An Analysis of Current Language Learning Software
Laura Vawter and Alke Martens
Computer Science Department, Rostock University, Albert-Einstein-Str. 22, Rostock, Germany
Keywords: Language Learning, Computer Assisted Language Learning.
Abstract: To start the development of an optimal digital learning environment for language learning we have started
with the first question: What current language learning software is available to users? To answer this question
an analysis of current computer Assisted Language Learning (CALL) software is necessary. This paper
expounds on the systematic analysis of 69 current language software. Based on this structured analysis, we
have developed a first framework of requirements for an digital language learning environment. For this
purpose, control, user input, software feedback and theoretical educational frameworks were analysed within
this investigation. The analysis demonstrates a lack of constructivist frameworks and a higher prevalence of
behaviourist educational frameworks in current language software.
1 INTRODUCTION
In the context of computer based training (CBT) or
computer aided instruction (CAI), a plethora of
systems are available. On one hand, there are many
forms of software types available, e.g. simple web-
based training systems (WBT), adaptive systems,
intelligent tutoring systems, etc. From the perspective
of computer science, these system types are all based
on different programming ideas, models or even
paradigms. To develop these systems, the computer
scientists make use of a variety of techniques,
stemming from artificial intelligence, agent
technology and/or software patterns. These
developments are often influenced by modern
research trends in computer science. On the other
hand, educational psychology and insights from
instructional design (aka. didactics) have influenced
the development of computer-based learning
software. Additionally, the way instructional design
and educational psychology influence a computer-
based learning software development, is often
dependent on the amount of time available for the
development of the software. For example, to develop
a software which is based on behaviouristic learning
paradigm is comparably easy, whereas developing a
cognitively demanding or a constructivist
environment is demanding for programmers and
content developers.
Computer Assisted Language Learning (CALL)
has been used in and outside of language classrooms
since the 1960’s. Current research has sought to
explore how historical uses of CALL impact language
learning as well as how CALL has been influenced by
educational theories and research language
acquisition (Hegelheimer and Chapelle, 2000,
Hulstijn, 2000, Chapelle, 1998, and Doughty 1987; as
referenced in Bordonaro, 2003).
The first step in our research seeks to go beyond
the historical uses of CALL and investigate what
CALL software is today. In order to investigate what
CALL software is available, a retrospective analysis
must be made regarding types of language learning
systems as well as forms of CALL software.
1.1 Systems
From a computer science perspective, there are many
systems used in CALL software. Historical systems
like CBT or CAI (Martens, 2004), are not as prevalent
as Interactive Learning Environments (ILE) or
Intelligent Tutoring Systems (ITS) in modern CALL.
The first ITS systems were developed by learning
psychologists in the late 1970s. However, the core of
ITS has remained the same. Martens expands on how
ITS incorporates expert knowledge, pedagogical
knowledge, learner, and user interface models.
Furthermore, she expounds that these systems are
often a combination of Artificial Intelligence and
Computer Aided Instruction. The ITS system acts as
a tutor that reacts to the users “progress and needs, his
level of knowledge, and his performance in the actual
Vawter, L. and Martens, A.
An Analysis of Current Language Learning Software.
DOI: 10.5220/0007727101750183
In Proceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019), pages 175-183
ISBN: 978-989-758-367-4
Copyright
c
 2019 by SCITEPRESS – Science and Technology Publications, Lda. All r ights reserved
175

context” (Martens, 2003). Thus, an ITS can,
depending on the underlying learner model, make
adaptation to the learner’s progress, decisions and/or
prior knowledge and expertise. Adaptation can take
place regarding the content, the navigation elements,
and the presentation style. This overwhelming
amount of flexibility comes with comparably high
development costs and time Consequently, ITS is
nice to have, but often not realized by companies due
to cost.
Chou and Hillman, et. al. describe ILE as
involving the interactions of “learner-content,
learner-learning, learner-instructor, and learner
interface” within a software (as referenced in Wang,
et. al., 2009). However, system adaptation is not
always present in ILE software. In general ILE is a
niche development, which realizes only some aspects
of ITS.
ILE and ITS are, in most cases, are individual
learner focused. However, in the context of language
learning where communication is the focus, we find
the following software types:
 Computer Mediated Communication (CMC)
 Computer Supported Collaborative Learning
(CSCL)
 Network Based Language Training (NBLT)
CMC is described by Stockwell and Tanaka-Ellis
as “distance environments” or “blended learning
environments” (Stockwell and Tanaka-Ellis, 2012).
