for making greater use of language analytics.
We will be able to better understand the process of
spelling acquisition by carrying out an in-depth analysis
of the spelling mistakes learners make. In addition, we
will be able to make predictions about future performance
of students. Furthermore, learning materials can be
improved by using these results by considering the most
problematic areas of spelling acquisition based on
empirical evidence. For teachers and parents, in particu-
lar, the platform will offer a benchmark for the student
performance and provide recommendations for personal-
ized exercises and reflection on these recommended
exercises. The results will be presented with age-appro-
priate graphics and information for students as well as
their parents and teachers.
The spelling mistakes in the intelligent dictionary are
categorized by different linguistically predefined aspects,
which have been further fine-tuned. An analytical approach
can help to discover correlations of occurred spelling
mistakes from these categories. Similar approaches can be
found in the literature of other educational fields such as
mathematics [52–54].
Furthermore, we will be able to analyse the words usage
frequency of pupils aged between 8 and 12. This will be
very useful for all areas of language teaching since word
lists by frequency are currently available only on the basis
of adult language use and not on that of the words used by
children.
The system allows to conduct analysis on various levels
from fine-grained to coarse-grained. Concerning fine-
grained analyses, for example, we will be able to state how
often a specific word is used in general and also how often
it is spelled either correctly or incorrectly. In the context of
misspelled word forms we will be able to carry out further
distribution analyses in different categories. In coarse-
grained analyses, for example, we will be able to make
meaningful statements about the distribution of mastering
and disregarding specific categories and orthographic
phenomena.
Due to the fact that the intelligent dictionary only con-
tains a selection of words and their misspellings, a great
deal of free space is available for improving the system by
adding new words and their potential misspellings based on
the actual performance of the users.
As some categories take into account the differences in
pronunciation in different German dialects, we can gain
some insight into the impact of dialects in spelling
acquisition.
A frequent feature of recommender systems or learning
applications [52] is that users can be clustered according to
their so-called answering behaviour to the system. This can
be defined as simple spelling mistakes or the evolution of
spelling mistakes made by the users over time and in
accordance with influencing parameters. A similar
approach can be found in the work of Taraghi et al. [55],
which considers simple mistakes in multiplication prob-
lems. Last but not least, if user clustering is already
implemented, further research can be done to achieve an
adaptive learning algorithm that can be implemented in an
intelligent learning application using common machine
learning approaches in education [52,55]. In such an
Univ Access Inf Soc (2018) 17:305–323 321
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

application the system is able to intelligently adapt the
learning algorithm to the new requirements of the learner,
in dependence on the competence level he or she has
achieved. Furthermore, the adaptive algorithm would be
able to provide the learner with appropriate learning
exercises, which will help the user to reach the next
competence level.
Acknowledgements Open access funding provided by Graz
University of Technology. This research project is supported by the
European Commission Erasmus ?programme in the framework of
the Project IDeRBlog under Grant VG-SPS-SL-14-001616-3. For
more information about the IDeRBlog-Project and its project partners
from Germany: Gros, M., Adolph, H., Steinhauer, N. (LPM Saar-
land;)
12
Biermeier, S., Ankner, L. (Albert-Weisgerber-Schule, St.
Ingbert;)
13
from Belgium: Huppertz, A., Cormann, M. (GS Raeren;)
14
from Austria: Ebner, M., Taraghi, B., Ebner, M. (TU Graz;)
15
Gabriel,
S., Wintschnig, M. (KPH Wien/Krems;)
16
Aspalter, Ch., Martich, S.,
Ullmann, M. (PH Wien;)
17
Edtstadler, K. (PH Steiermark,)
18
please
visit the website: http://iderblog.eu/ (German language only).
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://crea
tivecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
made.
References
1. Johnson, L., Adams Becker, S., Estrada, V., Freeman, A., Kam-
pylis, P., Vuorikari, R., Punie, Y.: Horizon Report Europe 2014
Schools. Publications Office of the European Union, The New
Media Consortium, Austin (2014)
2. Breit, S., Bruneforth, M., Schreiner, C. (eds.): Stan-
dardu
¨berpru
¨fung 2015 Deutsch/Lesen/Schreiben, 4. Schulstufe.