In these settings the software provides the connection
between the user, instructor, content and assessments.
One common representation of this format is
language schools, university departments or
institutions offering classes or seminars online. Blake
describes CMC as utilizing “social computing tools”
like forums, blogs, emails, Skype, or instant
messenger programs. In most forms, thus, we find a
combination between computer-based settings (or
CMC) and the presence of teachers and learners (e.g.
classroom) (Blake, 2011).
Scott, C. and Engal describe CSCL as a “cultural
constructivist approach” (Scott, C. and Engal, 1992).
Chapelle describes it as a software or platform
through which users interact and collaborate with
each other or an instance where users in the same
room or through local area network connections
interact and collaborate (Chapelle, 2001).
NBLT is characterized as taking place on a “local
area network” or “wide area network”. (Chapelle
2001). Additionally, Chapelle categorizes
pedagogical activities included in NBLTs as
Microworlds, Grammar Checkers, Pronunciation
Feedback Systems, ITS, Concordances Programs and
Word Processors (Chapelle, 2001).
1.2 Educational Framework
CALL software systems also differ in how
Behaviourist, Cognitivist and Constructivist
educational theories influence them.
Behaviourists educational elements can be
identified with Skinner’s research into “drill and
practice integrated learning systems”. The tasks
within these systems are scaffolded in a hierarchical
structure based on complexity and managed
according to a “stimulus/response feedback loop” (as
referenced in Niederhauser and Stoddart, 2001). The
feedback the user receives in these systems is
immediate and based the “correctness” of their input.
Egenfeldt-Nielsen further explains the reliance of
these systems on rewards (Egenfeldt-Nielsen, 2006).
The cognitivist educational psychology is evident
in these systems by the prevalence of differing tools,
activities or formats that promote higher order
thinking (Stockwell, 2012). Interestingly, these
manifestations often mimic Bloom’s Taxonomy and
require users to predict, produce and reflect on their
language input.
In CALL systems influenced by constructivist
learning theory, users manipulate, discover and
explore content within the system (Hogle, 1996,
Niederhauser and Stoddart, 2001). They may
incorporate micro-worlds (Egenfeldt-Nielsen, 2006)
or the support of peer-peer interaction (Becta, 2001,
referenced in Mitchell and Saville-Smith, 2004).
With all of this insight into the complexity of
language software systems the question remains:
what CALL software systems are available
nowadays? Furthermore, what elements are found in
these software systems?
2 BACKGROUND
An initial investigation of linguistic and computer
science research specified what form our evaluation
must take. The following is a short explanation of the
research behind our questions.
2.1 Research Questions
Martens describes an adaptive system as flexible to
any changes in the learner’s development or in the
condition of the user’s input into the system (Martens,
2004). Similarly, Brusilovsky expresses that an
adaptive system modifies its feedback to the user’s
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needs, problem solving strategies, and understanding
demonstrated in the learning process. This includes
the altering of feedback in relation to a user’s repeat
mistakes- like the provision of hints or clues to
address these user-specific problems. (Brusilovsky
1998). Thus, we sought to answer the questions: how
does the software respond to user’s input? What
feedback does it give?
M. Hron defines adaptability and flexibility in
software systems as the ability of learners to have
unrestricted access to content within a system.
(referenced in Martens, 2014). From the perception of
language learning, flexibility is related to the ability
of users or learners to negotiation the meaning of
content (Long, 1996). Adaptation and flexibility is
also seen by Pennington and Stevens, as providing
users with the ability to choose “the mode and format
to demonstrate their knowledge” as well as the
freedom to learn according to their interests”
(Pennington and Stevens, 1992). Thus, we sought to
answer the question: what level of control do users
have in the software?
Pennington and Stevens ascertain that by providing
learners with diverse modes of input and requiring user
production of content rather than imitation and
memorization, the learner’s acquisition of language
may be positively affected (Pennington and Stevens,
1992). Similarly, Hulsyojn and Laufer found a corrila-
tion between user involvment in a task and language
acquisition (as referenced in DeHaan, 2005). Thus, we
sought to answer the questions: what is the user input
within the software? What forms does it take?
Niederhauser and Stoddart describe how
behaviourist styled drill and practice systems are used
in language education (Niederhauser and Stoddart,
2001). Also, Reinders and Darasawang describe the
benefits of using cognitivist “metacognitive
strategies” in language learning (referenced in
Stockwell 2012). Rieber describes the positive effect
of exploration and discovery in constructivist systems
on learning (Rieber, 2005). Thus, with this criteria,
we sought to answer the question: What type of
educational psychology frameworks are evident in
the systems?
Much research has found CMC systems to be
beneficial to language learners (Zhao, 2003).
Additionally, Chapelle expands on the use of
collaborative learning with CSCL in language
classroom and the effects on language acquisition.
Similarly, Chapelle expounds on the importance of
identifying NBLT aspects to have a more accurate
inference of the effects on language learners
(Chapelle, 2001). Thus, we sought to answer the
following question: What systems types are evident?
3 ANALYSIS
This paper details our research into current CALL
software system including our evaluation process of
these system. A total of 69 systems were investigated.
3.1 Feedback
First, we sought to differentiate between systems that
had an awareness of user’s input and systems that did
not. An example of a system that didn’t have system
awareness would be a software program that offered
videos, clips or text in regard to a topic and didn’t
track if the user watched or read the content. Similar
systems received the label “No User Awareness”. In
contrast, as system that tracked what videos or clips
the user watched and those they didn’t would be
considered in this investigation as having user
awareness and would have received the label of “User
Awareness”. In the investigation, we further sought to
analyse the forms of user awareness that were present
in the systems. We further categorized the awareness
of a system as either “immediate” or “accumulated”
and further specified forms from there
In regard to “immediate” awareness the system
identified whether the user’s response was correct or
incorrect it received the label of “Answer”. If the
system in addition to identifying the correctness of
the input gave an “explanation”, “hint” or
“translation” it received such labels (see Figure 2). A
label of “Audio” was received if the system gave a
sound following user input- this was not necessarily
in response to the correctness or incorrectness of the
input. In contrast, if, for example, the system played
an audio clip without the user clicking on a button it
received the label of “No User Awareness: Audio”.
Figure 1: Software Feedback.
We intended to further specify immediate
feedback within the system by measuring what form
the software’s feedback took. If the system gave a
short explanation of why user input was correct or
incorrect it received the label “explanation”. This is
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177

in contrast to the system giving an explanation of a
grammar rule without user input. This would receive
the label of “No User Awareness: Explanation”.
Likewise, if a system gives a translation of a word or
sentences without user input the system receives the
label “No User Awareness: Translation”.
Additionally, if the system indicated which part of the
user’s input was incorrect the system received the
label of “Hint”.
As pertaining to “accumulated” system feedback
the label “leaderboard” was used in systems that had
leaderboards, and the label “progress” was used for
systems that tracked users long-term use. “Progress”
may be in the format of a system tracking how often
the user logged-in, how many exercises, units, levels
or lessons the user completed, how many vocabulary
words the user learned, or how many experience
points they earned from completing a certain type or
amount of exercises. Similarly, the label of “goal”
was given to systems that set goals for the user in
relation to their progress (i.e. learn this many words
today). Finally, if the system kept record of the
accuracy level of the user’s input it received the label
of “Knowledge”.
3.2 Adaptation
The second analysis we conducted was in regard to
system adaptation to the user. There are four types of
choice investigated in each software Choice,
Repetition, Feedback and Difficulty (see Figure 2).
Figure 2: Adaptation in CALL.
If the system allowed the user to choose which
exercises to complete (this could involve skipping
some activities or exercises or choosing the order in
which they do each activity), it received the label of
“Choice: Exercises” If the system allowed the user to
skip or change units, levels, stages, topics, or models
etc. it was given the label “Choice: Units”. If the user
could choose what language level (i.e beginner,
intermediate etc) the software received the label
“Choice: User Level”. Finally, if the user could select
the vocabulary present in the units and exercises the
software received the label of “Choice: Vocabulary
Sets”.
In addition to the user’s choice within a system, if
the user could repeat a set of exercises the software
received the label of “Repetition: Exercises”. In
contrast, if the user could not repeat individual
exercises, but could repeat a set of exercises the
software would receive a label of “Repetition: Units”.
Additionally, if the user could repeat input within an
exercise the system received the label “Repetition:
Answers”. If there was a restriction within the system
as to how many times the user could repeat an answer,
the software received either the labels of “Repetition:
Answers: Limited” or “Repetition, Answer:
Unlimited”.
In addition to choice and repetition, we
investigated “Feedback” and “Difficulty”. If the user
can give input on the system as a whole or the
systems’ correction of the user’s input the system
received the label “Feedback”. The feedback could
occur in or outside of the system -- a separate link to
the software website, or a discussion board or blog
within the software. If the user can change or alter
how difficult an exercise or set of exercises are within
the system the software received a label of
“Difficulty”.