Bundesergebnisbericht, Bifie, Salzburg (2016)
3. Edtstadler, K., Ebner, M., Ebner, M.: Improved German Spelling
Acquisition through Learning Analytics. In: eLearning papers 45,
pp. 17–28 (2015)
4. Ebner, M., Taraghi, B., Ebner, M., Aspalter, C., Biermeier, S.,
Edtstadler, K., Gabriel, S., Goor, G., Gros, M., Huppertz, A.,
Martich, S., Steinhauer, N., Ullmann, M., Ziegler, K.: Design fu
¨r
eine Plattform zum Schreibenlernen im Grundschulalter. In:
Rathmayer, S. Pongratz, H. (eds.) Proceedings of DeLFI Work-
shops 2015 co-located with 13th e-Learning Conference of the
German Computer Society (DeLFI 2015) Munich, Germany,
September 1st, 2015, pp. 118–122 (2015)
5. Ebner, M., Taraghi, B., Saranti, A., Scho
¨n, S.: Seven features of
smart learning analytics-lessons learned from four years of
research with learning analytics. In: eLearning papers 40,
pp. 51–55 (2015)
6. Piety, P.J.: Assessing the Educational Data Movement. Teachers
College Press, New York (2013)
7. Duval, E.: Attention Please! Learning Analytics for Visualization
and Recommendation. In: Proceedings of LAK11: 1st Interna-
tional Conference on Learning Analytics and Knowledge 2011,
(2011)
8. Khalil, M., Ebner, M.: Learning analytics: principles and con-
straints. In: Proceedings of World Conference on Educational
Multimedia, Hypermedia and Telecommunications, EdMedia
2015. AACE Waynesville, NC, USA, pp. 1326–1336 (2015)
9. Siemens, G., Long, P.: Penetrating the fog: analytics in learning
and education. EDUCAUSE Rev. 46(5), 30 (2011)
10. Greller, W., Drachsler, H.: Translating learning into numbers: a
generic framework for learning analytics. J. Educ. Technol. Soc.
15(3), 42–57 (2012)
11. Nerius, D. (ed.): Deutsche Orthographie. 4. neu bearbeitete.
Georg Olms, Hildesheim (2007)
12. Frith, U.: Beneath the Surface of Developmental Dyslexia. In:
Patterson, K.E., Marshall, J.C., Coltheart, M. (eds.) Surface
Dyslexia Neuropsychological and Cognitive Studies of Phono-
logical Reading, pp. 301–330. Lawrence Erlbaum, London
(1985)
13. May, P.: HSP 1-9. Diagnose orthographischer Kompetenz. Zur
Erfassung der grundlegenden Rechtschreibstrategien mit der
Hamburger Schreibprobe. Manual. Klett, Stuttgart (2010)
14. Mu
¨ller, A.: Rechtschreiben lernen. Die Schriftstruktur ent-
decken—Grundlagen und U
¨bungsvorschla
¨ge. Klett & Kallmeyer,
Seelze (2010)
15. Valtin, R.: Methoden des basalen Lese- und Schreibunterrichts.
In: Bredel, U., Hartmut, G., Klotz, P., Ossner, J., Siebert-Ott, G.
(eds.) Didaktik der deutschen Sprache, 2nd edn, pp. 760–771.
Scho
¨nigh, Paderborn (2006)
16. Hinney, G.: Was ist Rechtschreibkompetenz? In: Bredel, U.,
Reißig, T. (eds.) Weiterfu
¨hrender Orthographieerwerb,
pp. 191–225. Schneider Verlag Hohengehren, Baltmannsweiler
(2011)
17. Berndt, B.-E., Thelen, T.: Rechtschreib-Lern und Rechtschreib-
Pru
¨fprogramme. In: Bredel, U., Reißig, T. (eds.) Weiterfu
¨hrender
Orthographieerwerb, pp. 457–472. Schneider Verlag Hohengeh-
ren, Baltmannsweiler (2011)
18. Schreibmotorik-Institut (2016) Elternumfrage zur Wichtigkeit der
Handschrift. Problembeschreibung, Ursachen, Zusammenha
¨nge,
Unterschiede und Handlungsmo
¨glichkeiten: Auswertung einer
bundesweiten Befragung von Mu
¨ttern in Kooperation mit dem
Bundeselternrat und Vergleich mit Ergebnissen aus einer
Lehrerbefragung. http://www.schreibmotorik-institut.com/ima
ges/PDF/Elternumfrage_2016.pdf. Accessed 13 Nov 2016
19. Frederking, V.: Symmedialita
¨t und Syna
¨sthetik. Die digitale
Revolution im medientheoretischen, medienkulturgeschichtlichen
und mediendidaktischen Blick. In: Frederking, V., F., Krommer,
A. & Mo
¨bius, T. (eds.) Digitale Medien im Deutschunterricht,2.
Auflage. Baltmannsweiler: Schneider Verlag Hohengehren,
pp. 3–49 (2016)
20. Abraham, U.: Digitale Schreib-, Pra
¨sentations- und Publikation-
smedien. In: Frederking, V., Krommer, A., Mo
¨bius, T. (eds.)
Digitale Medien im Deutschunterricht, 2nd edn, pp. 269–289.