3.3 User Input
First, we differinciated between input the user gave in
and outside of the software system. The input that
users gave outside of the system received the label
“Outside” and any input given by the user within the
software system received the lable “Inside”. From
here different forms of “outside” and “inside” input
was broken down into different forms (Figure 3):
Figure 3: User Input.
If there was a text, passage, blog, post etc that the
system didn’t track if or when the user read the
content it received the label “Outside: Read”.
Additionally, videos or clips provided by the system
without awareness of user acess received the label
“Outside: Watch”. Along the same lines- if the system
provided printable worksheets with activities or
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exercise or provided a downloadable PDF versions of
it’s content it received the label of “Outside: Write”.
If the system connected a user with another user for
instruction or speaking practice, but the user had to
connect with them outside of the system using Skype
or another medium it received the label “Outside:
Speak”. If the system connected users but did not give
feedback on user’s input like in a discussion forum
the system received a label of “Outside: Connect”. If,
in contrast, the system connected users and the it
recorded, responded, or tracked the users spoken
input the system received a label of “Inside: Spoken”.
If the system recorded the spoken input of the
user, the recorded input was divided into whether the
input was a repetition of a pronunciation (label
“repeat”), a spoken response following an exact
pattern specified by the system (label “structured”),
or a spoken response with no constraints by the
system (label “free”). The “structured” response
could also be in response to a multiple choice or fill
in the blank task. Similarly, if the user’s written input
needed to follow an exact pattern specified by the
system it received the label “Written: Structured”- if
not it, it received the label “Written: free”.
If the user’s input was in the form of clicking, the
input was distinguished by the task the user was
preforming: matching text or objects (label
“matching”), a multiple choice of objects, pictures or
texts (label “multiple choice”), tracing letters and
numbers (“trace”), arranging words or letters
(“arrange”), or playing a mini-game (label “play”).
3.4 Educational Framework
The final categorization we completed was for
educational psychological frameworks. Any system
that emphasised the repetition of material for
acquisition of language or the refinement of user
input through reward and punishment, it received the
label “Behaviourist”. Furtherore, any system that
emphasized stages of Bloom’s Taxonomy in its
content received the label “Cognitivist”. Finally, any
system that had aspects of user-user collaboration,
interaction or competition, as well as systems with
exploratory content received the label of
“Constructivist”.
4 RESULTS
The following section relays the results of the
analysis. The results are organized according to each
topic and research questions.
4.1 Software Feedback
As to the feedback present in current CALL systems,
91.30% presented user awareness at some level.
Overall 79.71% presented immediate feedback and
69.57% presented accumulated feedback.
Of the immediate feedback and in response to user
input, 23.19% of the systems played a sound bite.
Overall, 88.71%, identified if the user input was
correct or incorrect (label “answer”). Of those, 7.27%
gave a translation, 47.27% gave an explanation, and
5.46% gave a hint in response to incorrect user input
(see Figure 4).
Figure 4: System response to incorrect input.
In total, 93.75% of the systems tracked the
progress of the user, and 45.83% tracked the user’s
knowledge. Additionally 22.92% of software systems
set goals for the user and 10.42% offered a leader
board (see Figure 5).
Overall, 40.58% of the systems had elements that
did not have an awareness of user input. Of these,
72% offered translations, 92% offered audio clips,
and 32% offered explanation.
Figure 5: Accumulated feedback.
From our analysis, the systems present rudimentary
adaptability to the user’s needs. Though there was a
variation in the forms of feedback in our analysis, there
was no adaptation of feedback to learner’s problem
An Analysis of Current Language Learning Software
179

solving strategies or repeated mistakes. In general, the
varying of feedback forms within a system was not
correlated to individual user input.
4.2 Adaptation
From the investigation of system adaptation, only
11.59% of the software allowed for user feedback.
Likewise, only 10.15% of the software allowed for user
control of difficulty. Overall, 95.65% of the software
allowed for repetition of content. Of those, 66.67%
allowed repetition of exercises and 56.06% allowed for
repetition of units. As to the repetition within tasks,
56.52% allowed for the repetition of input within tasks.
Of these, 58.97% allowed for unlimited repetition and
41.03% allowed limited repetition.
As to choice, 66.18% of systems surveyed
allowed for user choice. Of those, 98.55% allowed for
user choice of level, 63.24% allowed for user control
over exercises, 8.82% allowed for user control over
the vocabulary, and only 7.35% of systems allowed
control over user level (See Figure 6).