Schneider Verlag Hohengehren, Baltmannsweiler (2016)
21. Naumann, C.L.: Zur Rechtschreibkompetenz und ihrer Entwick-
lung. In: Bremerich-Vos A., Granzer D., Ko
¨ller O. (eds.) Lern-
standbestimmung im Fach Deutsch, Beltz, pp. 134–159 (2008)
12
LPM Saarland, Beethovenstraße 26, 66125 Saarbru
¨cken,
Germany.
13
Albert-Weisgerber School St. Ingbert, Robert-Koch-Straße 4,
66386 St. Ingbert, Germany.
14
School of Raeren, Hauptstraße 45, 4730 Raeren, Belgium.
15
Graz University of Technology, Department Educational Tech-
nology, Mu
¨nzgrabenstraße 35a, 8010 Graz, Austria.
16
University College of Teacher Education Vienna/Krems, Mayer-
weckstraße 1, 1210 Vienna, Austria.
17
University College of Teacher Education Vienna, IBS/DiZeTIK,
Grenzackerstraße 18, 1100 Vienna, Austria.
18
University College of Teacher Education Styria, Hasnerplatz 12,
8010 Graz, Austria.
322 Univ Access Inf Soc (2018) 17:305–323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

22. Reichardt, A.: Rechtschreibung im Textraum. Modellierung der
Schreibkompetenz in der Grundschule. Gilles & Francke, Duis-
burg (2015)
23. Mann, C.: Selbstbestimmtes Rechtschreiblernen: Rechtschrei-
bunterricht als Strategievermittlung, Beltz (1991)
24. Frederking, V.: Mediale Leerstellen. Empirische Befunde zum
Einsatz analoger und digitaler Medien im Deutschunterricht. In:
Frederking, V., Krommer, A., Mo
¨bius, T. (eds.) Digitale Medien
im Deutschunterricht, 2nd edn, pp. 359–379. Schneider Verlag
Hohengehren, Baltmannsweiler (2016)
25. Schneider, H.: Schreiben im Internet. Forschungsmethodische
Perspektiven. In: Knopf, J. (ed.) Medienvielfalt in der Deutsch-
didaktik Erkenntnisse und Perspektiven fu
¨r Theorie, Empirie und
Praxis, pp. 66–75. Schneider Verlag Hohengehren, Balt-
mannsweiler (2015)
26. Ma
¨der, R.: Youtype—Die digitale Schreibplattform. Schulblatt
10/2016. http://www.fhnw.ch/ph/publikationen/schulblaetter-
und-bildungsseiten/sb-ag-so. Accessed: 13 Nov 2016
27. Siemens, G., Gasevic, D.: Guest editorial—learning and knowl-
edge analytics. Educ. Technol. Soc. 15(3), 1–3 (2012)
28. Campbell, J.P., DeBlois, P.B., Oblinger, D.G.: Academic ana-
lytics: a new tool for a new era. EDUCAUSE Rev. 42(4), 40
(2007)
29. Clow, D.: The learning analytics cycle: closing the loop effec-
tively. In: Buckingham Shum, S., Gasevic, D., Ferguson, R. (eds.)
Proceedings of 2nd International Conference on Learning Ana-
lytics & Knowledge (LAK’12), New York, USA, pp. 134–138
(2012)
30. Khalil, M., Ebner, M.: De-identification in learning analytics.
J. Learn. Anal. 3(1), 129–138 (2016)
31. Siemens, G.: Learning analytics: envisioning a research discipline
and a domain of practice. In: Proceedings of the 2nd International
Conference on Learning Analytics and Knowledge, ACM,
pp. 4–8 (2012)
32. Baker, R.S.J.D., Duval, E., Stamper, J., Wiley, D., Buckingham
Shum, S.: Panel: educational data mining meets learning ana-
lytics. In: Buckingham Shum, S., Gasevic, D., Ferguson, R. (eds.)
Proceedings of 2nd International Conference on Learning Ana-
lytics & Knowledge (LAK’12), New York, USA, p. 20 (2012)
33. Neuhold, B.: Learning Analytics-Mathematik Lernen neu
gedacht, BoD–Books on Demand (2013)
34. Taraghi, B., Saranti, A., Ebner, M., Mu
¨ller, V., Großmann, A.:
Towards a learning-aware application guided by hierarchical
classification of learner profiles. J. Univ. Comput. Sci. 21(1),
93–109 (2015)
35. Taraghi, B., Frey, M., Saranti, A., Ebner, M., Mu
¨ller, V.,
Großmann, A.: Determining the Causing Factors of Errors for
Multiplication Problems. In: Ebner, M., Erenli, K., Malaka, R.,
Pirker, J., Walsh, A. (eds.) Immersive Education, Springer,
pp. 27–38 (2015)
36. Government of South Australia. Department for Education and
Child Development, issuing body.: Spelling: from Beginnings to
Proficiency: A Spelling Resource for Planning, Teaching,
Assessing and Reporting on Progress, Adelaide, South Australia,
Department for Education and Child Development (2011)
37. Tsesmeli, S.N., Seymour, P.H.K.: Derivational morphology and
spelling in dyslexia. Read. Writ. 19(6), 587–625 (2006)
38. Ebner, M., Edtstadler, K., Ebner, M.: (accepted, in print)
Learning Analytics and spelling acquisition in German—proof of
concept. HCI International 2017, Vancouver, BC, Canada
39. Voutilainen, A.: Part-of-speech tagging. The Oxford Handbook
of Computational Linguistics, pp. 219–232 (2003)
40. Klicpera, Ch., Schabmann, A., Gasteiger-Klicpera, B.: Legas-
thenie. Reinhardt. (2003), (2016)
41. Edtstadler, K., Ebner, M., Ebner, M.: Poster session, presented at
Symposion Deutschdidaktik 2016, Ludwigsburg, Germany
(2016)
42. Edtstadler, K.: Qualitative Fehleranalyse im Schriftspracherwerb.
Kritik und Kriterien. In: Lindner, D., Gabriel, S., Beer, R. (eds.)
Dialog Forschung—Tag der Forschung 2015, Lit-Verlag,
pp. 169–178 (2016)
43. Bartnitzky, H.: Individuell fo
¨rdern–Kompetenzen sta
¨rken.
Grundschule aktuell 9, 6–11 (2010)
44. Ebner, M., Ebner, M., Edtstadler, K.: Learning analytics and
spelling acquisition in German—a first prototype. In: Panayiotis,
Z., Ioannou, A. (eds.) Learning and Collaboration Technologies:
Third International Conference, LCT 2016, Held as Part of HCI
International 2016. Springer International, Toronto, ON, Canada,
pp. 405–416, (2016). doi: 10.1007/978-3-319-39483-1_37
45. Gros, M., Steinhauer, N., Ebner, M., Taraghi, B., Ebner, M.,
Aspalter, C., Martich, S., Edtstadler, K., Gabriel, S., Huppertz,
A., Goor, G., Biermeier, S., Ziegler, K.: Schreiben—
Rechtschreiben lernen und Lesen mit der Plattform Individuell
Differenziert Rechtschreiben mit Blogs—kurz IDeRBlog (www.
iderblog.eu). In: LA-Multimedia 4, pp. 22–24 (2015)
46. Liebal, J., Exner, M.: Usability fu¨ r Kids. Springer Fachmedien
Wiesbaden (2011)
47. Holzinger, A., Errath, M., Searle, G., Thurnher, B., Slany, W.:
From extreme programming and usability engineering to extreme
usability in software engineering education (XP ?UE ?XU).
In: Computer Software and Applications Conference, 2005.
COMPSAC 2005. 29th Annual International (2), IEEE,
pp. 169–172 (2005)
48. Andrews, K.: Human-Computer Interaction: Lecture Notes.
http://courses.iicm.tugraz.at/hci/hci.pdf (2013). Accessed: 14 Feb
2017
49. Barnum Carol, M.: Usability Testing Essentials: ready, set…
test!. Morgan Kaufmann, ISBN 012375092X (2010)
50. Prensky, M.: Digital natives, digital immigrants part 1. On
Horizon 9(5), 1–6 (2001)
51. Scho
¨n, M., Ebner, M., Kothmeier, G.: It’s just about learning the
multiplication table. In: Proceedings of the 2nd International
Conference on Learning Analytics and Knowledge, ACM,
pp. 73–81 (2012)
52. Taraghi, B., Saranti, A., Ebner, M., Scho
¨n, M.: Markov chain and
classification of difficulty levels enhances the learning path in one
digit multiplication. In International Conference on Learning and
Collaboration Technologies, Springer International Publishing,
pp. 322–333 (2014)
53. Taraghi, B., Ebner, M., Saranti, A., Scho
¨n, M.: On using markov
chain to evidence the learning structures and difficulty levels of
one digit multiplication. In: Proceedings of the Fourth Interna-
tional Conference on Learning Analytics and Knowledge, ACM,
pp. 68–72 (2014)
54. Taraghi, B., Saranti, A., Legenstein, R., Ebner, M.: Bayesian
modelling of student misconceptions in the one-digit multipli-
cation with probabilistic programming. In: Proceedings of the
Sixth International Conference on Learning Analytics &
Knowledge, ACM, pp. 449–453 (2016)
55. Taraghi, B., Saranti, A., Ebner, M., Großmann, A., Mu
¨ller, V.:
Adaptive learner profiling provides the optimal sequence of posed
basic mathematical problems. In: European Conference on
Technology Enhanced Learning, Springer International Publish-
ing, pp. 592–593 (2014)
Univ Access Inf Soc (2018) 17:305–323 323
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com