Figure 6: User choice within the systems.
Most systems we analysed had little to no system
adaptability or flexibility. Though users had some
control over the content of the systems, as well as some
control over repetition and difficulty, users did not
have unrestricted access to the content. In all cases the
systems, in the least, determined the method for which
the users explored the content. Likewise, though some
systems changed content based on user selection of
vocabulary or topic, no system adapted the learning
path of the content to the user- a characteristic of a true
adaptive ITS system (Martens 2004). Thus, though the
systems had aspects of adaptability present, they could
not be considered to have high adaptability.
4.3 User Input
From the analysis user input, we found that 44.93%
of systems allowed for input “Outside” of the system
and 88.41% allowed for input “inside” the system.
Of the input outside of the system, 54.84%
provided reading material, and 38.71% provided
videos to watch. Furthermore, 45.16% connected
users in either a CMC or CSCL format. Additionally,
35.48% provided a platform for face to face
interaction (label “Speak”) and 22.58% provided a
platform for written discussion.
Of the input inside of the system, 91.80% was
“Click”, 47.54% was “Written” and 34.43% was
“Spoken” (See Figure 7).
Of the click input, 89.29% was a multiple choice
task, 48.21% was an arranging task, 10.71% was a
tracing task, and 21.43% was a mini-game (label
“play”). Additionally, of the written input, 69.23% was
structured, and 34.62% was free. Of the spoken input,
95.24% was repetition, 66.67% was a structured
response and 23.81% was a free response.
Figure 7: User input in the systems.
Strictly from a task-based perspective, most
investigated systems provided variation in user input.
It was evident in our analysis that many systems
preferred one form of input over another, but even if
the system restricted user input to one form (for
example, only written input), the systems still provided
a diverse amount of tasks within that form.
4.4 Educational Framework and
System Identification
From the analysis of software it is clear that a majority
of the CALL software, 81.16% can be categorized as
Behaviouristic or having behaviourist elements.
Additionally, 24.64% were categorized as having
cognitivists elements and 31.88% were categorized as
constructivist. Furthermore, 15.90% were CMC
systems, 5.80% were CSCL systems, and 88.40%
were NBLT systems. Finally, 11.59% of the systems
were ILE- the remaining were categorized as ITS
(See Figure 8).
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Software System Framework
17 min
Languages
NBLT ITS Behaviourist
Constructivist
ABA English NBLT
CMC
ITS Behaviourist
AudioNovo NBLT ITS Behaviourist
Babble NBLT ITS Behaviourist
Book Punch NBLT ITS Cognitivist
Business Letter
Punch
NBLT ITS Cognitivist
Busuu NBLT
CSCL
ITS Behaviourist
Constructivist
Cant Wait to
Learn
NBLT ITS Behaviourist
Constructivist
Capt'n Sharky NBLT ITS Behaviourist
Confused Words
Fix Up
NBLT ITS Behaviourist
Critical
Thinking Skills:
Upper Grades
NBLT ITS Behaviourist
Critical
Thinking Skills:
Reading
NBLT ITS Behaviourist
CyberTeachers NBLT
CMC
ITS Behaviourist
Drops NBLT ITS Behaviourist
Duolingo NBLT
CSCL
ITS Behaviourist
Constructivist
Earworms NBLT ITS Behaviourist
Easy Peasy:
English for Kids
NBLT ITS Behaviourist
eLanguage NBLT ITS Behaviourist
Cognitivist
Emil und
Pauline Auf dem
Hausboot
NBLT ITS Behaviourist
Emil und
Pauline Auf
Madagaskar
NBLT ITS Behaviourist
Emil und
Pauline Deutsch
und Mathe
NBLT ITS Behaviourist
Emil und
Pauline in
England
NBLT ITS Behaviourist
Exceller NBLT ITS Behaviourist
Go Talk NBLT ITS Behaviourist
Grammar
Fitness -
Advanced
NBLT ITS Behaviourist
Grammar
Fitness - Basic
NBLT ITS Behaviourist
Grammar
Fitness -
Intermediate
NBLT ITS Behaviourist
HandsOn
Turkish-
compact
NBLT ITS Behaviourist
HandsOn
Turkish
NBLT ITS Behaviourist
iTalki CMC ILE Constructivist
Johnny
Grammar Word
Challenge
NBLT ITS Behaviourist
Kidspeak NBLT
CSCL
ITS Behaviourist
Constructivist
LearnEnglish CMC ILE Constructivist
Cognitivist
LearnEnglish
Grammar
NBLT ITS Behaviourist
Cognitivist
LearnEnglish
Kids: Playtime
NBLT ITS Behaviourist
LearnOasis NBLT ITS Behaviourist
Lernerfolg
Grundschule
NBLT ITS Behaviourist
LinguaLeo NBLT ITS Behaviourist
LinguaPlex CMC ILE Constructivist
Little Pim NBLT ITS Behaviourist
Memrise NBLT ITS Behaviourist
Michel Thomas
Method
NBLT ITS Behaviourist
Mondly NBLT ITS Behaviourist
Constructivist
MosaLingua NBLT ITS Behaviourist
Muzzy NBLT ITS Behaviourist
Open Punch NBLT ITS Cognitivist
Paragraph Punch NBLT ITS Cognitivist
Pimsluer NBLT ITS Behaviourist
Pim Track NBLT ITS Behaviourist
Preply CMC ILE Constructivist
Prinzessin
Lillifee
NBLT ITS Behaviourist
Reading
Comprehension
Booster
NBLT ITS Behaviourist
Reading Skill
Builder
NBLT ITS Behaviourist
RealTalk CMC ILE Constructivist
Rocket
Languages
NBLT ITS Behaviourist
Cognitivist
Rosetta Stone NBLT ITS Behaviourist
Speexx NBLT ITS Behaviourist
Figure 8: Software identification.
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181

Software System Framework
Starter
Paragraph Punch
NBLT ITS Cognitivist
Study Cat NBLT ITS Behaviourist
Tandem-
Language
Exchange
CMC ILE Constructivist
Teach Your
Monster To Read
NBLT ITS Behaviourist
The Talk List CMC ILE Behaviourist
Transparent
Language Online
NBLT ITS Behaviourist
Cognitivist
UTalk NBLT ITS Behaviourist
Verbling CMC
CSCL
ILE Constructivist
Yabla NBLT ITS Behaviourist
Vocabulary
Stretch
NBLT ITS Behaviourist
Vocabulary
Super Stretch
NBLT ITS Behaviourist
Voxy NBLT
CMC
ITS Behaviourist
Constructivist
Figure 8: Software identification (cont.).
Our analysis found that the systems which were
primarily NBLT, even if they had CMC or CSCL
elements were ITS systems. Furthermore, we found
that there was much variation in the extent of user
adaptability within the ITS systems. Some systems
simply track user progress or user knowledge, but
have little to no adaptation of the content or system to
this tracking.
5 FURTHER RESEARCH
From a CALL perspective, only the forms of NBLT,
CSCL, and CMC were analysed. Further research is
needed in order to fully understand all CALL
software forms available to users. Furthermore, an
even greater database would be beneficial to the
analysis of current systems.
As to interface of these systems, no analysis was
done. The examination of the relation of software’s
interface, including changes with the addition of a
third party like a teacher or parent would be
beneficial. More information is needed as to how each
software incorporates these third parties and what
changes that causes (if any )to the workings of the
software units, activities, reward systems or
educational frameworks. Subsequently further
investigation is needed into intended users. Is the
software geared to 3 year olds or 10 year olds? What
is the gender of the intended user? Can the software
be adaptive to group settings or peer-to peer activities
or just is it primarily for individual users?
Additionally, further study could investigate what
percentage of each program incorporates behaviourist
elements like drill and practice, cognitivist elements
that mirror Bloom’s Taxonomy or constructivist
elements of peer-to-peer collaboration.
In addition to these further possibilities, the most
important further examination that is needed is in
regard to the ITS in CALL software. Due to the great
variability in user awareness and adaptation, a
detailed analysis is needed to determine what specific
aspects of a CALL system are flexible and how are
they adaptive to the user. Withstanding that from this
investigation a spotlight will be shown on which
systems have the highest user adaptability.
Finally, the additionally and private goal of the
authors’ is in-depth investigation into what a
constructivist language learning software demands in
comparison to a behaviourist language learning
software. This can be accomplished through the
analysis of a constructivist focused software system
like Minecraft. From here, the elements of a
constructivist learning environment can be grasped
and said concepts can be applied to a language
learning software.
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learning. Annual Review of Applied Linguistics, 31, 1-
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Bloom, T. M. E. (1965). Bloom’s taxonomy of educational
objectives. Longman.
Bordonaro, K. (2003). Perceptions of Technology and
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